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Qi G, Si Z, Xuan L, Han Z, Hu Y, Fang L, Dai F, Zhang T. Unravelling the genetic basis and regulation networks related to fibre quality improvement using chromosome segment substitution lines in cotton. PLANT BIOTECHNOLOGY JOURNAL 2024. [PMID: 39046162 DOI: 10.1111/pbi.14436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 07/02/2024] [Accepted: 07/06/2024] [Indexed: 07/25/2024]
Abstract
The elucidation of genetic architecture and molecular regulatory networks underlying complex traits remains a significant challenge in life science, largely due to the substantial background effects that arise from epistasis and gene-environment interactions. The chromosome segment substitution line (CSSL) is an ideal material for genetic and molecular dissection of complex traits due to its near-isogenic properties; yet a comprehensive analysis, from the basic identification of substitution segments to advanced regulatory network, is still insufficient. Here, we developed two cotton CSSL populations on the Gossypium hirsutum background, representing wide adaptation and high lint yield, with introgression from G. barbadense, representing superior fibre quality. We sequenced 99 CSSLs that demonstrated significant differences from G. hirsutum in fibre, and characterized 836 dynamic fibre transcriptomes in three crucial developmental stages. We developed a workflow for precise resolution of chromosomal substitution segments; the genome sequencing revealed substitutions collectively representing 87.25% of the G. barbadense genome. Together, the genomic and transcriptomic survey identified 18 novel fibre-quality-related quantitative trait loci with high genetic contributions and the comprehensive landscape of fibre development regulation. Furthermore, analysis determined unique cis-expression patterns in CSSLs to be the driving force for fibre quality alteration; building upon this, the co-expression regulatory network revealed biological relationships among the noted pathways and accurately described the molecular interactions of GhHOX3, GhRDL1 and GhEXPA1 during fibre elongation, along with reliable predictions for their interactions with GhTBA8A5. Our study will enhance more strategic employment of CSSL in crop molecular biology and breeding programmes.
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Affiliation(s)
- Guoan Qi
- Hainan Institute of Zhejiang University, Yazhou Bay Science and Technology City, Sanya, Hainan, China
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zhanfeng Si
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Lisha Xuan
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zegang Han
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yan Hu
- Hainan Institute of Zhejiang University, Yazhou Bay Science and Technology City, Sanya, Hainan, China
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Lei Fang
- Hainan Institute of Zhejiang University, Yazhou Bay Science and Technology City, Sanya, Hainan, China
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Fan Dai
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang, China
| | - Tianzhen Zhang
- Hainan Institute of Zhejiang University, Yazhou Bay Science and Technology City, Sanya, Hainan, China
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang, China
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Wang H, Cai X, Umer MJ, Xu Y, Hou Y, Zheng J, Liu F, Wang K, Chen M, Ma S, Yu J, Zhou Z. Genetic Analysis of Cotton Fiber Traits in Gossypium Hybrid Lines. PHYSIOLOGIA PLANTARUM 2024; 176:e14442. [PMID: 39030776 DOI: 10.1111/ppl.14442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 04/25/2024] [Indexed: 07/22/2024]
Abstract
Cotton plays a crucial role in the progress of the textile industry and the betterment of human life by providing natural fibers. In our study, we explored the genetic determinants of cotton architecture and fiber yield and quality by crossbreeding Gossypium hirsutum and Gossypium barbadense, creating a recombinant inbred line (RIL) population. Utilizing SNP markers, we constructed an extensive genetic map encompassing 7,730 markers over 2,784.2 cM. We appraised two architectural and seven fiber traits within six environments, identifying 58 QTLs, of which 49 demonstrated stability across these environments. These encompassed QTLs for traits such as lint percentage (LP), boll weight (BW), fiber strength (STRENGTH), seed index (SI), and micronaire (MIC), primarily located on chromosomes chr-A07, chr-D06, and chr-D07. Notably, chr-D07 houses a QTL region affecting SI, corroborated by multiple studies. Within this region, the genes BZIP043 and SEP2 were identified as pivotal, with SEP2 particularly showing augmented expression in developing ovules. These discoveries contribute significantly to marker-assisted selection, potentially elevating both the yield and quality of cotton fiber production. These findings provide valuable insights into marker-assisted breeding strategies, offering crucial information to enhance fiber yield and quality in cotton production.
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Affiliation(s)
- Heng Wang
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization/Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, Henan, China
| | - Xiaoyan Cai
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization/Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, Henan, China
- Hainan Yazhou Bay Seed Laboratory, Sanya 572024, China/ National Nanfan Research Institute (Sanya), Chinese Academy of Agriculture Sciences, Sanya, China
- Henan International Joint Laboratory of Cotton Biology, Anyang, Henan, China
| | - Muhammad Jawad Umer
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization/Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, Henan, China
| | - Yanchao Xu
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization/Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, Henan, China
| | - Yuqing Hou
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization/Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, Henan, China
- Henan International Joint Laboratory of Cotton Biology, Anyang, Henan, China
| | - Jie Zheng
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization/Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, Henan, China
- Hainan Yazhou Bay Seed Laboratory, Sanya 572024, China/ National Nanfan Research Institute (Sanya), Chinese Academy of Agriculture Sciences, Sanya, China
- Henan International Joint Laboratory of Cotton Biology, Anyang, Henan, China
| | - Fang Liu
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization/Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, Henan, China
- Hainan Yazhou Bay Seed Laboratory, Sanya 572024, China/ National Nanfan Research Institute (Sanya), Chinese Academy of Agriculture Sciences, Sanya, China
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou, China
- Henan International Joint Laboratory of Cotton Biology, Anyang, Henan, China
| | - Kunbo Wang
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization/Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, Henan, China
| | - Mengshan Chen
- Chinese Academy of Agricultural Science, Beijing, China
| | | | - Jingzhong Yu
- Standing Committee of the People's Congress of Jiangsu Province, Nanjing, China
| | - Zhongli Zhou
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization/Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, Henan, China
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Liú R, Xiāo X, Gōng J, Lǐ J, Yán H, Gě Q, Lú Q, Lǐ P, Pān J, Shāng H, Shí Y, Chén Q, Yuán Y, Gǒng W. Genetic linkage analysis of stable QTLs in Gossypium hirsutum RIL population revealed function of GhCesA4 in fiber development. J Adv Res 2023:S2090-1232(23)00379-X. [PMID: 38065406 DOI: 10.1016/j.jare.2023.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/27/2023] [Accepted: 12/02/2023] [Indexed: 02/12/2024] Open
Abstract
INTRODUCTION Upland cotton is an important allotetrapolyploid crop providing natural fibers for textile industry. Under the present high-level breeding and production conditions, further simultaneous improvement of fiber quality and yield is facing unprecedented challenges due to their complex negative correlations. OBJECTIVES The study was to adequately identify quantitative trait loci (QTLs) and dissect how they orchestrate the formation of fiber quality and yield. METHODS A high-density genetic map (HDGM) based on an intraspecific recombinant inbred line (RIL) population consisting of 231 individuals was used to identify QTLs and QTL clusters of fiber quality and yield traits. The weighted gene correlation network analysis (WGCNA) package in R software was utilized to identify WGCNA network and hub genes related to fiber development. Gene functions were verified via virus-induced gene silencing (VIGS) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 strategies. RESULTS An HDGM consisting of 8045 markers was constructed spanning 4943.01 cM of cotton genome. A total of 295 QTLs were identified based on multi-environmental phenotypes. Among 139 stable QTLs, including 35 newly identified ones, seventy five were of fiber quality and 64 yield traits. A total of 33 QTL clusters harboring 74 QTLs were identified. Eleven candidate hub genes were identified via WGCNA using genes in all stable QTLs and QTL clusters. The relative expression profiles of these hub genes revealed their correlations with fiber development. VIGS and CRISPR/Cas9 edition revealed that the hub gene cellulose synthase 4 (GhCesA4, GH_D07G2262) positively regulate fiber length and fiber strength formation and negatively lint percentage. CONCLUSION Multiple analyses demonstrate that the hub genes harbored in the QTLs orchestrate the fiber development. The hub gene GhCesA4 has opposite pleiotropic effects in regulating trait formation of fiber quality and yield. The results facilitate understanding the genetic basis of negative correlation between cotton fiber quality and yield.
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Affiliation(s)
- Ruìxián Liú
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China; Engineering Research Centre of Cotton, Ministry of Education, College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, Xinjiang, China
| | - Xiànghuī Xiāo
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China; Engineering Research Centre of Cotton, Ministry of Education, College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, Xinjiang, China; College of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang 455000, Henan, China
| | - Jǔwǔ Gōng
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China; Zhengzhou Research Base, National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou University, Zhengzhou 450001, Henan, China
| | - Jùnwén Lǐ
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China; Zhengzhou Research Base, National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou University, Zhengzhou 450001, Henan, China
| | - Hàoliàng Yán
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Qún Gě
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China; Zhengzhou Research Base, National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou University, Zhengzhou 450001, Henan, China
| | - Quánwěi Lú
- College of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang 455000, Henan, China
| | - Péngtāo Lǐ
- College of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang 455000, Henan, China
| | - Jìngtāo Pān
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Hǎihóng Shāng
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China; Zhengzhou Research Base, National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou University, Zhengzhou 450001, Henan, China
| | - Yùzhēn Shí
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Qúanjiā Chén
- Engineering Research Centre of Cotton, Ministry of Education, College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, Xinjiang, China.
| | - Yǒulù Yuán
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China; Engineering Research Centre of Cotton, Ministry of Education, College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, Xinjiang, China; Zhengzhou Research Base, National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou University, Zhengzhou 450001, Henan, China.
| | - Wànkuí Gǒng
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, 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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Gowda SA, Shrestha N, Harris TM, Phillips AZ, Fang H, Sood S, Zhang K, Bourland F, Bart R, Kuraparthy V. Identification and genomic characterization of major effect bacterial blight resistance locus (BB-13) in Upland cotton (Gossypium hirsutum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:4421-4436. [PMID: 36208320 DOI: 10.1007/s00122-022-04229-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
Identification and genomic characterization of major resistance locus against cotton bacterial blight (CBB) using GWAS and linkage mapping to enable genomics-based development of durable CBB resistance and gene discovery in cotton. Cotton bacterial leaf blight (CBB), caused by Xanthomonas citri subsp. malvacearum (Xcm), has periodically been a damaging disease in the USA. Identification and deployment of genetic resistance in cotton cultivars is the most economical and efficient means of reducing crop losses due to CBB. In the current study, genome-wide association study (GWAS) of CBB resistance using an elite diversity panel of 380 accessions, genotyped with the cotton single nucleotide polymorphism (SNP) 63 K array, and phenotyped with race-18 of CBB, localized the CBB resistance to a 2.01-Mb region in the long arm of chromosome D02. Molecular genetic mapping using an F6 recombinant inbred line (RIL) population showed the CBB resistance in cultivar Arkot 8102 was controlled by a single locus (BB-13). The BB-13 locus was mapped within the 0.95-cM interval near the telomeric region in the long arm of chromosome D02. Flanking SNP markers, i04890Gh and i04907Gh of the BB-13 locus, identified from the combined linkage analysis and GWAS, targeted it to a 371-Kb genomic region. Candidate gene analysis identified thirty putative gene sequences in the targeted genomic region. Nine of these putative genes and two NBS-LRR genes adjacent to the targeted region were putatively involved in plant disease resistance and are possible candidate genes for BB-13 locus. Genetic mapping and genomic targeting of the BB13 locus in the current study will help in cloning the CBB-resistant gene and establishing the molecular genetic architecture of the BB-13 locus towards developing durable resistance to CBB in cotton.
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Affiliation(s)
- S Anjan Gowda
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA
| | - Navin Shrestha
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA
| | - Taylor M Harris
- Donald Danforth Plant Science Center, 975 N Warson Rd, St Louis, MO, 63132, USA
- Division of Biology & Biomedical Sciences, Washington University in St. Louis, St Louis, MO, 63110, USA
| | - Anne Z Phillips
- Donald Danforth Plant Science Center, 975 N Warson Rd, St Louis, MO, 63132, USA
| | - Hui Fang
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA
| | - Shilpa Sood
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA
| | - Kuang Zhang
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA
| | - Fred Bourland
- NE Research & Extension Center, Crop, Soil, and Environmental Sciences, University of Arkansas, Keiser, AR, 72351, USA
| | - Rebecca Bart
- Donald Danforth Plant Science Center, 975 N Warson Rd, St Louis, MO, 63132, USA
| | - Vasu Kuraparthy
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA.
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Duan Y, Chen Q, Chen Q, Zheng K, Cai Y, Long Y, Zhao J, Guo Y, Sun F, Qu Y. Analysis of transcriptome data and quantitative trait loci enables the identification of candidate genes responsible for fiber strength in Gossypium barbadense. G3 GENES|GENOMES|GENETICS 2022; 12:6650278. [PMID: 35881688 PMCID: PMC9434320 DOI: 10.1093/g3journal/jkac167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 06/23/2022] [Indexed: 11/13/2022]
Abstract
Gossypium barbadense possesses a superior fiber quality because of its fiber length and strength. An in-depth analysis of the underlying genetic mechanism could aid in filling the gap in research regarding fiber strength and could provide helpful information for Gossypium barbadense breeding. Three quantitative trait loci related to fiber strength were identified from a Gossypium barbadense recombinant inbred line (PimaS-7 × 5917) for further analysis. RNA sequencing was performed in the fiber tissues of PimaS-7 × 5917 0–35 days postanthesis. Four specific modules closely related to the secondary wall-thickening stage were obtained using the weighted gene coexpression network analysis. In total, 55 genes were identified as differentially expressed from 4 specific modules. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes were used for enrichment analysis, and Gbar_D11G032910, Gbar_D08G020540, Gbar_D08G013370, Gbar_D11G033670, and Gbar_D11G029020 were found to regulate fiber strength by playing a role in the composition of structural constituents of cytoskeleton and microtubules during fiber development. Quantitative real-time PCR results confirmed the accuracy of the transcriptome data. This study provides a quick strategy for exploring candidate genes and provides new insights for improving fiber strength in cotton.
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Affiliation(s)
- Yajie Duan
- College of Agronomy, Xinjiang Agricultural University , Urumqi, Xinjiang 830052, China
| | - Qin Chen
- College of Agronomy, Xinjiang Agricultural University , Urumqi, Xinjiang 830052, China
| | - Quanjia Chen
- College of Agronomy, Xinjiang Agricultural University , Urumqi, Xinjiang 830052, China
| | - Kai Zheng
- College of Agronomy, Xinjiang Agricultural University , Urumqi, Xinjiang 830052, China
| | - Yongsheng Cai
- College of Agronomy, Xinjiang Agricultural University , Urumqi, Xinjiang 830052, China
| | - Yilei Long
- College of Agronomy, Xinjiang Agricultural University , Urumqi, Xinjiang 830052, China
| | - Jieyin Zhao
- College of Agronomy, Xinjiang Agricultural University , Urumqi, Xinjiang 830052, China
| | - Yaping Guo
- College of Agronomy, Xinjiang Agricultural University , Urumqi, Xinjiang 830052, China
| | - Fenglei Sun
- College of Agronomy, Xinjiang Agricultural University , Urumqi, Xinjiang 830052, China
| | - Yanying Qu
- College of Agronomy, Xinjiang Agricultural University , Urumqi, Xinjiang 830052, China
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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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Li C, Dong C, Zhao H, Wang J, Du L, Ai N. Identification of superior parents with high fiber quality using molecular markers and phenotypes based on a core collection of upland cotton ( Gossypium hirsutum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:30. [PMID: 37312963 PMCID: PMC10248707 DOI: 10.1007/s11032-022-01300-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 05/22/2022] [Indexed: 06/15/2023]
Abstract
The combination of molecular markers and phenotypes to select superior parents has become the goal of modern breeders. In this study, 491 upland cotton (Gossypium hirsutum L.) accessions were genotyped using the CottonSNP80K array and then a core collection (CC) was constructed. Superior parents with high fiber quality were identified using molecular markers and phenotypes based on the CC. The Nei diversity index, Shannon's diversity index, and polymorphism information content among chromosomes for 491 accessions ranged from 0.307 to 0.402, 0.467 to 0.587, and 0.246 to 0.316, with mean values of 0.365, 0.542, and 0.291, respectively. A CC containing 122 accessions was established and was categorized into eight clusters based on the K2P genetic distances. From the CC, 36 superior parents (including duplicates) were selected, which contained the elite alleles of markers and ranked in the top 10% of phenotypic values for each fiber quality trait. Among the 36 materials, eight were for fiber length, four were for fiber strength, nine were for fiber micronaire, five were for fiber uniformity, and ten were for fiber elongation. In particular, the nine materials, 348 (Xinluzhong34), 319 (Xinluzhong3), 325 (Xinluzhong9), 397 (L1-14), 205 (XianIII9704), 258 (9D208), 464 (DP201), 467 (DP150), and 465 (DP208), possessed the elite alleles of markers for at least two traits and could be given priority in breeding applications for a more synchronous improvement of fiber quality. The work provides an efficient method for superior parent selection and will facilitate the application of molecular design breeding to cotton fiber quality. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01300-0.
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Affiliation(s)
- Chengqi Li
- Life Science College, Yuncheng University, Yuncheng, 044000 China
| | - Chengguang Dong
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, 832000 China
| | - Haihong Zhao
- Life Science College, Yuncheng University, Yuncheng, 044000 China
| | - Juan Wang
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, 832000 China
| | - Lei Du
- Life Science College, Yuncheng University, Yuncheng, 044000 China
| | - Nijiang Ai
- Shihezi Agricultural Science Research Institute, Shihezi, 832000 China
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Liu T, He J, Dong K, Wang X, Zhang L, Ren R, Huang S, Sun X, Pan W, Wang W, Yang P, Yang T, Zhang Z. Genome-wide identification of quantitative trait loci for morpho-agronomic and yield-related traits in foxtail millet (Setaria italica) across multi-environments. Mol Genet Genomics 2022; 297:873-888. [PMID: 35451683 PMCID: PMC9130181 DOI: 10.1007/s00438-022-01894-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 03/31/2022] [Indexed: 11/21/2022]
Abstract
Foxtail millet (Setaria italica) is an ideal model of genetic system for functional genomics of the Panicoideae crop. Identification of QTL responsible for morpho-agronomic and yield-related traits facilitates dissection of genetic control and breeding in cereal crops. Here, based on a Yugu1 × Longgu7 RIL population and genome-wide resequencing data, an updated linkage map harboring 2297 bin and 74 SSR markers was constructed, spanning 1315.1 cM with an average distance of 0.56 cM between adjacent markers. A total of 221 QTL for 17 morpho-agronomic and yield-related traits explaining 5.5 ~ 36% of phenotypic variation were identified across multi-environments. Of these, 109 QTL were detected in two to nine environments, including the most stable qLMS6.1 harboring a promising candidate gene Seita.6G250500, of which 70 were repeatedly identified in different trials in the same geographic location, suggesting that foxtail millet has more identical genetic modules under the similar ecological environment. One hundred-thirty QTL with overlapping intervals formed 22 QTL clusters. Furthermore, six superior recombinant inbred lines, RIL35, RIL48, RIL77, RIL80, RIL115 and RIL125 with transgressive inheritance and enrichment of favorable alleles in plant height, tiller, panicle morphology and yield related-traits were screened by hierarchical cluster. These identified QTL, QTL clusters and superior lines lay ground for further gene-trait association studies and breeding practice in foxtail millet.
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Affiliation(s)
- Tianpeng Liu
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
- Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, 730070, China
| | - Jihong He
- Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, 730070, China
| | - Kongjun Dong
- Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, 730070, China
| | - Xuewen Wang
- Institute of Plant Breeding, Genetics, and Genomics, University of Georgia, Athens, GA, 30601, USA
| | - Lei Zhang
- Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, 730070, China
| | - Ruiyu Ren
- Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, 730070, China
| | - Sha Huang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Xiaoting Sun
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Wanxiang Pan
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Wenwen Wang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Peng Yang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Tianyu Yang
- Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, 730070, China.
| | - Zhengsheng Zhang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China.
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Boopathi NM, Tiwari GJ, Jena SN, Nandhini K, Sri Subalakhshmi VKI, Shyamala P, Joshi B, Premalatha N, Rajeswari S. Identification of Stable and Multiple Environment Interaction QTLs and Candidate Genes for Fiber Productive Traits Under Irrigated and Water Stress Conditions Using Intraspecific RILs of Gossypium hirsutum var. MCU5 X TCH1218. FRONTIERS IN PLANT SCIENCE 2022; 13:851504. [PMID: 35519814 PMCID: PMC9062235 DOI: 10.3389/fpls.2022.851504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 03/07/2022] [Indexed: 06/14/2023]
Abstract
Cotton productivity under water-stressed conditions is controlled by multiple quantitative trait loci (QTL). Enhancement of these productivity traits under water deficit stress is crucial for the genetic improvement of upland cotton, Gossypium hirsutum. In the present study, we constructed a genetic map with 504 single nucleotide polymorphisms (SNPs) covering a total span length of 4,416 cM with an average inter-marker distance of 8.76 cM. A total of 181 intra-specific recombinant inbred lines (RILs) were derived from a cross between G. hirsutum var. MCU5 and TCH1218 were used. Although 2,457 polymorphic SNPs were detected between the parents using the CottonSNP50K assay, only 504 SNPs were found to be useful for the construction of the genetic map. In the SNP genotyping, a large number of SNPs showed either >20% missing data, duplication, or segregation distortion. However, the mapped SNPs of this study showed collinearity with the physical map of the reference genome (G. hirsutum var.TM-1), indicating that there was no chromosomal rearrangement within the studied mapping population. RILs were evaluated under multi-environments and seasons for which the phenotypic data were acquired. A total of 53 QTL controlling plant height (PH), number of sympodial branches, boll number (BN), and boll weight (BW) were dissected by QTL analysis under irrigated and water stress conditions. Additionally, it was found that nine QTL hot spots not only co-localized for more than one investigated trait but were also stable with major QTL, i.e., with > 10% of phenotypic variation. One QTL hotspot on chromosome 22 flanked by AX-182254626-AX-182264770 with a span length of 89.4 cM co-localized with seven major and stable QTL linked to a number of sympodial branches both under irrigated and water stress conditions. In addition, putative candidate genes associated with water stress in the QTL hotspots were identified. Besides, few QTL from the hotspots were previously reported across various genetic architects in cotton validating the potential applications of these identified QTL for cotton breeding and improvement. Thus, the major and stable QTL identified in the present study would improve the cotton productivity under water-limited environments through marker-assisted selection.
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Affiliation(s)
| | - Gopal Ji Tiwari
- Plant Molecular Genetics Laboratory, CSIR-National Botanical Research Institute, Lucknow, India
| | - Satya Narayan Jena
- Plant Molecular Genetics Laboratory, CSIR-National Botanical Research Institute, Lucknow, India
| | - Kemparaj Nandhini
- Department of Cotton, CPBG, Tamil Nadu Agricultural University, Coimbatore, India
| | | | - Pilla Shyamala
- Department of Plant Biotechnology, CPMB&B, Tamil Nadu Agricultural University, Coimbatore, India
| | - Babita Joshi
- Plant Molecular Genetics Laboratory, CSIR-National Botanical Research Institute, Lucknow, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | | | - S. Rajeswari
- Department of Cotton, CPBG, Tamil Nadu Agricultural University, Coimbatore, India
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Razzaq A, Zafar MM, Ali A, Hafeez A, Sharif F, Guan X, Deng X, Pengtao L, Shi Y, Haroon M, Gong W, Ren M, Yuan Y. The Pivotal Role of Major Chromosomes of Sub-Genomes A and D in Fiber Quality Traits of Cotton. Front Genet 2022; 12:642595. [PMID: 35401652 PMCID: PMC8988190 DOI: 10.3389/fgene.2021.642595] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 10/25/2021] [Indexed: 02/02/2023] Open
Abstract
Lack of precise information about the candidate genes involved in a complex quantitative trait is a major obstacle in the cotton fiber quality improvement, and thus, overall genetic gain in conventional phenotypic selection is low. Recent molecular interventions and advancements in genome sequencing have led to the development of high-throughput molecular markers, quantitative trait locus (QTL) fine mapping, and single nucleotide polymorphisms (SNPs). These advanced tools have resolved the existing bottlenecks in trait-specific breeding. This review demonstrates the significance of chromosomes 3, 7, 9, 11, and 12 of sub-genomes A and D carrying candidate genes for fiber quality. However, chromosome 7 carrying SNPs for stable and potent QTLs related to fiber quality provides great insights for fiber quality-targeted research. This information can be validated by marker-assisted selection (MAS) and transgene in Arabidopsis and subsequently in cotton.
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Affiliation(s)
- Abdul Razzaq
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan
- *Correspondence: Abdul Razzaq, ; Youlu Yuan , ; Maozhi Ren,
| | - Muhammad Mubashar Zafar
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | - Arfan Ali
- FB Genetics Four Brothers Group, Lahore, Pakistan
| | - Abdul Hafeez
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | - Faiza Sharif
- University Institute of Physical Therapy, The University of Lahore, Lahore, Pakistan
| | | | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | - Li Pengtao
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Yuzhen Shi
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | - Muhammad Haroon
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | - Maozhi Ren
- State Key Laboratory of Cotton Biology, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
- *Correspondence: Abdul Razzaq, ; Youlu Yuan , ; Maozhi Ren,
| | - Youlu Yuan
- Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
- *Correspondence: Abdul Razzaq, ; Youlu Yuan , ; Maozhi Ren,
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12
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Development and evaluation of India’s first intraspecific Gossypium barbadense cotton recombinant inbred mapping population for extra-long staple fibre traits. J Genet 2022. [DOI: 10.1007/s12041-021-01338-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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13
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Jiang X, Gong J, Zhang J, Zhang Z, Shi Y, Li J, Liu A, Gong W, Ge Q, Deng X, Fan S, Chen H, Kuang Z, Pan J, Che J, Zhang S, Jia T, Wei R, Chen Q, Wei S, Shang H, Yuan Y. Quantitative Trait Loci and Transcriptome Analysis Reveal Genetic Basis of Fiber Quality Traits in CCRI70 RIL Population of Gossypium hirsutum. FRONTIERS IN PLANT SCIENCE 2021; 12:753755. [PMID: 34975939 PMCID: PMC8716697 DOI: 10.3389/fpls.2021.753755] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 11/11/2021] [Indexed: 06/14/2023]
Abstract
Upland cotton (Gossypium hirsutum) is widely planted around the world for its natural fiber, and producing high-quality fiber is essential for the textile industry. CCRI70 is a hybrid cotton plant harboring superior yield and fiber quality, whose recombinant inbred line (RIL) population was developed from two upland cotton varieties (sGK156 and 901-001) and were used here to investigate the source of high-quality related alleles. Based on the material of the whole population, a high-density genetic map was constructed using specific locus-amplified fragment sequencing (SLAF-seq). It contained 24,425 single nucleotide polymorphism (SNP) markers, spanning a distance of 4,850.47 centimorgans (cM) over 26 chromosomes with an average marker interval of 0.20 cM. In evaluating three fiber quality traits in nine environments to detect multiple environments stable quantitative trait loci (QTLs), we found 289 QTLs, of which 36 of them were stable QTLs and 18 were novel. Based on the transcriptome analysis for two parents and two RILs, 24,941 unique differentially expressed genes (DEGs) were identified, 473 of which were promising genes. For the fiber strength (FS) QTLs, 320 DEGs were identified, suggesting that pectin synthesis, phenylpropanoid biosynthesis, and plant hormone signaling pathways could influence FS, and several transcription factors may regulate fiber development, such as GAE6, C4H, OMT1, AFR18, EIN3, bZIP44, and GAI. Notably, the marker D13_56413025 in qFS-chr18-4 provides a potential basis for enhancing fiber quality of upland cotton via marker-assisted breeding and gene cloning of important fiber quality traits.
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Affiliation(s)
- Xiao Jiang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- College of Agriculture, Engineering Research Centre of Cotton of Ministry of Education, Xinjiang Agricultural University, Ürümqi, China
| | - Jianhong Zhang
- Institute of Cotton, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Zhen Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Yuzhen Shi
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Senmiao Fan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Haodong Chen
- Cotton Sciences Research Institute of Hunan, National Hybrid Cotton Research Promotion Center, Changde, China
| | - Zhengcheng Kuang
- Cotton Sciences Research Institute of Hunan, National Hybrid Cotton Research Promotion Center, Changde, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jincan Che
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou, China
| | - Shuya Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Tingting Jia
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Renhui Wei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanjia Chen
- College of Agriculture, Engineering Research Centre of Cotton of Ministry of Education, Xinjiang Agricultural University, Ürümqi, China
| | - Shoujun Wei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou, China
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- College of Agriculture, Engineering Research Centre of Cotton of Ministry of Education, Xinjiang Agricultural University, Ürümqi, China
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou, China
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14
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Shukla RP, Tiwari GJ, Joshi B, Song-Beng K, Tamta S, Boopathi NM, Jena SN. GBS-SNP and SSR based genetic mapping and QTL analysis for drought tolerance in upland cotton. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2021; 27:1731-1745. [PMID: 34539113 PMCID: PMC8405779 DOI: 10.1007/s12298-021-01041-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 07/26/2021] [Accepted: 07/27/2021] [Indexed: 05/16/2023]
Abstract
UNLABELLED A recombinant inbred line mapping population of intra-species upland cotton was generated from a cross between the drought-tolerant female parent (AS2) and the susceptible male parent (MCU13). A linkage map was constructed deploying 1,116 GBS-based SNPs and public domain-based 782 SSRs spanning a total genetic distance of 28,083.03 cM with an average chromosomal span length of 1,080.12 cM with inter-marker distance of 10.19 cM.A total of 19 quantitative trait loci (QTLs) were identified in nine chromosomes for field drought tolerance traits. Chromosomes 3 and 8 harbored important drought tolerant QTLs for chlorophyll stability index trait while for relative water content trait, three QTLs on chromosome 8 and one QTL each on chromosome 4, 12 were identified. One QTL on each chromosome 8, 5, and 7, and two QTLs on chromosome 15 linking to proline content were identified. For the nitrate reductase activity trait, two QTLs were identified on chromosome 3 and one on each chromosome 8, 13, and 26. To complement our QTL study, a meta-analysis was conducted along with the public domain database and resulted in a consensus map for chromosome 8. Under field drought stress, chromosome 8 harbored a drought tolerance QTL hotspot with two in-house QTLs for chlorophyll stability index (qCSI01, qCSI02) and three public domain QTLs (qLP.FDT_1, qLP.FDT_2, qCC.ST_3). Identified QTL hotspot on chromosome 8 could play a crucial role in exploring abiotic stress-associated genes/alleles for drought trait improvement. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s12298-021-01041-y.
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Affiliation(s)
- Ravi Prakash Shukla
- Plant Molecular Genetics Laboratory, CSIR-National Botanical Research Institute, Rana Pratap Marg, Lucknow, (U.P.) 226001 India
- Aakash Institute, Bhopal, Madhya Pradesh 462011 India
| | - Gopal Ji Tiwari
- Plant Molecular Genetics Laboratory, CSIR-National Botanical Research Institute, Rana Pratap Marg, Lucknow, (U.P.) 226001 India
| | - Babita Joshi
- Plant Molecular Genetics Laboratory, CSIR-National Botanical Research Institute, Rana Pratap Marg, Lucknow, (U.P.) 226001 India
- Acamedy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002 India
| | - Kah Song-Beng
- School of Science, Monash University Malaysia, 46150 Bandar Sunway, Selangor Malaysia
| | - Sushma Tamta
- Department of Botany, D.S.B. Campus, Kumaun University, Nainital, Uttarakhand 263002 India
| | - N. Manikanda Boopathi
- Department of Plant Biotechnology, CPMP & B, Tamil Nadu Agricultural University, Coimbatore, India
| | - Satya Narayan Jena
- Plant Molecular Genetics Laboratory, CSIR-National Botanical Research Institute, Rana Pratap Marg, Lucknow, (U.P.) 226001 India
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15
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Liu Z, Wang X, Sun Z, Zhang Y, Meng C, Chen B, Wang G, Ke H, Wu J, Yan Y, Wu L, Li Z, Yang J, Zhang G, Ma Z. Evolution, expression and functional analysis of cultivated allotetraploid cotton DIR genes. BMC PLANT BIOLOGY 2021; 21:89. [PMID: 33568051 PMCID: PMC7876823 DOI: 10.1186/s12870-021-02859-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 01/27/2021] [Indexed: 05/13/2023]
Abstract
BACKGROUND Dirigent (DIR) proteins mediate regioselectivity and stereoselectivity during lignan biosynthesis and are also involved in lignin, gossypol and pterocarpan biosynthesis. This gene family plays a vital role in enhancing stress resistance and in secondary cell-wall development, but systematical understanding is lacking in cotton. RESULTS In this study, 107 GbDIRs and 107 GhDIRs were identified in Gossypium barbadense and Gossypium hirsutum, respectively. Most of these genes have a classical gene structure without intron and encode proteins containing a signal peptide. Phylogenetic analysis showed that cotton DIR genes were classified into four distinct subfamilies (a, b/d, e, and f). Of these groups, DIR-a and DIR-e were evolutionarily conserved, and segmental and tandem duplications contributed equally to their formation. In contrast, DIR-b/d mainly expanded by recent tandem duplications, accompanying with a number of gene clusters. With the rapid evolution, DIR-b/d-III was a Gossypium-specific clade involved in atropselective synthesis of gossypol. RNA-seq data highlighted GhDIRs in response to Verticillium dahliae infection and suggested that DIR gene family could confer Verticillium wilt resistance. We also identified candidate DIR genes related to fiber development in G. barbadense and G. hirsutum and revealed their differential expression. To further determine the involvement of DIR genes in fiber development, we overexpressed a fiber length-related gene GbDIR78 in Arabidopsis and validated its function in trichomes and hypocotyls. CONCLUSIONS These findings contribute novel insights towards the evolution of DIR gene family and provide valuable information for further understanding the roles of DIR genes in cotton fiber development as well as in stress responses.
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Affiliation(s)
- Zhengwen Liu
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Xingfen Wang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Zhengwen Sun
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Yan Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Chengsheng Meng
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Bin Chen
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Guoning Wang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Huifeng Ke
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Jinhua Wu
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Yuanyuan Yan
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Liqiang Wu
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Zhikun Li
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Jun Yang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China
| | - Guiyin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China.
| | - Zhiying Ma
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Hebei Agricultural University, Baoding, 071001, China.
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Pei W, Song J, Wang W, Ma J, Jia B, Wu L, Wu M, Chen Q, Qin Q, Zhu H, Hu C, Lei H, Gao X, Hu H, Zhang Y, Zhang J, Yu J, Qu Y. Quantitative Trait Locus Analysis and Identification of Candidate Genes for Micronaire in an Interspecific Backcross Inbred Line Population of Gossypium hirsutum × Gossypium barbadense. FRONTIERS IN PLANT SCIENCE 2021; 12:763016. [PMID: 34777444 PMCID: PMC8579039 DOI: 10.3389/fpls.2021.763016] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 09/22/2021] [Indexed: 05/08/2023]
Abstract
Cotton is the most important fiber crop and provides indispensable natural fibers for the textile industry. Micronaire (MIC) is determined by fiber fineness and maturity and is an important component of fiber quality. Gossypium barbadense L. possesses long, strong and fine fibers, while upland cotton (Gossypium hirsutum L.) is high yielding with high MIC and widely cultivated worldwide. To identify quantitative trait loci (QTLs) and candidate genes for MIC in G. barbadense, a population of 250 backcross inbred lines (BILs), developed from an interspecific cross of upland cotton CRI36 × Egyptian cotton (G. barbadense) Hai7124, was evaluated in 9 replicated field tests. Based on a high-density genetic map with 7709 genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) markers, 25 MIC QTLs were identified, including 12 previously described QTLs and 13 new QTLs. Importantly, two stable MIC QTLs (qMIC-D03-2 on D03 and qMIC-D08-1 on D08) were identified. Of a total of 338 genes identified within the two QTL regions, eight candidate genes with differential expression between TM-1 and Hai7124 were identified. Our research provides valuable information for improving MIC in cotton breeding.
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Affiliation(s)
- Wenfeng Pei
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, 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
| | - Jikun Song
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wenkui Wang
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jianjiang Ma
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Bing Jia
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Luyao Wu
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanjia Chen
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
| | - Qin Qin
- Western Agriculture Research Centre, Chinese Academy of Agricultural Sciences, Changji, China
| | - Haiyong Zhu
- Western Agriculture Research Centre, Chinese Academy of Agricultural Sciences, Changji, China
| | - Chengcheng Hu
- Western Agriculture Research Centre, Chinese Academy of Agricultural Sciences, Changji, China
| | - Hai Lei
- Seed Management Station, Department of Agriculture and Rural Affairs of Xinjiang, Urumqi, China
| | - Xuefei Gao
- Join Hope Seed Co., Ltd., Changji, China
| | - Haijun Hu
- Join Hope Seed Co., Ltd., Changji, China
| | - Yu Zhang
- Join Hope Seed Co., Ltd., Changji, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, United States
- Jinfa Zhang,
| | - Jiwen Yu
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, 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: Jiwen Yu,
| | - Yanying Qu
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- Yanying Qu,
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Liu W, Song C, Ren Z, Zhang Z, Pei X, Liu Y, He K, Zhang F, Zhao J, Zhang J, Wang X, Yang D, Li W. Genome-wide association study reveals the genetic basis of fiber quality traits in upland cotton (Gossypium hirsutum L.). BMC PLANT BIOLOGY 2020; 20:395. [PMID: 32854609 PMCID: PMC7450593 DOI: 10.1186/s12870-020-02611-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 08/18/2020] [Indexed: 05/08/2023]
Abstract
BACKGROUND Fiber quality is an important economic trait of cotton, and its improvement is a major goal of cotton breeding. To better understand the genetic mechanisms responsible for fiber quality traits, we conducted a genome-wide association study to identify and mine fiber-quality-related quantitative trait loci (QTLs) and genes. RESULTS In total, 42 single nucleotide polymorphisms (SNPs) and 31 QTLs were identified as being significantly associated with five fiber quality traits. Twenty-five QTLs were identified in previous studies, and six novel QTLs were firstly identified in this study. In the QTL regions, 822 genes were identified and divided into four clusters based on their expression profiles. We also identified two pleiotropic SNPs. The SNP locus i52359Gb was associated with fiber elongation, strength, length and uniformity, while i11316Gh was associated with fiber strength and length. Moreover, these two SNPs were nonsynonymous and located in genes Gh_D09G2376 and Gh_D06G1908, respectively. RT-qPCR analysis revealed that these two genes were preferentially expressed at one or more stages of cotton fiber development, which was consistent with the RNA-seq data. Thus, Gh_D09G2376 and Gh_D06G1908 may be involved in fiber developmental processes. CONCLUSIONS The findings of this study provide insights into the genetic bases of fiber quality traits, and the identified QTLs or genes may be applicable in cotton breeding to improve fiber quality.
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Affiliation(s)
- Wei Liu
- Collaborative Innovation Center of Henan Grain Crops, Agronomy College, Henan Agricultural University, Zhengzhou, 450002, China
| | - Chengxiang Song
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Zhongying Ren
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Zhiqiang Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Xiaoyu Pei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Yangai Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Kunlun He
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Fei Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Junjie Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Jie Zhang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China
| | - Xingxing Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China
| | - Daigang Yang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China
| | - Wei Li
- Collaborative Innovation Center of Henan Grain Crops, Agronomy College, Henan Agricultural University, Zhengzhou, 450002, China.
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China.
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Shi Y, Liu A, Li J, Zhang J, Li S, Zhang J, Ma L, He R, Song W, Guo L, Lu Q, Xiang X, Gong W, Gong J, Ge Q, Shang H, Deng X, Pan J, Yuan Y. Examining two sets of introgression lines across multiple environments reveals background-independent and stably expressed quantitative trait loci of fiber quality in cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:2075-2093. [PMID: 32185421 PMCID: PMC7311500 DOI: 10.1007/s00122-020-03578-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 03/07/2020] [Indexed: 05/29/2023]
Abstract
Background-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported. Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum × G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI- and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.
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Affiliation(s)
- Yuzhen Shi
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Shaoqi Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jinfeng Zhang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Liujun Ma
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Rui He
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Weiwu Song
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Lixue Guo
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Quanwei Lu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Xianghui Xiang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
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Wang F, Zhang J, Chen Y, Zhang C, Gong J, Song Z, Zhou J, Wang J, Zhao C, Jiao M, Liu A, Du Z, Yuan Y, Fan S, Zhang J. Identification of candidate genes for key fibre-related QTLs and derivation of favourable alleles in Gossypium hirsutum recombinant inbred lines with G. barbadense introgressions. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:707-720. [PMID: 31446669 PMCID: PMC7004909 DOI: 10.1111/pbi.13237] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 08/15/2019] [Indexed: 05/02/2023]
Abstract
Fine mapping QTLs and identifying candidate genes for cotton fibre-quality and yield traits would be beneficial to cotton breeding. Here, we constructed a high-density genetic map by specific-locus amplified fragment sequencing (SLAF-seq) to identify QTLs associated with fibre-quality and yield traits using 239 recombinant inbred lines (RILs), which was developed from LMY22 (a high-yield Gossypium hirsutumL. cultivar) × LY343 (a superior fibre-quality germplasm with G. barbadenseL. introgressions). The genetic map spanned 3426.57 cM, including 3556 SLAF-based SNPs and 199 SSR marker loci. A total of 104 QTLs, including 67 QTLs for fibre quality and 37 QTLs for yield traits, were identified with phenotypic data collected from 7 environments. Among these, 66 QTLs were co-located in 19 QTL clusters on 12 chromosomes, and 24 QTLs were detected in three or more environments and determined to be stable. We also investigated the genomic components of LY343 and their contributions to fibre-related traits by deep sequencing the whole genome of LY343, and we found that genomic components from G. hirsutum races (which entered LY343 via its G. barbadense parent) contributed more favourable alleles than those from G. barbadense. We further identified six putative candidate genes for stable QTLs, including Gh_A03G1147 (GhPEL6), Gh_D07G1598 (GhCSLC6) and Gh_D13G1921 (GhTBL5) for fibre-length QTLs and Gh_D03G0919 (GhCOBL4), Gh_D09G1659 (GhMYB4) and Gh_D09G1690 (GhMYB85) for lint-percentage QTLs. Our results provide comprehensive insight into the genetic basis of the formation of fibre-related traits and would be helpful for cloning fibre-development-related genes as well as for marker-assisted genetic improvement in cotton.
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Affiliation(s)
- Furong Wang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Jingxia Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Yu Chen
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Chuanyun Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Juwu Gong
- State Key Laboratory of Cotton BiologyKey Laboratory of Biological and Genetic Breeding of CottonMinistry of AgricultureInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangChina
| | - Zhangqiang Song
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Juan Zhou
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Jingjing Wang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Chengjie Zhao
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Mengjia Jiao
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Aiying Liu
- State Key Laboratory of Cotton BiologyKey Laboratory of Biological and Genetic Breeding of CottonMinistry of AgricultureInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangChina
| | - Zhaohai Du
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Youlu Yuan
- State Key Laboratory of Cotton BiologyKey Laboratory of Biological and Genetic Breeding of CottonMinistry of AgricultureInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangChina
| | - Shoujin Fan
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Jun Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
- College of Life SciencesShandong Normal UniversityJinanChina
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20
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QTL mapping of yield component traits on bin map generated from resequencing a RIL population of foxtail millet (Setaria italica). BMC Genomics 2020; 21:141. [PMID: 32041544 PMCID: PMC7011527 DOI: 10.1186/s12864-020-6553-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Accepted: 02/04/2020] [Indexed: 01/19/2023] Open
Abstract
Background Foxtail millet (Setaria italica) has been developed into a model genetical system for deciphering architectural evolution, C4 photosynthesis, nutritional properties, abiotic tolerance and bioenergy in cereal grasses because of its advantageous characters with the small genome size, self-fertilization, short growing cycle, small growth stature, efficient genetic transformation and abundant diverse germplasm resources. Therefore, excavating QTLs of yield component traits, which are closely related to aspects mentioned above, will further facilitate genetic research in foxtail millet and close cereal species. Results Here, 164 Recombinant inbreed lines from a cross between Longgu7 and Yugu1 were created and 1,047,978 SNPs were identified between both parents via resequencing. A total of 3413 bin markers developed from SNPs were used to construct a binary map, containing 3963 recombinant breakpoints and totaling 1222.26 cM with an average distance of 0.36 cM between adjacent markers. Forty-seven QTLs were identified for four traits of straw weight, panicle weight, grain weight per plant and 1000-grain weight. These QTLs explained 5.5–14.7% of phenotypic variance. Thirty-nine favorable QTL alleles were found to inherit from Yugu1. Three stable QTLs were detected in multi-environments, and nine QTL clusters were identified on Chromosome 3, 6, 7 and 9. Conclusions A high-density genetic map with 3413 bin markers was constructed and three stable QTLs and 9 QTL clusters for yield component traits were identified. The results laid a powerful foundation for fine mapping, identifying candidate genes, elaborating molecular mechanisms and application in foxtail millet breeding programs by marker-assisted selection.
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21
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Genetic Analysis of the Transition from Wild to Domesticated Cotton ( Gossypium hirsutum L.). G3-GENES GENOMES GENETICS 2020; 10:731-754. [PMID: 31843806 PMCID: PMC7003101 DOI: 10.1534/g3.119.400909] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The evolution and domestication of cotton is of great interest from both economic and evolutionary standpoints. Although many genetic and genomic resources have been generated for cotton, the genetic underpinnings of the transition from wild to domesticated cotton remain poorly known. Here we generated an intraspecific QTL mapping population specifically targeting domesticated cotton phenotypes. We used 466 F2 individuals derived from an intraspecific cross between the wild Gossypium hirsutum var. yucatanense (TX2094) and the elite cultivar G. hirsutum cv. Acala Maxxa, in two environments, to identify 120 QTL associated with phenotypic changes under domestication. While the number of QTL recovered in each subpopulation was similar, only 22 QTL were considered coincident (i.e., shared) between the two locations, eight of which shared peak markers. Although approximately half of QTL were located in the A-subgenome, many key fiber QTL were detected in the D-subgenome, which was derived from a species with unspinnable fiber. We found that many QTL are environment-specific, with few shared between the two environments, indicating that QTL associated with G. hirsutum domestication are genomically clustered but environmentally labile. Possible candidate genes were recovered and are discussed in the context of the phenotype. We conclude that the evolutionary forces that shape intraspecific divergence and domestication in cotton are complex, and that phenotypic transformations likely involved multiple interacting and environmentally responsive factors.
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Zhang Z, Li J, Jamshed M, Shi Y, Liu A, Gong J, Wang S, Zhang J, Sun F, Jia F, Ge Q, Fan L, Zhang Z, Pan J, Fan S, Wang Y, Lu Q, Liu R, Deng X, Zou X, Jiang X, Liu P, Li P, Iqbal MS, Zhang C, Zou J, Chen H, Tian Q, Jia X, Wang B, Ai N, Feng G, Wang Y, Hong M, Li S, Lian W, Wu B, Hua J, Zhang C, Huang J, Xu A, Shang H, Gong W, Yuan Y. Genome-wide quantitative trait loci reveal the genetic basis of cotton fibre quality and yield-related traits in a Gossypium hirsutum recombinant inbred line population. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:239-253. [PMID: 31199554 PMCID: PMC6920336 DOI: 10.1111/pbi.13191] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 05/30/2019] [Accepted: 06/11/2019] [Indexed: 05/02/2023]
Abstract
Cotton is widely cultivated globally because it provides natural fibre for the textile industry and human use. To identify quantitative trait loci (QTLs)/genes associated with fibre quality and yield, a recombinant inbred line (RIL) population was developed in upland cotton. A consensus map covering the whole genome was constructed with three types of markers (8295 markers, 5197.17 centimorgans (cM)). Six fibre yield and quality traits were evaluated in 17 environments, and 983 QTLs were identified, 198 of which were stable and mainly distributed on chromosomes 4, 6, 7, 13, 21 and 25. Thirty-seven QTL clusters were identified, in which 92.8% of paired traits with significant medium or high positive correlations had the same QTL additive effect directions, and all of the paired traits with significant medium or high negative correlations had opposite additive effect directions. In total, 1297 genes were discovered in the QTL clusters, 414 of which were expressed in two RNA-Seq data sets. Many genes were discovered, 23 of which were promising candidates. Six important QTL clusters that included both fibre quality and yield traits were identified with opposite additive effect directions, and those on chromosome 13 (qClu-chr13-2) could increase fibre quality but reduce yield; this result was validated in a natural population using three markers. These data could provide information about the genetic basis of cotton fibre quality and yield and help cotton breeders to improve fibre quality and yield simultaneously.
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23
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Xiao X, Lu Q, Liu R, Gong J, Gong W, Liu A, Ge Q, Li J, Shang H, Li P, Deng X, Li S, Zhang Q, Niu D, Chen Q, Shi Y, Zhang H, Yuan Y. Genome-wide characterization of the UDP-glycosyltransferase gene family in upland cotton. 3 Biotech 2019; 9:453. [PMID: 31832300 DOI: 10.1007/s13205-019-1984-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Accepted: 11/04/2019] [Indexed: 01/27/2023] Open
Abstract
Uridine diphosphate (UDP)-glycosyltransferases (UGTs) involved in many metabolic processes are ubiquitous in plants, animals, microorganisms and other organisms and are essential for their growth and development. Upland cotton contains a large number of UGT genes. In this study, we aimed to identify UGT family members in the genome of upland cotton (Gossypium hirsutum L.) and analyze their expression patterns. Bioinformatics methods were used to identify UGT genes from the whole genome of upland cotton (Gossypium hirsutum L. acc. TM-1). Phylogenetic analysis was conducted based on alignment of UGT proteins from upland cotton, and the gene structure, motif and chromosome localization were analyzed for the H subgroup of the UGT family. And the physical and chemical properties and expressions of the genes in the H subgroup of this family were also analyzed. A total of 274 UGT genes were identified from the whole genome of upland cotton and were divided into nine subgroups based on phylogenetic analyses. In subgroup H, 36 genes were distributed on 18 chromosomes. The subfamily genes were simple in the structure, 19 of its members contained two introns, and the others contained only one intron. The qRT-PCR results and transcriptomic data indicated that most of the genes had a wide range of tissue expression characteristics. And the phylogenetic analysis results and expression profiles of these genes revealed tissues and different UGT genes from this crop. Taking RNA-seq, RT-qPCR, and quantitative trait locus (QTL) mapping together, our results suggested that GhUGT6 and GhUGT105 in subgroup H of the GhUGT gene family could be potential candidate genes for cotton yield, and GhUGT16, GhUGT103 might play a vital role in fiber development.
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Affiliation(s)
- Xianghui Xiao
- 1College of Agronomy, Xinjiang Agricultural University, Urumqi, China
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanwei Lu
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- 3School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Ruixian Liu
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Juwu Gong
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wankui Gong
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Aiying Liu
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qun Ge
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Junwen Li
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Haihong Shang
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Pengtao Li
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- 3School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Xiaoying Deng
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Shaoqi Li
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qi Zhang
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Doudou Niu
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanjia Chen
- 1College of Agronomy, Xinjiang Agricultural University, Urumqi, China
| | - Yuzhen Shi
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Hua Zhang
- 1College of Agronomy, Xinjiang Agricultural University, Urumqi, China
| | - Youlu Yuan
- 1College of Agronomy, Xinjiang Agricultural University, Urumqi, China
- 2State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
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Zhang K, Kuraparthy V, Fang H, Zhu L, Sood S, Jones DC. High-density linkage map construction and QTL analyses for fiber quality, yield and morphological traits using CottonSNP63K array in upland cotton (Gossypium hirsutum L.). BMC Genomics 2019; 20:889. [PMID: 31771502 PMCID: PMC6878679 DOI: 10.1186/s12864-019-6214-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 10/22/2019] [Indexed: 12/14/2022] Open
Abstract
Background Improving fiber quality and yield are the primary research objectives in cotton breeding for enhancing the economic viability and sustainability of Upland cotton production. Identifying the quantitative trait loci (QTL) for fiber quality and yield traits using the high-density SNP-based genetic maps allows for bridging genomics with cotton breeding through marker assisted and genomic selection. In this study, a recombinant inbred line (RIL) population, derived from cross between two parental accessions, which represent broad allele diversity in Upland cotton, was used to construct high-density SNP-based linkage maps and to map the QTLs controlling important cotton traits. Results Molecular genetic mapping using RIL population produced a genetic map of 3129 SNPs, mapped at a density of 1.41 cM. Genetic maps of the individual chromosomes showed good collinearity with the sequence based physical map. A total of 106 QTLs were identified which included 59 QTLs for six fiber quality traits, 38 QTLs for four yield traits and 9 QTLs for two morphological traits. Sub-genome wide, 57 QTLs were mapped in A sub-genome and 49 were mapped in D sub-genome. More than 75% of the QTLs with favorable alleles were contributed by the parental accession NC05AZ06. Forty-six mapped QTLs each explained more than 10% of the phenotypic variation. Further, we identified 21 QTL clusters where 12 QTL clusters were mapped in the A sub-genome and 9 were mapped in the D sub-genome. Candidate gene analyses of the 11 stable QTL harboring genomic regions identified 19 putative genes which had functional role in cotton fiber development. Conclusion We constructed a high-density genetic map of SNPs in Upland cotton. Collinearity between genetic and physical maps indicated no major structural changes in the genetic mapping populations. Most traits showed high broad-sense heritability. One hundred and six QTLs were identified for the fiber quality, yield and morphological traits. Majority of the QTLs with favorable alleles were contributed by improved parental accession. More than 70% of the mapped QTLs shared the similar map position with previously reported QTLs which suggest the genetic relatedness of Upland cotton germplasm. Identification of QTL clusters could explain the correlation among some fiber quality traits in cotton. Stable and major QTLs and QTL clusters of traits identified in the current study could be the targets for map-based cloning and marker assisted selection (MAS) in cotton breeding. The genomic region on D12 containing the major stable QTLs for micronaire, fiber strength and lint percentage could be potential targets for MAS and gene cloning of fiber quality traits in cotton.
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Affiliation(s)
- Kuang Zhang
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA
| | - Vasu Kuraparthy
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA.
| | - Hui Fang
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA
| | - Linglong Zhu
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA
| | - Shilpa Sood
- Crop & Soil Sciences Department, North Carolina State University, Raleigh, NC, 27695, USA.,4 Cityplace drive, The Climate Corporation (Bayer U.S. Crop Science), St. Louis, MO, 63141, USA
| | - Don C Jones
- Cotton Incorporated, 6399 Weston Parkway, Cary, NC, 27513, USA
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Enhancing Upland cotton for drought resilience, productivity, and fiber quality: comparative evaluation and genetic dissection. Mol Genet Genomics 2019; 295:155-176. [PMID: 31620883 DOI: 10.1007/s00438-019-01611-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 09/22/2019] [Indexed: 01/09/2023]
Abstract
To provision the world sustainably, modern society must increase overall crop production, while conserving and preserving natural resources. Producing more with diminishing water resources is an especially daunting endeavor. Toward the goal of genetically improving drought resilience of cultivated Upland cotton (Gossypium hirsutum L.), this study addresses the genetics of differential yield components referred to as productivity and fiber quality traits under regular-water versus low-water (LW) field conditions. We used ten traits to assess water stress deficit, which included six productivity and four fiber quality traits on two recombinant inbred line (RIL) populations from reciprocally crossed cultivars, Phytogen 72 and Stoneville 474. To facilitate genetic inferences, we genotyped RILs with the CottonSNP63K array, assembled high-density linkage maps of over 7000 SNPs and then analyzed quantitative trait variations. Analysis of variance revealed significant differences for all traits (p < 0.05) in these RIL populations. Although the LW irrigation regime significantly reduced all traits, except lint percent, the RILs exhibited a broad phenotypic spectrum of heritable differences across the water regimes. Transgressive segregation occurred among the RILs, suggesting the possibility of genetic gain through phenotypic selection for drought resilience and perhaps through marker-based selection. Analyses revealed more than 150 quantitative trait loci (QTLs) associated with productivity and fiber quality traits (p < 0.005) on different genomic regions of the cotton genome. The multiple-QTL models analysis with LOD > 3.0 detected 21 QTLs associated with productivity and 22 QTLs associated with fiber quality. For fiber traits, strong clustering and QTL associations occurred in c08 and its homolog c24 as well as c10, c14, and c21. Using contemporary genome sequence assemblies and bioinformatically related information, the identification of genomic regions associated with responses to plant stress/drought elevates the possibility of using marker-assisted and omics-based selection to enhance breeding for drought resilient cultivars and identifying candidate genes and networks. RILs with different responses to drought indicated that it is possible to maintain high fiber quality under LW conditions or reduce the of LW impact on quality. The heritable variation among elite bi-parental RILs for productivity and quality under field drought conditions, and their association of QTLs, and thus specific genomic regions, indicate opportunities for breeding-based gains in water resource conservation, i.e., enhancing cotton's agricultural sustainability.
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26
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Dilnur T, Peng Z, Pan Z, Palanga KK, Jia Y, Gong W, Du X. Association Analysis of Salt Tolerance in Asiatic cotton ( Gossypium arboretum) with SNP Markers. Int J Mol Sci 2019; 20:ijms20092168. [PMID: 31052464 PMCID: PMC6540053 DOI: 10.3390/ijms20092168] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 04/28/2019] [Accepted: 04/30/2019] [Indexed: 12/12/2022] Open
Abstract
Salinity is not only a major environmental factor which limits plant growth and productivity, but it has also become a worldwide problem. However, little is known about the genetic basis underlying salt tolerance in cotton. This study was carried out to identify marker-trait association signals of seven salt-tolerance-related traits and one salt tolerance index using association analysis for 215 accessions of Asiatic cotton. According to a comprehensive index of salt tolerance (CIST), 215 accessions were mainly categorized into four groups, and 11 accessions with high salinity tolerance were selected for breeding. Genome-wide association studies (GWAS) revealed nine SNP rich regions significantly associated with relative fresh weight (RFW), relative stem length (RSL), relative water content (RWC) and CIST. The nine SNP rich regions analysis revealed 143 polymorphisms that distributed 40 candidate genes and significantly associated with salt tolerance. Notably, two SNP rich regions on chromosome 7 were found to be significantly associated with two salinity related traits, RFW and RSL, by the threshold of −log10P ≥ 6.0, and two candidate genes (Cotton_A_37775 and Cotton_A_35901) related to two key SNPs (Ca7_33607751 and Ca7_77004962) were possibly associated with salt tolerance in G. arboreum. These can provide fundamental information which will be useful for future molecular breeding of cotton, in order to release novel salt tolerant cultivars.
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Affiliation(s)
- Tussipkan Dilnur
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| | - Zhen Peng
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| | - Zhaoe Pan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| | - Koffi Kibalou Palanga
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| | - Yinhua Jia
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| | - Wenfang Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| | - Xiongming Du
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
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Ijaz B, Zhao N, Kong J, Hua J. Fiber Quality Improvement in Upland Cotton ( Gossypium hirsutum L.): Quantitative Trait Loci Mapping and Marker Assisted Selection Application. FRONTIERS IN PLANT SCIENCE 2019; 10:1585. [PMID: 31921240 PMCID: PMC6917639 DOI: 10.3389/fpls.2019.01585] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Accepted: 11/12/2019] [Indexed: 05/17/2023]
Abstract
Genetic improvement in fiber quality is one of the main challenges for cotton breeders. Fiber quality traits are controlled by multiple genes and are classified as complex quantitative traits, with a negative relationship with yield potential, so the genetic gain is low in traditional genetic improvement by phenotypic selection. The availability of Gossypium genomic sequences facilitates the development of high-throughput molecular markers, quantitative trait loci (QTL) fine mapping and gene identification, which helps us to validate candidate genes and to use marker assisted selection (MAS) on fiber quality in breeding programs. Based on developments of high density linkage maps, QTLs fine mapping, marker selection and omics, we have performed trait dissection on fiber quality traits in diverse populations of upland cotton. QTL mapping combined with multi-omics approaches such as, RNA sequencing datasets to identify differentially expressed genes have benefited the improvement of fiber quality. In this review, we discuss the application of molecular markers, QTL mapping and MAS for fiber quality improvement in upland cotton.
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Affiliation(s)
- Babar Ijaz
- 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, Beijing, 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, Beijing, China
| | - Jie Kong
- Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, 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, Beijing, China
- *Correspondence: Jinping Hua,
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28
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Zhang C, Li L, Liu Q, Gu L, Huang J, Wei H, Wang H, Yu S. Identification of Loci and Candidate Genes Responsible for Fiber Length in Upland Cotton ( Gossypium hirsutum L.) via Association Mapping and Linkage Analyses. FRONTIERS IN PLANT SCIENCE 2019; 10:53. [PMID: 30804954 PMCID: PMC6370998 DOI: 10.3389/fpls.2019.00053] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 01/16/2019] [Indexed: 05/12/2023]
Abstract
Fiber length (FL) is an important fiber quality trait in cotton. Although many fiber quality quantitative trait loci (QTL) responsible for FL have been identified, most cannot be applied to breeding programs, mainly due to unstable environments or large confidence intervals. In this study, we combined a genome-wide association study (GWAS) and linkage mapping to identify and validate high-quality QTLs responsible for FL. For the GWAS, we developed 93,250 high-quality single-nucleotide polymorphism (SNP) markers based on 355 accessions, and the FL was measured in eight different environments. For the linkage mapping, we constructed an F 2 population from two extreme accessions. The high-density linkage maps spanned 3,848.29 cM, with an average marker interval of 1.41 cM. In total, 14 and 13 QTLs were identified in the association and linkage mapping analyses, respectively. Most importantly, a major QTL on chromosome D03 identified in both populations explained more than 10% of the phenotypic variation (PV). Furthermore, we found that a sucrose synthesis-related gene (Gh_D03G1338) was associated with FL in this QTL region. The RNA-seq data showed that Gh_D03G1338 was highly expressed during the fiber development stage, and the qRT-PCR analysis showed significant expression differences between the long fiber and short fiber varieties. These results suggest that Gh_D03G1338 may determine cotton fiber elongation by regulating the synthesis of sucrose. Favorable QTLs and candidate genes should be useful for increasing fiber quality in cotton breeding.
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Affiliation(s)
- Chi Zhang
- College of Agronomy, Northwest A&F University, Yangling, China
- State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Lin’an, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Libei Li
- State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Lin’an, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qibao Liu
- State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Lin’an, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Lijiao Gu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jianqin Huang
- State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Lin’an, China
| | - Hengling Wei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Hantao Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Shuxun Yu
- College of Agronomy, Northwest A&F University, Yangling, China
- State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Lin’an, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- *Correspondence: Shuxun Yu,
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Ali I, Teng Z, Bai Y, Yang Q, Hao Y, Hou J, Jia Y, Tian L, Liu X, Tan Z, Wang W, Kenneth K, Sharkh AYA, Liu D, Guo K, Zhang J, Liu D, Zhang Z. A high density SLAF-SNP genetic map and QTL detection for fibre quality traits in Gossypium hirsutum. BMC Genomics 2018; 19:879. [PMID: 30522437 PMCID: PMC6282304 DOI: 10.1186/s12864-018-5294-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 11/21/2018] [Indexed: 12/17/2022] Open
Abstract
Background Upland Cotton (Gossypium hirsutum) is a very important cash crop known for its high quality natural fiber. Recent advances in sequencing technologies provide powerful tools with which to explore the cotton genome for single nucleotide polymorphism marker identification and high density genetic map construction toward more reliable quantitative trait locus mapping. Results In the present study, a RIL population was developed by crossing a Chinese high fiber quality cultivar (Yumian 1) and an American high fiber quality line (CA3084), with distinct genetic backgrounds. Specific locus amplified fragment sequencing (SLAF-seq) technology was used to discover SNPs, and a genetic map containing 6254 SNPs was constructed, covering 3141.72 cM with an average distance of 0.5 cM between markers. A total of 95 QTL were detected for fiber quality traits in three environments, explaining 5.5-24.6% of the phenotypic variance. Fifty-five QTL found in multiple environments were considered stable QTL. Nine of the stable QTL were found in all three environments. We identified 14 QTL clusters on 13 chromosomes, each containing one or more stable QTL. Conclusion A high-density genetic map of Gossypium hirsutum developed by using specific locus amplified fragment sequencing technology provides detailed mapping of fiber quality QTL, and identification of ‘stable QTL’ found in multiple environments. A marker-rich genetic map provides a foundation for fine mapping, candidate gene identification and marker-assisted selection of favorable alleles at stable QTL in breeding programs. Electronic supplementary material The online version of this article (10.1186/s12864-018-5294-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Iftikhar Ali
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Zhonghua Teng
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Yuting Bai
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Qing Yang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Yongshui Hao
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Juan Hou
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Yongbin Jia
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Lixia Tian
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Xueying Liu
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Zhaoyun Tan
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Wenwen Wang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Kiirya Kenneth
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | | | - Dexin Liu
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Kai Guo
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Jian Zhang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Dajun Liu
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Zhengsheng Zhang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China.
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30
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Li P, Kirungu JN, Lu H, Magwanga RO, Lu P, Cai X, Zhou Z, Wang X, Hou Y, Wang Y, Xu Y, Peng R, Cai Y, Zhou Y, Wang K, Liu F. SSR-Linkage map of interspecific populations derived from Gossypium trilobum and Gossypium thurberi and determination of genes harbored within the segregating distortion regions. PLoS One 2018; 13:e0207271. [PMID: 30419064 PMCID: PMC6231669 DOI: 10.1371/journal.pone.0207271] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 10/29/2018] [Indexed: 12/17/2022] Open
Abstract
Wild cotton species have significant agronomic traits that can be introgressed into elite cultivated varieties. The use of a genetic map is important in exploring, identification and mining genes which carry significant traits. In this study, 188 F2mapping individuals were developed from Gossypium thurberi (female) and Gossypium trilobum (male), and were genotyped by using simple sequence repeat (SSR) markers. A total of 12,560 simple sequence repeat (SSR) markers, developed by Southwest University, thus coded SWU were screened out of which only 994 were found to be polymorphic, and 849 markers were linked in all the 13 chromosomes. The map had a length of 1,012.458 cM with an average marker distance of 1.193 cM. Segregation distortion regions (SDRs) were observed on Chr01, Chr02, Chr06, Chr07 Chr09, Chr10 and Chr11 with a large proportion of the SDR regions segregating towards the heterozygous allele. There was good syntenic block formation that revealed good collinearity between the genetic and physical map of G. raimondii, compared to the Dt_sub genome of the G. hirsutum and G. barbadense. A total of 2,496 genes were mined within the SSR related regions. The proteins encoding the mined genes within the SDR had varied physiochemical properties; their molecular weights ranged from 6.586 to 252.737 kDa, charge range of -39.5 to 52, grand hydropathy value (GRAVY) of -1.177 to 0.936 and isoelectric (pI) value of 4.087 to 12.206. The low GRAVY values detected showed that the proteins encoding these genes were hydrophilic in nature, a property common among the stress responsive genes. The RNA sequence analysis revealed more of the genes were highly upregulated in various stages of fiber development for instance; Gorai.002G241300 was highly up regulated at 5, 10, 20 and 25 day post anthesis (DPA). Validation through RT-qPCR further revealed that these genes mined within the SDR regions might be playing a significant role under fiber development stages, therefore we infer that Gorai.007G347600 (TFCA), Gorai.012G141600 (FOLB1), Gorai.006G024500 (NMD3), Gorai.002G229900 (LST8) and Gorai.002G235200 (NSA2) are significantly important in fiber development and in turn the quality, and further researches needed to be done to elucidate their exact roles in the fiber development process. The construction of the genetic map between the two wild species paves away for the mapping of quantitative trait loci (QTLs) since the average distance between the markers is small, and mining of genes on the SSR regions will provide an insight in identifying key genes that can be introgressed into the cultivated cotton cultivars.
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Affiliation(s)
- Pengcheng Li
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
- School of Life Science, Henan University/State Key Laboratory of Cotton Biology/Henan Key Laboratory of Plant Stress Biology, Kaifeng, Henan, China
| | - Joy Nyangasi Kirungu
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
| | - Hejun Lu
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
| | - Richard Odongo Magwanga
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
- School of Biological and Physical Sciences (SBPS), Jaramogi Oginga Odinga University of Science and Technology (JOOUST), Bondo- Kenya
| | - Pu Lu
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
| | - Xiaoyan Cai
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
| | - Zhongli Zhou
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
| | - Xingxing Wang
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
| | - Yuqing Hou
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
| | - Yuhong Wang
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
| | - Yanchao Xu
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
| | - Renhai Peng
- Biological and Food Engineering, Anyang Institute of technology, Anyang, Henan, China
| | - Yingfan Cai
- School of Life Science, Henan University/State Key Laboratory of Cotton Biology/Henan Key Laboratory of Plant Stress Biology, Kaifeng, Henan, China
| | - Yun Zhou
- School of Life Science, Henan University/State Key Laboratory of Cotton Biology/Henan Key Laboratory of Plant Stress Biology, Kaifeng, Henan, China
- * E-mail: (YZ); (KW); (FL)
| | - Kunbo Wang
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
- * E-mail: (YZ); (KW); (FL)
| | - Fang Liu
- State Key Laboratory of Cotton Biology /Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, China
- * E-mail: (YZ); (KW); (FL)
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Liu R, Gong J, Xiao X, Zhang Z, Li J, Liu A, Lu Q, Shang H, Shi Y, Ge Q, Iqbal MS, Deng X, Li S, Pan J, Duan L, Zhang Q, Jiang X, Zou X, Hafeez A, Chen Q, Geng H, Gong W, Yuan Y. GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers. FRONTIERS IN PLANT SCIENCE 2018; 9:1067. [PMID: 30283462 PMCID: PMC6157485 DOI: 10.3389/fpls.2018.01067] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Accepted: 07/02/2018] [Indexed: 05/18/2023]
Abstract
It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18-24.45 and 1.68-28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly "pleiotropic." This study provided important information for MAS and candidate gene functional studies.
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Affiliation(s)
- Ruixian Liu
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Juwu Gong
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xianghui Xiao
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Zhen Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanwei Lu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Yuzhen Shi
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Muhammad S. Iqbal
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Shaoqi Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Li Duan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qi Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiao Jiang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xianyan Zou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Abdul Hafeez
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanjia Chen
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
| | - Hongwei Geng
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Youlu Yuan
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
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Chen Y, Liu G, Ma H, Song Z, Zhang C, Zhang J, Zhang J, Wang F, Zhang J. Identification of Introgressed Alleles Conferring High Fiber Quality Derived From Gossypium barbadense L. in Secondary Mapping Populations of G. hirsutum L. FRONTIERS IN PLANT SCIENCE 2018; 9:1023. [PMID: 30073008 PMCID: PMC6058274 DOI: 10.3389/fpls.2018.01023] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Accepted: 06/25/2018] [Indexed: 05/02/2023]
Abstract
The improvement of fiber quality is an essential goal in cotton breeding. In our previous studies, several quantitative trait loci (QTLs) contributing to improved fiber quality were identified in different introgressed chromosomal regions from Sea Island cotton (Gossypium barbadense L.) in a primary introgression population (Pop. A) of upland cotton (G. hirsutum L.). In the present study, to finely map introgressed major QTLs and accurately dissect the genetic contribution of the target introgressed chromosomal segments, we backcrossed two selected recombinant inbred lines (RILs) that presented desirable high fiber quality with their high lint-yielding recurrent parent to ultimately develop two secondary mapping populations (Pop. B and Pop. C). Totals of 20 and 27 QTLs for fiber quality were detected in Pop. B and Pop. C, respectively, including four and five for fiber length, four and eight for fiber micronaire, two and four for fiber uniformity, five and four for fiber elongation, and six and four for fiber strength, respectively. Two QTLs for lint percentage were detected only in Pop. C. In addition, seven stable QTLs were identified, including two for both fiber length and fiber strength and three for fiber elongation. Five QTL clusters for fiber quality were identified in the introgressed chromosomal regions, and negative effects of these chromosomal regions on lint percentage (a major lint yield parameter) were not observed. Candidate genes with a QTL-cluster associated with fiber strength and fiber length in the introgressed region of Chr.7 were further identified. The results may be helpful for revealing the genetic basis of superior fiber quality contributed by introgressed alleles from G. barbadense. Possible strategies involving marker-assisted selection (MAS) for simultaneously improving upland cotton fiber quality and lint yield in breeding programs was also discussed.
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Affiliation(s)
- Yu Chen
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan, China
| | - Guodong Liu
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan, China
| | - Hehuan Ma
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan, China
- College of Life Sciences, Shandong Normal University, Jinan, China
| | - Zhangqiang Song
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan, China
| | - Chuanyun Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan, China
| | - Jingxia Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan, China
| | - Junhao Zhang
- College of Agriculture, Nanjing Agricultural University, Nanjing, China
| | - Furong Wang
- Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of 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, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan, China
- College of Life Sciences, Shandong Normal University, Jinan, China
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33
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Li C, Fu Y, Sun R, Wang Y, Wang Q. Single-Locus and Multi-Locus Genome-Wide Association Studies in the Genetic Dissection of Fiber Quality Traits in Upland Cotton ( Gossypium hirsutum L.). FRONTIERS IN PLANT SCIENCE 2018; 9:1083. [PMID: 30177935 PMCID: PMC6109694 DOI: 10.3389/fpls.2018.01083] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 07/04/2018] [Indexed: 05/04/2023]
Abstract
A major breeding target in Upland cotton (Gossypium hirsutum L.) is to improve the fiber quality. To address this issue, 169 diverse accessions, genotyped by 53,848 high-quality single-nucleotide polymorphisms (SNPs) and phenotyped in four environments, were used to conduct genome-wide association studies (GWASs) for fiber quality traits using three single-locus and three multi-locus models. As a result, 342 quantitative trait nucleotides (QTNs) controlling fiber quality traits were detected. Of the 342 QTNs, 84 were simultaneously detected in at least two environments or by at least two models, which include 29 for fiber length, 22 for fiber strength, 11 for fiber micronaire, 12 for fiber uniformity, and 10 for fiber elongation. Meanwhile, nine QTNs with 10% greater sizes (R2) were simultaneously detected in at least two environments and between single- and multi-locus models, which include TM80185 (D13) for fiber length, TM1386 (A1) and TM14462 (A6) for fiber strength, TM18616 (A7), TM54735 (D3), and TM79518 (D12) for fiber micronaire, TM77489 (D12) and TM81448 (D13) for fiber uniformity, and TM47772 (D1) for fiber elongation. This indicates the possibility of marker-assisted selection in future breeding programs. Among 455 genes within the linkage disequilibrium regions of the nine QTNs, 113 are potential candidate genes and four are promising candidate genes. These findings reveal the genetic control underlying fiber quality traits and provide insights into possible genetic improvements in Upland cotton fiber quality.
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Affiliation(s)
- Chengqi Li
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Yuanzhi Fu
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Runrun Sun
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Yuanyuan Wang
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Qinglian Wang
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
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