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Safiullina AK, Ernazarova DK, Turaev OS, Rafieva FU, Ernazarova ZA, Arslanova SK, Toshpulatov AK, Oripova BB, Kudratova MK, Khalikov KK, Iskandarov AA, Khidirov MT, Yu JZ, Kushanov FN. Genetic Diversity and Subspecific Races of Upland Cotton ( Gossypium hirsutum L.). Genes (Basel) 2024; 15:1533. [PMID: 39766800 PMCID: PMC11675639 DOI: 10.3390/genes15121533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2024] [Revised: 11/24/2024] [Accepted: 11/25/2024] [Indexed: 01/11/2025] Open
Abstract
Background/Objectives: The classification and phylogenetic relationships of Gossypium hirsutum L. landraces, despite their proximity to southern Mexico, remain unresolved. This study aimed to clarify these relationships using SSR markers and hybridization methods, focusing on subspecies and race differentiation within G. hirsutum L. Methods: Seventy polymorphic SSR markers (out of 177 tested) were used to analyze 141 alleles and calculate genetic distances among accessions. Phylogenetic relationships were determined using MEGA software (version 11.0.13) and visualized in a phylogenetic tree. ANOVA in NCSS 12 was used for statistical analysis. Over 1000 inter-race crosses were conducted to assess boll-setting rates. Results: Distinct phylogenetic patterns were identified between G. hirsutum subspecies and races, correlating with boll-setting rates. Latifolium, richmondii, and morilli showed no significant increase in boll-setting rates in reciprocal crosses. Cultivars Omad and Bakht, as paternal parents, yielded higher boll-setting rates. Religiosum and yucatanense displayed high boll- and seed-setting rates as maternal parents but low rates as paternal parents. Additionally, phylogenetic analysis revealed a close relationship between cultivars 'Omad' and 'Bakht' with G. hirsutum race richmondii, indicating their close evolutionary relationship. Conclusions: Reciprocal differentiation characteristics of G. hirsutum subspecies and races, particularly religiosum and yucatanense, should be considered during hybridization for genetic and breeding studies. Understanding the phylogenetic relationships among G. hirsutum taxa is crucial for exploring the genetic diversity of this economically important species.
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Affiliation(s)
- Asiya K. Safiullina
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
| | - Dilrabo K. Ernazarova
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
- Department of Genetics, National University of Uzbekistan, Tashkent 100174, Uzbekistan
| | - Ozod S. Turaev
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
- Department of Genetics, National University of Uzbekistan, Tashkent 100174, Uzbekistan
- Research Institute of Plant Genetic Resources, National Center for Knowledge and Innovation in Agriculture, Tashkent 100180, Uzbekistan
| | - Feruza U. Rafieva
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
| | - Ziraatkhan A. Ernazarova
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
| | - Sevara K. Arslanova
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
| | - Abdulqahhor Kh. Toshpulatov
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
| | - Barno B. Oripova
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
| | - Mukhlisa K. Kudratova
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
| | - Kuvandik K. Khalikov
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
| | - Abdulloh A. Iskandarov
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
| | - Mukhammad T. Khidirov
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
| | - John Z. Yu
- United States Department of Agriculture (USDA)—Agricultural Research Service (ARS), Southern Plains Agricultural Research Center, College Station, TX 77845, USA;
| | - Fakhriddin N. Kushanov
- Institute of Genetics and Plant Experimental Biology Academy of Sciences of Uzbekistan, Tashkent 111208, Uzbekistan
- Department of Genetics, National University of Uzbekistan, Tashkent 100174, Uzbekistan
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2
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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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Ma C, Zhang Q, Lv J, Qiao K, Fan S, Ma Q, Zhang C. Genome-Wide Analysis of the Phospholipase D Family in Five Cotton Species, and Potential Role of GhPLD2 in Fiber Development and Anther Dehiscence. FRONTIERS IN PLANT SCIENCE 2021; 12:728025. [PMID: 34659294 PMCID: PMC8517146 DOI: 10.3389/fpls.2021.728025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Accepted: 09/08/2021] [Indexed: 05/27/2023]
Abstract
Phospholipase D (PLD) and its hydrolysis product phosphatidic acid play an important role in the regulation of several cellular processes, including root growth, pollen tube elongation, and microtubule reorganization. Here, we systematically identified and analyzed the membership, characterization, and evolutionary relationship of PLDs in five species of cotton. The results of the transcriptomic analysis suggested that the evaluated PLD genes showed high expression levels in anther tissue and during the fiber initiation and elongation periods. Quantitative real-time polymerase chain reaction showed differential expression of GhPLD genes in the anthers of photoperiod sensitive male sterility mutant 5 (psm5). Previous research on multiple stable quantitative trait loci also suggests the role of PLD genes in the fiber development. Further analyses showed that GhPLD2 protein is localized to the plasma membrane. The virus-induced gene silencing of GhPLD2 in cotton seedlings repressed its expression by 40-70%, which led to a reduction in reactive oxygen species (ROS) levels, 22% anther indehiscence, and disrupted fiber initiation and elongation. Thus, we inferred that GhPLD2 may promote ROS production, which, in turn, may regulate anther dehiscence and fiber development.
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Affiliation(s)
- Changkai Ma
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Qian Zhang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Jiaoyan Lv
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Kaikai Qiao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Shuli Fan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Qifeng Ma
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Chaojun Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
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4
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Chen Q, Wang W, Khanal S, Han J, Zhang M, Chen Y, Li Z, Wang K, Paterson AH, Yu J, Chee PW, Wang B. Transcriptome analysis reveals genes potentially related to high fiber strength in a Gossypium hirsutum line IL9 with Gossypium mustelinum introgression. Genome 2021; 64:985-995. [PMID: 34253086 DOI: 10.1139/gen-2020-0177] [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] [Indexed: 11/22/2022]
Abstract
Cotton (Gossypium L.) is the most important fiber crop worldwide. Here, transcriptome analysis was conducted on developing fibers of a G. mustelinum introgression line, IL9, and its recurrent parent, PD94042, at 17 and 21 days post-anthesis (dpa). Differentially expressed genes (DEGs) of PD94042 and IL9 were identified. Gene Ontology (GO) enrichment analysis showed that the annotated DEGs were rich in two main biological processes and two main molecular functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis likewise showed that the annotated DEGs were mainly enriched in metabolic pathways and biosynthesis of secondary metabolites. In total, 52 DEGs were selected as candidate genes based on comparison of the DEGs and GO function annotation information. Quantitative real-time PCR (RT-qPCR) analysis results for 12 randomly selected DEGs were consistent with transcriptome analysis. SNP identification based on G. mustelinum chromatin segment introgression showed that 394 SNPs were identified in 268 DEGs, and two genes with known functions were identified within fiber strength quantitative trait loci (QTL) regions or near the confidence intervals. We identified 52 key genes potentially related to high fiber strength in a G. mustelinum introgression line and provided significant insights into the study of cotton fiber quality improvement.
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Affiliation(s)
- Qi Chen
- School of Life Sciences, Nantong University, Nantong, Jiangsu 226019, P.R. China
| | - Wei Wang
- Jiangsu Coastal Area Institute of Agricultural Sciences/Jiangsu Collaborative Innovation Center for Modern Crop Production, Yancheng, Jiangsu 224002, P.R. China
| | - Sameer Khanal
- Department of Crop and Soil Sciences, University of Georgia, 2356 Rainwater Road, Tifton, GA 31793, USA
| | - Jinlei Han
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, P.R. China
| | - Mi Zhang
- School of Life Sciences, Nantong University, Nantong, Jiangsu 226019, P.R. China
| | - Yan Chen
- School of Life Sciences, Nantong University, Nantong, Jiangsu 226019, P.R. China
| | - Zhenjiang Li
- School of Life Sciences, Nantong University, Nantong, Jiangsu 226019, P.R. China
| | - Kai Wang
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, P.R. China
| | - Andrew H Paterson
- Plant Genome Mapping Laboratory, University of Georgia, 111 Riverbend Road, Athens, GA 30602, USA
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology/Chinese Academy of Agricultural Sciences Cotton Research Institute, Anyang, Henan 455000, P.R. China
| | - Peng W Chee
- Department of Crop and Soil Sciences, University of Georgia, 2356 Rainwater Road, Tifton, GA 31793, USA
| | - Baohua Wang
- School of Life Sciences, Nantong University, Nantong, Jiangsu 226019, P.R. China
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Hafeez A, Razzaq A, Ahmed A, Liu A, Qun G, Junwen L, Shi Y, Deng X, Zafar MM, Ali A, Gong W, Yuan Y. Identification of hub genes through co-expression network of major QTLs of fiber length and strength traits in multiple RIL populations of cotton. Genomics 2021; 113:1325-1337. [PMID: 33713821 DOI: 10.1016/j.ygeno.2021.02.023] [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: 11/17/2020] [Revised: 02/08/2021] [Accepted: 02/16/2021] [Indexed: 11/30/2022]
Abstract
The present study demonstrated a de novo correlation among fiber quality genes in multiple RIL populations including sGK9708 × 0-153, LMY22 × LY343 and Lumianyan28 × Xinluzao24. The current study was conducted to identify the major common QTLs including fiber length and strength, and to identify the co-expression networks of fiber length and strength QTLs harbored genes to target the hub genes. The RNA-seq data of sGK9708 × 0-153 population highlighted 50 and 48 candidate genes of fiber length and fiber strength QTLs. A total of 29 and 21 hub genes were identified in fiber length and strength co-expression network modules. The absolute values of correlation coefficient close to 1 resulted highly positive correlation among hub genes. Results also suggested that the gene correlation significantly influence the gene expression at different fiber development stages. These results might provide useful reference for further experiments in multiple RIL populations and suggest potential candidate genes for functional studies in cotton.
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Affiliation(s)
- Abdul Hafeez
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China; Sindh Agriculture University Tandojam, 70060 Hyderabad, Sindh, Pakistan
| | - Abdul Razzaq
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Aijaz Ahmed
- Sindh Agriculture University Tandojam, 70060 Hyderabad, Sindh, Pakistan
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Ge Qun
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Li Junwen
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Yuzhen Shi
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Muhammad Mubashar Zafar
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Arfan Ali
- FB Genetics Four Brothers Group, Lahore, Pakistan
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
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Guo AH, Su Y, Huang Y, Wang YM, Nie HS, Zhao N, Hua JP. QTL controlling fiber quality traits under salt stress in upland cotton (Gossypium hirsutum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:661-685. [PMID: 33386428 PMCID: PMC7843563 DOI: 10.1007/s00122-020-03721-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Accepted: 10/31/2020] [Indexed: 05/04/2023]
Abstract
QTL for fiber quality traits under salt stress discerned candidate genes controlling fatty acid metabolism. Salinity stress seriously affects plant growth and limits agricultural productivity of crop plants. To dissect the genetic basis of response to salinity stress, a recombinant inbred line population was developed to compare fiber quality in upland cotton (Gossypium hirsutum L.) under salt stress and normal conditions. Based on three datasets of (1) salt stress, (2) normal growth, and (3) the difference value between salt stress and normal conditions, 51, 70, and 53 QTL were mapped, respectively. Three QTL for fiber length (FL) (qFL-Chr1-1, qFL-Chr5-5, and qFL-Chr24-4) were detected under both salt and normal conditions and explained 4.26%, 9.38%, and 3.87% of average phenotypic variation, respectively. Seven genes within intervals of two stable QTL (qFL-Chr1-1 and qFL-Chr5-5) were highly expressed in lines with extreme long fiber. A total of 35 QTL clusters comprised of 107 QTL were located on 18 chromosomes and exhibited pleiotropic effects. Thereinto, two clusters were responsible for improving five fiber quality traits, and 6 influenced FL and fiber strength (FS). The QTL with positive effect for fiber length exhibited active effects on fatty acid synthesis and elongation, but the ones with negative effect played passive roles on fatty acid degradation under salt stress.
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Affiliation(s)
- An-Hui Guo
- Laboratory of Cotton Genetics; Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian district, Beijing, 100193, China
| | - Ying Su
- Laboratory of Cotton Genetics; Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian district, Beijing, 100193, China
| | - Yi Huang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, Hubei, China
| | - Yu-Mei Wang
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, 430064, Hubei, China
| | - Hu-Shuai Nie
- Laboratory of Cotton Genetics; Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian district, Beijing, 100193, China
| | - Nan Zhao
- Laboratory of Cotton Genetics; Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian district, Beijing, 100193, China
| | - Jin-Ping Hua
- Laboratory of Cotton Genetics; Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, No. 2, Yuanmingyuan West Rd, Haidian district, Beijing, 100193, China.
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7
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Pei W, Song J, Wang W, Ma J, Jia B, Wu L, Wu M, Chen Q, Qin Q, Zhu H, Hu C, Lei H, Gao X, Hu H, Zhang Y, Zhang J, Yu J, Qu Y. Quantitative Trait Locus Analysis and Identification of Candidate Genes for Micronaire in an Interspecific Backcross Inbred Line Population of Gossypium hirsutum × Gossypium barbadense. FRONTIERS IN PLANT SCIENCE 2021; 12:763016. [PMID: 34777444 PMCID: PMC8579039 DOI: 10.3389/fpls.2021.763016] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 09/22/2021] [Indexed: 05/08/2023]
Abstract
Cotton is the most important fiber crop and provides indispensable natural fibers for the textile industry. Micronaire (MIC) is determined by fiber fineness and maturity and is an important component of fiber quality. Gossypium barbadense L. possesses long, strong and fine fibers, while upland cotton (Gossypium hirsutum L.) is high yielding with high MIC and widely cultivated worldwide. To identify quantitative trait loci (QTLs) and candidate genes for MIC in G. barbadense, a population of 250 backcross inbred lines (BILs), developed from an interspecific cross of upland cotton CRI36 × Egyptian cotton (G. barbadense) Hai7124, was evaluated in 9 replicated field tests. Based on a high-density genetic map with 7709 genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) markers, 25 MIC QTLs were identified, including 12 previously described QTLs and 13 new QTLs. Importantly, two stable MIC QTLs (qMIC-D03-2 on D03 and qMIC-D08-1 on D08) were identified. Of a total of 338 genes identified within the two QTL regions, eight candidate genes with differential expression between TM-1 and Hai7124 were identified. Our research provides valuable information for improving MIC in cotton breeding.
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Affiliation(s)
- Wenfeng Pei
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Jikun Song
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wenkui Wang
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jianjiang Ma
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Bing Jia
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Luyao Wu
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanjia Chen
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
| | - Qin Qin
- Western Agriculture Research Centre, Chinese Academy of Agricultural Sciences, Changji, China
| | - Haiyong Zhu
- Western Agriculture Research Centre, Chinese Academy of Agricultural Sciences, Changji, China
| | - Chengcheng Hu
- Western Agriculture Research Centre, Chinese Academy of Agricultural Sciences, Changji, China
| | - Hai Lei
- Seed Management Station, Department of Agriculture and Rural Affairs of Xinjiang, Urumqi, China
| | - Xuefei Gao
- Join Hope Seed Co., Ltd., Changji, China
| | - Haijun Hu
- Join Hope Seed Co., Ltd., Changji, China
| | - Yu Zhang
- Join Hope Seed Co., Ltd., Changji, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, United States
- Jinfa Zhang,
| | - Jiwen Yu
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
- *Correspondence: Jiwen Yu,
| | - Yanying Qu
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- Yanying Qu,
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8
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Gu Q, Ke H, Liu Z, Lv X, Sun Z, Zhang M, Chen L, Yang J, Zhang Y, Wu L, Li Z, Wu J, Wang G, Meng C, Zhang G, Wang X, Ma Z. A high-density genetic map and multiple environmental tests reveal novel quantitative trait loci and candidate genes for fibre quality and yield in cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:3395-3408. [PMID: 32894321 DOI: 10.1007/s00122-020-03676-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 08/21/2020] [Indexed: 05/18/2023]
Abstract
A high-density linkage map of an intraspecific RIL population was constructed using 6187 bins to identify QTLs for fibre quality- and yield-related traits in upland cotton by whole-genome resequencing. Good fibre quality and high yield are important production goals in cotton (Gossypium hirsutum L.), which is a leading natural fibre crop worldwide. However, a greater understanding of the genetic variants underlying fibre quality- and yield-related traits is still required. In this study, a large-scale population including 588 F7 recombinant inbred lines, derived from an intraspecific cross between the upland cotton cv. Nongdamian13, which exhibits high quality, and Nongda601, which exhibits a high yield, was genotyped by using 232,946 polymorphic single-nucleotide polymorphisms obtained via a whole-genome resequencing strategy with 4.3-fold genome coverage. We constructed a high-density bin linkage map containing 6187 bin markers spanning 4478.98 cM with an average distance of 0.72 cM. We identified 58 individual quantitative trait loci (QTLs) and 25 QTL clusters harbouring 94 QTLs, and 119 previously undescribed QTLs controlling 13 fibre quality and yield traits across eight environments. Importantly, the QTL counts for fibre quality in the Dt subgenome were more than two times that in the At subgenome, and chromosome D02 harboured the greatest number of QTLs and clusters. Furthermore, we discovered 24 stable QTLs for fibre quality and 12 stable QTLs for yield traits. Four novel major stable QTLs related to fibre length, fibre strength and lint percentage, and seven previously unreported candidate genes with significantly differential expression between the two parents were identified and validated by RNA-seq. Our research provides valuable information for improving the fibre quality and yield in cotton breeding.
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Affiliation(s)
- Qishen Gu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Huifeng Ke
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Zhengwen Liu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Xing Lv
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Zhengwen Sun
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Man Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Liting Chen
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Jun Yang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Yan Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Liqiang Wu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Zhikun Li
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Jinhua Wu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Guoning Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Chengsheng Meng
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Guiyin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China
| | - Xingfen Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China.
| | - Zhiying Ma
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, 071001, China.
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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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10
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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: 23] [Impact Index Per Article: 3.8] [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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11
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Enhancing Upland cotton for drought resilience, productivity, and fiber quality: comparative evaluation and genetic dissection. Mol Genet Genomics 2019; 295:155-176. [PMID: 31620883 DOI: 10.1007/s00438-019-01611-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 09/22/2019] [Indexed: 01/09/2023]
Abstract
To provision the world sustainably, modern society must increase overall crop production, while conserving and preserving natural resources. Producing more with diminishing water resources is an especially daunting endeavor. Toward the goal of genetically improving drought resilience of cultivated Upland cotton (Gossypium hirsutum L.), this study addresses the genetics of differential yield components referred to as productivity and fiber quality traits under regular-water versus low-water (LW) field conditions. We used ten traits to assess water stress deficit, which included six productivity and four fiber quality traits on two recombinant inbred line (RIL) populations from reciprocally crossed cultivars, Phytogen 72 and Stoneville 474. To facilitate genetic inferences, we genotyped RILs with the CottonSNP63K array, assembled high-density linkage maps of over 7000 SNPs and then analyzed quantitative trait variations. Analysis of variance revealed significant differences for all traits (p < 0.05) in these RIL populations. Although the LW irrigation regime significantly reduced all traits, except lint percent, the RILs exhibited a broad phenotypic spectrum of heritable differences across the water regimes. Transgressive segregation occurred among the RILs, suggesting the possibility of genetic gain through phenotypic selection for drought resilience and perhaps through marker-based selection. Analyses revealed more than 150 quantitative trait loci (QTLs) associated with productivity and fiber quality traits (p < 0.005) on different genomic regions of the cotton genome. The multiple-QTL models analysis with LOD > 3.0 detected 21 QTLs associated with productivity and 22 QTLs associated with fiber quality. For fiber traits, strong clustering and QTL associations occurred in c08 and its homolog c24 as well as c10, c14, and c21. Using contemporary genome sequence assemblies and bioinformatically related information, the identification of genomic regions associated with responses to plant stress/drought elevates the possibility of using marker-assisted and omics-based selection to enhance breeding for drought resilient cultivars and identifying candidate genes and networks. RILs with different responses to drought indicated that it is possible to maintain high fiber quality under LW conditions or reduce the of LW impact on quality. The heritable variation among elite bi-parental RILs for productivity and quality under field drought conditions, and their association of QTLs, and thus specific genomic regions, indicate opportunities for breeding-based gains in water resource conservation, i.e., enhancing cotton's agricultural sustainability.
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12
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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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13
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Ma L, Wang Y, Ijaz B, Hua J. Cumulative and different genetic effects contributed to yield heterosis using maternal and paternal backcross populations in Upland cotton. Sci Rep 2019; 9:3984. [PMID: 30850683 PMCID: PMC6408543 DOI: 10.1038/s41598-019-40611-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 02/20/2019] [Indexed: 11/15/2022] Open
Abstract
Heterosis has been utilized in commercial production, but the heterosis mechanism has remained vague. Hybrid cotton is suitable to dissect the heterosis mechanism. In order to explore the genetic basis of heterosis in Upland cotton, we generated paternal and maternal backcross (BC/P and BC/M) populations. Data for yield and yield-component traits were collected over 2 years in three replicated BC/P field trials and four replicated BC/M field trials. At single-locus level, 26 and 27 QTLs were identified in BC/P and BC/M populations, respectively. Six QTLs shared in both BC populations. A total of 27 heterotic loci were detected. Partial dominant and over-dominant QTLs mainly determined yield heterosis in the BC/P and BC/M populations. QTLs for different traits displayed varied genetic effects in two BC populations. Eleven heterotic loci overlapped with QTLs but no common heterotic locus was detected in both BC populations. We resolved the 333 kb (48 genes) and 516 kb (25 genes) physical intervals based on 16 QTL clusters and 35 common QTLs, respectively, in more than one environment or population. We also identified 189 epistatic QTLs and a number of QTL × environment interactions in two BC populations and the corresponding MPH datasets. The results indicated that cumulative effects contributed to yield heterosis in Upland cotton, including epistasis, QTL × environment interaction, additive, partial dominance and over-dominance.
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Affiliation(s)
- Lingling Ma
- Laboratory of Cotton Genetics, Genomics and Breeding/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Yumei Wang
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, 430064, Hubei, China
| | - Babar Ijaz
- Laboratory of Cotton Genetics, Genomics and Breeding/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Jinping Hua
- Laboratory of Cotton Genetics, Genomics and Breeding/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
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Ijaz B, Zhao N, Kong J, Hua J. Fiber Quality Improvement in Upland Cotton ( Gossypium hirsutum L.): Quantitative Trait Loci Mapping and Marker Assisted Selection Application. FRONTIERS IN PLANT SCIENCE 2019; 10:1585. [PMID: 31921240 PMCID: PMC6917639 DOI: 10.3389/fpls.2019.01585] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [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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15
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Słomnicka R, Olczak-Woltman H, Korzeniewska A, Gozdowski D, Niemirowicz-Szczytt K, Bartoszewski G. Genetic mapping of psl locus and quantitative trait loci for angular leaf spot resistance in cucumber ( Cucumis sativus L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2018; 38:111. [PMID: 30174539 PMCID: PMC6105252 DOI: 10.1007/s11032-018-0866-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Accepted: 08/06/2018] [Indexed: 05/16/2023]
Abstract
One of the most important cucumber diseases is bacterial angular leaf spot (ALS), whose increased occurrence in open-field production has been observed over the last years. To map ALS resistance genes, a recombinant inbred line (RIL) mapping population was developed from a narrow cross of cucumber line Gy14 carrying psl resistance gene and susceptible B10 line. Parental lines and RILs were tested under growth chamber conditions as well as in the field for angular leaf spot symptoms. Based on simple sequence repeat and DArTseq, genotyping a genetic map was constructed, which contained 717 loci in seven linkage groups, spanning 599.7 cM with 0.84 cM on average between markers. Monogenic inheritance of the lack of chlorotic halo around the lesions, which is typical for ALS resistance and related with the presence of recessive psl resistance gene, was confirmed. The psl locus was mapped on cucumber chromosome 5. Two major quantitative trait loci (QTL) psl5.1 and psl5.2 related to disease severity were found and located next to each other on chromosome 5; moreover, psl5.1 was co-located with psl locus. Identified QTL were validated in the field experiment. Constructed genetic map and markers linked to ALS resistance loci are novel resources that can contribute to cucumber breeding programs.
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Affiliation(s)
- Renata Słomnicka
- Department of Plant Genetics Breeding and Biotechnology, Faculty of Horticulture Biotechnology and Landscape Architecture, Warsaw University of Life Sciences–SGGW, Warsaw, Poland
| | - Helena Olczak-Woltman
- Department of Plant Genetics Breeding and Biotechnology, Faculty of Horticulture Biotechnology and Landscape Architecture, Warsaw University of Life Sciences–SGGW, Warsaw, Poland
| | - Aleksandra Korzeniewska
- Department of Plant Genetics Breeding and Biotechnology, Faculty of Horticulture Biotechnology and Landscape Architecture, Warsaw University of Life Sciences–SGGW, Warsaw, Poland
| | - Dariusz Gozdowski
- Department of Experimental Design and Bioinformatics, Faculty of Agriculture and Biology, Warsaw University of Life Sciences–SGGW, Warsaw, Poland
| | - Katarzyna Niemirowicz-Szczytt
- Department of Plant Genetics Breeding and Biotechnology, Faculty of Horticulture Biotechnology and Landscape Architecture, Warsaw University of Life Sciences–SGGW, Warsaw, Poland
| | - Grzegorz Bartoszewski
- Department of Plant Genetics Breeding and Biotechnology, Faculty of Horticulture Biotechnology and Landscape Architecture, Warsaw University of Life Sciences–SGGW, Warsaw, Poland
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16
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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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17
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Li C, Fu Y, Sun R, Wang Y, Wang Q. Single-Locus and Multi-Locus Genome-Wide Association Studies in the Genetic Dissection of Fiber Quality Traits in Upland Cotton ( Gossypium hirsutum L.). FRONTIERS IN PLANT SCIENCE 2018; 9:1083. [PMID: 30177935 PMCID: PMC6109694 DOI: 10.3389/fpls.2018.01083] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 07/04/2018] [Indexed: 05/04/2023]
Abstract
A major breeding target in Upland cotton (Gossypium hirsutum L.) is to improve the fiber quality. To address this issue, 169 diverse accessions, genotyped by 53,848 high-quality single-nucleotide polymorphisms (SNPs) and phenotyped in four environments, were used to conduct genome-wide association studies (GWASs) for fiber quality traits using three single-locus and three multi-locus models. As a result, 342 quantitative trait nucleotides (QTNs) controlling fiber quality traits were detected. Of the 342 QTNs, 84 were simultaneously detected in at least two environments or by at least two models, which include 29 for fiber length, 22 for fiber strength, 11 for fiber micronaire, 12 for fiber uniformity, and 10 for fiber elongation. Meanwhile, nine QTNs with 10% greater sizes (R2) were simultaneously detected in at least two environments and between single- and multi-locus models, which include TM80185 (D13) for fiber length, TM1386 (A1) and TM14462 (A6) for fiber strength, TM18616 (A7), TM54735 (D3), and TM79518 (D12) for fiber micronaire, TM77489 (D12) and TM81448 (D13) for fiber uniformity, and TM47772 (D1) for fiber elongation. This indicates the possibility of marker-assisted selection in future breeding programs. Among 455 genes within the linkage disequilibrium regions of the nine QTNs, 113 are potential candidate genes and four are promising candidate genes. These findings reveal the genetic control underlying fiber quality traits and provide insights into possible genetic improvements in Upland cotton fiber quality.
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Affiliation(s)
- Chengqi Li
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Yuanzhi Fu
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Runrun Sun
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Yuanyuan Wang
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Qinglian Wang
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
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