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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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Khidirov MT, Ernazarova DK, Rafieva FU, Ernazarova ZA, Toshpulatov AK, Umarov RF, Kholova MD, Oripova BB, Kudratova MK, Gapparov BM, Khidirova MM, Komilov DJ, Turaev OS, Udall JA, Yu JZ, Kushanov FN. Genomic and Cytogenetic Analysis of Synthetic Polyploids between Diploid and Tetraploid Cotton ( Gossypium) Species. PLANTS (BASEL, SWITZERLAND) 2023; 12:4184. [PMID: 38140511 PMCID: PMC10748080 DOI: 10.3390/plants12244184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 12/08/2023] [Accepted: 12/12/2023] [Indexed: 12/24/2023]
Abstract
Cotton (Gossypium spp.) is the most important natural fiber source in the world. The genetic potential of cotton can be successfully and efficiently exploited by identifying and solving the complex fundamental problems of systematics, evolution, and phylogeny, based on interspecific hybridization of cotton. This study describes the results of interspecific hybridization of G. herbaceum L. (A1-genome) and G. mustelinum Miers ex Watt (AD4-genome) species, obtaining fertile hybrids through synthetic polyploidization of otherwise sterile triploid forms with colchicine (C22H25NO6) treatment. The fertile F1C hybrids were produced from five different cross combinations: (1) G. herbaceum subsp. frutescens × G. mustelinum; (2) G. herbaceum subsp. pseudoarboreum × G. mustelinum; (3) G. herbaceum subsp. pseudoarboreum f. harga × G. mustelinum; (4) G. herbaceum subsp. africanum × G. mustelinum; (5) G. herbaceum subsp. euherbaceum (variety A-833) × G. mustelinum. Cytogenetic analysis discovered normal conjugation of bivalent chromosomes in addition to univalent, open, and closed ring-shaped quadrivalent chromosomes at the stage of metaphase I in the F1C and F2C hybrids. The setting of hybrid bolls obtained as a result of these crosses ranged from 13.8-92.2%, the fertility of seeds in hybrid bolls from 9.7-16.3%, and the pollen viability rates from 36.6-63.8%. Two transgressive plants with long fiber of 35.1-37.0 mm and one plant with extra-long fiber of 39.1-41.0 mm were identified in the F2C progeny of G. herbaceum subsp. frutescens × G. mustelinum cross. Phylogenetic analysis with 72 SSR markers that detect genomic changes showed that tetraploid hybrids derived from the G. herbaceum × G. mustelinum were closer to the species G. mustelinum. The G. herbaceum subsp. frutescens was closer to the cultivated form, and its subsp. africanum was closer to the wild form. New knowledge of the interspecific hybridization and synthetic polyploidization was developed for understanding the genetic mechanisms of the evolution of tetraploid cotton during speciation. The synthetic polyploids of cotton obtained in this study would provide beneficial genes for developing new cotton varieties of the G. hirsutum species, with high-quality cotton fiber and strong tolerance to biotic or abiotic stress. In particular, the introduction of these polyploids to conventional and molecular breeding can serve as a bridge of transferring valuable genes related to high-quality fiber and stress tolerance from different cotton species to the new cultivars.
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Affiliation(s)
- Mukhammad T. Khidirov
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
| | - Dilrabo K. Ernazarova
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
- Department of Genetics, National University of Uzbekistan, Tashkent 100174, Uzbekistan;
| | - Feruza U. Rafieva
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
| | - Ziraatkhan A. Ernazarova
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
| | - Abdulqahhor Kh. Toshpulatov
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
| | - Ramziddin F. Umarov
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
| | - Madina D. Kholova
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
| | - Barno B. Oripova
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
| | - Mukhlisa K. Kudratova
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
| | - Bunyod M. Gapparov
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
| | | | - Doniyor J. Komilov
- Department of Biology, Namangan State University, Uychi Street-316, Namangan 160100, Uzbekistan;
| | - Ozod S. Turaev
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
- Department of Genetics, National University of Uzbekistan, Tashkent 100174, Uzbekistan;
| | - Joshua A. Udall
- United States Department of Agriculture (USDA)-Agricultural Research Service (ARS), Southern Plains Agricultural Research Center, 2881 F&B Road, College Station, TX 77845, USA;
| | - John Z. Yu
- United States Department of Agriculture (USDA)-Agricultural Research Service (ARS), Southern Plains Agricultural Research Center, 2881 F&B Road, College Station, TX 77845, USA;
| | - Fakhriddin N. Kushanov
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of the Republic of Uzbekistan, Tashkent 111226, Uzbekistan; (M.T.K.); (D.K.E.); (F.U.R.); (Z.A.E.); (A.K.T.); (R.F.U.); (M.D.K.); (B.B.O.); (M.K.K.); (B.M.G.); (O.S.T.)
- Department of Genetics, National University of Uzbekistan, Tashkent 100174, Uzbekistan;
- Department of Biology, Namangan State University, Uychi Street-316, Namangan 160100, Uzbekistan;
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3
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Zhu Y, Thyssen GN, Abdelraheem A, Teng Z, Fang DD, Jenkins JN, McCarty JC, Wedegaertner T, Hake K, Zhang J. A GWAS identified a major QTL for resistance to Fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) race 4 in a MAGIC population of Upland cotton and a meta-analysis of QTLs for Fusarium wilt resistance. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2297-2312. [PMID: 35577933 DOI: 10.1007/s00122-022-04113-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Accepted: 04/20/2022] [Indexed: 05/16/2023]
Abstract
A major QTL conferring resistance to Fusarium wilt race 4 in a narrow region of chromosome D02 was identified in a MAGIC population of 550 RILs of Upland cotton. Numerous studies have been conducted to investigate the genetic basis of Fusarium wilt (FW, caused by Fusarium oxysporum f. sp. vasinfectum, FOV) resistance using bi-parental and association mapping populations in cotton. In this study, a multi-parent advanced generation inter-cross (MAGIC) population of 550 recombinant inbred lines (RILs), together with their 11 Upland cotton (Gossypium hirsutum) parents, was used to identify QTLs for FOV race 4 (FOV4) resistance. Among the parents, Acala Ultima, M-240 RNR, and Stoneville 474 were the most resistant, while Deltapine Acala 90, Coker 315, and Stoneville 825 were the most susceptible. Twenty-two MAGIC lines were consistently resistant to FOV4. Through a genome-wide association study (GWAS) based on 473,516 polymorphic SNPs, a major FOV4 resistance QTL within a narrow region on chromosomes D02 was detected, allowing identification of 14 candidate genes. Additionally, a meta-analysis of 133 published FW resistance QTLs showed a D subgenome and individual chromosome bias and no correlation between homeologous chromosome pairs. This study represents the first GWAS study using a largest genetic population and the most comprehensive meta-analysis for FW resistance in cotton. The results illustrated that 550 lines were not enough for high resolution mapping to pinpoint a candidate gene, and experimental errors in phenotyping cotton for FW resistance further compromised the accuracy and precision in QTL localization and identification of candidate genes. This study identified FOV4-resistant parents and MAGIC lines, and the first major QTL for FOV4 resistance in Upland cotton, providing useful information for developing FOV4-resistant cultivars and further genomic studies towards identification of causal genes for FOV4 resistance in cotton.
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Affiliation(s)
- Yi Zhu
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Gregory N Thyssen
- Cotton Fiber Bioscience and Cotton Chemistry and Utilization Research Units, USDA-ARS-SRRC, New Orleans, LA, USA
| | - Abdelraheem Abdelraheem
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Zonghua Teng
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - David D Fang
- Cotton Fiber Bioscience Research Unit, USDA-ARS-SRRC, New Orleans, LA, USA
| | - Johnie N Jenkins
- Crop Science Research Laboratory, USDA-ARS, Mississippi State, MS, USA
| | - Jack C McCarty
- Crop Science Research Laboratory, USDA-ARS, Mississippi State, MS, USA
| | | | | | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA.
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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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Kumar P, Nimbal S, Budhlakoti N, Singh V, Sangwan RS. Genetic diversity and population structure analysis for morphological traits in upland cotton (Gossypium hirsutum L.). J Appl Genet 2021; 63:87-101. [PMID: 34718944 DOI: 10.1007/s13353-021-00667-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 10/13/2021] [Accepted: 10/19/2021] [Indexed: 11/27/2022]
Abstract
A total of 96 different genotypes of upland cotton (Gossypium hirsutum) were selected from the breeding material and germplasm available at CCS HAU, India, to find the novel marker-trait associations for morphological traits used for registration of variety in upland cotton. Twenty-three morphological traits of the selected genotypes were recorded in field trials conducted in two replication of randomized block design during Kharif 2018 and 2019. A total of 11 traits showed sufficient variations in the screened germplasm and the same were further used for association mapping. A total of 168 SSRs were used for genotyping, of which 97 SSRs showed polymorphism amplifying 293 different alleles with an average of 3.02 alleles per SSR. Clustering, principal component analysis, and population structure analysis advocated that the current germplasm panel has enough diversity to be considered for association mapping. A total of 20 significant marker-trait associations were identified by the mixed linear model (MLM) and compressed mixed linear model (CMLM), of which 15 were common to both models, hence considered as promising associations. To the best of our knowledge, it is a first attempt to identify the linked markers in relation to morphological traits for the cotton crop. Results of the present study will be highly useful in speeding up variety registration programmes of upland cotton complementing to Distinctiveness, Uniformity, and Stability (DUS) testing.
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Affiliation(s)
- Pawan Kumar
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, 125004, India
| | - Somveer Nimbal
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, 125004, India.
| | - Neeraj Budhlakoti
- ICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012, India
| | - Varsha Singh
- Department of Molecular Biology, Biotechnology and Bioinformatics, CCS Haryana Agricultural University, 125004, Hisar, India
| | - Rajvir Singh Sangwan
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, 125004, India
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Huang C, Shen C, Wen T, Gao B, Zhu D, Li D, Lin Z. Genome-wide association mapping for agronomic traits in an 8-way Upland cotton MAGIC population by SLAF-seq. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:2459-2468. [PMID: 33912997 DOI: 10.1007/s00122-021-03835-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 04/12/2021] [Indexed: 06/12/2023]
Abstract
One sub-MAGIC population was genotyped using SLAF-seq, and QTLs and candidate genes for agronomic traits were identified in Upland cotton. The agronomic traits of Upland cotton have serious impacts on cotton production, as well as economic benefits. To discover the genetic basis of important agronomic traits in Upland cotton, a subset MAGIC (multi-parent advanced generation inter-cross) population containing 372 lines (SMLs) was selected from an 8-way MAGIC population with 960 lines. The 372 lines and 8 parents were phenotyped in six environments and deeply genotyped by SLAF-seq with 60,495 polymorphic SNPs. The genetic diversity indexes of all SNPs were 0.324 and 0.362 for the parents and MAGIC lines, respectively. The LD decay distance of the SMLs was 600 kb (r2 = 0.1). Genome-wide association mapping was performed using 60,495 SNPs and the phenotypic data of the SMLs, and 177 SNPs were identified to be significantly associated with 9 stable agronomic traits in multiple environments. The identified SNPs were divided into 117 QTLs (quantitative trait loci) by LD decay distance, explaining 5.44% to 31.64% of the phenotypic variation. Among the 117 QTLs, 3 QTLs were stable in multiple environments, and 11 QTL regions were proven to have pleiotropism associated with multiple traits. Within QTL regions, 154 genes were preferentially expressed in correlated tissues, and 8 genes with known functions were identified as priori candidate genes. Two genes, GhACT1 and GhGASL3, reported to have clear functions, were, respectively, located in qFE-A05-4 and qFE-D04-3, two stable QTLs for FE. This study revealed the genetic basis of important agronomic traits of Upland cotton, and the results will facilitate molecular breeding in cotton.
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Affiliation(s)
- Cong Huang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Chao Shen
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Tianwang Wen
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Bin Gao
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - De Zhu
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Dingguo Li
- Institute of Crop Genetic and Breeding, Yangtze University, Jingzhou, 434025, Hubei, China.
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
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Kumar P, Nimbal S, Sangwan RS, Budhlakoti N, Singh V, Mishra DC, Sagar, Choudhary RR. Identification of Novel Marker-Trait Associations for Lint Yield Contributing Traits in Upland Cotton ( Gossypium hirsutum L.) Using SSRs. FRONTIERS IN PLANT SCIENCE 2021; 12:653270. [PMID: 34122477 PMCID: PMC8187916 DOI: 10.3389/fpls.2021.653270] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 04/16/2021] [Indexed: 11/10/2023]
Abstract
Improving the yield of lint is the main objective for most of the cotton crop improvement programs throughout the world as it meets the demand of fiber for textile industries. In the current study, 96 genotypes of Gossypium hirsutum were used to find novel simple sequence repeat marker-based associations for lint yield contributing traits by linkage disequilibrium. Extensive phenotyping of 96 genotypes for various agronomic traits was done for two consecutive years (2018 and 2019) in early, normal, and late sown environments. Out of 168 SSR markers screened over the 96 genotypes, a total of 97 polymorphic markers containing 293 alleles were used for analysis. Three different models, i.e., mixed linear model (MLM), compressed mixed linear model (CMLM), and multiple locus mixed linear model (MLMM), were used to detect the significant marker-trait associations for six different environments separately. A total of 38 significant marker-trait associations that were common to at least two environments were considered as promising associations and detailed annotation of the significant markers has been carried out. Twenty-two marker-trait associations were found to be novel in the current study. These results will be very useful for crop improvement programs using marker-assisted cotton breeding.
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Affiliation(s)
- Pawan Kumar
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | - Somveer Nimbal
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | - Rajvir Singh Sangwan
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | - Neeraj Budhlakoti
- Indian Council of Agricultural Research-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Varsha Singh
- Department of Molecular Biology and Biotechnology, CCS Haryana Agricultural University, Hisar, India
| | - Dwijesh Chandra Mishra
- Indian Council of Agricultural Research-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Sagar
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | - Raju Ram Choudhary
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
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8
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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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Zhang TT, Zhang NY, Li W, Zhou XJ, Pei XY, Liu YG, Ren ZY, He KL, Zhang WS, Zhou KH, Zhang F, Ma XF, Yang DG, Li ZH. Genetic structure, gene flow pattern, and association analysis of superior germplasm resources in domesticated upland cotton ( Gossypium hirsutum L.). PLANT DIVERSITY 2020; 42:189-197. [PMID: 32695952 PMCID: PMC7361167 DOI: 10.1016/j.pld.2020.03.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 02/28/2020] [Accepted: 03/03/2020] [Indexed: 06/11/2023]
Abstract
Gene flow patterns and the genetic structure of domesticated crops like cotton are not well understood. Furthermore, marker-assisted breeding of cotton has lagged far behind that of other major crops because the loci associated with cotton traits such as fiber yield and quality have scarcely been identified. In this study, we used 19 microsatellites to first determine the population genetic structure and patterns of gene flow of superior germplasm resources in upland cotton. We then used association analysis to identify which markers were associated with 15 agronomic traits (including ten yield and five fiber quality traits). The results showed that the upland cotton accessions have low levels of genetic diversity (polymorphism information content = 0.427), although extensive gene flow occurred among different ecological and geographic regions. Bayesian clustering analysis indicated that the cotton resources used in this study did not belong to obvious geographic populations, which may be the consequence of a single source of domestication followed by frequent genetic introgression mediated by human transference. A total of 82 maker-trait associations were examined in association analysis and the related ratios for phenotypic variations ranged from 3.04% to 47.14%. Interestingly, nine SSR markers were detected in more than one environmental condition. In addition, 14 SSR markers were co-associated with two or more different traits. It was noteworthy that NAU4860 and NAU5077 markers detected at least in two environments were simultaneously associated with three fiber quality traits (uniformity index, specific breaking strength and micronaire value). In conclusion, these findings provide new insights into the population structure and genetic exchange pattern of cultivated cotton accessions. The quantitative trait loci of domesticated cotton identified will also be very useful for improvement of yield and fiber quality of cotton in molecular breeding programs.
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Affiliation(s)
- Ting-Ting Zhang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, 710069, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Na-Yao Zhang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, 710069, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Wei Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Xiao-Jian Zhou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Xiao-Yu Pei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Yan-Gai Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Zhong-Ying Ren
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Kun-Lun He
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Wen-Sheng Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Ke-Hai Zhou
- 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
| | - Xiong-Feng Ma
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Dai-Gang Yang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Zhong-Hu Li
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, 710069, China
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Development of SSR markers based on transcriptome data and association mapping analysis for fruit shell thickness associated traits in oil palm ( Elaeis guineensis Jacq.). 3 Biotech 2020; 10:280. [PMID: 32537380 DOI: 10.1007/s13205-020-02269-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 05/20/2020] [Indexed: 10/24/2022] Open
Abstract
Present study mainly aimed to ascertain the distribution characteristics of gene-based microsatellite loci and to develop polymorphic SSR markers from the already available transcriptome data of Elaeis guineensis Jacq, an important oil crop. From this study, we identified the sum of 5791 SSRs across 51,425 unigenes from the transcripts of oil palm. We were able to evaluate 331primer pairs and characterized 183 polymorphic gene-based SSR markers. We identified a total of 506 alleles from the 183 polymorphic SSR loci, with an average of 2.77 alleles per locus. The characterized gene-based SSR markers from the transcriptome data of oil palm exhibited moderate levels of polymorphism with a significant level of heterozygosity ranges from 0.096 to 0.594 (mean = 0.336 ± 0.11). Among the identified SSR markers, sixty polymorphic markers were used to analyze genotypes of 55 oil palm accessions selected from three different provinces of China. Association mapping analysis provided the information of four markers that are associated with fruit shell thickness trait of oil palm. Among the four markers identified from association analysis, one SSR marker obtained from Unigene17150 is strictly associated with the oil palm fruit shell thickness trait.
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11
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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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12
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Ma J, Pei W, Ma Q, Geng Y, Liu G, Liu J, Cui Y, Zhang X, Wu M, Li X, Li D, Zang X, Song J, Tang S, Zhang J, Yu S, Yu J. QTL analysis and candidate gene identification for plant height in cotton based on an interspecific backcross inbred line population of Gossypium hirsutum × Gossypium barbadense. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:2663-2676. [PMID: 31236630 DOI: 10.1007/s00122-019-03380-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 06/14/2019] [Indexed: 05/24/2023]
Abstract
We constructed the first high-quality and high-density genetic linkage map for an interspecific BIL population in cotton by specific-locus amplified fragment sequencing for QTL mapping. A novel gene GhPIN3 for plant height was identified in cotton. Ideal plant height (PH) is important for improving lint yield and mechanized harvesting in cotton. Most published genetic studies on cotton have focused on fibre yield and quality traits rather than PH. To facilitate the understanding of the genetic basis in PH, an interspecific backcross inbred line (BIL) population of 250 lines derived from upland cotton (Gossypium hirsutum L.) CRI36 and Egyptian cotton (G. barbadense L.) Hai7124 was used to construct a high-density genetic linkage map for quantitative trait locus (QTL) mapping. The high-density genetic map harboured 7,709 genotyping-by-sequencing (GBS)-based single nucleotide polymorphism (SNP) markers that covered 3,433.24 cM with a mean marker interval of 0.67 cM. In total, ten PH QTLs were identified and each explained 4.27-14.92% of the phenotypic variation, four of which were stable as they were mapped in at least two tests or based on best linear unbiased prediction in seven field tests. Based on functional annotation of orthologues in Arabidopsis and transcriptome data for the genes within the stable QTL regions, GhPIN3 encoding for the hormone auxin efflux carrier protein was identified as a candidate gene located in the stable QTL qPH-Dt1-1 region. A qRT-PCR analysis showed that the expression level of GhPIN3 in apical tissues was significantly higher in four short-statured cotton genotypes than that in four tall-statured cotton genotypes. Virus-induced gene silencing cotton has significantly increased PH when the expression of the GhPIN3 gene was suppressed.
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Affiliation(s)
- Jianjiang Ma
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
- College of Agriculture, Northwest A&F University, Yangling, 712100, Shanxi, China
| | - Wenfeng Pei
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, 830001, China
| | - Qifeng Ma
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Yanhui Geng
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Guoyuan Liu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Ji Liu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Yupeng Cui
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Xia Zhang
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Xingli Li
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Dan Li
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - XinShan Zang
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Jikun Song
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Shurong Tang
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, 880033, USA.
| | - Shuxun Yu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China.
- College of Agriculture, Northwest A&F University, Yangling, 712100, Shanxi, China.
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China.
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13
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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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14
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You FM, Xiao J, Li P, Yao Z, Jia G, He L, Kumar S, Soto-Cerda B, Duguid SD, Booker HM, Rashid KY, Cloutier S. Genome-Wide Association Study and Selection Signatures Detect Genomic Regions Associated with Seed Yield and Oil Quality in Flax. Int J Mol Sci 2018; 19:ijms19082303. [PMID: 30082613 PMCID: PMC6121305 DOI: 10.3390/ijms19082303] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 08/02/2018] [Accepted: 08/03/2018] [Indexed: 12/31/2022] Open
Abstract
A genome-wide association study (GWAS) was performed on a set of 260 lines which belong to three different bi-parental flax mapping populations. These lines were sequenced to an averaged genome coverage of 19× using the Illumina Hi-Seq platform. Phenotypic data for 11 seed yield and oil quality traits were collected in eight year/location environments. A total of 17,288 single nucleotide polymorphisms were identified, which explained more than 80% of the phenotypic variation for days to maturity (DTM), iodine value (IOD), palmitic (PAL), stearic, linoleic (LIO) and linolenic (LIN) acid contents. Twenty-three unique genomic regions associated with 33 quantitative trait loci (QTL) for the studied traits were detected, thereby validating four genomic regions previously identified. The 33 QTL explained 48–73% of the phenotypic variation for oil content, IOD, PAL, LIO and LIN but only 8–14% for plant height, DTM and seed yield. A genome-wide selective sweep scan for selection signatures detected 114 genomic regions that accounted for 7.82% of the flax pseudomolecule and overlapped with the 11 GWAS-detected genomic regions associated with 18 QTL for 11 traits. The results demonstrate the utility of GWAS combined with selection signatures for dissection of the genetic structure of traits and for pinpointing genomic regions for breeding improvement.
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Affiliation(s)
- Frank M You
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada.
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB R6M 1Y5, Canada.
| | - Jin Xiao
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada.
- Department of Agronomy, Nanjing Agricultural University, Nanjing 210095, China.
| | - Pingchuan Li
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada.
| | - Zhen Yao
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB R6M 1Y5, Canada.
| | - Gaofeng Jia
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada.
- Crop Development Centre, University of Saskatchewan, Saskatoon, SK S7N 5A8, Canada.
| | - Liqiang He
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada.
| | - Santosh Kumar
- Brandon Research and Development Centre, Agriculture and Agri-Food Canada, Brandon, MB R7A 5Y3, Canada.
| | - Braulio Soto-Cerda
- Department of Plant Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada.
- Agriaquaculture Nutritional Genomic Center, CGNA, Temuco 4871158, Chile.
| | - Scott D Duguid
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB R6M 1Y5, Canada.
| | - Helen M Booker
- Crop Development Centre, University of Saskatchewan, Saskatoon, SK S7N 5A8, Canada.
| | - Khalid Y Rashid
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB R6M 1Y5, Canada.
| | - Sylvie Cloutier
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada.
- Department of Plant Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada.
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