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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.
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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.
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Guo A, Li H, Huang Y, Ma X, Li B, Du X, Cui Y, Zhao N, Hua J. Yield-related quantitative trait loci identification and lint percentage hereditary dissection under salt stress in upland cotton. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024; 119:115-136. [PMID: 38573794 DOI: 10.1111/tpj.16747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 01/07/2024] [Accepted: 03/14/2024] [Indexed: 04/06/2024]
Abstract
Salinity is frequently mentioned as a major constraint in worldwide agricultural production. Lint percentage (LP) is a crucial yield-component in cotton lint production. While the genetic factors affect cotton yield in saline soils are still unclear. Here, we employed a recombinant inbred line population in upland cotton (Gossypium hirsutum L.) and investigated the effects of salt stress on five yield and yield component traits, including seed cotton yield per plant, lint yield per plant, boll number per plant, boll weight, and LP. Between three datasets of salt stress (E1), normal growth (E2), and the difference values dataset of salt stress and normal conditions (D-value), 87, 82, and 55 quantitative trait loci (QTL) were detectable, respectively. In total, five QTL (qLY-Chr6-2, qBNP-Chr4-1, qBNP-Chr12-1, qBNP-Chr15-5, qLP-Chr19-2) detected in both in E1 and D-value were salt related QTL, and three stable QTL (qLP-Chr5-3, qLP-Chr13-1, qBW-Chr5-5) were detected both in E1 and E2 across 3 years. Silencing of nine genes within a stable QTL (qLP-Chr5-3) highly expressed in fiber developmental stages increased LP and decreased fiber length (FL), indicating that multiple minor-effect genes clustered on Chromosome 5 regulate LP and FL. Additionally, the difference in LP caused by Gh_A05G3226 is mainly in transcription level rather than in the sequence difference. Moreover, silencing of salt related gene (GhDAAT) within qBNP-Chr4-1 decreased salt tolerance in cotton. Our findings shed light on the regulatory mechanisms underlining cotton salt tolerance and fiber initiation.
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Affiliation(s)
- Anhui Guo
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian District, Beijing, 100193, China
| | - Huijing Li
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian District, Beijing, 100193, China
| | - Yi Huang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Xiaoqing Ma
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian District, Beijing, 100193, China
| | - Bin Li
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian District, Beijing, 100193, China
| | - Xiaoqi Du
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian District, Beijing, 100193, China
| | - Yanan Cui
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian District, Beijing, 100193, China
| | - Nan Zhao
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian District, Beijing, 100193, China
| | - Jinping Hua
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian District, Beijing, 100193, China
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Wang Y, Guo X, Xu Y, Sun R, Cai X, Zhou Z, Qin T, Tao Y, Li B, Hou Y, Wang Q, Liu F. Genome-wide association study for boll weight in Gossypium hirsutum races. Funct Integr Genomics 2023; 23:331. [PMID: 37940771 DOI: 10.1007/s10142-023-01261-3] [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: 10/03/2023] [Revised: 10/21/2023] [Accepted: 10/23/2023] [Indexed: 11/10/2023]
Abstract
High yield has always been an essential target in almost all of the cotton breeding programs. Boll weight (BW) is a key component of cotton yield. Numerous linkage mapping and genome-wide association studies (GWAS) have been performed to understand the genetic mechanism of BW, but information on the markers/genes controlling BW remains limited. In this study, we conducted a GWAS for BW using 51,268 high-quality single-nucleotide polymorphisms (SNPs) and 189 Gossypium hirsutum accessions across five different environments. A total of 55 SNPs significantly associated with BW were detected, of which 29 and 26 were distributed in the A and D subgenomes, respectively. Five SNPs were simultaneously detected in two environments. For TM5655, TM8662, TM36371, and TM50258, the BW grouped by alleles of each SNP was significantly different. The ± 550 kb regions around these four key SNPs contained 262 genes. Of them, Gh_A02G1473, Gh_A10G1765, and Gh_A02G1442 were expressed highly at 0 to 1 days post-anthesis (dpa), - 3 to 0 dpa, and - 3 to 0 dpa in ovule of TM-1, respectively. They were presumed as the candidate genes for fiber cell differentiation, initiation, or elongation based on gene annotation of their homologs. Overall, these results supplemented valuable information for dissecting the genetic architecture of BW and might help to improve cotton yield through molecular marker-assisted selection breeding and molecular design breeding.
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Affiliation(s)
- Yuanyuan Wang
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Henan International Joint Laboratory of Functional Genomics and Molecular Breeding of Cotton, Henan Institute of Science and Technology, Xinxiang, 453003, China
| | - Xinlei Guo
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Henan International Joint Laboratory of Functional Genomics and Molecular Breeding of Cotton, Henan Institute of Science and Technology, Xinxiang, 453003, 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 Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Henan International Joint Laboratory of Functional Genomics and Molecular Breeding of Cotton, 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
| | - Zhongli Zhou
- 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
| | - Ye Tao
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Henan International Joint Laboratory of Functional Genomics and Molecular Breeding of Cotton, Henan Institute of Science and Technology, Xinxiang, 453003, China
| | - Baihui Li
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Henan International Joint Laboratory of Functional Genomics and Molecular Breeding of Cotton, Henan Institute of Science and Technology, Xinxiang, 453003, China
| | - Yuqing Hou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Qinglian Wang
- Collaborative Innovation Center of Modern Biological Breeding of Henan Province, Henan Key Laboratory Molecular Ecology and Germplasm Innovation of Cotton and Wheat, Henan International Joint Laboratory of Functional Genomics and Molecular Breeding of Cotton, 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.
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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.
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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
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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.
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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.
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Liu Q, Wang Y, Fu Y, Du L, Zhang Y, Wang Q, Sun R, Ai N, Feng G, Li C. Genetic dissection of lint percentage in short-season cotton using combined QTL mapping and RNA-seq. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:205. [PMID: 37668671 DOI: 10.1007/s00122-023-04453-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 08/23/2023] [Indexed: 09/06/2023]
Abstract
KEY MESSAGE In total, 17 QTLs for lint percentage in short-season cotton, including three stable QTLs, were detected. Twenty-eight differentially expressed genes located within the stable QTLs were identified, and two genes were validated by qRT-PCR. The breeding and use of short-season cotton have significant values in addressing the question of occupying farmlands with either cotton or cereals. However, the fiber yields of short-season cotton varieties are significantly lower than those of middle- and late-maturing varieties. How to effectively improve the fiber yield of short-season cotton has become a focus of cotton research. Here, a high-density genetic map was constructed using genome resequencing and an RIL population generated from the hybridization of two short-season cotton accessions, Dong3 and Dong4. The map contained 4960 bin markers across the 26 cotton chromosomes and spanned 3971.08 cM, with an average distance of 0.80 cM between adjacent markers. Based on the genetic map, quantitative trait locus (QTL) mapping for lint percentage (LP, %), an important yield component trait, was performed. In total, 17 QTLs for LP, including three stable QTLs, qLP-A02, qLP-D04, and qLP-D12, were detected. Three out of 11 non-redundant QTLs overlapped with previously reported QTLs, whereas the other eight were novel QTLs. A total of 28 differentially expressed genes associated with the three stable QTLs were identified using RNA-seq of ovules and fibers at different seed developmental stages from the parental materials. The two genes, Ghir_A02G017640 and Ghir_A02G018500, may be related to LP as determined by further qRT-PCR validation. This study provides useful information for the genetic dissection of LP and promotes the molecular breeding of short-season cotton.
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Affiliation(s)
- Qiao Liu
- School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, 453003, China
| | - Yuanyuan Wang
- School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, 453003, China
| | - Yuanzhi Fu
- School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, 453003, China
| | - Lei Du
- Life Science College, Yuncheng University, Yuncheng, 044000, China
| | - Yilin Zhang
- Life Science College, Yuncheng University, Yuncheng, 044000, China
| | - Qinglian Wang
- School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, 453003, China
| | - Runrun Sun
- School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, 453003, China
| | - Nijiang Ai
- Shihezi Academy of Agricultural Sciences, Shihezi, 832000, China
| | - Guoli Feng
- Shihezi Academy of Agricultural Sciences, Shihezi, 832000, China
| | - Chengqi Li
- Life Science College, Yuncheng University, Yuncheng, 044000, China.
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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.
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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
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Niu H, Kuang M, Huang L, Shang H, Yuan Y, Ge Q. Lint percentage and boll weight QTLs in three excellent upland cotton (Gossypium hirsutum): ZR014121, CCRI60, and EZ60. BMC PLANT BIOLOGY 2023; 23:179. [PMID: 37020180 PMCID: PMC10074700 DOI: 10.1186/s12870-023-04147-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 03/01/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND Upland cotton (Gossypium hirsutum L.) is the most economically important species in the cotton genus (Gossypium spp.). Enhancing the cotton yield is a major goal in cotton breeding programs. Lint percentage (LP) and boll weight (BW) are the two most important components of cotton lint yield. The identification of stable and effective quantitative trait loci (QTLs) will aid the molecular breeding of cotton cultivars with high yield. RESULTS Genotyping by target sequencing (GBTS) and genome-wide association study (GWAS) with 3VmrMLM were used to identify LP and BW related QTLs from two recombinant inbred line (RIL) populations derived from high lint yield and fiber quality lines (ZR014121, CCRI60 and EZ60). The average call rate of a single locus was 94.35%, and the average call rate of an individual was 92.10% in GBTS. A total of 100 QTLs were identified; 22 of them were overlapping with the reported QTLs, and 78 were novel QTLs. Of the 100 QTLs, 51 QTLs were for LP, and they explained 0.29-9.96% of the phenotypic variation; 49 QTLs were for BW, and they explained 0.41-6.31% of the phenotypic variation. One QTL (qBW-E-A10-1, qBW-C-A10-1) was identified in both populations. Six key QTLs were identified in multiple-environments; three were for LP, and three were for BW. A total of 108 candidate genes were identified in the regions of the six key QTLs. Several candidate genes were positively related to the developments of LP and BW, such as genes involved in gene transcription, protein synthesis, calcium signaling, carbon metabolism, and biosynthesis of secondary metabolites. Seven major candidate genes were predicted to form a co-expression network. Six significantly highly expressed candidate genes of the six QTLs after anthesis were the key genes regulating LP and BW and affecting cotton yield formation. CONCLUSIONS A total of 100 stable QTLs for LP and BW in upland cotton were identified in this study; these QTLs could be used in cotton molecular breeding programs. Putative candidate genes of the six key QTLs were identified; this result provided clues for future studies on the mechanisms of LP and BW developments.
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Affiliation(s)
- Hao Niu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Institute of Cotton Research, The Ministry of Agriculture, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Meng Kuang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Institute of Cotton Research, The Ministry of Agriculture, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Longyu Huang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Institute of Cotton Research, The Ministry of Agriculture, 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, Institute of Cotton Research, The Ministry of Agriculture, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, Henan, China.
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, Institute of Cotton Research, The Ministry of Agriculture, 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, Institute of Cotton Research, The Ministry of Agriculture, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
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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: 2] [Impact Index Per Article: 2.0] [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.
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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,
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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.
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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
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11
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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.
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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.
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12
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Niu H, Ge Q, Shang H, Yuan Y. Inheritance, QTLs, and Candidate Genes of Lint Percentage in Upland Cotton. Front Genet 2022; 13:855574. [PMID: 35450216 PMCID: PMC9016478 DOI: 10.3389/fgene.2022.855574] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 02/22/2022] [Indexed: 11/13/2022] Open
Abstract
Cotton (Gossypium spp.) is an important natural fiber plant. Lint percentage (LP) is one of the most important determinants of cotton yield and is a typical quantitative trait with high variation and heritability. Many cotton LP genetic linkages and association maps have been reported. This work summarizes the inheritance, quantitative trait loci (QTLs), and candidate genes of LP to facilitate LP genetic study and molecular breeding. More than 1439 QTLs controlling LP have been reported. Excluding replicate QTLs, 417 unique QTLs have been identified on 26 chromosomes, including 243 QTLs identified at LOD >3. More than 60 are stable, major effective QTLs that can be used in marker-assisted selection (MAS). More than 90 candidate genes for LP have been reported. These genes encode MYB, HOX, NET, and other proteins, and most are preferentially expressed during fiber initiation and elongation. A putative molecular regulatory model of LP was constructed and provides the foundation for the genetic study and molecular breeding of LP.
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Affiliation(s)
- Hao Niu
- 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, 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, 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, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
- *Correspondence: Haihong Shang, ; Youlu Yuan,
| | - 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, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
- *Correspondence: Haihong Shang, ; Youlu Yuan,
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13
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Gao Y, Chen Y, Song Z, Zhang J, Lv W, Zhao H, Huo X, Zheng L, Wang F, Zhang J, Zhang T. Comparative Dynamic Transcriptome Reveals the Delayed Secondary-Cell-Wall Thickening Results in Altered Lint Percentage and Fiber Elongation in a Chromosomal Segment Substitution Line of Cotton ( Gossypium hirsutum L.). FRONTIERS IN PLANT SCIENCE 2021; 12:756434. [PMID: 34759948 PMCID: PMC8573213 DOI: 10.3389/fpls.2021.756434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 09/23/2021] [Indexed: 06/13/2023]
Abstract
Lint percentage (LP) is an important yield component in cotton that is usually affected by initial fiber number and cell wall thickness. To explore how fiber cell wall development affects LP, phenotypic identification and dynamic transcriptome analysis were conducted using a single segment substitution line of chromosome 15 (SL15) that harbors a major quantitative trait locus (QTL) for LP. Compared to its recurrent parent LMY22, SL15 did not differ in initial fiber number, but the fiber cell wall thickness and single-fiber weight decreased significantly, altering LP. The comparative transcriptome profiles revealed that the secondary cell wall (SCW) development phase of SL15 was relatively delayed. Meanwhile, the expression of genes related to cell expansion decreased more slightly in SL15 with fiber development, resulting in relatively higher expression at SL15_25D than at LMY22_25D. SCW development-related genes, such as GhNACs and GhMYBs, in the putative NAC-MYB-CESA network differentially expressed at SL15_25D, along with the lower expression of CESA6, CSLC12, and CSLA2. The substituted chromosomal interval was further investigated, and found 6 of 146 candidate genes were differentially expressed in all four cell development periods including 10, 15, 20 and 25 DPA. Genetic variation and co-expression analysis showed that GH_D01G0052, GH_D01G0099, GH_D01G0100, and GH_D01G0140 may be important candidate genes associated with qLP-C15-1. Our results provide novel insights into cell wall development and its relationship with LP, which is beneficial for lint yield and fiber quality improvement.
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Affiliation(s)
- Yang Gao
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture and Rural Affairs, Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Yu Chen
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture and Rural Affairs, Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Zhangqiang Song
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture and Rural Affairs, Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Jingxia Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture and Rural Affairs, Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Wanyu Lv
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture and Rural Affairs, Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
- College of Life Sciences, Shandong Normal University, Jinan, China
| | - Han Zhao
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture and Rural Affairs, Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
- College of Life Sciences, Shandong Normal University, Jinan, China
| | - Xuehan Huo
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture and Rural Affairs, Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
- College of Life Sciences, Shandong Normal University, Jinan, China
| | - Ling Zheng
- College of Life Sciences, Shandong Normal University, Jinan, China
| | - Furong Wang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture and Rural Affairs, Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
- College of Life Sciences, Shandong Normal University, Jinan, China
| | - Jun Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture and Rural Affairs, Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
- College of Life Sciences, Shandong Normal University, Jinan, China
| | - Tianzhen Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
- Zhejiang Provincial Key Laboratory of Crop Genetic Resources, Institute of Crop Science, College of Agriculture and Biotechnology, Plant Precision Breeding Academy, Zhejiang University, Hangzhou, China
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14
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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.
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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.
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Zhu G, Hou S, Song X, Wang X, Wang W, Chen Q, Guo W. Genome-wide association analysis reveals quantitative trait loci and candidate genes involved in yield components under multiple field environments in cotton (Gossypium hirsutum). BMC PLANT BIOLOGY 2021; 21:250. [PMID: 34059007 PMCID: PMC8167989 DOI: 10.1186/s12870-021-03009-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 05/05/2021] [Indexed: 05/18/2023]
Abstract
BACKGROUND Numerous quantitative trait loci (QTLs) and candidate genes associated with yield-related traits have been identified in cotton by genome-wide association study (GWAS) analysis. However, most of the phenotypic data were from a single or few environments, and the stable loci remained to be validated under multiple field environments. RESULTS Here, 242 upland cotton accessions collected from different origins were continuously investigated for phenotypic data of four main yield components, including boll weight (BW) and lint percentage (LP) under 13 field environments, and boll number per plant (BN) and seed index (SI) under 11 environments. Correlation analysis revealed a positive correlation between BN and LP, BW and SI, while SI had a negative correlation with LP and BN. Genetic analysis indicated that LP had the highest heritability estimates of 94.97%, followed by 92.08% for SI, 86.09% for BW, and 72.92% for BN, indicating LP and SI were more suitable traits for genetic improvement. Based on 56,010 high-quality single nucleotide polymorphisms (SNPs) and GWAS analysis, a total of 95 non-redundant QTLs were identified, including 12 of BN, 23 of BW, 45 of LP, and 33 of SI, respectively. Of them, 10 pairs of homologous QTLs were detected between A and D sub-genomes. We also found that 15 co-located QTLs with more than two traits and 12 high-confidence QTLs were detected under more than six environments, respectively. Further, two NET genes (GH_A08G0716 and GH_A08G0783), located in a novel QTL hotspot (qtl24, qtl25 and qlt26) were predominately expressed in early fiber development stages, exhibited significant correlation with LP and SI. The GH_A07G1389 in the stable qtl19 region encoded a tetratricopeptide repeat (TPR)-like superfamily protein and was a homologous gene involved in short fiber mutant ligon lintless-y (Liy), implying important roles in cotton yield. CONCLUSIONS The present study provides a foundation for understanding the regulatory mechanisms of yield components and may enhance yield improvement through molecular breeding in cotton.
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Affiliation(s)
- Guozhong Zhu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Germplasm Enhancement and Application Engineering Research Center (Ministry of Education), Nanjing Agricultural University, Nanjing, 210095 China
| | - Sen Hou
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Germplasm Enhancement and Application Engineering Research Center (Ministry of Education), Nanjing Agricultural University, Nanjing, 210095 China
| | - Xiaohui Song
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Germplasm Enhancement and Application Engineering Research Center (Ministry of Education), Nanjing Agricultural University, Nanjing, 210095 China
| | - Xing Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Germplasm Enhancement and Application Engineering Research Center (Ministry of Education), Nanjing Agricultural University, Nanjing, 210095 China
| | - Wei Wang
- Institute of Agricultural Sciences in Coastal Area of Jiangsu Province, Yancheng, 224002 China
| | - Quanjia Chen
- Engineering Research Center for Cotton (the Ministry of Education), Xinjiang Agricultural University, Urumqi, 830052 China
| | - Wangzhen Guo
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Germplasm Enhancement and Application Engineering Research Center (Ministry of Education), Nanjing Agricultural University, Nanjing, 210095 China
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Gao L, Meng C, Yi T, Xu K, Cao H, Zhang S, Yang X, Zhao Y. Genome-wide association study reveals the genetic basis of yield- and quality-related traits in wheat. BMC PLANT BIOLOGY 2021; 21:144. [PMID: 33740889 PMCID: PMC7980635 DOI: 10.1186/s12870-021-02925-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Accepted: 03/11/2021] [Indexed: 05/08/2023]
Abstract
BACKGROUND Identifying the loci and dissecting the genetic architecture underlying wheat yield- and quality-related traits are essential for wheat breeding. A genome-wide association study was conducted using a high-density 90 K SNP array to analyze the yield- and quality-related traits of 543 bread wheat varieties. RESULTS A total of 11,140 polymorphic SNPs were distributed on 21 chromosomes, including 270 significant SNPs associated with 25 yield- and quality-related traits. Additionally, 638 putative candidate genes were detected near the significant SNPs based on BLUP data, including three (TraesCS7A01G482000, TraesCS4B01G343700, and TraesCS6B01G295400) related to spikelet number per spike, diameter of the first internode, and grain volume. The three candidate genes were further analyzed using stage- and tissue- specific gene expression data derived from an RNA-seq analysis. These genes are promising candidates for enhancing yield- and quality-related traits in wheat. CONCLUSIONS The results of this study provide a new insight to understand the genetic basis of wheat yield and quality. Furthermore, the markers detected in this study may be applicable for marker-assisted selection in wheat breeding programs.
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Affiliation(s)
- Le Gao
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071000, Hebei, China
| | - Chengsheng Meng
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071000, Hebei, China
| | - Tengfei Yi
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071000, Hebei, China
| | - Ke Xu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071000, Hebei, China
| | - Huiwen Cao
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071000, Hebei, China
| | - Shuhua Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071000, Hebei, China
| | - Xueju Yang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071000, Hebei, China.
| | - Yong Zhao
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071000, Hebei, China.
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17
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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.
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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.
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18
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Su X, Zhu G, Song X, Xu H, Li W, Ning X, Chen Q, Guo W. Genome-wide association analysis reveals loci and candidate genes involved in fiber quality traits in sea island cotton (Gossypium barbadense). BMC PLANT BIOLOGY 2020; 20:289. [PMID: 32571222 PMCID: PMC7310526 DOI: 10.1186/s12870-020-02502-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Accepted: 06/17/2020] [Indexed: 05/13/2023]
Abstract
BACKGROUND Sea island cotton (Gossypium barbadense) has markedly superior high quality fibers, which plays an important role in the textile industry and acts as a donor for upland cotton (G. hirsutum) fiber quality improvement. The genetic characteristics analysis and the identification of key genes will be helpful to understand the mechanism of fiber development and breeding utilization in sea island cotton. RESULTS In this study, 279 sea island cotton accessions were collected from different origins for genotyping and phenotyping fiber quality traits. A set of 6303 high quality single nucleotide polymorphisms (SNPs) were obtained by high-density CottonSNP80K array. The population characteristics showed that the sea island cotton accessions had wide genetic diversity and were clustered into three groups, with Group1 closely related to Menoufi, an original sea island cotton landrace, and Group2 and Group3 related to widely introduced accessions from Egypt, USA and Former Soviet Union. Further, we used 249 accessions and evaluated five fiber quality traits under normal and salt environments over 2 years. Except for fiber uniformity (FU), fiber length (FL) and fiber elongation (FE) were significantly decreased in salt conditions, while fiber strength (FS) and fiber micronaire (MIC) were increased. Based on 6303 SNPs and genome-wide association study (GWAS) analysis, a total of 34 stable quantitative trait loci (QTLs) were identified for the five fiber quality traits with 25 detected simultaneously under normal and salt environments. Gene Ontology (GO) analysis indicated that candidate genes in the 25 overlapped QTLs were enriched mostly in "cellular and biological process". In addition, "xylem development" and "response to hormone" pathways were also found. Haplotype analyses found that GB_A03G0335 encoding an E3 ubiquitin-protein ligase in QTL TM6004 had SNP variation (A/C) in gene region, was significantly correlated with FL, FS, FU, and FE, implying a crucial role in fiber quality. CONCLUSIONS The present study provides a foundation for genetic diversity of sea island cotton accessions and will contribute to fiber quality improvement in breeding practice.
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Affiliation(s)
- Xiujuan Su
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Engineering Research Center of Hybrid Cotton Development (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095 China
- Engineering Research Center for Cotton (the Ministry of Education), Xinjiang Agricultural University, Urumqi, 830052 China
| | - Guozhong Zhu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Engineering Research Center of Hybrid Cotton Development (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095 China
| | - Xiaohui Song
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Engineering Research Center of Hybrid Cotton Development (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095 China
| | - Haijiang Xu
- Institute of Industrial Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091 China
| | - Weixi Li
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Engineering Research Center of Hybrid Cotton Development (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095 China
| | - Xinzhu Ning
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, 832000 China
| | - Quanjia Chen
- Engineering Research Center for Cotton (the Ministry of Education), Xinjiang Agricultural University, Urumqi, 830052 China
| | - Wangzhen Guo
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Engineering Research Center of Hybrid Cotton Development (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095 China
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Gě Q, Cūi Y, Lǐ J, Gōng J, Lú Q, Lǐ P, Shí Y, Shāng H, Liú À, Dèng X, Pān J, Chén Q, Yuán Y, Gǒng W. Disequilibrium evolution of the Fructose-1,6-bisphosphatase gene family leads to their functional biodiversity in Gossypium species. BMC Genomics 2020; 21:379. [PMID: 32482161 PMCID: PMC7262775 DOI: 10.1186/s12864-020-6773-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 05/06/2020] [Indexed: 11/26/2022] Open
Abstract
Background Fructose-1,6-bisphosphatase (FBP) is a key enzyme in the plant sucrose synthesis pathway, in the Calvin cycle, and plays an important role in photosynthesis regulation in green plants. However, no systemic analysis of FBPs has been reported in Gossypium species. Results A total of 41 FBP genes from four Gossypium species were identified and analyzed. These FBP genes were sorted into two groups and seven subgroups. Results revealed that FBP family genes were under purifying selection pressure that rendered FBP family members as being conserved evolutionarily, and there was no tandem or fragmental DNA duplication in FBP family genes. Collinearity analysis revealed that a FBP gene was located in a translocated DNA fragment and the whole FBP gene family was under disequilibrium evolution that led to a faster evolutionary progress of the members in G. barbadense and in At subgenome than those in other Gossypium species and in the Dt subgenome, respectively, in this study. Through RNA-seq analyses and qRT-PCR verification, different FBP genes had diversified biological functions in cotton fiber development (two genes in 0 DPA and 1DPA ovules and four genes in 20–25 DPA fibers), in plant responses to Verticillium wilt onset (two genes) and to salt stress (eight genes). Conclusion The FBP gene family displayed a disequilibrium evolution pattern in Gossypium species, which led to diversified functions affecting not only fiber development, but also responses to Verticillium wilt and salt stress. All of these findings provide the foundation for further study of the function of FBP genes in cotton fiber development and in environmental adaptability.
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Affiliation(s)
- Qún Gě
- College of Agriculture, Engineering Research Centre of Cotton of Ministry of Education, Xinjiang Agricultural University, Urumqi, China, 311 Nongda East Road, Urumqi, 830052, China.,State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Yànli Cūi
- College of Agriculture, Engineering Research Centre of Cotton of Ministry of Education, Xinjiang Agricultural University, Urumqi, China, 311 Nongda East Road, Urumqi, 830052, China.,State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jùnwén Lǐ
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jǔwǔ Gōng
- College of Agriculture, Engineering Research Centre of Cotton of Ministry of Education, Xinjiang Agricultural University, Urumqi, China, 311 Nongda East Road, Urumqi, 830052, China.,State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quánwěi Lú
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China.,Research Base, State Key Laboratory of Cotton Biology, Anyang Institute of Technology, Anyang, China
| | - Péngtāo Lǐ
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China.,Research Base, State Key Laboratory of Cotton Biology, Anyang Institute of Technology, Anyang, China
| | - Yùzhēn Shí
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Hǎihóng Shāng
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China.,Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Àiyīng Liú
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiǎoyīng Dèng
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jìngtāo Pān
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qúanjiā Chén
- College of Agriculture, Engineering Research Centre of Cotton of Ministry of Education, Xinjiang Agricultural University, Urumqi, China, 311 Nongda East Road, Urumqi, 830052, China.
| | - Yǒulù Yuán
- College of Agriculture, Engineering Research Centre of Cotton of Ministry of Education, Xinjiang Agricultural University, Urumqi, China, 311 Nongda East Road, Urumqi, 830052, China. .,State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China. .,Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
| | - Wànkuí Gǒng
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China. .,Research Base, State Key Laboratory of Cotton Biology, Anyang Institute of Technology, Anyang, China.
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20
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Song C, Li W, Pei X, Liu Y, Ren Z, He K, Zhang F, Sun K, Zhou X, Ma X, Yang D. Dissection of the genetic variation and candidate genes of lint percentage by a genome-wide association study in upland cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:1991-2002. [PMID: 30982110 DOI: 10.1007/s00122-019-03333-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Accepted: 03/20/2019] [Indexed: 05/10/2023]
Abstract
A genome-wide associated study identified six novel QTLs for lint percentage. Two candidate genes underlying this trait were also detected. Increasing lint percentage (LP) is a core goal of cotton breeding. To better understand the genetic basis of LP, a genome-wide association study (GWAS) was conducted using 276 upland cotton accessions planted in multiple environments and genotyped with a CottonSNP63K array. After filtering, 10,660 high-quality single-nucleotide polymorphisms (SNPs) were retained. Population structure, principal component and neighbor-joining phylogenetic tree analyses divided the accessions into two subpopulations. These results along with linkage disequilibrium decay indicated accessions were not highly structured and exhibited weak relatedness. GWAS uncovered 23 polymorphic SNPs and 15 QTLs significantly associated with LP, with six new QTLs identified. Two candidate genes, Gh_D05G0313 and Gh_D05G1124, both contained one significant SNP, highly expressed during ovule and fiber development stages, implying that the two genes may act as the most promising regulators of LP. Furthermore, the phenotypic value of LP was found to be positively correlated with the number of favorable SNP alleles. These favorable alleles for LP identified in the study may be useful for improving lint yield.
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Affiliation(s)
- Chengxiang Song
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Wei Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Xiaoyu Pei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Yangai Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Zhongying Ren
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Kunlun He
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Fei Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Kuan Sun
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Xiaojian Zhou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Xiongfeng Ma
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
| | - Daigang Yang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
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21
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Dai P, Miao Y, He S, Pan Z, Jia Y, Cai Y, Sun J, Wang L, Pang B, Wang M, Du X. Identifying favorable alleles for improving key agronomic traits in upland cotton. BMC PLANT BIOLOGY 2019; 19:138. [PMID: 30975072 PMCID: PMC6458685 DOI: 10.1186/s12870-019-1725-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Accepted: 03/19/2019] [Indexed: 05/22/2023]
Abstract
BACKGROUND Gossypium hirsutum L. is grown worldwide and is the largest source of natural fiber crop. We focus on exploring the favorable alleles (FAs) for upland cotton varieties improvement, and further understanding the history of accessions selection and acumination of favorable allele during breeding. RESULTS The genetic basis of phenotypic variation has been studied. But the accumulation of favorable alleles in cotton breeding history in unknown, and potential favorable alleles to enhance key agronomic traits in the future cotton varieties have not yet been identified. Therefore, 419 upland cotton accessions were screened, representing a diversity of phenotypic variations of 7362 G. hirsutum, and 15 major traits were investigated in 6 environments. These accessions were categorized into 3 periods (early, medium, and modern) according to breeding history. All accessions were divided into two major groups using 299 polymorphic microsatellite markers: G1 (high fiber yield and quality, late maturity) and G2 (low fiber yield and quality, early maturity). The proportion of G1 genotype gradually increased from early to modern breeding periods. Furthermore, 21 markers (71 alleles) were significantly associated (-log P > 4) with 15 agronomic traits in multiple environments. Seventeen alleles were identified as FAs; these alleles accumulated more in the modern period than in other periods, consistent with their phenotypic variation trends in breeding history. Our results demonstrate that the favorable alleles accumulated through breeding effects, especially for common favorable alleles. However, the potential elite accessions could be rapidly screened by rare favorable alleles. CONCLUSION In our study, genetic variation and genome-wide associations for 419 upland cotton accessions were analyzed. Two favorable allele types were identified during three breeding periods, providing important information for yield/quality improvement of upland cotton germplasm.
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Affiliation(s)
- Panhong Dai
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000 Henan China
- Agricultural College, Yangtze University, Jingzhou, 434000 China
| | - Yuchen Miao
- State Key Laboratory of Cotton Biology, Henan Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, Kaifeng, 475000 China
| | - Shoupu He
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000 Henan China
| | - Zhaoe Pan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000 Henan China
| | - Yinhua Jia
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000 Henan China
| | - Yingfan Cai
- State Key Laboratory of Cotton Biology, Henan Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, Kaifeng, 475000 China
| | - Junling Sun
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000 Henan China
| | - Liru Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000 Henan China
| | - Baoyin Pang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000 Henan China
| | - Mi Wang
- Agricultural College, Yangtze University, Jingzhou, 434000 China
| | - Xiongming Du
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000 Henan China
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