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Yang P, Sun X, Liu X, Wang W, Hao Y, Chen L, Liu J, He H, Zhang T, Bao W, Tang Y, He X, Ji M, Guo K, Liu D, Teng Z, Liu D, Zhang J, Zhang Z. Identification of Candidate Genes for Lint Percentage and Fiber Quality Through QTL Mapping and Transcriptome Analysis in an Allotetraploid Interspecific Cotton CSSLs Population. FRONTIERS IN PLANT SCIENCE 2022; 13:882051. [PMID: 35574150 PMCID: PMC9100888 DOI: 10.3389/fpls.2022.882051] [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: 02/23/2022] [Accepted: 04/06/2022] [Indexed: 06/15/2023]
Abstract
Upland cotton (Gossypium hirsutum) has long been an important fiber crop, but the narrow genetic diversity of modern G. hirsutum limits the potential for simultaneous improvement of yield and fiber quality. It is an effective approach to broaden the genetic base of G. hirsutum through introgression of novel alleles from G. barbadense with excellent fiber quality. In the present study, an interspecific chromosome segment substitution lines (CSSLs) population was established using G. barbadense cultivar Pima S-7 as the donor parent and G. hirsutum cultivar CCRI35 as the recipient parent. A total of 105 quantitative trait loci (QTL), including 85 QTL for fiber quality and 20 QTL for lint percentage (LP), were identified based on phenotypic data collected from four environments. Among these QTL, 25 stable QTL were detected in two or more environments, including four for LP, eleven for fiber length (FL), three for fiber strength (FS), six for fiber micronaire (FM), and one for fiber elongation (FE). Eleven QTL clusters were observed on nine chromosomes, of which seven QTL clusters harbored stable QTL. Moreover, eleven major QTL for fiber quality were verified through analysis of introgressed segments of the eight superior lines with the best comprehensive phenotypes. A total of 586 putative candidate genes were identified for 25 stable QTL associated with lint percentage and fiber quality through transcriptome analysis. Furthermore, three candidate genes for FL, GH_A08G1681 (GhSCPL40), GH_A12G2328 (GhPBL19), and GH_D02G0370 (GhHSP22.7), and one candidate gene for FM, GH_D05G1346 (GhAPG), were identified through RNA-Seq and qRT-PCR analysis. These results lay the foundation for understanding the molecular regulatory mechanism of fiber development and provide valuable information for marker-assisted selection (MAS) in cotton breeding.
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Li Y, Mo T, Ran L, Zeng J, Wang C, Liang A, Dai Y, Wu Y, Zhong Z, Xiao Y. Genome resequencing-based high-density genetic map and QTL detection for yield and fiber quality traits in diploid Asiatic cotton (Gossypium arboreum). Mol Genet Genomics 2022; 297:199-212. [PMID: 35048185 DOI: 10.1007/s00438-021-01848-0] [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: 03/11/2021] [Accepted: 12/14/2021] [Indexed: 10/19/2022]
Abstract
Cotton is the most important fiber crop in the world. Asiatic cotton (Gossypium arboreum, genome A2) is a diploid cotton species producing spinnable fibers and important germplasm for cotton breeding and a significant model for fiber biology. However, the genetic map of Asiatic cotton has been lagging behind tetraploid cottons, as well as other stable crops. This study aimed to construct a high-density SNP genetic map and to map QTLs for important yield and fiber quality traits. Using a recombinant inbred line (RIL) population and genome resequencing technology, we constructed a high-density genetic map that covered 1980.17 cM with an average distance of 0.61 cM between adjacent markers. QTL analysis revealed a total of 297 QTLs for 13 yield and fiber quality traits in three environments, explaining 5.0-37.4% of the phenotypic variance, among which 75 were stably detected in two or three environments. Besides, 47 QTL clusters, comprising 131 QTLs for representative traits, were identified. Our works laid solid foundation for fine mapping and cloning of QTL for yield and fiber quality traits in Asiatic cotton.
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Affiliation(s)
- Yaohua Li
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Tong Mo
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Lingfang Ran
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Jianyan Zeng
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Chuannan Wang
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Aimin Liang
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Yonglu Dai
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Yiping Wu
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Ziman Zhong
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Yuehua Xiao
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China.
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Liu X, Yang L, Wang J, Wang Y, Guo Z, Li Q, Yang J, Wu Y, Chen L, Teng Z, Liu D, Liu D, Guo K, Zhang Z. Analyzing Quantitative Trait Loci for Fiber Quality and Yield-Related Traits From a Recombinant Inbred Line Population With Gossypium hirsutum Race palmeri as One Parent. FRONTIERS IN PLANT SCIENCE 2022; 12:817748. [PMID: 35046989 PMCID: PMC8763314 DOI: 10.3389/fpls.2021.817748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 12/01/2021] [Indexed: 06/14/2023]
Abstract
Fiber quality and yield-related traits are important agronomic traits in cotton breeding. To detect the genetic basis of fiber quality and yield related traits, a recombinant inbred line (RIL) population consisting of 182 lines was established from a cross between Gossypium hirsutum cultivar CCRI35 and G. hirsutum race palmeri accession TX-832. The RIL population was deeply genotyped using SLAF-seq and was phenotyped in six environments. A high-density genetic linkage map with 15,765 SNP markers and 153 SSR markers was constructed, with an average distance of 0.30 cM between adjacent markers. A total of 210 fiber quality quantitative trait loci (QTLs) and 73 yield-related QTLs were identified. Of the detected QTLs, 62 fiber quality QTLs and 10 yield-related QTLs were stable across multiple environments. Twelve and twenty QTL clusters were detected on the At and Dt subgenome, respectively. Twenty-three major QTL clusters were further validated through associated analysis and five candidate genes of four stable fiber quality QTLs were identified. This study revealed elite loci influencing fiber quality and yield and significant phenotypic selection regions during G. hirsutum domestication, and set a stage for future utilization of molecular marker assisted breeding in cotton breeding programs.
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Feng L, Zhou C, Su Q, Xu M, Yue H, Zhang S, Zhou B. Fine-mapping and candidate gene analysis of qFS-Chr. D02, a QTL for fibre strength introgressed from a semi-wild cotton into Gossypium hirsutum. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2020; 297:110524. [PMID: 32563462 DOI: 10.1016/j.plantsci.2020.110524] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 02/12/2020] [Accepted: 05/06/2020] [Indexed: 06/11/2023]
Abstract
Fibre strength (FS) is an important quality attribute in the modern textile industry, which is genetically controlled by quantitative trait loci (QTLs). Fine-mapping stable QTLs for FS to identify candidate genes would be valuable for uncovering the genetic basis of fibre quality traits in cotton. Here, a single segment introgression line, IL-D2-2, from the cross of (TM-1×TX-1046) reported in our previous studies, was found to have significantly improved FS compared with the recurrent parent TM-1. To fine-map the QTLs of the FS, we further crossed IL-D2-2 with its recurrent parent TM-1 to produce F2 and F2:3 populations. QTL analysis and substitution mapping showed qFS-Chr. D02 was anchored into a 550.66 kb-interval between two markers, INTR1027 and JESPR-231. This interval contained 67 genes, among which 27 genes related to cell-wall synthesis were selected to conduct qRT-PCR. The results revealed seven genes were expressed significantly differently during the fibre secondary-wall-thickening stage (10-25 days post-anthesis), three being upregulated and four downregulated in IL-D2-2. Both GH_D02G2269 (UDP-glucosyl transferase 84B1) and GH_D02G2289 (unknown function (DUF869)) with nonsynonymous SNPs in IL-D2-2 had significantly downregulated expression, suggesting they were candidates for qFS-Chr. D02. This research provides information about marker-assisted selection for cotton fibre strength improvement.
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Affiliation(s)
- Liuchun Feng
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, MOE Hybrid Cotton R&D Engineering Research Center, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Chenhui Zhou
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, MOE Hybrid Cotton R&D Engineering Research Center, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Qiao Su
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, MOE Hybrid Cotton R&D Engineering Research Center, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Min Xu
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, MOE Hybrid Cotton R&D Engineering Research Center, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Haoran Yue
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, MOE Hybrid Cotton R&D Engineering Research Center, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Shuwen Zhang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, MOE Hybrid Cotton R&D Engineering Research Center, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, People's Republic of China; Institute of Horticulture, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, Zhejiang, People's Republic of China
| | - Baoliang Zhou
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, MOE Hybrid Cotton R&D Engineering Research Center, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, People's Republic of 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: 1.2] [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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Patel JD, Huang X, Lin L, Das S, Chandnani R, Khanal S, Adhikari J, Shehzad T, Guo H, Roy-Zokan EM, Rong J, Paterson AH. The Ligon lintless -2 Short Fiber Mutation Is Located within a Terminal Deletion of Chromosome 18 in Cotton. PLANT PHYSIOLOGY 2020; 183:277-288. [PMID: 32102829 PMCID: PMC7210651 DOI: 10.1104/pp.19.01531] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 01/28/2020] [Indexed: 05/06/2023]
Abstract
Extreme elongation distinguishes about one-fourth of cotton (Gossypium sp.) seed epidermal cells as "lint" fibers, useful for the textile industry, from "fuzz" fibers (<5 mm). Ligon lintless-2 (Li 2 ), a dominant mutation that results in no lint fiber but normal fuzz fiber, offers insight into pathways and mechanisms that differentiate spinnable cotton from its progenitors. A genetic map developed using 1,545 F2 plants showed that marker CISP15 was 0.4 cM from Li 2 , and "dominant" simple sequence repeat (SSR) markers (i.e. with null alleles in the Li 2 genotype) SSR7 and SSR18 showed complete linkage with Li 2 Nonrandom distribution of markers with null alleles suggests that the Li 2 phenotype results from a 176- to 221-kb deletion of the terminal region of chromosome 18 that may have been masked in prior pooled-sample mapping strategies. The deletion includes 10 genes with putative roles in fiber development. Two Glycosyltransferase Family 1 genes showed striking expression differences during elongation of wild-type versus Li 2 fiber, and virus-induced silencing of these genes in the wild type induced Li 2 -like phenotypes. Further, at least 7 of the 10 putative fiber development genes in the deletion region showed higher expression in the wild type than in Li 2 mutants during fiber development stages, suggesting coordinated regulation of processes in cell wall development and cell elongation, consistent with the hypothesis that some fiber-related quantitative trait loci comprise closely spaced groups of functionally diverse but coordinately regulated genes.
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Affiliation(s)
- Jinesh D Patel
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
| | - Xianzhong Huang
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
- Plant Genomics Laboratory, College of Life Sciences, Shihezi University, 832003 Shihezi, China
| | - Lifeng Lin
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
| | - Sayan Das
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
| | - Rahul Chandnani
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
| | - Sameer Khanal
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
| | - Jeevan Adhikari
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
| | - Tariq Shehzad
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
- Department of Biological and Environmental Sciences, College of Arts and Sciences, Qatar University, 2713 Doha, Qatar
| | - Hui Guo
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
| | - Eileen M Roy-Zokan
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
| | - Junkang Rong
- Zhejiang A&F University, Linan, Hangzhou 311300, Zhejiang, China
| | - Andrew H Paterson
- Plant Genome Mapping Laboratory, University of Georgia, Athens, Georgia 30602
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Li SQ, Liu AY, Kong LL, Gong JW, Li JW, Gong WK, Lu QW, Li PT, Ge Q, Shang HH, Xiao XH, Liu RX, Zhang Q, Shi YZ, Yuan YL. QTL mapping and genetic effect of chromosome segment substitution lines with excellent fiber quality from Gossypium hirsutum × Gossypium barbadense. Mol Genet Genomics 2019. [PMID: 31030276 DOI: 10.1007/s00438-00019-01566-00438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Chromosome segment substitution lines (CSSLs) are ideal materials for identifying genetic effects. In this study, CSSL MBI7561 with excellent fiber quality that was selected from BC4F3:5 of CCRI45 (Gossypium hirsutum) × Hai1 (Gossypium barbadense) was used to construct 3 secondary segregating populations with 2 generations (BC5F2 and BC5F2:3). Eighty-one polymorphic markers related to 33 chromosome introgressive segments on 18 chromosomes were finally screened using 2292 SSR markers which covered the whole tetraploid cotton genome. A total of 129 quantitative trait loci (QTL) associated with fiber quality (103) and yield-related traits (26) were detected on 17 chromosomes, explaining 0.85-30.35% of the phenotypic variation; 39 were stable (30.2%), 53 were common (41.1%), 76 were new (58.9%), and 86 had favorable effects on the related traits. More QTL were distributed in the Dt subgenome than in the At subgenome. Twenty-five stable QTL clusters (with stable or common QTL) were detected on 22 chromosome introgressed segments. Finally, the 6 important chromosome introgressed segments (Seg-A02-1, Seg-A06-1, Seg-A07-2, Seg-A07-3, Seg-D07-3, and Seg-D06-2) were identified as candidate chromosome regions for fiber quality, which should be given more attention in future QTL fine mapping, gene cloning, and marker-assisted selection (MAS) breeding.
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Affiliation(s)
- Shao-Qi Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Ai-Ying Liu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Ling-Lei Kong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Ju-Wu Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Jun-Wen Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Wan-Kui Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Quan-Wei Lu
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, 455000, Henan, China
| | - Peng-Tao Li
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, 455000, Henan, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Hai-Hong Shang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Xiang-Hui Xiao
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Rui-Xian Liu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Qi Zhang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Yu-Zhen Shi
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China.
| | - You-Lu Yuan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China.
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Shi Y, Liu A, Li J, Zhang J, Zhang B, Ge Q, Jamshed M, Lu Q, Li S, Xiang X, Gong J, Gong W, Shang H, Deng X, Pan J, Yuan Y. Dissecting the genetic basis of fiber quality and yield traits in interspecific backcross populations of Gossypium hirsutum × Gossypium barbadense. Mol Genet Genomics 2019; 294:1385-1402. [PMID: 31201519 DOI: 10.1007/s00438-019-01582-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2018] [Accepted: 05/29/2019] [Indexed: 12/31/2022]
Abstract
Fiber quality and yield are important traits of cotton. Quantitative trait locus (QTL) mapping is a prerequisite for marker-assisted selection (MAS) in cotton breeding. To identify QTLs for fiber quality and yield traits, 4 backcross-generation populations (BC1F1, BC1S1, BC2F1, and BC3F0) were developed from an interspecific cross between CCRI36 (Gossypium hirsutum L.) and Hai1 (G. barbadense L.). A total of 153 QTLs for fiber quality and yield traits were identified based on data from the BC1F1, BC1S1, BC2F1 and BC3F0 populations in the field and from the BC2F1 population in an artificial disease nursery using a high-density genetic linkage map with 2292 marker loci covering 5115.16 centimorgans (cM) from the BC1F1 population. These QTLs were located on 24 chromosomes, and each could explain 4.98-19.80% of the observed phenotypic variations. Among the 153 QTLs, 30 were consistent with those identified previously. Specifically, 23 QTLs were stably detected in 2 or 3 environments or generations, 6 of which were consistent with those identified previously and the other 17 of which were stable and novel. Ten QTL clusters for different traits were found and 9 of them were novel, which explained the significant correlations among some phenotypic traits in the populations. The results including these stable or consensus QTLs provide valuable information for marker-assisted selection (MAS) in cotton breeding and will help better understand the genetic basis of fiber quality and yield traits, which can then be used in QTL cloning.
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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
| | - Baocai 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
| | - 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
| | - Muhammad Jamshed
- 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
| | - 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
| | - 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
| | - 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
| | - 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
| | - 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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9
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QTL mapping and genetic effect of chromosome segment substitution lines with excellent fiber quality from Gossypium hirsutum × Gossypium barbadense. Mol Genet Genomics 2019; 294:1123-1136. [PMID: 31030276 DOI: 10.1007/s00438-019-01566-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 04/03/2019] [Indexed: 10/26/2022]
Abstract
Chromosome segment substitution lines (CSSLs) are ideal materials for identifying genetic effects. In this study, CSSL MBI7561 with excellent fiber quality that was selected from BC4F3:5 of CCRI45 (Gossypium hirsutum) × Hai1 (Gossypium barbadense) was used to construct 3 secondary segregating populations with 2 generations (BC5F2 and BC5F2:3). Eighty-one polymorphic markers related to 33 chromosome introgressive segments on 18 chromosomes were finally screened using 2292 SSR markers which covered the whole tetraploid cotton genome. A total of 129 quantitative trait loci (QTL) associated with fiber quality (103) and yield-related traits (26) were detected on 17 chromosomes, explaining 0.85-30.35% of the phenotypic variation; 39 were stable (30.2%), 53 were common (41.1%), 76 were new (58.9%), and 86 had favorable effects on the related traits. More QTL were distributed in the Dt subgenome than in the At subgenome. Twenty-five stable QTL clusters (with stable or common QTL) were detected on 22 chromosome introgressed segments. Finally, the 6 important chromosome introgressed segments (Seg-A02-1, Seg-A06-1, Seg-A07-2, Seg-A07-3, Seg-D07-3, and Seg-D06-2) were identified as candidate chromosome regions for fiber quality, which should be given more attention in future QTL fine mapping, gene cloning, and marker-assisted selection (MAS) breeding.
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10
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Balakrishnan D, Surapaneni M, Mesapogu S, Neelamraju S. Development and use of chromosome segment substitution lines as a genetic resource for crop improvement. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:1-25. [PMID: 30483819 DOI: 10.1007/s00122-018-3219-y] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 10/24/2018] [Indexed: 05/27/2023]
Abstract
CSSLs are a complete library of introgression lines with chromosomal segments of usually a distant genotype in an adapted background and are valuable genetic resources for basic and applied research on improvement of complex traits. Chromosome segment substitution lines (CSSLs) are genetic stocks representing the complete genome of any genotype in the background of a cultivar as overlapping segments. Ideally, each CSSL has a single chromosome segment from the donor with a maximum recurrent parent genome recovered in the background. CSSL development program requires population-wide backcross breeding and genome-wide marker-assisted selection followed by selfing. Each line in a CSSL library has a specific marker-defined large donor segment. CSSLs are evaluated for any target phenotype to identify lines significantly different from the parental line. These CSSLs are then used to map quantitative trait loci (QTLs) or causal genes. CSSLs are valuable prebreeding tools for broadening the genetic base of existing cultivars and harnessing the genetic diversity from the wild- and distant-related species. These are resources for genetic map construction, mapping QTLs, genes or gene interactions and their functional analysis for crop improvement. In the last two decades, the utility of CSSLs in identification of novel genomic regions and QTL hot spots influencing a wide range of traits has been well demonstrated in food and commercial crops. This review presents an overview of how CSSLs are developed, their status in major crops and their use in genomic studies and gene discovery.
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Affiliation(s)
- Divya Balakrishnan
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India
| | - Malathi Surapaneni
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India
| | - Sukumar Mesapogu
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India
| | - Sarla Neelamraju
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India.
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11
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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: 1.1] [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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12
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Diouf L, Magwanga RO, Gong W, He S, Pan Z, Jia YH, Kirungu JN, Du X. QTL Mapping of Fiber Quality and Yield-Related Traits in an Intra-Specific Upland Cotton Using Genotype by Sequencing (GBS). Int J Mol Sci 2018; 19:E441. [PMID: 29389902 PMCID: PMC5855663 DOI: 10.3390/ijms19020441] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Revised: 01/12/2018] [Accepted: 01/28/2018] [Indexed: 01/04/2023] Open
Abstract
Fiber quality and yield improvement are crucial for cotton domestication and breeding. With the transformation in spinning techniques and multiplicity needs, the development of cotton fiber quality and yield is of great importance. A genetic map of 5178 Single Nucleotide Polymorphism (SNP) markers were generated using 277 F2:3 population, from an intra-specific cross between two upland cotton accessions, CCRI35 a high fiber quality as female and Nan Dan Ba Di Da Hua (NH), with good yield properties as male parent. The map spanned 4768.098 cM with an average distance of 0.92 cM. A total of 110 Quantitative Traits Loci (QTLs) were identified for 11 traits, but only 30 QTLs were consistent in at least two environments. The highest percentage of phenotypic variance explained by a single QTL was 15.45%. Two major cluster regions were found, cluster 1 (chromosome17-D03) and cluster 2 (chromosome26-D12). Five candidate genes were identified in the two QTL cluster regions. Based on GO functional annotation, all the genes were highly correlated with fiber development, with functions such as protein kinase and phosphorylation. The five genes were associated with various fiber traits as follows: Gh_D03G0889 linked to qFM-D03_cb, Gh_D12G0093, Gh_D12G0410, Gh_D12G0435 associated with qFS-D12_cb and Gh_D12G0969 linked to qFY-D12_cb. Further structural annotation and fine mapping is needed to determine the specific role played by the five identified genes in fiber quality and yield related pathway.
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Affiliation(s)
- Latyr Diouf
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
- Senegalese River Valley Development Agency (SAED), Saint-Louis Bp74, Senegal.
| | - Richard Odongo Magwanga
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
- School of Physical and Biological Sciences (SPBS), Jaramogi Oginga Odinga University of Science and Technology (JOOUST), Main Campus, P.O. Box 210-40601, Bondo, Kenya.
| | - Wenfang Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| | - Shoupu He
- 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.
| | - Yin Hua Jia
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| | - Joy Nyangasi Kirungu
- 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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13
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Liu X, Teng Z, Wang J, Wu T, Zhang Z, Deng X, Fang X, Tan Z, Ali I, Liu D, Zhang J, Liu D, Liu F, Zhang Z. Enriching an intraspecific genetic map and identifying QTL for fiber quality and yield component traits across multiple environments in Upland cotton (Gossypium hirsutum L.). Mol Genet Genomics 2017; 292:1281-1306. [PMID: 28733817 DOI: 10.1007/s00438-017-1347-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 06/29/2017] [Indexed: 10/19/2022]
Abstract
Cotton is a significant commercial crop that plays an indispensable role in many domains. Constructing high-density genetic maps and identifying stable quantitative trait locus (QTL) controlling agronomic traits are necessary prerequisites for marker-assisted selection (MAS). A total of 14,899 SSR primer pairs designed from the genome sequence of G. raimondii were screened for polymorphic markers between mapping parents CCRI 35 and Yumian 1, and 712 SSR markers showing polymorphism were used to genotype 180 lines from a (CCRI 35 × Yumian 1) recombinant inbred line (RIL) population. Genetic linkage analysis was conducted on 726 loci obtained from the 712 polymorphic SSR markers, along with 1379 SSR loci obtained in our previous study, and a high-density genetic map with 2051 loci was constructed, which spanned 3508.29 cM with an average distance of 1.71 cM between adjacent markers. Marker orders on the linkage map are highly consistent with the corresponding physical orders on a G. hirsutum genome sequence. Based on fiber quality and yield component trait data collected from six environments, 113 QTLs were identified through two analytical methods. Among these 113 QTLs, 50 were considered stable (detected in multiple environments or for which phenotypic variance explained by additive effect was greater than environment effect), and 18 of these 50 were identified with stability by both methods. These 18 QTLs, including eleven for fiber quality and seven for yield component traits, could be priorities for MAS.
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Affiliation(s)
- Xueying Liu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Zhonghua Teng
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Jinxia Wang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Tiantian Wu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Zhiqin Zhang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Xianping Deng
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Xiaomei Fang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Zhaoyun Tan
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Iftikhar Ali
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Dexin Liu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Jian Zhang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Dajun Liu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Fang Liu
- State Key Laboratory of Cotton Biology/Cotton Research Institute, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
| | - Zhengsheng Zhang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China.
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