1
|
Wu C, Xiao S, Zhang X, Ren W, Shangguan X, Li S, Zuo D, Cheng H, Zhang Y, Wang Q, Lv L, Li P, Song G. GhHDZ76, a cotton HD-Zip transcription factor, involved in regulating the initiation and early elongation of cotton fiber development in G. hirsutum. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2024; 345:112132. [PMID: 38788903 DOI: 10.1016/j.plantsci.2024.112132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 05/17/2024] [Accepted: 05/20/2024] [Indexed: 05/26/2024]
Abstract
In this study, the whole HD-Zip family members of G. hirsutum were identified, and GhHDZ76 was classified into the HD-Zip IV subgroup. GhHDZ76 was predominantly expressed in the 0-5 DPA of fiber development stage and localized in the nucleus. Overexpression of GhHDZ76 significantly increased the length and density of trichomes in Arabidopsis thaliana. The fiber length of GhHDZ76 knockout lines by CRISPR/Cas9 was significantly shorter than WT at the early elongation and mature stage, indicating that GhHDZ76 positively regulate the fiber elongation. Scanning electron microscopy showed that the number of ovule surface protrusion of 0 DPA of GhHDZ76 knockout lines was significantly lower than WT, suggesting that GhHDZ76 can also promote the initiation of fiber development. The transcript level of GhWRKY16, GhRDL1, GhEXPA1 and GhMYB25 genes related to fiber initiation and elongation in GhHDZ76 knockout lines were significantly decreased. Yeast two-hybrid and Luciferase complementation imaging (LCI) assays showed that GhHDZ76 can interact with GhWRKY16 directly. As a transcription factor, GhHDZ76 has transcriptional activation activity, which could bind to L1-box elements of the promoters of GhRDL1 and GhEXPA1. Double luciferase reporter assay showed that the GhWRKY16 could enhance the transcriptional activity of GhHDZ76 to pGhRDL1, but it did not promote the transcriptional activity of GhHDZ76 to pGhEXPA1. GhHDZ76 protein may also promote the transcriptional activity of GhWRKY16 to the downstream target gene GhMYB25. Our results provided a new gene resource for fiber development and a theoretical basis for the genetic improvement of cotton fiber quality.
Collapse
Affiliation(s)
- Cuicui Wu
- Cotton Research Institute of Shanxi Agricultural University, Yuncheng 044000, China
| | - Shuiping Xiao
- Jiangxi Provincial Key Laboratory of Plantation and High Valued Utilization of Specialty Fruit Tree and Tea, Economic Crops Research Institute of Jiangxi Province, Nanchang 330000, China
| | - Xianliang Zhang
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang 455000, China; Western Research Institute, Chinese Academy of Agricultural Sciences (CAAS), changji 831100, China
| | - Wenbin Ren
- Cotton Research Institute of Shanxi Agricultural University, Yuncheng 044000, China
| | - Xiaoxia Shangguan
- Cotton Research Institute of Shanxi Agricultural University, Yuncheng 044000, China
| | - Shuyan Li
- Anyang Institute of Technology, Anyang 455000, China
| | - Dongyun Zuo
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Hailiang Cheng
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Youping Zhang
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Qiaolian Wang
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Limin Lv
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Pengbo Li
- Cotton Research Institute of Shanxi Agricultural University, Yuncheng 044000, China.
| | - Guoli Song
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| |
Collapse
|
2
|
Gu Q, Lv X, Zhang D, Zhang Y, Wang X, Ke H, Yang J, Chen B, Wu L, Zhang G, Wang X, Sun Z, Ma Z. Deepening genomic sequences of 1081 Gossypium hirsutum accessions reveals novel SNPs and haplotypes relevant for practical breeding utility. Genomics 2024; 116:110848. [PMID: 38663523 DOI: 10.1016/j.ygeno.2024.110848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 04/16/2024] [Accepted: 04/21/2024] [Indexed: 06/03/2024]
Abstract
Fiber quality is a major breeding goal in cotton, but phenotypically direct selection is often hindered. In this study, we identified fiber quality and yield related loci using GWAS based on 2.97 million SNPs obtained from 10.65× resequencing data of 1081 accessions. The results showed that 585 novel fiber loci, including two novel stable SNP peaks associated with fiber length on chromosomes At12 and Dt05 and one novel genome regions linked with fiber strength on chromosome Dt12 were identified. Furthermore, by means of gene expression analysis, GhM_A12G0090, GhM_D05G1692, GhM_D12G3135 were identified and GhM_D11G2208 function was identified in Arabidopsis. Additionally, 14 consistent and stable superior haplotypes were identified, and 25 accessions were detected as possessing these 14 superior haplotype in breeding. This study providing fundamental insight relevant to identification of genes associated with fiber quality and yield will enhance future efforts toward improvement of upland cotton.
Collapse
Affiliation(s)
- Qishen Gu
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Xing Lv
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Dongmei Zhang
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Yan Zhang
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Xingyi Wang
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Huifeng Ke
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Jun Yang
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Bin Chen
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Liqiang Wu
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Guiyin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Xingfen Wang
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China
| | - Zhengwen Sun
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China.
| | - Zhiying Ma
- State Key Laboratory of North China Crop Improvement and Regulation / North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory for Crop Germplasm Resources of Hebei Province / Hebei Agricultural University, Baoding, China.
| |
Collapse
|
3
|
Tang L, Liu C, Li X, Wang H, Zhang S, Cai X, Zhang J. An aldehyde dehydrogenase gene, GhALDH7B4_A06, positively regulates fiber strength in upland cotton ( Gossypium hirsutum L.). FRONTIERS IN PLANT SCIENCE 2024; 15:1377682. [PMID: 38736450 PMCID: PMC11082362 DOI: 10.3389/fpls.2024.1377682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Accepted: 04/09/2024] [Indexed: 05/14/2024]
Abstract
High fiber strength (FS) premium cotton has significant market demand. Consequently, enhancing FS is a major objective in breeding quality cotton. However, there is a notable lack of known functionally applicable genes that can be targeted for breeding. To address this issue, our study used specific length-amplified fragment sequencing combined with bulk segregant analysis to study FS trait in an F2 population. Subsequently, we integrated these results with previous quantitative trait locus mapping results regarding fiber quality, which used simple sequence repeat markers in F2, F2:3, and recombinant inbred line populations. We identified a stable quantitative trait locus qFSA06 associated with FS located on chromosome A06 (90.74-90.83 Mb). Within this interval, we cloned a gene, GhALDH7B4_A06, which harbored a critical mutation site in coding sequences that is distinct in the two parents of the tested cotton line. In the paternal parent Ji228, the gene is normal and referred to as GhALDH7B4_A06O; however, there is a nonsense mutation in the maternal parent Ji567 that results in premature termination of protein translation, and this gene is designated as truncated GhALDH7B4_A06S. Validation using recombinant inbred lines and gene expression analysis revealed that this mutation site is correlated with cotton FS. Virus-induced gene silencing of GhALDH7B4 in cotton caused significant decreases in FS and fiber micronaire. Conversely, GhALDH7B4_A06O overexpression in Arabidopsis boosted cell wall component contents in the stem. The findings of our study provide a candidate gene for improving cotton fiber quality through molecular breeding.
Collapse
Affiliation(s)
| | | | | | | | | | | | - Jianhong Zhang
- Institute of Cotton, Hebei Academy of Agriculture and Forestry Sciences, Key Laboratory of Cotton Biology and Genetic Breeding in Huanghuaihai Semiarid Area, Ministry of Agriculture and Rural Affairs, Shijiazhuang, Hebei, China
| |
Collapse
|
4
|
Huang Y, Qi Z, Li J, You J, Zhang X, Wang M. Genetic interrogation of phenotypic plasticity informs genome-enabled breeding in cotton. J Genet Genomics 2023; 50:971-982. [PMID: 37211312 DOI: 10.1016/j.jgg.2023.05.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/19/2023] [Accepted: 05/04/2023] [Indexed: 05/23/2023]
Abstract
Phenotypic plasticity, or the ability to adapt to and thrive in changing climates and variable environments, is essential for developmental programs in plants. Despite its importance, the genetic underpinnings of phenotypic plasticity for key agronomic traits remain poorly understood in many crops. In this study, we aim to fill this gap by using genome-wide association studies to identify genetic variations associated with phenotypic plasticity in upland cotton (Gossypium hirsutum L.). We identified 73 additive quantitative trait loci (QTLs), 32 dominant QTLs, and 6799 epistatic QTLs associated with 20 traits. We also identified 117 additive QTLs, 28 dominant QTLs, and 4691 epistatic QTLs associated with phenotypic plasticity in 19 traits. Our findings reveal new genetic factors, including additive, dominant, and epistatic QTLs, that are linked to phenotypic plasticity and agronomic traits. Meanwhile, we find that the genetic factors controlling the mean phenotype and phenotypic plasticity are largely independent in upland cotton, indicating the potential for simultaneous improvement. Additionally, we envision a genomic design strategy by utilizing the identified QTLs to facilitate cotton breeding. Taken together, our study provides new insights into the genetic basis of phenotypic plasticity in cotton, which should be valuable for future breeding.
Collapse
Affiliation(s)
- Yuefan Huang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Zhengyang Qi
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Jianying Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Jiaqi You
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, Hubei 430070, China.
| | - Maojun Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, Hubei 430070, China.
| |
Collapse
|
5
|
Li S, Kong L, Xiao X, Li P, Liu A, Li J, Gong J, Gong W, Ge Q, Shang H, Pan J, Chen H, Peng Y, Zhang Y, Lu Q, Shi Y, Yuan Y. Genome-wide artificial introgressions of Gossypium barbadense into G. hirsutum reveal superior loci for simultaneous improvement of cotton fiber quality and yield traits. J Adv Res 2023; 53:1-16. [PMID: 36460274 PMCID: PMC10658236 DOI: 10.1016/j.jare.2022.11.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 10/31/2022] [Accepted: 11/24/2022] [Indexed: 12/02/2022] Open
Abstract
INTRODUCTION The simultaneous improvement of fiber quality and yield for cotton is strongly limited by the narrow genetic backgrounds of Gossypium hirsutum (Gh) and the negative genetic correlations among traits. An effective way to overcome the bottlenecks is to introgress the favorable alleles of Gossypium barbadense (Gb) for fiber quality into Gh with high yield. OBJECTIVES This study was to identify superior loci for the improvement of fiber quality and yield. METHODS Two sets of chromosome segment substitution lines (CSSLs) were generated by crossing Hai1 (Gb, donor-parent) with cultivar CCRI36 (Gh) and CCRI45 (Gh) as genetic backgrounds, and cultivated in 6 and 8 environments, respectively. The kmer genotyping strategy was improved and applied to the population genetic analysis of 743 genomic sequencing data. A progeny segregating population was constructed to validate genetic effects of the candidate loci. RESULTS A total of 68,912 and 83,352 genome-wide introgressed kmers were identified in the CCRI36 and CCRI45 populations, respectively. Over 90 % introgressions were homologous exchanges and about 21 % were reverse insertions. In total, 291 major introgressed segments were identified with stable genetic effects, of which 66(22.98 %), 64(21.99 %), 35(12.03 %), 31(10.65 %) and 18(6.19 %) were beneficial for the improvement of fiber length (FL), strength (FS), micronaire, lint-percentage (LP) and boll-weight, respectively. Thirty-nine introgression segments were detected with stable favorable additive effects for simultaneous improvement of 2 or more traits in Gh genetic background, including 6 could increase FL/FS and LP. The pyramiding effects of 3 pleiotropic segments (A07:C45Clu-081, D06:C45Clu-218, D02:C45Clu-193) were further validated in the segregating population. CONCLUSION The combining of genome-wide introgressions and kmer genotyping strategy showed significant advantages in exploring genetic resources. Through the genome-wide comprehensive mining, a total of 11 clusters (segments) were discovered for the stable simultaneous improvement of FL/FS and LP, which should be paid more attention in the future.
Collapse
Affiliation(s)
- Shaoqi Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Linglei Kong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Xianghui Xiao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Pengtao Li
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Hong Chen
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi 832000, China
| | - Yan Peng
- Third Division of the Xinjiang Production and Construction Corps Agricultural Research Institute, Tumushuke 843900, China
| | - Yuanming Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Quanwei Lu
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China.
| | - Yuzhen Shi
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
| |
Collapse
|
6
|
Liu R, Zhu M, Shi Y, Li J, Gong J, Xiao X, Chen Q, Yuan Y, Gong W. QTL Verification and Candidate Gene Screening of Fiber Quality and Lint Percentage in the Secondary Segregating Population of Gossypium hirsutum. PLANTS (BASEL, SWITZERLAND) 2023; 12:3737. [PMID: 37960093 PMCID: PMC10650182 DOI: 10.3390/plants12213737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023]
Abstract
Fiber quality traits, especially fiber strength, length, and micronaire (FS, FL, and FM), have been recognized as critical fiber attributes in the textile industry, while the lint percentage (LP) was an important indicator to evaluate the cotton lint yield. So far, the genetic mechanism behind the formation of these traits is still unclear. Quantitative trait loci (QTL) identification and candidate gene validation provide an effective methodology to uncover the genetic and molecular basis of FL, FS, FM, and LP. A previous study identified three important QTL/QTL cluster loci, harboring at least one of the above traits on chromosomes A01, A07, and D12 via a recombinant inbred line (RIL) population derived from a cross of Lumianyan28 (L28) × Xinluzao24 (X24). A secondary segregating population (F2) was developed from a cross between L28 and an RIL, RIL40 (L28 × RIL40). Based on the population, genetic linkage maps of the previous QTL cluster intervals on A01 (6.70-10.15 Mb), A07 (85.48-93.43 Mb), and D12 (0.40-1.43 Mb) were constructed, which span 12.25, 15.90, and 5.56 cM, with 2, 14, and 4 simple sequence repeat (SSR) and insertion/deletion (Indel) markers, respectively. QTLs of FL, FS, FM, and LP on these three intervals were verified by composite interval mapping (CIM) using WinQTL Cartographer 2.5 software via phenotyping of F2 and its derived F2:3 populations. The results validated the previous primary QTL identification of FL, FS, FM, and LP. Analysis of the RNA-seq data of the developing fibers of L28 and RIL40 at 10, 20, and 30 days post anthesis (DPA) identified seven differentially expressed genes (DEGs) as potential candidate genes. qRT-PCR verified that five of them were consistent with the RNA-seq result. These genes may be involved in regulating fiber development, leading to the formation of FL, FS, FM, and LP. This study provides an experimental foundation for further exploration of these functional genes to dissect the genetic mechanism of cotton fiber development.
Collapse
Affiliation(s)
- Ruixian Liu
- Engineering Research Centre of Cotton, Ministry of Education, College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China;
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China (J.G.); (X.X.)
| | - Minghui Zhu
- Agricultural Technology Extension Center of Kashi District, Kashi 844000, China;
| | - Yongqiang Shi
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China (J.G.); (X.X.)
| | - Junwen Li
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China (J.G.); (X.X.)
- Zhengzhou Research Base, National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Zhengzhou University, Zhengzhou 450001, China
| | - Juwu Gong
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China (J.G.); (X.X.)
- Zhengzhou Research Base, National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Zhengzhou University, Zhengzhou 450001, China
| | - Xianghui Xiao
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China (J.G.); (X.X.)
| | - Quanjia Chen
- Engineering Research Centre of Cotton, Ministry of Education, College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China;
| | - Youlu Yuan
- Engineering Research Centre of Cotton, Ministry of Education, College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China;
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China (J.G.); (X.X.)
- Zhengzhou Research Base, National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Zhengzhou University, Zhengzhou 450001, China
| | - Wankui Gong
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China (J.G.); (X.X.)
| |
Collapse
|
7
|
Joshi B, Singh S, Tiwari GJ, Kumar H, Boopathi NM, Jaiswal S, Adhikari D, Kumar D, Sawant SV, Iquebal MA, Jena SN. Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton ( Gossypium hirsutum L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1252746. [PMID: 37941674 PMCID: PMC10630025 DOI: 10.3389/fpls.2023.1252746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 09/11/2023] [Indexed: 11/10/2023]
Abstract
Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.
Collapse
Affiliation(s)
- Babita Joshi
- Plant Genetic Resources and Improvement, CSIR-National Botanical Research Institute, Lucknow, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Sanjay Singh
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Gopal Ji Tiwari
- Plant Genetic Resources and Improvement, CSIR-National Botanical Research Institute, Lucknow, India
| | - Harish Kumar
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Regional Research Station, Faridkot, Punjab, India
| | - Narayanan Manikanda Boopathi
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India
| | - Sarika Jaiswal
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Dibyendu Adhikari
- Plant Ecology and Climate Change Science, CSIR-National Botanical Research Institute, Lucknow, India
| | - Dinesh Kumar
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Samir V. Sawant
- Molecular Biology & Biotechnology, CSIR-National Botanical Research Institute, Lucknow, India
| | - Mir Asif Iquebal
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Satya Narayan Jena
- Plant Genetic Resources and Improvement, CSIR-National Botanical Research Institute, Lucknow, India
| |
Collapse
|
8
|
Han Z, Ke H, Li X, Peng R, Zhai D, Xu Y, Wu L, Wang W, Cui Y. Detection of epistasis interaction loci for fiber quality-related trait via 3VmrMLM in upland cotton. FRONTIERS IN PLANT SCIENCE 2023; 14:1250161. [PMID: 37841603 PMCID: PMC10568130 DOI: 10.3389/fpls.2023.1250161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 09/04/2023] [Indexed: 10/17/2023]
Abstract
Cotton fiber quality-related traits, such as fiber length, fiber strength, and fiber elongation, are affected by complex mechanisms controlled by multiple genes. Determining the QTN-by-QTN interactions (QQIs) associated with fiber quality-related traits is therefore essential for accelerating the genetic enhancement of cotton breeding. In this study, a natural population of 1,245 upland cotton varieties with 1,122,352 SNPs was used for detecting the main-effect QTNs and QQIs using the 3V multi-locus random-SNP-effect mixed linear model (3VmrMLM) method. A total of 171 significant main-effect QTNs and 42 QQIs were detected, of which 22 were both main-effect QTNs and QQIs. Of the detected 42 QQIs, a total of 13 significant loci and 5 candidate genes were reported in previous studies. Among the three interaction types, the AD interaction type has a preference for the trait of FE. Additionally, the QQIs have a substantial impact on the enhancement predictability for fiber quality-related traits. The study of QQIs is crucial for elucidating the genetic mechanism of cotton fiber quality and enhancing breeding efficiency.
Collapse
Affiliation(s)
- Zhimin Han
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Huifeng Ke
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Xiaoyu Li
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Ruoxuan Peng
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Dongdong Zhai
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Yang Xu
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, Jiangsu, China
| | - Liqiang Wu
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Wensheng Wang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, China
| | - Yanru Cui
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| |
Collapse
|
9
|
Sun F, Yang Y, Wang P, Ma J, Du X. Quantitative trait loci and candidate genes for yield-related traits of upland cotton revealed by genome-wide association analysis under drought conditions. BMC Genomics 2023; 24:531. [PMID: 37679709 PMCID: PMC10485960 DOI: 10.1186/s12864-023-09640-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 08/30/2023] [Indexed: 09/09/2023] Open
Abstract
BACKGROUND Due to the influence of extreme weather, the environment in China's main cotton-producing areas is prone to drought stress conditions, which affect the growth and development of cotton and lead to a decrease in cotton yield. RESULTS In this study, 188 upland cotton germplasm resources were phenotyped for data of 8 traits (including 3 major yield traits) under drought conditions in three environments for two consecutive years. Correlation analysis revealed significant positive correlations between the three yield traits. Genetic analysis showed that the estimated heritability of the seed cotton index (SC) under drought conditions was the highest (80.81%), followed by that of boll weight (BW) (80.64%) and the lint cotton index (LC) (70.49%) With genome-wide association study (GWAS) analysis, a total of 75 quantitative trait loci (QTLs) were identified, including two highly credible new QTL hotspots. Three candidate genes (Gh_D09G064400, Gh_D10G261000 and Gh_D10G254000) located in the two new QTL hotspots, QTL51 and QTL55, were highly expressed in the early stage of fiber development and showed significant correlations with SC, LC and BW. The expression of three candidate genes in two extreme materials after drought stress was analyzed by qRT-PCR, and the expression of these two materials in fibers at 15, 20 and 25 DPA. The expression of these three candidate genes was significantly upregulated after drought stress and was significantly higher in drought-tolerant materials than in drought-sensitive materials. In addition, the expression levels of the three candidate genes were higher in the early stage of fiber development (15 DPA), and the expression levels in drought-tolerant germplasm were higher than those in drought-sensitive germplasm. These three candidate genes may play an important role in determining cotton yield under drought conditions. CONCLUSIONS This study is helpful for understanding the regulatory genes affecting cotton yield under drought conditions and provides germplasm and candidate gene resources for breeding high-yield cotton varieties under these conditions.
Collapse
Affiliation(s)
- Fenglei Sun
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- Hainan Yazhou Bay Seed Laboratory, Sanya, Hainan, 572000, China
| | - Yanlong Yang
- Research Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
| | - Penglong Wang
- Research Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
| | - Jun Ma
- Research Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
| | - Xiongming Du
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
| |
Collapse
|
10
|
Wang Y, Guo X, Cai X, Xu Y, Sun R, Umer MJ, Wang K, Qin T, Hou Y, Wang Y, Zhang P, Wang Z, Liu F, Wang Q, Zhou Z. Genome-Wide Association Study of Lint Percentage in Gossypium hirsutum L. Races. Int J Mol Sci 2023; 24:10404. [PMID: 37373552 DOI: 10.3390/ijms241210404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 06/08/2023] [Accepted: 06/15/2023] [Indexed: 06/29/2023] Open
Abstract
Lint percentage is one of the most essential yield components and an important economic index for cotton planting. Improving lint percentage is an effective way to achieve high-yield in cotton breeding worldwide, especially upland cotton (Gossypium hirsutum L.). However, the genetic basis controlling lint percentage has not yet been systematically understood. Here, we performed a genome-wide association mapping for lint percentage using a natural population consisting of 189 G. hirsutum accessions (188 accessions of G. hirsutum races and one cultivar TM-1). The results showed that 274 single-nucleotide polymorphisms (SNPs) significantly associated with lint percentage were detected, and they were distributed on 24 chromosomes. Forty-five SNPs were detected at least by two models or at least in two environments, and their 5 Mb up- and downstream regions included 584 makers related to lint percentage identified in previous studies. In total, 11 out of 45 SNPs were detected at least in two environments, and their 550 Kb up- and downstream region contained 335 genes. Through RNA sequencing, gene annotation, qRT-PCR, protein-protein interaction analysis, the cis-elements of the promotor region, and related miRNA prediction, Gh_D12G0934 and Gh_A08G0526 were selected as key candidate genes for fiber initiation and elongation, respectively. These excavated SNPs and candidate genes could supplement marker and gene information for deciphering the genetic basis of lint percentage and facilitate high-yield breeding programs of G. hirsutum ultimately.
Collapse
Affiliation(s)
- Yuanyuan Wang
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Institute of Science and Technology, Xinxiang 453003, China
| | - Xinlei Guo
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Institute of Science and Technology, Xinxiang 453003, China
| | - Xiaoyan Cai
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
- Hainan Yazhou Bay Seed Laboratory, National Nanfan Research Institute of Chinese Academy of Agriculture Sciences, Sanya 572025, China
| | - Yanchao Xu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Runrun Sun
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Institute of Science and Technology, Xinxiang 453003, China
| | - Muhammad Jawad Umer
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Kunbo Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Tengfei Qin
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yuqing Hou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Yuhong Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Pan Zhang
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Institute of Science and Technology, Xinxiang 453003, China
| | - Zihan Wang
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Institute of Science and Technology, Xinxiang 453003, China
| | - Fang Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
- Hainan Yazhou Bay Seed Laboratory, National Nanfan Research Institute of Chinese Academy of Agriculture Sciences, Sanya 572025, China
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Qinglian Wang
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Institute of Science and Technology, Xinxiang 453003, China
| | - Zhongli Zhou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| |
Collapse
|
11
|
Yang Z, Gao C, Zhang Y, Yan Q, Hu W, Yang L, Wang Z, Li F. Recent progression and future perspectives in cotton genomic breeding. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2023; 65:548-569. [PMID: 36226594 DOI: 10.1111/jipb.13388] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 10/11/2022] [Indexed: 05/26/2023]
Abstract
Upland cotton is an important global cash crop for its long seed fibers and high edible oil and protein content. Progress in cotton genomics promotes the advancement of cotton genetics, evolutionary studies, functional genetics, and breeding, and has ushered cotton research and breeding into a new era. Here, we summarize high-impact genomics studies for cotton from the last 10 years. The diploid Gossypium arboreum and allotetraploid Gossypium hirsutum are the main focus of most genetic and genomic studies. We next review recent progress in cotton molecular biology and genetics, which builds on cotton genome sequencing efforts, population studies, and functional genomics, to provide insights into the mechanisms shaping abiotic and biotic stress tolerance, plant architecture, seed oil content, and fiber development. We also suggest the application of novel technologies and strategies to facilitate genome-based crop breeding. Explosive growth in the amount of novel genomic data, identified genes, gene modules, and pathways is now enabling researchers to utilize multidisciplinary genomics-enabled breeding strategies to cultivate "super cotton", synergistically improving multiple traits. These strategies must rise to meet urgent demands for a sustainable cotton industry.
Collapse
Affiliation(s)
- Zhaoen Yang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Chenxu Gao
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
| | - Yihao Zhang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
| | - Qingdi Yan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Wei Hu
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
| | - Lan Yang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Zhi Wang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572000, China
- Sanya Institute, Zhengzhou University, Sanya, 572000, China
| | - Fuguang Li
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| |
Collapse
|
12
|
Sun F, Ma J, Shi W, Yang Y. Genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions. FRONTIERS IN PLANT SCIENCE 2023; 14:1135302. [PMID: 37123844 PMCID: PMC10130383 DOI: 10.3389/fpls.2023.1135302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 03/10/2023] [Indexed: 05/03/2023]
Abstract
Drought is one of the major abiotic stresses seriously affecting cotton yield. At present, the main cotton-producing areas in China are primarily arid and semiarid regions. Therefore, the identification of molecular markers and genes associated with cotton yield traits under drought conditions is of great importance for stabilize cotton yield under such conditions. In this study, resequencing data were used to conduct a genome-wide association study (GWAS) on 8 traits of 150 cotton germplasms. Under drought stress, 18 SNPs were significantly correlated with yield traits (single-boll weight (SBW) and seed (SC)), and 8 SNPs were identified as significantly correlated with effective fruit shoot number (EFBN) traits (a trait that is positively correlated with yield). Finally, a total of 15 candidate genes were screened. The combined results of the GWAS and transcriptome data analysis showed that four genes were highly expressed after drought stress, and these genes had significantly increased expression at 10, 15 and 25 DPA of fiber development. qRT-PCR was performed on two samples with drought tolerance extremes (drought-resistant Xinluzao 45 and drought-sensitive Xinluzao 26), revealing that three of the genes had the same differential expression pattern. This study provides a theoretical basis for the genetic analysis of cotton yield traits under drought stress, and provides gene resources for improved breeding of cotton yield traits under drought stress.
Collapse
Affiliation(s)
- Fenglei Sun
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
- Hainan Yazhou Bay Seed Laboratory, Sanya, Hainan, China
| | - Jun Ma
- Research Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, China
| | - Weijun Shi
- Research Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, China
| | - Yanlong Yang
- Research Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, China
- *Correspondence: Yanlong Yang,
| |
Collapse
|
13
|
Liu Y, Anderson NO. Phenotypic differences among and within extant populations of Chrysanthemum arcticum L. and C. a. subsp. arcticum. BMC PLANT BIOLOGY 2022; 22:517. [PMID: 36335304 PMCID: PMC9636833 DOI: 10.1186/s12870-022-03902-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 10/21/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Chrysanthemum arcticum, arctic daisy and its two subspecies (Chrysanthemum arcticum subsp. arcticum, Chrysanthemum arcticum subsp. polaré) are the only chrysanthemum species native to North America. A study on species' variation in morphological and diagnostic traits is important to link morphological traits with previously described single nucleotide polymorphism (SNP) markers, particularly when the genomes are sequenced. The purpose of this study was to establish phenotypic differences and soil conditions among wild C. arcticum and C. a. subsp. arcticum populations, when grown in a uniform environment for two years, for potential linkages with our SNP library. Sixteen quantitative morphological traits and five qualitative morphological traits were investigated for 255 individuals from nine C. arcticum populations and 326 individuals from 21 C. a. subsp. arcticum populations. RESULTS In long-day controlled environment, C. arcticum flowering rate was 0% in Year 1, increased to 2.7% in Year 2, while C. a. subsp. arcticum flowering rate was 98.5% in Year 2. Two distinct clusters, distributed by taxonomic classification, were detected by Principal component analysis (PCoA) for 551 individuals from C. arcticum and C. a. subsp. arcticum. Pearson's correlation coefficient analysis indicated a positive and significant correlation between plant height, flower fresh and dry weights. Flower fresh weights were correlated with Δflower weight, while inflorescence length had showed a negative correlation with leaf number. Soil samples had high Na levels along with heavy metals. Thus, the species are salt-tolerant. CONCLUSION A high level of salt tolerance (Na) is tolerated by these maritime species which is a unique trait in Chrysanthemum. A new diagnostic trait of inflorescence length was discovered to distinguish among C. arcticum and C. a. subsp. arcticum. Significant flowering differences occurred among the species C. arcticum and C. a. subsp. arcticum under same photoperiodic environment, including flowering rates and visible bud date. This study on the species' variation in morphological and diagnostic traits is of importance to link morphological traits with single nucleotide polymorphism (SNP) markers.
Collapse
Affiliation(s)
- Yunjia Liu
- Department of Horticultural Science, University of Minnesota, St. Paul, MN, 55018, USA
| | - Neil O Anderson
- Department of Plant Biology, The Huck Institutes of the Life Sciences, Pennsylvania State University, 101 Life Sciences Bldg., University Park, PA, 16802, USA.
| |
Collapse
|
14
|
Chen H, Han Z, Ma Q, Dong C, Ning X, Li J, Lin H, Xu S, Li Y, Hu Y, Si Z, Song Q. Identification of elite fiber quality loci in upland cotton based on the genotyping-by-target-sequencing technology. FRONTIERS IN PLANT SCIENCE 2022; 13:1027806. [PMID: 36407612 PMCID: PMC9669494 DOI: 10.3389/fpls.2022.1027806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 09/14/2022] [Indexed: 06/16/2023]
Abstract
Genome-wide association studies (GWAS) of fiber quality traits of upland cotton were conducted to identify the single-nucleotide polymorphic (SNP) loci associated with cotton fiber quality, which lays the foundation for the mining of elite] cotton fiber gene resources and its application in molecular breeding. A total of 612 upland cotton accessions were genotyped using the ZJU Cotton Chip No. 1 40K chip array via the liquid-phase probe hybridization-based genotyping-by-target-sequencing (GBTS) technology. In the present study, five fiber quality traits, namely fiber length, fiber strength, micronaire, uniformity and elongation, showed different degrees of variation in different environments. The average coefficient of variation of fiber strength was the greatest, whereas the average coefficient of variation of uniformity was the least. Significant or extremely significant correlations existed among the five fiber quality traits, especially fiber length, strength, uniformity and elongation all being significantly negative correlated with micronaire. Population cluster analysis divided the 612 accessions into four groups: 73 assigned to group I, 226 to group II, 220 to group III and 93 to group IV. Genome-wide association studies of five fiber quality traits in five environments was performed and a total of 42 SNP loci associated with target traits was detected, distributed on 19 chromosomes, with eight loci associated with fiber length, five loci associated with fiber strength, four loci associated with micronaire, twelve loci associated with fiber uniformity and thirteen loci associated with fiber elongation. Of them, seven loci were detected in more than two environments. Nine SNP loci related to fiber length, fiber strength, uniformity and elongation were found on chromosome A07, seven loci related to fiber length, fiber strength, micronaire and elongation were detected on chromosome D01, and five loci associated with fiber length, uniformity and micronaire were detected on chromosome D11. The results from this study could provide more precise molecular markers and genetic resources for cotton breeding for better fiber quality in the future.
Collapse
Affiliation(s)
- Hong Chen
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding of Ministry of Agriculture, Shihezi, China
| | - Zegang Han
- Zhejiang Provincial Key Laboratory of Crop Genetic Resources, The Advanced Seed Research Institute, Plant Precision Breeding Academy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Qi Ma
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding of Ministry of Agriculture, Shihezi, China
| | - Chengguang Dong
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding of Ministry of Agriculture, Shihezi, China
| | - Xinzhu Ning
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding of Ministry of Agriculture, Shihezi, China
| | - Jilian Li
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding of Ministry of Agriculture, Shihezi, China
| | - Hai Lin
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding of Ministry of Agriculture, Shihezi, China
| | - Shouzhen Xu
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding of Ministry of Agriculture, Shihezi, China
| | - Yiqian Li
- Zhejiang Provincial Key Laboratory of Crop Genetic Resources, The Advanced Seed Research Institute, Plant Precision Breeding Academy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Yan Hu
- Zhejiang Provincial Key Laboratory of Crop Genetic Resources, The Advanced Seed Research Institute, Plant Precision Breeding Academy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Zhanfeng Si
- Zhejiang Provincial Key Laboratory of Crop Genetic Resources, The Advanced Seed Research Institute, Plant Precision Breeding Academy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Qingping Song
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding of Ministry of Agriculture, Shihezi, China
| |
Collapse
|
15
|
Yasir M, Kanwal HH, Hussain Q, Riaz MW, Sajjad M, Rong J, Jiang Y. Status and prospects of genome-wide association studies in cotton. FRONTIERS IN PLANT SCIENCE 2022; 13:1019347. [PMID: 36330239 PMCID: PMC9623101 DOI: 10.3389/fpls.2022.1019347] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 09/08/2022] [Indexed: 06/16/2023]
Abstract
Over the last two decades, the use of high-density SNP arrays and DNA sequencing have allowed scientists to uncover the majority of the genotypic space for various crops, including cotton. Genome-wide association study (GWAS) links the dots between a phenotype and its underlying genetics across the genomes of populations. It was first developed and applied in the field of human disease genetics. Many areas of crop research have incorporated GWAS in plants and considerable literature has been published in the recent decade. Here we will provide a comprehensive review of GWAS studies in cotton crop, which includes case studies on biotic resistance, abiotic tolerance, fiber yield and quality traits, current status, prospects, bottlenecks of GWAS and finally, thought-provoking question. This review will serve as a catalog of GWAS in cotton and suggest new frontiers of the cotton crop to be studied with this important tool.
Collapse
Affiliation(s)
- Muhammad Yasir
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Advanced Agricultural Sciences, Zhejiang A&F University, Hangzhou, China
| | - Hafiza Hamrah Kanwal
- School of Computer Science, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Quaid Hussain
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou, China
| | - Muhammad Waheed Riaz
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou, China
| | - Muhammad Sajjad
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou, China
| | - Junkang Rong
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Advanced Agricultural Sciences, Zhejiang A&F University, Hangzhou, China
| | - Yurong Jiang
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, College of Advanced Agricultural Sciences, Zhejiang A&F University, Hangzhou, China
| |
Collapse
|
16
|
Ma J, Jiang Y, Pei W, Wu M, Ma Q, Liu J, Song J, Jia B, Liu S, Wu J, Zhang J, Yu J. Expressed genes and their new alleles identification during fibre elongation reveal the genetic factors underlying improvements of fibre length in cotton. PLANT BIOTECHNOLOGY JOURNAL 2022; 20:1940-1955. [PMID: 35718938 PMCID: PMC9491459 DOI: 10.1111/pbi.13874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 05/29/2022] [Accepted: 06/11/2022] [Indexed: 05/27/2023]
Abstract
Interspecific breeding in cotton takes advantage of genetic recombination among desirable genes from different parental lines. However, the expression new alleles (ENAs) from crossovers within genic regions and their significance in fibre length (FL) improvement are currently not understood. Here, we generated resequencing genomes of 191 interspecific backcross inbred lines derived from CRI36 (Gossypium hirsutum) × Hai7124 (Gossypium barbadense) and 277 dynamic fibre transcriptomes to identify the ENAs and extremely expressed genes (eGenes) potentially influencing FL, and uncovered the dynamic regulatory network of fibre elongation. Of 35 420 eGenes in developing fibres, 10 366 ENAs were identified and preferentially distributed in chromosomes subtelomeric regions. In total, 1056-1255 ENAs showed transgressive expression in fibres at 5-15 dpa (days post-anthesis) of some BILs, 520 of which were located in FL-quantitative trait locus (QTLs) and GhFLA9 (recombination allele) was identified with a larger effect for FL than GhFLA9 of CRI36 allele. Using ENAs as a type of markers, we identified three novel FL-QTLs. Additionally, 456 extremely eGenes were identified that were preferentially distributed in recombination hotspots. Importantly, 34 of them were significantly associated with FL. Gene expression quantitative trait locus analysis identified 1286, 1089 and 1059 eGenes that were colocalized with the FL trait at 5, 10 and 15 dpa, respectively. Finally, we verified the Ghir_D10G011050 gene linked to fibre elongation by the CRISPR-cas9 system. This study provides the first glimpse into the occurrence, distribution and expression of the developing fibres genes (especially ENAs) in an introgression population, and their possible biological significance in FL.
Collapse
Affiliation(s)
- Jianjiang Ma
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
- Zhengzhou Research Base, State Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhouChina
| | - Yafei Jiang
- Novogene Bioinformatics InstituteBeijingChina
| | - Wenfeng Pei
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Man Wu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Qifeng Ma
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Ji Liu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Jikun Song
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Bing Jia
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Shang Liu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Jianyong Wu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
- Zhengzhou Research Base, State Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhouChina
| | - Jinfa Zhang
- Department of Plant and Environmental SciencesNew Mexico State UniversityLas CrucesNew MexicoUSA
| | - Jiwen Yu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
- Zhengzhou Research Base, State Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhouChina
| |
Collapse
|
17
|
Chen Y, Gao Y, Chen P, Zhou J, Zhang C, Song Z, Huo X, Du Z, Gong J, Zhao C, Wang S, Zhang J, Wang F, Zhang J. Genome-wide association study reveals novel quantitative trait loci and candidate genes of lint percentage in upland cotton based on the CottonSNP80K array. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2279-2295. [PMID: 35570221 DOI: 10.1007/s00122-022-04111-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 04/19/2022] [Indexed: 06/15/2023]
Abstract
Thirty-four SNPs corresponding with 22 QTLs for lint percentage, including 13 novel QTLs, was detected via GWAS. Two candidate genes underlying this trait were also identified. Cotton (Gossypium spp.) is an important natural textile fiber and oilseed crop cultivated worldwide. Lint percentage (LP, %) is one of the important yield components, and increasing LP is a core goal of cotton breeding improvement. However, the genetic and molecular mechanisms underlying LP in upland cotton remain unclear. Here, we performed a genome-wide association study (GWAS) for LP based on 254 upland cotton accessions in four environments as well as the best linear unbiased predictors using the high-density CottonSNP80K array. In total, 41,413 high-quality single-nucleotide polymorphisms (SNPs) were screened, and 34 SNPs within 22 quantitative trait loci (QTLs) were significantly associated with LP. In total, 175 candidate genes were identified from two major genomic loci (GR1 and GR2), and 50 hub genes were identified through GO enrichment and weighted gene co-expression network analysis. Two candidate genes (Gh_D01G0162 and Gh_D07G0463), which may participate in early fiber development to affect the number of fiber protrusions and LP, were also identified. Their genetic variation and expression were verified by linkage disequilibrium blocks, haplotypes, and quantitative real-time polymerase chain reaction, respectively. The weighted gene interaction network analysis showed that the expression of Gh_D07G0463 was significantly correlated with that of Gh_D01G0162. These identified SNPs, QTLs and candidate genes provide important insights into the genetic and molecular mechanisms underlying variations in LP and serve as a foundation for LP improvement via marker-assisted breeding.
Collapse
Affiliation(s)
- Yu Chen
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Yang Gao
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Nanjing, 210095, China
| | - Pengyun Chen
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Juan Zhou
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Chuanyun Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Zhangqiang Song
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Xuehan Huo
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Zhaohai Du
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Chengjie Zhao
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Shengli Wang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Jingxia Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Furong Wang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
| | - Jun Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
| |
Collapse
|
18
|
Guo X, Wang Y, Hou Y, Zhou Z, Sun R, Qin T, Wang K, Liu F, Wang Y, Huang Z, Xu Y, Cai X. Genome-Wide Dissection of the Genetic Basis for Drought Tolerance in Gossypium hirsutum L. Races. FRONTIERS IN PLANT SCIENCE 2022; 13:876095. [PMID: 35837453 PMCID: PMC9274165 DOI: 10.3389/fpls.2022.876095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 05/31/2022] [Indexed: 06/15/2023]
Abstract
Drought seriously threats the growth and development of Gossypium hirsutum L. To dissect the genetic basis for drought tolerance in the G. hirsutum L. germplasm, a population, consisting of 188 accessions of G. hirsutum races and a cultivar (TM-1), was genotyped using the Cotton80KSNP biochip, and 51,268 high-quality single-nucleotide polymorphisms (SNPs) were obtained. Based on the phenotypic data of eight drought relative traits from four environments, we carried out association mapping with five models using GAPIT software. In total, thirty-six SNPs were detected significantly associated at least in two environments or two models. Among these SNPs, 8 and 28 (including 24 SNPs in 5 peak regions) were distributed in the A and D subgenome, respectively; eight SNPs were found to be distributed within separate genes. An SNP, TM73079, located on chromosome D10, was simultaneously associated with leaf fresh weight, leaf wilted weight, and leaf dry weight. Another nine SNPs, TM47696, TM33865, TM40383, TM10267, TM59672, TM59675, TM59677, TM72359, and TM72361, on chromosomes A13, A10, A12, A5, D6, and D9, were localized within or near previously reported quantitative trait loci for drought tolerance. Moreover, 520 genes located 200 kb up- and down-stream of 36 SNPs were obtained and analyzed based on gene annotation and transcriptome sequencing. The results showed that three candidate genes, Gh_D08G2462, Gh_A03G0043, and Gh_A12G0369, may play important roles in drought tolerance. The current GWAS represents the first investigation into mapping QTL for drought tolerance in G. hirsutum races and provides important information for improving cotton cultivars.
Collapse
Affiliation(s)
- Xinlei Guo
- Henan Institute of Science and Technology, Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Xinxiang, China
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yuanyuan Wang
- Henan Institute of Science and Technology, Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Xinxiang, China
| | - Yuqing Hou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Zhongli Zhou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Runrun Sun
- Henan Institute of Science and Technology, Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Xinxiang, China
| | - Tengfei Qin
- Henan Institute of Science and Technology, Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Xinxiang, China
| | - Kunbo Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Fang Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Yuhong Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Zhongwen Huang
- Henan Institute of Science and Technology, Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Xinxiang, China
| | - Yanchao Xu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiaoyan Cai
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| |
Collapse
|
19
|
Li C, Dong C, Zhao H, Wang J, Du L, Ai N. Identification of superior parents with high fiber quality using molecular markers and phenotypes based on a core collection of upland cotton ( Gossypium hirsutum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:30. [PMID: 37312963 PMCID: PMC10248707 DOI: 10.1007/s11032-022-01300-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 05/22/2022] [Indexed: 06/15/2023]
Abstract
The combination of molecular markers and phenotypes to select superior parents has become the goal of modern breeders. In this study, 491 upland cotton (Gossypium hirsutum L.) accessions were genotyped using the CottonSNP80K array and then a core collection (CC) was constructed. Superior parents with high fiber quality were identified using molecular markers and phenotypes based on the CC. The Nei diversity index, Shannon's diversity index, and polymorphism information content among chromosomes for 491 accessions ranged from 0.307 to 0.402, 0.467 to 0.587, and 0.246 to 0.316, with mean values of 0.365, 0.542, and 0.291, respectively. A CC containing 122 accessions was established and was categorized into eight clusters based on the K2P genetic distances. From the CC, 36 superior parents (including duplicates) were selected, which contained the elite alleles of markers and ranked in the top 10% of phenotypic values for each fiber quality trait. Among the 36 materials, eight were for fiber length, four were for fiber strength, nine were for fiber micronaire, five were for fiber uniformity, and ten were for fiber elongation. In particular, the nine materials, 348 (Xinluzhong34), 319 (Xinluzhong3), 325 (Xinluzhong9), 397 (L1-14), 205 (XianIII9704), 258 (9D208), 464 (DP201), 467 (DP150), and 465 (DP208), possessed the elite alleles of markers for at least two traits and could be given priority in breeding applications for a more synchronous improvement of fiber quality. The work provides an efficient method for superior parent selection and will facilitate the application of molecular design breeding to cotton fiber quality. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01300-0.
Collapse
Affiliation(s)
- Chengqi Li
- Life Science College, Yuncheng University, Yuncheng, 044000 China
| | - Chengguang Dong
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, 832000 China
| | - Haihong Zhao
- Life Science College, Yuncheng University, Yuncheng, 044000 China
| | - Juan Wang
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, 832000 China
| | - Lei Du
- Life Science College, Yuncheng University, Yuncheng, 044000 China
| | - Nijiang Ai
- Shihezi Agricultural Science Research Institute, Shihezi, 832000 China
| |
Collapse
|
20
|
Li L, Cui S, Dang P, Yang X, Wei X, Chen K, Liu L, Chen CY. GWAS and bulked segregant analysis reveal the Loci controlling growth habit-related traits in cultivated Peanut (Arachis hypogaea L.). BMC Genomics 2022; 23:403. [PMID: 35624420 PMCID: PMC9145184 DOI: 10.1186/s12864-022-08640-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 05/05/2022] [Indexed: 11/10/2022] Open
Abstract
Background Peanut (Arachis hypogaea L.) is a grain legume crop that originated from South America and is now grown around the world. Peanut growth habit affects the variety’s adaptability, planting patterns, mechanized harvesting, disease resistance, and yield. The objective of this study was to map the quantitative trait locus (QTL) associated with peanut growth habit-related traits by combining the genome-wide association analysis (GWAS) and bulked segregant analysis sequencing (BSA-seq) methods. Results GWAS was performed with 17,223 single nucleotide polymorphisms (SNPs) in 103 accessions of the U.S. mini core collection genotyped using an Affymetrix version 2.0 SNP array. With a total of 12,342 high-quality polymorphic SNPs, the 90 suggestive and significant SNPs associated with lateral branch angle (LBA), main stem height (MSH), lateral branch height (LBL), extent radius (ER), and the index of plant type (IOPT) were identified. These SNPs were distributed among 15 chromosomes. A total of 597 associated candidate genes may have important roles in biological processes, hormone signaling, growth, and development. BSA-seq coupled with specific length amplified fragment sequencing (SLAF-seq) method was used to find the association with LBA, an important trait of the peanut growth habit. A 4.08 Mb genomic region on B05 was associated with LBA. Based on the linkage disequilibrium (LD) decay distance, we narrowed down and confirmed the region within the 160 kb region (144,193,467–144,513,467) on B05. Four candidate genes in this region were involved in plant growth. The expression levels of Araip.E64SW detected by qRT-PCR showed significant difference between ‘Jihua 5’ and ‘M130’. Conclusions In this study, the SNP (AX-147,251,085 and AX-144,353,467) associated with LBA by GWAS was overlapped with the results in BSA-seq through combined analysis of GWAS and BSA-seq. Based on LD decay distance, the genome range related to LBA on B05 was shortened to 144,193,467–144,513,467. Three candidate genes related to F-box family proteins (Araip.E64SW, Araip.YG1LK, and Araip.JJ6RA) and one candidate gene related to PPP family proteins (Araip.YU281) may be involved in plant growth and development in this genome region. The expression analysis revealed that Araip.E64SW was involved in peanut growth habits. These candidate genes will provide molecular targets in marker-assisted selection for peanut growth habits. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08640-3.
Collapse
Affiliation(s)
- Li Li
- State Key Laboratory for Crop Improvement and Regulation in North China, College of Agronomy, Hebei Agricultural University, Baoding, 071001, The People's Republic of China.,Department of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, 36948, USA.,School of Landscape and Ecological Engineering, Hebei University of Engineering, Handan, 056038, The People's Republic of China
| | - Shunli Cui
- State Key Laboratory for Crop Improvement and Regulation in North China, College of Agronomy, Hebei Agricultural University, Baoding, 071001, The People's Republic of China
| | - Phat Dang
- USDA-ARS National Peanut Research Laboratory, Dawson, GA, 39842, USA
| | - Xinlei Yang
- State Key Laboratory for Crop Improvement and Regulation in North China, College of Agronomy, Hebei Agricultural University, Baoding, 071001, The People's Republic of China
| | - Xuejun Wei
- School of Landscape and Ecological Engineering, Hebei University of Engineering, Handan, 056038, The People's Republic of China
| | - Kai Chen
- School of Landscape and Ecological Engineering, Hebei University of Engineering, Handan, 056038, The People's Republic of China
| | - Lifeng Liu
- State Key Laboratory for Crop Improvement and Regulation in North China, College of Agronomy, Hebei Agricultural University, Baoding, 071001, The People's Republic of China.
| | - Charles Y Chen
- Department of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, 36948, USA.
| |
Collapse
|
21
|
Zhao N, Wang W, Grover CE, Jiang K, Pan Z, Guo B, Zhu J, Su Y, Wang M, Nie H, Xiao L, Guo A, Yang J, Cheng C, Ning X, Li B, Xu H, Adjibolosoo D, Aierxi A, Li P, Geng J, Wendel JF, Kong J, Hua J. Genomic and GWAS analyses demonstrate phylogenomic relationships of Gossypium barbadense in China and selection for fibre length, lint percentage and Fusarium wilt resistance. PLANT BIOTECHNOLOGY JOURNAL 2022; 20:691-710. [PMID: 34800075 PMCID: PMC8989498 DOI: 10.1111/pbi.13747] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 10/22/2021] [Accepted: 10/27/2021] [Indexed: 05/04/2023]
Abstract
Sea Island cotton (Gossypium barbadense) is the source of the world's finest fibre quality cotton, yet relatively little is understood about genetic variations among diverse germplasms, genes underlying important traits and the effects of pedigree selection. Here, we resequenced 336 G. barbadense accessions and identified 16 million SNPs. Phylogenetic and population structure analyses revealed two major gene pools and a third admixed subgroup derived from geographical dissemination and interbreeding. We conducted a genome-wide association study (GWAS) of 15 traits including fibre quality, yield, disease resistance, maturity and plant architecture. The highest number of associated loci was for fibre quality, followed by disease resistance and yield. Using gene expression analyses and VIGS transgenic experiments, we confirmed the roles of five candidate genes regulating four key traits, that is disease resistance, fibre length, fibre strength and lint percentage. Geographical and temporal considerations demonstrated selection for the superior fibre quality (fibre length and fibre strength), and high lint percentage in improving G. barbadense in China. Pedigree selection breeding increased Fusarium wilt disease resistance and separately improved fibre quality and yield. Our work provides a foundation for understanding genomic variation and selective breeding of Sea Island cotton.
Collapse
Affiliation(s)
- Nan Zhao
- Joint Laboratory for International Cooperation in Crop Molecular BreedingMinistry of Education/College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Weiran Wang
- Institute of Economic CropsXinjiang Academy of Agricultural SciencesXinjiangChina
| | - Corrinne E. Grover
- Department of Ecology, Evolution and Organismal BiologyIowa State UniversityAmesIAUSA
| | - Kaiyun Jiang
- Joint Laboratory for International Cooperation in Crop Molecular BreedingMinistry of Education/College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Zhuanxia Pan
- Institute of Cotton ResearchShanxi Agricultural UniversityShanxiChina
| | - Baosheng Guo
- Cotton Research InstituteHebei Academy of Agriculture and Forestry SciencesHebeiChina
| | - Jiahui Zhu
- Institute of Economic CropsXinjiang Academy of Agricultural SciencesXinjiangChina
| | - Ying Su
- Joint Laboratory for International Cooperation in Crop Molecular BreedingMinistry of Education/College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Meng Wang
- Institute of Economic CropsXinjiang Academy of Agricultural SciencesXinjiangChina
| | - Hushuai Nie
- Joint Laboratory for International Cooperation in Crop Molecular BreedingMinistry of Education/College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Li Xiao
- Institute of Economic CropsXinjiang Academy of Agricultural SciencesXinjiangChina
| | - Anhui Guo
- Joint Laboratory for International Cooperation in Crop Molecular BreedingMinistry of Education/College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Jing Yang
- Institute of Economic CropsXinjiang Academy of Agricultural SciencesXinjiangChina
| | - Cheng Cheng
- Joint Laboratory for International Cooperation in Crop Molecular BreedingMinistry of Education/College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Xinmin Ning
- Institute of Economic CropsXinjiang Academy of Agricultural SciencesXinjiangChina
| | - Bin Li
- Joint Laboratory for International Cooperation in Crop Molecular BreedingMinistry of Education/College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Haijiang Xu
- Institute of Economic CropsXinjiang Academy of Agricultural SciencesXinjiangChina
| | - Daniel Adjibolosoo
- Joint Laboratory for International Cooperation in Crop Molecular BreedingMinistry of Education/College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Alifu Aierxi
- Institute of Economic CropsXinjiang Academy of Agricultural SciencesXinjiangChina
| | - Pengbo Li
- Institute of Cotton ResearchShanxi Agricultural UniversityShanxiChina
| | - Junyi Geng
- Cotton Research InstituteHebei Academy of Agriculture and Forestry SciencesHebeiChina
| | - Jonathan F. Wendel
- Department of Ecology, Evolution and Organismal BiologyIowa State UniversityAmesIAUSA
| | - Jie Kong
- Institute of Economic CropsXinjiang Academy of Agricultural SciencesXinjiangChina
| | - Jinping Hua
- Joint Laboratory for International Cooperation in Crop Molecular BreedingMinistry of Education/College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| |
Collapse
|
22
|
Razzaq A, Zafar MM, Ali A, Hafeez A, Sharif F, Guan X, Deng X, Pengtao L, Shi Y, Haroon M, Gong W, Ren M, Yuan Y. The Pivotal Role of Major Chromosomes of Sub-Genomes A and D in Fiber Quality Traits of Cotton. Front Genet 2022; 12:642595. [PMID: 35401652 PMCID: PMC8988190 DOI: 10.3389/fgene.2021.642595] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 10/25/2021] [Indexed: 02/02/2023] Open
Abstract
Lack of precise information about the candidate genes involved in a complex quantitative trait is a major obstacle in the cotton fiber quality improvement, and thus, overall genetic gain in conventional phenotypic selection is low. Recent molecular interventions and advancements in genome sequencing have led to the development of high-throughput molecular markers, quantitative trait locus (QTL) fine mapping, and single nucleotide polymorphisms (SNPs). These advanced tools have resolved the existing bottlenecks in trait-specific breeding. This review demonstrates the significance of chromosomes 3, 7, 9, 11, and 12 of sub-genomes A and D carrying candidate genes for fiber quality. However, chromosome 7 carrying SNPs for stable and potent QTLs related to fiber quality provides great insights for fiber quality-targeted research. This information can be validated by marker-assisted selection (MAS) and transgene in Arabidopsis and subsequently in cotton.
Collapse
Affiliation(s)
- Abdul Razzaq
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan
- *Correspondence: Abdul Razzaq, ; Youlu Yuan , ; Maozhi Ren,
| | - Muhammad Mubashar Zafar
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | - Arfan Ali
- FB Genetics Four Brothers Group, Lahore, Pakistan
| | - Abdul Hafeez
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | - Faiza Sharif
- University Institute of Physical Therapy, The University of Lahore, Lahore, Pakistan
| | | | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | - Li Pengtao
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Yuzhen Shi
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | - Muhammad Haroon
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | - Maozhi Ren
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
- *Correspondence: Abdul Razzaq, ; Youlu Yuan , ; Maozhi Ren,
| | - Youlu Yuan
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
- *Correspondence: Abdul Razzaq, ; Youlu Yuan , ; Maozhi Ren,
| |
Collapse
|
23
|
Lu X, Lü P, Liu H, Chen H, Pan X, Liu P, Feng L, Zhong S, Zhou B. Identification of Chilling Accumulation-Associated Genes for Litchi Flowering by Transcriptome-Based Genome-Wide Association Studies. FRONTIERS IN PLANT SCIENCE 2022; 13:819188. [PMID: 35283888 PMCID: PMC8905319 DOI: 10.3389/fpls.2022.819188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 01/24/2022] [Indexed: 06/14/2023]
Abstract
Litchi is an important Sapindaceae fruit tree. Flowering in litchi is triggered by low temperatures in autumn and winter. It can be divided into early-, medium-, and late-flowering phenotypes according to the time for floral induction. Early-flowering varieties need low chilling accumulation level for floral induction, whereas the late-flowering varieties require high chilling accumulation level. In the present study, RNA-Seq of 87 accessions was performed and transcriptome-based genome-wide association studies (GWAS) was used to identify candidate genes involved in chilling accumulation underlying the time for floral induction. A total of 98,155 high-quality single-nucleotide polymorphism (SNP) sites were obtained. A total of 1,411 significantly associated SNPs and 1,115 associated genes (AGs) were identified, of which 31 were flowering-related, 23 were hormone synthesis-related, and 27 were hormone signal transduction-related. Association analysis between the gene expression of the AGs and the flowering phenotypic data was carried out, and differentially expressed genes (DEGs) in a temperature-controlled experiment were obtained. As a result, 15 flowering-related candidate AGs (CAGs), 13 hormone synthesis-related CAGs, and 11 hormone signal transduction-related CAGs were further screened. The expression levels of the CAGs in the early-flowering accessions were different from those in the late-flowering ones, and also between the flowering trees and non-flowering trees. In a gradient chilling treatment, flowering rates of the trees and the CAGs expression were affected by the treatment. Our present work for the first time provided candidate genes for genetic regulation of flowering in litchi using transcriptome-based GWAS.
Collapse
Affiliation(s)
- Xingyu Lu
- Guangdong Litchi Engineering Research Center, College of Horticulture, South China Agricultural University, Guangzhou, China
- College of Life and Health Science, Kaili University, Kaili, China
| | - Peitao Lü
- College of Horticulture, Fujian Agriculture and Forestry University-University of California Riverside (FAFU-UCR) Joint Center for Horticultural Biology and Metabolomics, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Hao Liu
- Guangdong Litchi Engineering Research Center, College of Horticulture, South China Agricultural University, Guangzhou, China
| | - Houbin Chen
- Guangdong Litchi Engineering Research Center, College of Horticulture, South China Agricultural University, Guangzhou, China
| | - Xifen Pan
- Guangdong Litchi Engineering Research Center, College of Horticulture, South China Agricultural University, Guangzhou, China
| | - Pengxu Liu
- Guangdong Litchi Engineering Research Center, College of Horticulture, South China Agricultural University, Guangzhou, China
| | - Lei Feng
- Guangdong Litchi Engineering Research Center, College of Horticulture, South China Agricultural University, Guangzhou, China
| | - Silin Zhong
- State Key Laboratory of Agrobiotechnology, School of Life Sciences, Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Biyan Zhou
- Guangdong Litchi Engineering Research Center, College of Horticulture, South China Agricultural University, Guangzhou, China
| |
Collapse
|
24
|
Peng Z, Li H, Sun G, Dai P, Geng X, Wang X, Zhang X, Wang Z, Jia Y, Pan Z, Chen B, Du X, He S. CottonGVD: A Comprehensive Genomic Variation Database for Cultivated Cottons. FRONTIERS IN PLANT SCIENCE 2021; 12. [PMID: 34992626 PMCID: PMC8724205 DOI: 10.3389/fpls.2021.803736] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Cultivated cottons are the most important economic crop, which produce natural fiber for the textile industry. In recent years, the genetic basis of several essential traits for cultivated cottons has been gradually elucidated by decoding their genomic variations. Although an abundance of resequencing data is available in public, there is still a lack of a comprehensive tool to exhibit the results of genomic variations and genome-wide association study (GWAS). To assist cotton researchers in utilizing these data efficiently and conveniently, we constructed the cotton genomic variation database (CottonGVD; http://120.78.174.209/ or http://db.cngb.org/cottonGVD). This database contains the published genomic information of three cultivated cotton species, the corresponding population variations (SNP and InDel markers), and the visualized results of GWAS for major traits. Various built-in genomic tools help users retrieve, browse, and query the variations conveniently. The database also provides interactive maps (e.g., Manhattan map, scatter plot, heatmap, and linkage disequilibrium block) to exhibit GWAS and expression GWAS results. Cotton researchers could easily focus on phenotype-associated loci visualization, and they are interested in and screen for candidate genes. Moreover, CottonGVD will continue to update by adding more data and functions.
Collapse
|
25
|
Zenda T, Liu S, Dong A, Li J, Wang Y, Liu X, Wang N, Duan H. Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value. FRONTIERS IN PLANT SCIENCE 2021; 12:774994. [PMID: 34925418 PMCID: PMC8672198 DOI: 10.3389/fpls.2021.774994] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 11/08/2021] [Indexed: 05/17/2023]
Abstract
Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.
Collapse
Affiliation(s)
- Tinashe Zenda
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
- Department of Crop Science, Faculty of Agriculture and Environmental Science, Bindura University of Science Education, Bindura, Zimbabwe
| | - Songtao Liu
- Academy of Agriculture and Forestry Sciences, Hebei North University, Zhangjiakou, China
| | - Anyi Dong
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Jiao Li
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Yafei Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Xinyue Liu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Nan Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Huijun Duan
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| |
Collapse
|
26
|
Ma Z, Zhang Y, Wu L, Zhang G, Sun Z, Li Z, Jiang Y, Ke H, Chen B, Liu Z, Gu Q, Wang Z, Wang G, Yang J, Wu J, Yan Y, Meng C, Li L, Li X, Mo S, Wu N, Ma L, Chen L, Zhang M, Si A, Yang Z, Wang N, Wu L, Zhang D, Cui Y, Cui J, Lv X, Li Y, Shi R, Duan Y, Tian S, Wang X. High-quality genome assembly and resequencing of modern cotton cultivars provide resources for crop improvement. Nat Genet 2021; 53:1385-1391. [PMID: 34373642 PMCID: PMC8423627 DOI: 10.1038/s41588-021-00910-2] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 07/08/2021] [Indexed: 12/01/2022]
Abstract
Cotton produces natural fiber for the textile industry. The genetic effects of genomic structural variations underlying agronomic traits remain unclear. Here, we generate two high-quality genomes of Gossypium hirsutum cv. NDM8 and Gossypium barbadense acc. Pima90, and identify large-scale structural variations in the two species and 1,081 G. hirsutum accessions. The density of structural variations is higher in the D-subgenome than in the A-subgenome, indicating that the D-subgenome undergoes stronger selection during species formation and variety development. Many structural variations in genes and/or regulatory regions potentially influencing agronomic traits were discovered. Of 446 significantly associated structural variations, those for fiber quality and Verticillium wilt resistance are located mainly in the D-subgenome and those for yield mainly in the A-subgenome. Our research provides insight into the role of structural variations in genotype-to-phenotype relationships and their potential utility in crop improvement. High-quality genomes of two cultivated tetraploid cottons Gossypium hirsutum cv. NDM8 and Gossypium barbadense acc. Pima90 and resequencing of 1,081 G. hirsutum accessions provide insights into the role of structural variations.
Collapse
Affiliation(s)
- Zhiying Ma
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China.
| | - Yan Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China.
| | - Liqiang Wu
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Guiyin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Zhengwen Sun
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Zhikun Li
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Yafei Jiang
- Novogene Bioinformatics Institute, Beijing, China
| | - Huifeng Ke
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Bin Chen
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Zhengwen Liu
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Qishen Gu
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Zhicheng Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Guoning Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Jun Yang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Jinhua Wu
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Yuanyuan Yan
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Chengsheng Meng
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Lihua Li
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Xiuxin Li
- Novogene Bioinformatics Institute, Beijing, China
| | - Shaojing Mo
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Nan Wu
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Limei Ma
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Liting Chen
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Man Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Aijun Si
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Zhanwu Yang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Nan Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Lizhu Wu
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Dongmei Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Yanru Cui
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Jing Cui
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Xing Lv
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Yang Li
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Rongkang Shi
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Yihong Duan
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China
| | - Shilin Tian
- Novogene Bioinformatics Institute, Beijing, China.
| | - Xingfen Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory for Crop Germplasm Resources of Hebei, Hebei Agricultural University, Baoding, China.
| |
Collapse
|
27
|
Chen B, Zhang Y, Sun Z, Liu Z, Zhang D, Yang J, Wang G, Wu J, Ke H, Meng C, Wu L, Yan Y, Cui Y, Li Z, Wu L, Zhang G, Wang X, Ma Z. Tissue-specific expression of GhnsLTPs identified via GWAS sophisticatedly coordinates disease and insect resistance by regulating metabolic flux redirection in cotton. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2021; 107:831-846. [PMID: 34008265 DOI: 10.1111/tpj.15349] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 05/08/2021] [Accepted: 05/12/2021] [Indexed: 05/26/2023]
Abstract
Cotton (Gossypium hirsutum) is constantly attacked by pathogens and insects. The most efficient control strategy is to develop resistant varieties using broad-spectrum gene resources. Several resistance loci harboured by superior varieties have been identified through genome-wide association studies. However, the key genes and/or loci have not been functionally identified. In this study, we identified a locus significantly associated with Verticillium wilt (VW) resistance, and within a 145.5-kb linkage disequilibrium, two non-specific lipid transfer protein genes (named GhnsLTPsA10) were highly expressed under Verticillium pathogen stress. The expression of GhnsLTPsA10 significantly increased in roots upon Verticillium dahliae stress but significantly decreased in leaves under insect attack. Furthermore, GhnsLTPsA10 played antagonistic roles in positively regulating VW and Fusarium wilt resistance and negatively mediating aphid and bollworm resistance in transgenic Arabidopsis and silenced cotton. By combining transcriptomic, histological and physiological analyses, we determined that GhnsLTPsA10-mediated phenylpropanoid metabolism further affected the balance of the downstream metabolic flux of flavonoid and lignin biosynthesis. The divergent expression of GhnsLTPsA10 in roots and leaves coordinated resistance of cotton against fungal pathogens and insects via the redirection of metabolic flux. In addition, GhnsLTPsA10 contributed to reactive oxygen species accumulation. Therefore, in this study, we elucidated the novel function of GhnsLTP and the molecular association between disease resistance and insect resistance, balanced by GhnsLTPsA10. This broadens our knowledge of the biological function of GhnsLTPsA10 in crops and provides a useful locus for genetic improvement of cotton.
Collapse
Affiliation(s)
- Bin Chen
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Yan Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Zhengwen Sun
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Zhengwen Liu
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Dongmei Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Jun Yang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Guoning Wang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Jinhua Wu
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Huifeng Ke
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Chengsheng Meng
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Lizhu Wu
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Yuanyuan Yan
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Yanru Cui
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Zhikun Li
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Liqiang Wu
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Guiyin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Xingfen Wang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Zhiying Ma
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| |
Collapse
|
28
|
Huang C, Shen C, Wen T, Gao B, Zhu D, Li D, Lin Z. Genome-wide association mapping for agronomic traits in an 8-way Upland cotton MAGIC population by SLAF-seq. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:2459-2468. [PMID: 33912997 DOI: 10.1007/s00122-021-03835-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 04/12/2021] [Indexed: 06/12/2023]
Abstract
One sub-MAGIC population was genotyped using SLAF-seq, and QTLs and candidate genes for agronomic traits were identified in Upland cotton. The agronomic traits of Upland cotton have serious impacts on cotton production, as well as economic benefits. To discover the genetic basis of important agronomic traits in Upland cotton, a subset MAGIC (multi-parent advanced generation inter-cross) population containing 372 lines (SMLs) was selected from an 8-way MAGIC population with 960 lines. The 372 lines and 8 parents were phenotyped in six environments and deeply genotyped by SLAF-seq with 60,495 polymorphic SNPs. The genetic diversity indexes of all SNPs were 0.324 and 0.362 for the parents and MAGIC lines, respectively. The LD decay distance of the SMLs was 600 kb (r2 = 0.1). Genome-wide association mapping was performed using 60,495 SNPs and the phenotypic data of the SMLs, and 177 SNPs were identified to be significantly associated with 9 stable agronomic traits in multiple environments. The identified SNPs were divided into 117 QTLs (quantitative trait loci) by LD decay distance, explaining 5.44% to 31.64% of the phenotypic variation. Among the 117 QTLs, 3 QTLs were stable in multiple environments, and 11 QTL regions were proven to have pleiotropism associated with multiple traits. Within QTL regions, 154 genes were preferentially expressed in correlated tissues, and 8 genes with known functions were identified as priori candidate genes. Two genes, GhACT1 and GhGASL3, reported to have clear functions, were, respectively, located in qFE-A05-4 and qFE-D04-3, two stable QTLs for FE. This study revealed the genetic basis of important agronomic traits of Upland cotton, and the results will facilitate molecular breeding in cotton.
Collapse
Affiliation(s)
- Cong Huang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Chao Shen
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Tianwang Wen
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Bin Gao
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - De Zhu
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Dingguo Li
- Institute of Crop Genetic and Breeding, Yangtze University, Jingzhou, 434025, Hubei, China.
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| |
Collapse
|
29
|
Gu Q, Ke H, Liu C, Lv X, Sun Z, Liu Z, Rong W, Yang J, Zhang Y, Wu L, Zhang G, Wang X, Ma Z. A stable QTL qSalt-A04-1 contributes to salt tolerance in the cotton seed germination stage. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:2399-2410. [PMID: 33928409 DOI: 10.1007/s00122-021-03831-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 03/30/2021] [Indexed: 06/12/2023]
Abstract
A stable QTL qSalt-A04-1 for salt tolerance in the cotton seed germination stage, and two candidate genes, GhGASA1 and GhADC2, that play negative roles by modulating the GA and PA signalling pathways, respectively, were identified. The successful transition of a seed into a seedling is a prerequisite for plant propagation and crop yield. Germination is a vulnerable stage in a plant's life cycle that is strongly affected by environmental conditions, such as salinity. In this study, we identified a novel quantitative trait locus (QTL) qRGR-A04-1 associated with the relative germination rate (RGR) after salt stress treatment based on a high-density genetic map under phytotron and field conditions, with LOD values that ranged from 6.65 to 16.83 and 6.11-12.63% phenotypic variations in all five environmental tests. Two candidate genes with significantly differential expression between the two parents were finally identified through RNA-seq and qRT-PCR analyses. Further functional analyses showed that GhGASA1- and GhADC2-overexpression lines were more sensitive to salt stress than wild-type Arabidopsis based on the regulation of the transcript levels of gibberellic acid (GA)- and polyamine (PA)- related genes in GA and PA biosynthesis and the reduction in the accumulation of GA and PA, respectively, under salt stress. Virus-induced gene silencing analysis showed that TRV:GASA1 and TRV:ADC2 were more tolerant to salt stress than TRV:00 based on the increased expression of GA synthesis genes and decreased H2O2 content, respectively. Taken together, our results suggested that QTL qRGR-A04-1 and its two harboured genes, GhGASA1 and GhADC2, are promising candidates for salt tolerance improvement in cotton.
Collapse
Affiliation(s)
- Qishen Gu
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Huifeng Ke
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Chenchen Liu
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Xing Lv
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Zhengwen Sun
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Zhengwen Liu
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Wei Rong
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Jun Yang
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Yan Zhang
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Liqiang Wu
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Guiyin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China
| | - Xingfen Wang
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China.
| | - Zhiying Ma
- State Key Laboratory of North China Crop Improvement and Regulation/North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, China.
| |
Collapse
|
30
|
Sun M, Zhang Z, Ren Z, Wang X, Sun W, Feng H, Zhao J, Zhang F, Li W, Ma X, Yang D. The GhSWEET42 Glucose Transporter Participates in Verticillium dahliae Infection in Cotton. FRONTIERS IN PLANT SCIENCE 2021; 12:690754. [PMID: 34386026 PMCID: PMC8353158 DOI: 10.3389/fpls.2021.690754] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 07/06/2021] [Indexed: 06/13/2023]
Abstract
The SWEET (sugars will eventually be exported transporter) proteins, a family of sugar transporters, mediate sugar diffusion across cell membranes. Pathogenic fungi can acquire sugars from plant cells to satisfy their nutritional demands for growth and infection by exploiting plant SWEET sugar transporters. However, the mechanism underlying the sugar allocation in cotton plants infected by Verticillium dahliae, the causative agent of Verticillium wilt, remains unclear. In this study, observations of the colonization of cotton roots by V. dahliae revealed that a large number of conidia had germinated at 48-hour post-inoculation (hpi) and massive hyphae had appeared at 96 hpi. The glucose content in the infected roots was significantly increased at 48 hpi. On the basis of an evolutionary analysis, an association analysis, and qRT-PCR assays, GhSWEET42 was found to be closely associated with V. dahliae infection in cotton. Furthermore, GhSWEET42 was shown to encode a glucose transporter localized to the plasma membrane. The overexpression of GhSWEET42 in Arabidopsis thaliana plants led to increased glucose content, and compromised their resistance to V. dahliae. In contrast, knockdown of GhSWEET42 expression in cotton plants by virus-induced gene silencing (VIGS) led to a decrease in glucose content, and enhanced their resistance to V. dahliae. Together, these results suggest that GhSWEET42 plays a key role in V. dahliae infection in cotton through glucose translocation, and that manipulation of GhSWEET42 expression to control the glucose level at the infected site is a useful method for inhibiting V. dahliae infection.
Collapse
Affiliation(s)
- Mengxi Sun
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Ministry of Agriculture and Rural Affairs, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Zhiqiang Zhang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Ministry of Agriculture and Rural Affairs, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Zhongying Ren
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Ministry of Agriculture and Rural Affairs, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xingxing Wang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Ministry of Agriculture and Rural Affairs, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Wenjie Sun
- Department of Plant Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Hongjie Feng
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Ministry of Agriculture and Rural Affairs, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Junjie Zhao
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Ministry of Agriculture and Rural Affairs, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Fei Zhang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Ministry of Agriculture and Rural Affairs, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wei Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Ministry of Agriculture and Rural Affairs, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Xiongfeng Ma
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Ministry of Agriculture and Rural Affairs, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Daigang Yang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Ministry of Agriculture and Rural Affairs, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| |
Collapse
|
31
|
Jiang X, Fan L, Li P, Zou X, Zhang Z, Fan S, Gong J, Yuan Y, Shang H. Co-expression network and comparative transcriptome analysis for fiber initiation and elongation reveal genetic differences in two lines from upland cotton CCRI70 RIL population. PeerJ 2021; 9:e11812. [PMID: 34327061 PMCID: PMC8308610 DOI: 10.7717/peerj.11812] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 06/28/2021] [Indexed: 01/23/2023] Open
Abstract
Upland cotton is the most widely planted for natural fiber around the world, and either lint percentage (LP) or fiber length (FL) is the crucial component tremendously affecting cotton yield and fiber quality, respectively. In this study, two lines MBZ70-053 and MBZ70-236 derived from G. hirsutum CCRI70 recombinant inbred line (RIL) population presenting different phenotypes in LP and FL traits were chosen to conduct RNA sequencing on ovule and fiber samples, aiming at exploring the differences of molecular and genetic mechanisms during cotton fiber initiation and elongation stages. As a result, 249/128, 369/206, 4296/1198 and 3547/2129 up-/down- regulated differentially expressed genes (DGEs) in L2 were obtained at -3, 0, 5 and 10 days post-anthesis (DPA), respectively. Seven gene expression profiles were discriminated using Short Time-series Expression Miner (STEM) analysis; seven modules and hub genes were identified using weighted gene co-expression network analysis. The DEGs were mainly enriched into energetic metabolism and accumulating as well as auxin signaling pathway in initiation and elongation stages, respectively. Meanwhile, 29 hub genes were identified as 14-3-3ω , TBL35, GhACS, PME3, GAMMA-TIP, PUM-7, etc., where the DEGs and hub genes revealed the genetic and molecular mechanisms and differences during cotton fiber development.
Collapse
Affiliation(s)
- Xiao Jiang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Liqiang Fan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.,School of Agricultural Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Pengtao Li
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, Henan, China
| | - Xianyan Zou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Zhen Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Senmiao Fan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.,School of Agricultural Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.,School of Agricultural Sciences, Zhengzhou University, Zhengzhou, Henan, China
| |
Collapse
|
32
|
Wu L, Chang Y, Wang L, Wu J, Wang S. Genetic dissection of drought resistance based on root traits at the bud stage in common bean. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:1047-1061. [PMID: 33426592 DOI: 10.1007/s00122-020-03750-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 12/09/2020] [Indexed: 06/12/2023]
Abstract
A whole-genome resequencing-derived SNP dataset used for genome-wide association analysis revealed 196 loci significantly associated with drought stress based on root traits. Candidate genes identified in the regions of these loci include homologs of known drought resistance genes in A. thaliana. Drought is the main abiotic constraint of the production of common bean. Improved adaptation to drought environments has become a main goal of crop breeding due to the increasing scarcity of water that will occur in the future. The overall objective of our study was to identify genomic regions associated with drought resistance based on root traits using genome-wide association analysis. A natural population of 438 common bean accessions was evaluated for root traits: root surface area, root average diameter, root volume, total root length, taproot length, lateral root number, root dry weight, lateral root length, special root weight/length, using seed germination pouches under drought conditions and in well-watered environments. The coefficient of variation ranged from 11.24% (root average diameter) to 38.19% (root dry weight) in the well-watered environment and from 9.61% (root average diameter) to 39.05% (lateral root length) under drought stress. A whole-genome resequencing-derived SNP dataset revealed 196 loci containing 230 candidate SNPs associated with drought resistance. Seventeen candidate SNPs were simultaneously associated with more than two traits. Forty-one loci were simultaneously associated with more than two traits, and eleven loci were colocated with loci previously reported to be related to drought resistance. Candidate genes of the associated loci included the ABA-responsive element-binding protein family, MYB, NAC, the protein kinase superfamily, etc. These results revealed promising alleles linked to drought resistance or root traits, providing insights into the genetic basis of drought resistance and roots, which will be useful for common bean improvement.
Collapse
Affiliation(s)
- Lei Wu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yujie Chang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Lanfen Wang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jing Wu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Shumin Wang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| |
Collapse
|
33
|
Zhang S, Jiang Z, Chen J, Han Z, Chi J, Li X, Yu J, Xing C, Song M, Wu J, Liu F, Zhang X, Zhang J, Zhang J. The cellulose synthase (CesA) gene family in four Gossypium species: phylogenetics, sequence variation and gene expression in relation to fiber quality in Upland cotton. Mol Genet Genomics 2021; 296:355-368. [PMID: 33438049 DOI: 10.1007/s00438-020-01758-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 12/21/2020] [Indexed: 12/20/2022]
Abstract
Cellulose synthases (CesAs) are multi-subunit enzymes found on the plasma membrane of plant cells and play a pivotal role in cellulose production. The cotton fiber is mainly composed of cellulose, and the genetic relationships between CesA genes and cotton fiber yield and quality are not fully understood. Through a phylogenetic analysis, the CesA gene family in diploid Gossypium arboreum and Gossypium raimondii, as well as tetraploid Gossypium hirsutum ('TM-1') and Gossypium barbadense ('Hai-7124' and '3-79'), was divided into 6 groups and 15 sub-groups, with each group containing two to five homologous genes. Most CesA genes in the four species are highly collinear. Among the five cotton genomes, 440 and 1929 single nucleotide polymorphisms (SNPs) in the CesA gene family were identified in exons and introns, respectively, including 174 SNPs resulting in amino acid changes. In total, 484 homeologous SNPs between the A and D genomes were identified in diploids, while 142 SNPs were detected between the two tetraploids, with 32 and 82 SNPs existing within G. hirsutum and G. barbadense, respectively. Additionally, 74 quantitative trait loci near 18 GhCesA genes were associated with fiber quality. One to four GhCesA genes were differentially expressed (DE) in ovules at 0 and 3 days post anthesis (DPA) between two backcross inbred lines having different fiber lengths, but no DE genes were identified between these lines in developing fibers at 10 DPA. Twenty-seven SNPs in above DE CesA genes were detected among seven cotton lines, including one SNP in Ghi_A08G03061 that was detected in four G. hirsutum genotypes. This study provides the first comprehensive characterization of the cotton CesA gene family, which may play important roles in determining cotton fiber quality.
Collapse
Affiliation(s)
- Sujun Zhang
- Institute of Cotton, Hebei Academy of Agriculture and Forestry Sciences, Key Laboratory Biology and Genetic Improvement of Cotton in Huanghuaihai Semiarid Area, Hebei, China.,Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, 88003, USA
| | | | - Jie Chen
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, 88003, USA.,College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Zongfu Han
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, 88003, USA.,Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Jina Chi
- Institute of Cotton, Hebei Academy of Agriculture and Forestry Sciences, Key Laboratory Biology and Genetic Improvement of Cotton in Huanghuaihai Semiarid Area, Hebei, China.,Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, 88003, USA
| | - Xihua Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research (ICR), Chinese Academy of Agricultural Sciences (CAAS), Anyang, 455000, China
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research (ICR), Chinese Academy of Agricultural Sciences (CAAS), Anyang, 455000, China
| | - Chaozhu Xing
- State Key Laboratory of Cotton Biology, Institute of Cotton Research (ICR), Chinese Academy of Agricultural Sciences (CAAS), Anyang, 455000, China
| | - Mingzhou Song
- Department of Computer Science, New Mexico State University, Las Cruces, 88003, USA
| | - Jianyong Wu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research (ICR), Chinese Academy of Agricultural Sciences (CAAS), Anyang, 455000, China
| | - Feng Liu
- Department of Computer Science, New Mexico State University, Las Cruces, 88003, USA
| | - Xiangyun Zhang
- Institute of Cotton, Hebei Academy of Agriculture and Forestry Sciences, Key Laboratory Biology and Genetic Improvement of Cotton in Huanghuaihai Semiarid Area, Hebei, China.
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, 88003, USA.
| | - Jianhong Zhang
- Institute of Cotton, Hebei Academy of Agriculture and Forestry Sciences, Key Laboratory Biology and Genetic Improvement of Cotton in Huanghuaihai Semiarid Area, Hebei, China.
| |
Collapse
|
34
|
Li M, Geng L, Xie S, Wu D, Ye L, Zhang G. Genome-Wide Association Study on Total Starch, Amylose and Amylopectin in Barley Grain Reveals Novel Putative Alleles. Int J Mol Sci 2021; 22:ijms22020553. [PMID: 33430526 PMCID: PMC7828029 DOI: 10.3390/ijms22020553] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 12/21/2020] [Accepted: 12/26/2020] [Indexed: 11/18/2022] Open
Abstract
The content and composition of starch in cereal grains are closely related to yield. Few studies have been done on the identification of the genes or loci associated with these traits in barley. This study was conducted to identify the genes or loci controlling starch traits in barley grains, including total starch (TS), amylose (AC) and amylopectin (AP) contents. A large genotypic variation was found in all examined starch traits. GWAS analysis detected 13, 2, 10 QTLs for TS, AC and AP, respectively, and 5 of them were commonly shared by AP and TS content. qTS-3.1, qAC-6.2 and qAP-5.1 may explain the largest variation of TS, AC and AP, respectively. Four putative candidate genes, i.e., HORVU6Hr1G087920, HORVU5Hr1G011230, HORVU5Hr1G011270 and HORVU5Hr1G011280, showed the high expression in the developing barley grains when starch accumulates rapidly. The examined 100 barley accessions could be divided into two groups based on the polymorphism of the marker S5H_29297679, with 93 accessions having allele GG and seven accessions having AA. Moreover, significantly positive correlation was found between the number of favorable alleles of the identified QTLs and TS, AC, AP content. In conclusion, the identified loci or genes in this study could be useful for genetic improvement of grains starch in barley.
Collapse
Affiliation(s)
- Mengdi Li
- Institute of Crop Science, Zhejiang University, Hangzhou 310058, China; (M.L.); (L.G.); (S.X.); (D.W.); (G.Z.)
| | - La Geng
- Institute of Crop Science, Zhejiang University, Hangzhou 310058, China; (M.L.); (L.G.); (S.X.); (D.W.); (G.Z.)
| | - Shanggeng Xie
- Institute of Crop Science, Zhejiang University, Hangzhou 310058, China; (M.L.); (L.G.); (S.X.); (D.W.); (G.Z.)
| | - Dezhi Wu
- Institute of Crop Science, Zhejiang University, Hangzhou 310058, China; (M.L.); (L.G.); (S.X.); (D.W.); (G.Z.)
| | - Lingzhen Ye
- Institute of Crop Science, Zhejiang University, Hangzhou 310058, China; (M.L.); (L.G.); (S.X.); (D.W.); (G.Z.)
- Shandong (Linyi) Institute of Modern Agriculture, Zhejiang University, Linyi 276000, China
- Correspondence:
| | - Guoping Zhang
- Institute of Crop Science, Zhejiang University, Hangzhou 310058, China; (M.L.); (L.G.); (S.X.); (D.W.); (G.Z.)
- Shandong (Linyi) Institute of Modern Agriculture, Zhejiang University, Linyi 276000, China
| |
Collapse
|
35
|
Xu P, Guo Q, Meng S, Zhang X, Xu Z, Guo W, Shen X. Genome-wide association analysis reveals genetic variations and candidate genes associated with salt tolerance related traits in Gossypium hirsutum. BMC Genomics 2021; 22:26. [PMID: 33407102 PMCID: PMC7789578 DOI: 10.1186/s12864-020-07321-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Accepted: 12/10/2020] [Indexed: 12/12/2022] Open
Abstract
Background Cotton is more resistant to salt and drought stresses as compared to other field crops, which makes itself as a pioneer industrial crop in saline-alkali lands. However, abiotic stresses still negatively affect its growth and development significantly. It is therefore important to breed salt tolerance varieties which can help accelerate the improvement of cotton production. The development of molecular markers linked to causal genes has provided an effective and efficient approach for improving salt tolerance. Results In this study, a genome-wide association study (GWAS) of salt tolerance related traits at seedling stage was performed based on 2 years of phenotype identification for 217 representative upland cotton cultivars by genotyping-by-sequencing (GBS) platform. A total of 51,060 single nucleotide polymorphisms (SNPs) unevenly distributed among 26 chromosomes were screened across the cotton cultivars, and 25 associations with 27 SNPs scattered over 12 chromosomes were detected significantly (−log10p > 4) associated with three salt tolerance related traits in 2016 and 2017. Among these, the associations on chromosome A13 and D08 for relative plant height (RPH), A07 for relative shoot fresh matter weight (RSFW), A08 and A13 for relative shoot dry matter weight (RSDW) were expressed in both environments, indicating that they were likely to be stable quantitative trait loci (QTLs). A total of 12 salt-induced candidate genes were identified differentially expressed by the combination of GWAS and transcriptome analysis. Three promising genes were selected for preliminary function verification of salt tolerance. The increase of GH_A13G0171-silenced plants in salt related traits under salt stress indicated its negative function in regulating the salt stress response. Conclusions These results provided important genetic variations and candidate genes for accelerating the improvement of salt tolerance in cotton.
Collapse
Affiliation(s)
- Peng Xu
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China.,Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China
| | - Qi Guo
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China
| | - Shan Meng
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China
| | - Xianggui Zhang
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China
| | - Zhenzhen Xu
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China
| | - Wangzhen Guo
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China.
| | - Xinlian Shen
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China.
| |
Collapse
|
36
|
Xu P, Guo Q, Meng S, Zhang X, Xu Z, Guo W, Shen X. Genome-wide association analysis reveals genetic variations and candidate genes associated with salt tolerance related traits in Gossypium hirsutum. BMC Genomics 2021; 22:26. [PMID: 33407102 DOI: 10.21203/rs.3.rs-66236/v4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Accepted: 12/10/2020] [Indexed: 05/29/2023] Open
Abstract
BACKGROUND Cotton is more resistant to salt and drought stresses as compared to other field crops, which makes itself as a pioneer industrial crop in saline-alkali lands. However, abiotic stresses still negatively affect its growth and development significantly. It is therefore important to breed salt tolerance varieties which can help accelerate the improvement of cotton production. The development of molecular markers linked to causal genes has provided an effective and efficient approach for improving salt tolerance. RESULTS In this study, a genome-wide association study (GWAS) of salt tolerance related traits at seedling stage was performed based on 2 years of phenotype identification for 217 representative upland cotton cultivars by genotyping-by-sequencing (GBS) platform. A total of 51,060 single nucleotide polymorphisms (SNPs) unevenly distributed among 26 chromosomes were screened across the cotton cultivars, and 25 associations with 27 SNPs scattered over 12 chromosomes were detected significantly (-log10p > 4) associated with three salt tolerance related traits in 2016 and 2017. Among these, the associations on chromosome A13 and D08 for relative plant height (RPH), A07 for relative shoot fresh matter weight (RSFW), A08 and A13 for relative shoot dry matter weight (RSDW) were expressed in both environments, indicating that they were likely to be stable quantitative trait loci (QTLs). A total of 12 salt-induced candidate genes were identified differentially expressed by the combination of GWAS and transcriptome analysis. Three promising genes were selected for preliminary function verification of salt tolerance. The increase of GH_A13G0171-silenced plants in salt related traits under salt stress indicated its negative function in regulating the salt stress response. CONCLUSIONS These results provided important genetic variations and candidate genes for accelerating the improvement of salt tolerance in cotton.
Collapse
Affiliation(s)
- Peng Xu
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China
| | - Qi Guo
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China
| | - Shan Meng
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China
| | - Xianggui Zhang
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China
| | - Zhenzhen Xu
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China
| | - Wangzhen Guo
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China.
| | - Xinlian Shen
- Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China.
| |
Collapse
|
37
|
Song X, Zhu G, Hou S, Ren Y, Amjid MW, Li W, Guo W. Genome-Wide Association Analysis Reveals Loci and Candidate Genes Involved in Fiber Quality Traits Under Multiple Field Environments in Cotton ( Gossypium hirsutum). FRONTIERS IN PLANT SCIENCE 2021; 12:695503. [PMID: 34421946 PMCID: PMC8374309 DOI: 10.3389/fpls.2021.695503] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 06/16/2021] [Indexed: 05/17/2023]
Abstract
Fiber length, fiber strength, and fiber micronaire are the main fiber quality parameters in cotton. Thus, mining the elite and stable loci/alleles related to fiber quality traits and elucidating the relationship between the two may accelerate genetic improvement of fiber quality in cotton. Here, genome-wide association analysis (GWAS) was performed for fiber quality parameters based on phenotypic data, and 56,010 high-quality single nucleotide polymorphisms (SNPs) using 242 upland cotton accessions under 12 field environments were obtained. Phenotypic analysis exhibited that fiber length (FL) had a positive correlation with fiber strength (FS) and had a negative correlation with fiber micronaire (Mic). Genetic analysis also indicated that FL, FS, and Mic had high heritability of more than 80%. A total of 67 stable quantitative trait loci (QTLs) were identified through GWAS analysis, including 31 for FL, 21 for FS, and 22 for Mic. Of them, three pairs homologous QTLs were detected between A and D subgenomes, and seven co-located QTLs with two fiber quality parameters were found. Compared with the reported QTLs, 34 co-located with previous studies, and 33 were newly revealed. Integrated with transcriptome analysis, we selected 256, 244, and 149 candidate genes for FL, FS, and Mic, respectively. Gene Ontology (GO) analysis showed that most of the genes located in QTLs interval of the three fiber quality traits were involved in sugar biosynthesis, sugar metabolism, microtubule, and cytoskeleton organization, which played crucial roles in fiber development. Through correlation analysis between haplotypes and phenotypes, three genes (GH_A05G1494, GH_D11G3097, and GH_A05G1082) predominately expressed in fiber development stages were indicated to be potentially responsible for FL, FS, and Mic, respectively. The GH_A05G1494 encoded a protein containing SGS-domain, which is related to tubulin-binding and ubiquitin-protein ligase binding. The GH_D11G3097 encoded 20S proteasome beta subunit G1, and was involved in the ubiquitin-dependent protein catabolic process. The GH_A05G1082 encoded RAN binding protein 1 with a molecular function of GTPase activator activity. These results provide new insights and candidate loci/genes for the improvement of fiber quality in cotton.
Collapse
|
38
|
Geng X, Sun G, Qu Y, Sarfraz Z, Jia Y, He S, Pan Z, Sun J, Iqbal MS, Wang Q, Qin H, Liu J, Liu H, Yang J, Ma Z, Xu D, Yang J, Zhang J, Li Z, Cai Z, Zhang X, Zhang X, Zhou G, Li L, Zhu H, Wang L, Pang B, Du X. Genome-wide dissection of hybridization for fiber quality- and yield-related traits in upland cotton. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 104:1285-1300. [PMID: 32996179 PMCID: PMC7756405 DOI: 10.1111/tpj.14999] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 07/14/2020] [Accepted: 09/03/2020] [Indexed: 06/11/2023]
Abstract
An evaluation of combining ability can facilitate the selection of suitable parents and superior F1 hybrids for hybrid cotton breeding, although the molecular genetic basis of combining ability has not been fully characterized. In the present study, 282 female parents were crossed with four male parents in accordance with the North Carolina II mating scheme to generate 1128 hybrids. The parental lines were genotyped based on restriction site-associated DNA sequencing and 306 814 filtered single nucleotide polymorphisms were used for genome-wide association analysis involving the phenotypes, general combining ability (GCA) values, and specific combining ability values of eight fiber quality- and yield-related traits. The main results were: (i) all parents could be clustered into five subgroups based on population structure analyses and the GCA performance of the female parents had significant differences between subgroups; (ii) 20 accessions with a top 5% GCA value for more than one trait were identified as elite parents for hybrid cotton breeding; (iii) 120 significant single nucleotide polymorphisms, clustered into 66 quantitative trait loci, such as the previously reported Gh_A07G1769 and GhHOX3 genes, were found to be significantly associated with GCA; and (iv) identified quantitative trait loci for GCA had a cumulative effect on GCA of the accessions. Overall, our results suggest that pyramiding the favorable loci for GCA may improve the efficiency of hybrid cotton breeding.
Collapse
Affiliation(s)
- Xiaoli Geng
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
| | - Gaofei Sun
- Anyang Institute of TechnologyAnyang455000China
| | - Yujie Qu
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Zareen Sarfraz
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Yinhua Jia
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
| | - Shoupu He
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
| | - Zhaoe Pan
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Junling Sun
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Muhammad S. Iqbal
- Cotton Research StationAyub Agricultural Research InstituteFaisalabad38000Pakistan
| | - Qinglian Wang
- Henan Institute of Science and TechnologyXinxiang453003China
| | - Hongde Qin
- Cash Crop InstituteHubei Academy of Agricultural SciencesWuhan430000China
| | - Jinhai Liu
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | - Hui Liu
- Jing Hua Seed Industry Technologies IncJingzhou434000China
| | - Jun Yang
- Cotton Research Institute of Jiangxi ProvinceJiujiang332000China
| | - Zhiying Ma
- Key Laboratory of Crop Germplasm Resources of HebeiHebei Agricultural UniversityBaoding071000China
| | - Dongyong Xu
- Guoxin Rural Technical Service AssociationHejian062450China
| | - Jinlong Yang
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | | | - Zhikun Li
- Key Laboratory of Crop Germplasm Resources of HebeiHebei Agricultural UniversityBaoding071000China
| | - Zhongmin Cai
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | - Xuelin Zhang
- Hunan Cotton Research InstituteChangde415000China
| | - Xin Zhang
- Henan Institute of Science and TechnologyXinxiang453003China
| | - Guanyin Zhou
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | - Lin Li
- Zhongli Company of ShandongDongying257000China
| | - Haiyong Zhu
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Liru Wang
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Baoyin Pang
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Xiongming Du
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
| |
Collapse
|
39
|
Gu Q, Ke H, Liu Z, Lv X, Sun Z, Zhang M, Chen L, Yang J, Zhang Y, Wu L, Li Z, Wu J, Wang G, Meng C, Zhang G, Wang X, Ma Z. A high-density genetic map and multiple environmental tests reveal novel quantitative trait loci and candidate genes for fibre quality and yield in cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:3395-3408. [PMID: 32894321 DOI: 10.1007/s00122-020-03676-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 08/21/2020] [Indexed: 05/18/2023]
Abstract
A high-density linkage map of an intraspecific RIL population was constructed using 6187 bins to identify QTLs for fibre quality- and yield-related traits in upland cotton by whole-genome resequencing. Good fibre quality and high yield are important production goals in cotton (Gossypium hirsutum L.), which is a leading natural fibre crop worldwide. However, a greater understanding of the genetic variants underlying fibre quality- and yield-related traits is still required. In this study, a large-scale population including 588 F7 recombinant inbred lines, derived from an intraspecific cross between the upland cotton cv. Nongdamian13, which exhibits high quality, and Nongda601, which exhibits a high yield, was genotyped by using 232,946 polymorphic single-nucleotide polymorphisms obtained via a whole-genome resequencing strategy with 4.3-fold genome coverage. We constructed a high-density bin linkage map containing 6187 bin markers spanning 4478.98 cM with an average distance of 0.72 cM. We identified 58 individual quantitative trait loci (QTLs) and 25 QTL clusters harbouring 94 QTLs, and 119 previously undescribed QTLs controlling 13 fibre quality and yield traits across eight environments. Importantly, the QTL counts for fibre quality in the Dt subgenome were more than two times that in the At subgenome, and chromosome D02 harboured the greatest number of QTLs and clusters. Furthermore, we discovered 24 stable QTLs for fibre quality and 12 stable QTLs for yield traits. Four novel major stable QTLs related to fibre length, fibre strength and lint percentage, and seven previously unreported candidate genes with significantly differential expression between the two parents were identified and validated by RNA-seq. Our research provides valuable information for improving the fibre quality and yield in cotton breeding.
Collapse
Affiliation(s)
- Qishen Gu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Huifeng Ke
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Zhengwen Liu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Xing Lv
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Zhengwen Sun
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Man Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Liting Chen
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Jun Yang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Yan Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Liqiang Wu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Zhikun Li
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Jinhua Wu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Guoning Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Chengsheng Meng
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Guiyin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Xingfen Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China.
| | - Zhiying Ma
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China.
| |
Collapse
|
40
|
Su J, Wang C, Ma Q, Zhang A, Shi C, Liu J, Zhang X, Yang D, Ma X. An RTM-GWAS procedure reveals the QTL alleles and candidate genes for three yield-related traits in upland cotton. BMC PLANT BIOLOGY 2020; 20:416. [PMID: 32894064 PMCID: PMC7487830 DOI: 10.1186/s12870-020-02613-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 08/18/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Cotton (Gossypium spp.) fiber yield is one of the key target traits, and improved fiber yield has always been thought of as an important objective in the breeding programs and production. Although some studies had been reported for the understanding of genetic bases for cotton yield-related traits, the detected quantitative trait loci (QTL) for the traits is still very limited. To uncover the whole-genome QTL controlling three yield-related traits in upland cotton (Gossypium hirsutum L.), phenotypic traits were investigated under four planting environments and 9244 single-nucleotide polymorphism linkage disequilibrium block (SNPLDB) markers were developed in an association panel consisting of 315 accessions. RESULTS A total of 53, 70 and 68 significant SNPLDB loci associated with boll number (BN), boll weight (BW) and lint percentage (LP), were respectively detected through a restricted two-stage multi-locus multi-allele genome-wide association study (RTM-GWAS) procedure in multiple environments. The haplotype/allele effects of the significant SNPLDB loci were estimated and the QTL-allele matrices were organized for offering the abbreviated genetic composition of the population. Among the significant SNPLDB loci, six of them were simultaneously identified in two or more single planting environments and were thought of as the stable SNPLDB loci. Additionally, a total of 115 genes were annotated in the nearby regions of the six stable SNPLDB loci, and 16 common potential candidate genes controlling target traits of them were predicted by two RNA-seq data. One of 16 genes (GH_D06G2161) was mainly expressed in the early ovule-development stages, and the stable SNPLDB locus (LDB_19_62926589) was mapped in its promoter region. CONCLUSION This study identified the QTL alleles and candidate genes that could provide important insights into the genetic basis of yield-related traits in upland cotton and might facilitate breeding cotton varieties with high yield.
Collapse
Affiliation(s)
- Junji Su
- Gansu Provincial Key Laboratory of Aridland Crop Science, College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
| | - Caixiang Wang
- Gansu Provincial Key Laboratory of Aridland Crop Science, College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
| | - Qi Ma
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, 832000, China
| | - Ai Zhang
- Gansu Provincial Key Laboratory of Aridland Crop Science, College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Chunhui Shi
- Gansu Provincial Key Laboratory of Aridland Crop Science, College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Juanjuan Liu
- Gansu Provincial Key Laboratory of Aridland Crop Science, College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Xianliang Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Delong Yang
- Gansu Provincial Key Laboratory of Aridland Crop Science, College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Xiongfeng Ma
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450001, China.
| |
Collapse
|
41
|
Liu W, Song C, Ren Z, Zhang Z, Pei X, Liu Y, He K, Zhang F, Zhao J, Zhang J, Wang X, Yang D, Li W. Genome-wide association study reveals the genetic basis of fiber quality traits in upland cotton (Gossypium hirsutum L.). BMC PLANT BIOLOGY 2020; 20:395. [PMID: 32854609 PMCID: PMC7450593 DOI: 10.1186/s12870-020-02611-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 08/18/2020] [Indexed: 05/08/2023]
Abstract
BACKGROUND Fiber quality is an important economic trait of cotton, and its improvement is a major goal of cotton breeding. To better understand the genetic mechanisms responsible for fiber quality traits, we conducted a genome-wide association study to identify and mine fiber-quality-related quantitative trait loci (QTLs) and genes. RESULTS In total, 42 single nucleotide polymorphisms (SNPs) and 31 QTLs were identified as being significantly associated with five fiber quality traits. Twenty-five QTLs were identified in previous studies, and six novel QTLs were firstly identified in this study. In the QTL regions, 822 genes were identified and divided into four clusters based on their expression profiles. We also identified two pleiotropic SNPs. The SNP locus i52359Gb was associated with fiber elongation, strength, length and uniformity, while i11316Gh was associated with fiber strength and length. Moreover, these two SNPs were nonsynonymous and located in genes Gh_D09G2376 and Gh_D06G1908, respectively. RT-qPCR analysis revealed that these two genes were preferentially expressed at one or more stages of cotton fiber development, which was consistent with the RNA-seq data. Thus, Gh_D09G2376 and Gh_D06G1908 may be involved in fiber developmental processes. CONCLUSIONS The findings of this study provide insights into the genetic bases of fiber quality traits, and the identified QTLs or genes may be applicable in cotton breeding to improve fiber quality.
Collapse
Affiliation(s)
- Wei Liu
- Collaborative Innovation Center of Henan Grain Crops, Agronomy College, Henan Agricultural University, Zhengzhou, 450002, China
| | - Chengxiang Song
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Zhongying Ren
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Zhiqiang Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Xiaoyu Pei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Yangai Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Kunlun He
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Fei Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Junjie Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Jie Zhang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China
| | - Xingxing Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China
| | - Daigang Yang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China
| | - Wei Li
- Collaborative Innovation Center of Henan Grain Crops, Agronomy College, Henan Agricultural University, Zhengzhou, 450002, China.
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China.
| |
Collapse
|
42
|
Shi Y, Liu A, Li J, Zhang J, Li S, Zhang J, Ma L, He R, Song W, Guo L, Lu Q, Xiang X, Gong W, Gong J, Ge Q, Shang H, Deng X, Pan J, Yuan Y. Examining two sets of introgression lines across multiple environments reveals background-independent and stably expressed quantitative trait loci of fiber quality in cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:2075-2093. [PMID: 32185421 PMCID: PMC7311500 DOI: 10.1007/s00122-020-03578-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 03/07/2020] [Indexed: 05/29/2023]
Abstract
Background-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported. Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum × G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI- and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.
Collapse
Affiliation(s)
- Yuzhen Shi
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Shaoqi Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jinfeng Zhang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Liujun Ma
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Rui He
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Weiwu Song
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Lixue Guo
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Quanwei Lu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Xianghui Xiang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
| |
Collapse
|
43
|
Zhang H, Chu Y, Dang P, Tang Y, Jiang T, Clevenger JP, Ozias-Akins P, Holbrook C, Wang ML, Campbell H, Hagan A, Chen C. Identification of QTLs for resistance to leaf spots in cultivated peanut (Arachis hypogaea L.) through GWAS analysis. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:2051-2061. [PMID: 32144466 DOI: 10.1007/s00122-020-03576-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 02/28/2020] [Indexed: 06/10/2023]
Abstract
Two QTLs on ChrB09 significantly associated with both early and late leaf spots were identified by genome-wide association study in the US peanut mini-core collection. Early leaf spot (ELS) and late leaf spot (LLS) are two serious peanut diseases in the USA, causing tens of millions of dollars of annual economic losses. However, the genetic factors underlying resistance to those diseases in peanuts have not been well-studied. We conducted a genome-wide association study for the two peanut diseases using Affymetrix version 2.0 SNP array with 120 genotypes mainly coming from the US peanut mini-core collection. A total of 46 quantitative trait loci (QTLs) were identified with phenotypic variation explained (PVE) from 10.19 to 24.11%, in which eighteen QTLs are for resistance to ELS and 28 QTLs for LLS. Among the 46 QTLs, there were four and two major QTLs with PVE higher than 16.99% for resistance ELS and LLS, respectively. Of the six major QTLs, five were located on the B sub-genome and only one was on the A sub-genome, which suggested that the B sub-genome has more potential resistance genomic regions than the A sub-genome. In addition, two genomic regions on chromosome B09 were found to provide significant resistance to both ELS and LLS. A total of 74 non-redundant genes were identified as resistance genes, among which, twelve candidate genes were in significant genomic regions including two candidate genes for both ELS and LLS, and other ten candidate genes for ELS. The QTLs and candidate genes obtained from this study will be useful to breed peanuts for resistances to the diseases.
Collapse
Affiliation(s)
- Hui Zhang
- Department of Crop, Soil, and Environmental Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ye Chu
- Center for Applied Genetic Technologies, University of Georgia, Tifton, GA, 31793, USA
| | - Phat Dang
- USDA-ARS National Peanut Research Laboratory, Dawson, GA, 39842, USA
| | - Yueyi Tang
- Department of Crop, Soil, and Environmental Sciences, Auburn University, Auburn, AL, 36849, USA
- Shandong Peanut Research Institute, Qingdao, 266100, China
| | - Tao Jiang
- Department of Crop, Soil, and Environmental Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Josh Paul Clevenger
- Center for Applied Genetic Technologies, University of Georgia, Tifton, GA, 31793, USA
| | - Peggy Ozias-Akins
- Center for Applied Genetic Technologies, University of Georgia, Tifton, GA, 31793, USA
| | - Corley Holbrook
- USDA-ARS Crop Genetics and Breeding Research, Tifton, GA, 31793, USA
| | - Ming Li Wang
- USDA-ARS Plant Genetic Resources Conservation, Griffin, GA, 30223, USA
| | - Howard Campbell
- Department of Entomology and Plant Pathology, Auburn University, Auburn, AL, 36849, USA
| | - Austin Hagan
- Department of Entomology and Plant Pathology, Auburn University, Auburn, AL, 36849, USA
| | - Charles Chen
- Department of Crop, Soil, and Environmental Sciences, Auburn University, Auburn, AL, 36849, USA.
| |
Collapse
|
44
|
Liu N, Huang L, Chen W, Wu B, Pandey MK, Luo H, Zhou X, Guo J, Chen H, Huai D, Chen Y, Lei Y, Liao B, Ren X, Varshney RK, Jiang H. Dissection of the genetic basis of oil content in Chinese peanut cultivars through association mapping. BMC Genet 2020; 21:60. [PMID: 32513099 PMCID: PMC7282078 DOI: 10.1186/s12863-020-00863-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 05/26/2020] [Indexed: 11/17/2022] Open
Abstract
Background Peanut is one of the primary sources for vegetable oil worldwide, and enhancing oil content is the main objective in several peanut breeding programs of the world. Tightly linked markers are required for faster development of high oil content peanut varieties through genomics-assisted breeding (GAB), and association mapping is one of the promising approaches for discovery of such associated markers. Results An association mapping panel consisting of 292 peanut varieties extensively distributed in China was phenotyped for oil content and genotyped with 583 polymorphic SSR markers. These markers amplified 3663 alleles with an average of 6.28 alleles per locus. The structure, phylogenetic relationship, and principal component analysis (PCA) indicated two subgroups majorly differentiating based on geographic regions. Genome-wide association analysis identified 12 associated markers including one (AGGS1014_2) highly stable association controlling up to 9.94% phenotypic variance explained (PVE) across multiple environments. Interestingly, the frequency of the favorable alleles for 12 associated markers showed a geographic difference. Two associated markers (AGGS1014_2 and AHGS0798) with 6.90–9.94% PVE were verified to enhance oil content in an independent RIL population and also indicated selection during the breeding program. Conclusion This study provided insights into the genetic basis of oil content in peanut and verified highly associated two SSR markers to facilitate marker-assisted selection for developing high-oil content breeding peanut varieties.
Collapse
Affiliation(s)
- Nian Liu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Li Huang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Weigang Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Bei Wu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Manish K Pandey
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), 502324, Hyderabad, India
| | - Huaiyong Luo
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Xiaojing Zhou
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Jianbin Guo
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Haiwen Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Dongxin Huai
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Yuning Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Yong Lei
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Boshou Liao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Xiaoping Ren
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), 502324, Hyderabad, India
| | - Huifang Jiang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, People's Republic of China.
| |
Collapse
|
45
|
Tong Z, Fang D, Chen X, Jiao F, Zhang Y, Li Y, Xiao B. Genome-wide association study of leaf chemistry traits in tobacco. BREEDING SCIENCE 2020; 70:253-264. [PMID: 32714047 PMCID: PMC7372018 DOI: 10.1270/jsbbs.19067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 10/27/2019] [Indexed: 06/11/2023]
Abstract
Leaf chemistry traits are some of the key factors influencing tobacco quality, which can be significantly reduced by lower chemical components in cured leaf. To improve tobacco quality through breeding, genetic diversity analysis, population structure analysis, and genome-wide association studies were performed in a panel of 347 tobacco germplasms and the markers associated with five leaf chemistry traits, including total sugar (TS), reducing sugar (RS), total nitrogen (TN), nicotine (NIC), and total potassium (TP) contents were identified. Four groups were classified at a genetic distance of 0.316 by genetic diversity analysis based on coefficient parameter NEI72 using a program NTSYS-pc2.10e, whereas four well-differentiated subpopulations were postulated in the 347 tobacco accessions. A total of 47 target trait-associated SNPs was detected in at least three environments as well as the best linear unbiased predictions (BLUPs) across all environments, among which two, two, four, six, and one highly suggestive associated SNPs were repeatedly detected in all environments and BLUPs for TS, RS, TN, NIC, and TP, respectively. On the basis of the phenotypic effects of the alleles corresponding to suggestive associated SNPs, five tobacco accessions harboring favorable alleles with elite phenotypic performance in leaf chemistry traits were identified. The results could facilitate quality tobacco breeding for higher leaf chemistry trait contents through molecular marker-assisted approaches.
Collapse
Affiliation(s)
- Zhijun Tong
- Key Laboratory of Tobacco Biotechnological Breeding, National Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming 650021, Yunnan, People’s Republic of China
| | - Dunhuang Fang
- Key Laboratory of Tobacco Biotechnological Breeding, National Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming 650021, Yunnan, People’s Republic of China
| | - Xuejun Chen
- Key Laboratory of Tobacco Biotechnological Breeding, National Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming 650021, Yunnan, People’s Republic of China
| | - Fangchan Jiao
- Key Laboratory of Tobacco Biotechnological Breeding, National Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming 650021, Yunnan, People’s Republic of China
| | - Yihan Zhang
- Key Laboratory of Tobacco Biotechnological Breeding, National Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming 650021, Yunnan, People’s Republic of China
| | - Yongping Li
- Key Laboratory of Tobacco Biotechnological Breeding, National Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming 650021, Yunnan, People’s Republic of China
| | - Bingguang Xiao
- Key Laboratory of Tobacco Biotechnological Breeding, National Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming 650021, Yunnan, People’s Republic of China
| |
Collapse
|
46
|
Wang F, Zhang J, Chen Y, Zhang C, Gong J, Song Z, Zhou J, Wang J, Zhao C, Jiao M, Liu A, Du Z, Yuan Y, Fan S, Zhang J. Identification of candidate genes for key fibre-related QTLs and derivation of favourable alleles in Gossypium hirsutum recombinant inbred lines with G. barbadense introgressions. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:707-720. [PMID: 31446669 PMCID: PMC7004909 DOI: 10.1111/pbi.13237] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 08/15/2019] [Indexed: 05/02/2023]
Abstract
Fine mapping QTLs and identifying candidate genes for cotton fibre-quality and yield traits would be beneficial to cotton breeding. Here, we constructed a high-density genetic map by specific-locus amplified fragment sequencing (SLAF-seq) to identify QTLs associated with fibre-quality and yield traits using 239 recombinant inbred lines (RILs), which was developed from LMY22 (a high-yield Gossypium hirsutumL. cultivar) × LY343 (a superior fibre-quality germplasm with G. barbadenseL. introgressions). The genetic map spanned 3426.57 cM, including 3556 SLAF-based SNPs and 199 SSR marker loci. A total of 104 QTLs, including 67 QTLs for fibre quality and 37 QTLs for yield traits, were identified with phenotypic data collected from 7 environments. Among these, 66 QTLs were co-located in 19 QTL clusters on 12 chromosomes, and 24 QTLs were detected in three or more environments and determined to be stable. We also investigated the genomic components of LY343 and their contributions to fibre-related traits by deep sequencing the whole genome of LY343, and we found that genomic components from G. hirsutum races (which entered LY343 via its G. barbadense parent) contributed more favourable alleles than those from G. barbadense. We further identified six putative candidate genes for stable QTLs, including Gh_A03G1147 (GhPEL6), Gh_D07G1598 (GhCSLC6) and Gh_D13G1921 (GhTBL5) for fibre-length QTLs and Gh_D03G0919 (GhCOBL4), Gh_D09G1659 (GhMYB4) and Gh_D09G1690 (GhMYB85) for lint-percentage QTLs. Our results provide comprehensive insight into the genetic basis of the formation of fibre-related traits and would be helpful for cloning fibre-development-related genes as well as for marker-assisted genetic improvement in cotton.
Collapse
Affiliation(s)
- Furong Wang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Jingxia Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Yu Chen
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Chuanyun Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Juwu Gong
- State Key Laboratory of Cotton BiologyKey Laboratory of Biological and Genetic Breeding of CottonMinistry of AgricultureInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangChina
| | - Zhangqiang Song
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Juan Zhou
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Jingjing Wang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Chengjie Zhao
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Mengjia Jiao
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Aiying Liu
- State Key Laboratory of Cotton BiologyKey Laboratory of Biological and Genetic Breeding of CottonMinistry of AgricultureInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangChina
| | - Zhaohai Du
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Youlu Yuan
- State Key Laboratory of Cotton BiologyKey Laboratory of Biological and Genetic Breeding of CottonMinistry of AgricultureInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangChina
| | - Shoujin Fan
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Jun Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
- College of Life SciencesShandong Normal UniversityJinanChina
| |
Collapse
|
47
|
Histone Deacetylase (HDAC) Gene Family in Allotetraploid Cotton and Its Diploid Progenitors: In Silico Identification, Molecular Characterization, and Gene Expression Analysis under Multiple Abiotic Stresses, DNA Damage and Phytohormone Treatments. Int J Mol Sci 2020; 21:ijms21010321. [PMID: 31947720 PMCID: PMC6981504 DOI: 10.3390/ijms21010321] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 12/31/2019] [Accepted: 01/01/2020] [Indexed: 01/11/2023] Open
Abstract
Histone deacetylases (HDACs) play a significant role in a plant’s development and response to various environmental stimuli by regulating the gene transcription. However, HDACs remain unidentified in cotton. In this study, a total of 29 HDACs were identified in allotetraploid Gossypium hirsutum, while 15 and 13 HDACs were identified in Gossypium arboretum and Gossypium raimondii, respectively. Gossypium HDACs were classified into three groups (reduced potassium dependency 3 (RPD3)/HDA1, HD2-like, and Sir2-like (SRT) based on their sequences, and Gossypium HDACs within each subgroup shared a similar gene structure, conserved catalytic domains and motifs. Further analysis revealed that Gossypium HDACs were under a strong purifying selection and were unevenly distributed on their chromosomes. Gene expression data revealed that G. hirsutumHDACs were differentially expressed in various vegetative and reproductive tissues, as well as at different developmental stages of cotton fiber. Furthermore, some G. hirsutum HDACs were co-localized with quantitative trait loci (QTLs) and single-nucleotide polymorphism (SNPs) of fiber-related traits, indicating their function in fiber-related traits. We also showed that G. hirsutum HDACs were differentially regulated in response to plant hormones (abscisic acid (ABA) and auxin), DNA damage agent (methyl methanesulfonate (MMS)), and abiotic stresses (cold, salt, heavy metals and drought), indicating the functional diversity and specification of HDACs in response to developmental and environmental cues. In brief, our results provide fundamental information regarding G.hirsutumHDACs and highlight their potential functions in cotton growth, fiber development and stress adaptations, which will be helpful for devising innovative strategies for the improvement of cotton fiber and stress tolerance.
Collapse
|
48
|
Zhang Z, Li J, Jamshed M, Shi Y, Liu A, Gong J, Wang S, Zhang J, Sun F, Jia F, Ge Q, Fan L, Zhang Z, Pan J, Fan S, Wang Y, Lu Q, Liu R, Deng X, Zou X, Jiang X, Liu P, Li P, Iqbal MS, Zhang C, Zou J, Chen H, Tian Q, Jia X, Wang B, Ai N, Feng G, Wang Y, Hong M, Li S, Lian W, Wu B, Hua J, Zhang C, Huang J, Xu A, Shang H, Gong W, Yuan Y. Genome-wide quantitative trait loci reveal the genetic basis of cotton fibre quality and yield-related traits in a Gossypium hirsutum recombinant inbred line population. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:239-253. [PMID: 31199554 PMCID: PMC6920336 DOI: 10.1111/pbi.13191] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 05/30/2019] [Accepted: 06/11/2019] [Indexed: 05/02/2023]
Abstract
Cotton is widely cultivated globally because it provides natural fibre for the textile industry and human use. To identify quantitative trait loci (QTLs)/genes associated with fibre quality and yield, a recombinant inbred line (RIL) population was developed in upland cotton. A consensus map covering the whole genome was constructed with three types of markers (8295 markers, 5197.17 centimorgans (cM)). Six fibre yield and quality traits were evaluated in 17 environments, and 983 QTLs were identified, 198 of which were stable and mainly distributed on chromosomes 4, 6, 7, 13, 21 and 25. Thirty-seven QTL clusters were identified, in which 92.8% of paired traits with significant medium or high positive correlations had the same QTL additive effect directions, and all of the paired traits with significant medium or high negative correlations had opposite additive effect directions. In total, 1297 genes were discovered in the QTL clusters, 414 of which were expressed in two RNA-Seq data sets. Many genes were discovered, 23 of which were promising candidates. Six important QTL clusters that included both fibre quality and yield traits were identified with opposite additive effect directions, and those on chromosome 13 (qClu-chr13-2) could increase fibre quality but reduce yield; this result was validated in a natural population using three markers. These data could provide information about the genetic basis of cotton fibre quality and yield and help cotton breeders to improve fibre quality and yield simultaneously.
Collapse
|
49
|
Gahlaut V, Jaiswal V, Singh S, Balyan HS, Gupta PK. Multi-Locus Genome Wide Association Mapping for Yield and Its Contributing Traits in Hexaploid Wheat under Different Water Regimes. Sci Rep 2019; 9:19486. [PMID: 31862891 PMCID: PMC6925107 DOI: 10.1038/s41598-019-55520-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Accepted: 11/29/2019] [Indexed: 11/20/2022] Open
Abstract
Multi-locus genome wide association study was undertaken using a set of 320 diverse spring wheat accessions, which were each genotyped for 9,626 SNPs. The association panel was grown in replicated trials in four environments [two each in irrigated (IR) and rainfed (RF) environments], and phenotypic data were recorded for five traits including days to heading, days to maturity, plant height, thousand grain weight and grain yield. Forty-six significant marker-trait associations (MTAs) were identified for five traits. These included 20 MTAs in IR and 19 MTAs in RF environments; seven additional MTAs were common to both the environments. Five of these MTAs were co-localized with previously known QTL/MTAs and the remaining MTAs were novel and add to the existing knowledge. Three desirable haplotypes for agronomic traits, one for improvement in RF environment and two for improvement in IR environment were identified. Eighteen (18) promising candidate genes (CGs) involved in seven different biological activities were also identified. The expression profiles of four (Trehalose-6-Phosphate, APETALA2/Ethylene-responsive factor, DNA-binding One Zinc Finger and Gibberellin-dioxygenases) of the 18 genes showed that they were induced by drought stress in the wheat seedlings. The MTAs, haplotypes and CG-based markers may be used in marker-assisted breeding for drought tolerance in wheat.
Collapse
Affiliation(s)
- Vijay Gahlaut
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, India
- Department of Plant Molecular Biology, University of Delhi, South Campus, New Delhi, India
| | - Vandana Jaiswal
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, India
- School of Life Sciences, Jawaharlal Nehru University, New Delhi, India
| | | | - H S Balyan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, India
| | - P K Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, India.
| |
Collapse
|
50
|
Wang Y, Li G, Guo X, Sun R, Dong T, Yang Q, Wang Q, Li C. Dissecting the genetic architecture of seed-cotton and lint yields in Upland cotton using genome-wide association mapping. BREEDING SCIENCE 2019; 69:611-620. [PMID: 31988625 PMCID: PMC6977443 DOI: 10.1270/jsbbs.19057] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 07/23/2019] [Indexed: 05/18/2023]
Abstract
Seed-cotton yield (SY) and lint yield (LY) are the most important yield traits of cotton. Thus, it is critical to dissect their genetic architecture. Upland cotton (Gossypium hirsutum) is widely grown worldwide. In this study, a genome-wide association mapping was performed based on the CottonSNP80K array to dissect the genetic architecture of SY and LY in Upland cotton. Twenty-three significant associations were detected within four environments, including 11 associated with SY and 12 associated with LY. Seven single nucleotide polymorphisms (SNPs), TM234, TM237, TM247, TM255, TM256, TM263, and TM264, were co-associated with the two traits, which may indicate pleiotropy or intergenic tight linkages. Five SNPs, TM13332, TM39771, TM57119, TM81653, and TM81660, were coincided with those of previous reports and could be used in marker-assisted selection. Combining functional annotations with expression analyses of the genes identified within 400 kb of the significantly associated SNPs, we hypothesize that the three genes, Gh_D05G1077 and Gh_D13G1571 for SY, and Gh_A11G0775 for LY, may have the potential to increase cotton yield. The results would provide useful information for understanding the genetic basis of yield traits in Upland cotton and for facilitating its high-yield breeding through molecular design.
Collapse
Affiliation(s)
- Yuanyuan Wang
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Guirong Li
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Xinlei Guo
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics,
Beijing 100081,
China
| | - Runrun Sun
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Tao Dong
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Qiuyue Yang
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Qinglian Wang
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Chengqi Li
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
- Corresponding author (e-mail: )
| |
Collapse
|