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Yang Z, Gao C, Zhang Y, Yan Q, Hu W, Yang L, Wang Z, Li F. Recent progression and future perspectives in cotton genomic breeding. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2023; 65:548-569. [PMID: 36226594 DOI: 10.1111/jipb.13388] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 10/11/2022] [Indexed: 05/26/2023]
Abstract
Upland cotton is an important global cash crop for its long seed fibers and high edible oil and protein content. Progress in cotton genomics promotes the advancement of cotton genetics, evolutionary studies, functional genetics, and breeding, and has ushered cotton research and breeding into a new era. Here, we summarize high-impact genomics studies for cotton from the last 10 years. The diploid Gossypium arboreum and allotetraploid Gossypium hirsutum are the main focus of most genetic and genomic studies. We next review recent progress in cotton molecular biology and genetics, which builds on cotton genome sequencing efforts, population studies, and functional genomics, to provide insights into the mechanisms shaping abiotic and biotic stress tolerance, plant architecture, seed oil content, and fiber development. We also suggest the application of novel technologies and strategies to facilitate genome-based crop breeding. Explosive growth in the amount of novel genomic data, identified genes, gene modules, and pathways is now enabling researchers to utilize multidisciplinary genomics-enabled breeding strategies to cultivate "super cotton", synergistically improving multiple traits. These strategies must rise to meet urgent demands for a sustainable cotton industry.
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Affiliation(s)
- Zhaoen Yang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Chenxu Gao
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
| | - Yihao Zhang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
| | - Qingdi Yan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Wei Hu
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
| | - Lan Yang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Zhi Wang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572000, China
- Sanya Institute, Zhengzhou University, Sanya, 572000, China
| | - Fuguang Li
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450000, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
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Li H, Zhang S, Zhao Y, Zhao X, Xie W, Guo Y, Wang Y, Li K, Guo J, Zhu QH, Zhang X, Jia KP, Miao Y. Identification and Characterization of Cinnamyl Alcohol Dehydrogenase Encoding Genes Involved in Lignin Biosynthesis and Resistance to Verticillium dahliae in Upland Cotton ( Gossypium hirsutum L.). FRONTIERS IN PLANT SCIENCE 2022; 13:840397. [PMID: 35574065 PMCID: PMC9096875 DOI: 10.3389/fpls.2022.840397] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 03/10/2022] [Indexed: 05/16/2023]
Abstract
Verticillium wilt, caused by the soil-borne fungus Verticillium dahliae, is one of the most devastating diseases in cotton (Gossypium spp.). Lignin in the cell wall forms a physical barrier to inhibit pathogen invasion, and defense-induced lignification reinforces secondary cell wall to prevent pathogens from further spreading. Cinnamyl alcohol dehydrogenases (CADs) catalyze the production of three main monolignols, p-coumaryl- (H), coniferyl- (G), and sinapyl-alcohols (S), which are the fundamental blocks of lignin. Here, we identified CAD genes in G. hirsutum, analyzed their expression profiles in cotton leaf, stem, and root from different developmental stages, and selected GhCAD35, GhCAD45, and GhCAD43, which were consistently induced by V. dahliae inoculation in G. hirsutum cultivars resistant or susceptible to V. dahliae. On the basis of confirmation of the in vitro enzymatic activity of the three proteins in generation of the three monolignols, we used virus-induced gene silencing (VIGS) to investigate the effects of silencing of GhCAD35, GhCAD45, or GhCAD43 on resistance to V. dahliae as well as on deposition and the composition of lignin. Silencing each of the three CADs impaired the defense-induced lignification and salicylic acid biosynthesis in stem, and compromised resistance to V. dahliae. Moreover, our study showed that silencing the three GhCADs severely affected the biosynthesis of S-lignin, leading to a decrease of the syringyl/guaiacyl (S/G) ratio. Heterogeneous overexpression of GhCAD35, GhCAD45, or GhCAD43 in Arabidopsis enhanced disease resistance. Taken together, our study demonstrates a role of the three GhCADs in defense-induced lignin biosynthesis and resistance to V. dahliae in G. hirsutum.
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Affiliation(s)
- Haipeng Li
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
| | - Shulin Zhang
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
- College of Biology and Food Engineering, Innovation and Practice Base for Postdoctors, Anyang Institute of Technology, Anyang, China
| | - Yunlei Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Xulong Zhao
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
| | - Wenfei Xie
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
| | - Yutao Guo
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
| | - Yujie Wang
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
| | - Kun Li
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
| | - Jinggong Guo
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
| | - Qian-Hao Zhu
- CSIRO Agriculture and Food, Canberra, ACT, Australia
| | - Xuebin Zhang
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
| | - Kun-Peng Jia
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
- *Correspondence: Kun-Peng Jia,
| | - Yuchen Miao
- State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, Kaifeng, China
- Yuchen Miao,
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Rashid MHO, Li PT, Chen TT, Palanga KK, Gong WK, Ge Q, Gong JW, Liu AY, Lu QW, Diouf L, Sarfraz Z, Jamshed M, Shi YZ, Yuan YL. Genome-wide quantitative trait loci mapping on Verticillium wilt resistance in 300 chromosome segment substitution lines from Gossypium hirsutum × Gossypium barbadense. G3-GENES GENOMES GENETICS 2021; 11:6128683. [PMID: 33846710 PMCID: PMC8104949 DOI: 10.1093/g3journal/jkab027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Accepted: 02/02/2021] [Indexed: 02/07/2023]
Abstract
Cotton Verticillium wilt (VW) is a devastating disease seriously affecting fiber yield and quality, and the most effective and economical prevention measure at present is selection and extension of Gossypium varieties harboring high resistance to VW. However, multiple attempts to improve the VW resistance of the most widely cultivated upland cottons have made little significant progress. The introduction of chromosome segment substitution lines (CSSLs) provide the practical solutions for merging the superior genes related with high yield and wide adaptation from Gossypium hirsutum and VW resistance and the excellent fiber quality from Gossypium barbadense. In this study, 300 CSSLs were chosen from the developed BC5F3:5 CSSLs constructed from CCRI36 (G. hirsutum) and Hai1 (G. barbadense) to conduct quantitative trait locus (QTL) mapping of VW resistance, and a total of 40 QTL relevant to VW disease index (DI) were identified. Phenotypic data were obtained from a 2-year investigation in two fields with two replications per year. All the QTL were distributed on 21 chromosomes, with phenotypic variation of 1.05%-10.52%, and 21 stable QTL were consistent in at least two environments. Based on a meta-analysis, 34 novel QTL were identified, while 6 loci were consistent with previously identified QTL. Meanwhile, 70 QTL hotspot regions were detected, including 44 novel regions. This study concentrates on QTL identification and screening for hotspot regions related with VW in the 300 CSSLs, and the results lay a solid foundation not only for revealing the genetic and molecular mechanisms of VW resistance but also for further fine mapping, gene cloning and molecular designing in breeding programs for resistant cotton varieties.
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Affiliation(s)
- Md Harun Or Rashid
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China.,Senior Scientific Officer, Breeding Division, Bangladesh Jute Research Institute, Dhaka-1207, Bangladesh
| | - Peng-Tao Li
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang 455000, Henan, China
| | - Ting-Ting Chen
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China.,College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, China
| | - Koffi Kibalou Palanga
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China.,Institut Supérieur des Métiers de l'Agriculture- Université de Kara (ISMA-UK), Kara, Togo
| | - Wan-Kui Gong
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Ju-Wu Gong
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Ai-Ying Liu
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Quan-Wei Lu
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang 455000, Henan, China
| | - Latyr Diouf
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Zareen Sarfraz
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Muhammad Jamshed
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Yu-Zhen Shi
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - You-Lu Yuan
- State Key Laboratory of Cotton Biology, Research Base, Anyang Institute of Technology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
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Cui Y, Ge Q, Zhao P, Chen W, Sang X, Zhao Y, Chen Q, Wang H. Rapid Mining of Candidate Genes for Verticillium Wilt Resistance in Cotton Based on BSA-Seq Analysis. FRONTIERS IN PLANT SCIENCE 2021; 12:703011. [PMID: 34691091 PMCID: PMC8531640 DOI: 10.3389/fpls.2021.703011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 08/24/2021] [Indexed: 05/05/2023]
Abstract
Cotton is a globally important cash crop. Verticillium wilt (VW) is commonly known as "cancer" of cotton and causes serious loss of yield and fiber quality in cotton production around the world. Here, we performed a BSA-seq analysis using an F2:3 segregation population to identify the candidate loci involved in VW resistance. Two QTLs (qvw-D05-1 and qvw-D05-2) related to VW resistance in cotton were identified using two resistant/susceptible bulks from the F2 segregation population constructed by crossing the resistant cultivar ZZM2 with the susceptible cultivar J11. A total of 30stop-lost SNPs and 42 stop-gained SNPs, which included 17 genes, were screened in the qvw-D05-2 region by SnpEff analysis. Further analysis of the transcriptome data and qRT-PCR revealed that the expression level of Ghir_D05G037630 (designated as GhDRP) varied significantly at certain time points after infection with V. dahliae. The virus-induced gene silencing of GhDRP resulted in higher susceptibility of the plants to V. dahliae than the control, suggesting that GhDRP is involved in the resistance to V. dahlia infection. This study provides a method for rapid mining of quantitative trait loci and screening of candidate genes, as well as enriches the genomic information and gene resources for the molecular breeding of disease resistance in cotton.
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Affiliation(s)
- Yanli Cui
- Engineering Research Centre of Cotton, Ministry of Education, Xinjiang Agricultural University, Ürümqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Pei Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wei Chen
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiaohui Sang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Yunlei Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- *Correspondence: Yunlei Zhao,
| | - Quanjia Chen
- Engineering Research Centre of Cotton, Ministry of Education, Xinjiang Agricultural University, Ürümqi, China
- Quanjia Chen,
| | - Hongmei Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Hongmei Wang,
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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: 20] [Impact Index Per Article: 5.0] [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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Identification of genomic regions associated with shoot fly resistance in maize and their syntenic relationships in the sorghum genome. PLoS One 2020; 15:e0234335. [PMID: 32516348 PMCID: PMC7282634 DOI: 10.1371/journal.pone.0234335] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 05/22/2020] [Indexed: 11/19/2022] Open
Abstract
Shoot fly (Atherigona naqvii) is one of the major insects affecting spring maize in North India and can cause yield loss up to 60 per cent. The genetics of insect resistance is complex as influenced by genotypic background, insect population and climatic conditions. Therefore, quantitative trait loci (QTL) mapping is a highly effective approach for studying genetically complex forms of insect resistance. The objective of the present study was to dissect the genetic basis of resistance and identification of genomic regions associated with shoot fly resistance. A total of 107 F2 population derived from the cross CM143 (resistant) x CM144 (susceptible) was genotyped with 120 SSR markers. Phenotypic data were recorded on replicated F2:3 progenies for various component traits imparting resistance to shoot fly at different time intervals. Resistance to shoot fly was observed to be under polygenic control as evidenced by the identification of 19 putative QTLs governed by overdominance to partial dominance and additive gene actions. The major QTLs conditioning shoot fly resistance viz., qDH9.1 (deadheart) and qEC9.1 (oviposition) explaining 15.03 and 18.89 per cent phenotypic variance, respectively were colocalized on chromosome 9. These QTLs are syntenic to regions of chromosome 10 of sorghum which were also accounted for deadheart and oviposition suggesting that the same gene block may be responsible for shoot fly resistance. The candidate genes such as cysteine protease, subtilisin-chymotrypsin inhibitor, cytochrome P450 involved in synthesis of alleochemicals, receptor kinases, glossy15 and ubiquitin-proteasome degradation pathway were identified within the predicted QTL regions. This is the first reported mapping of QTLs conferring resistance to shoot fly in maize, and the markers identified here will be a valuable resource for developing elite maize cultivars with resistance to shoot fly.
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Zhang L, Wang M, Li N, Wang H, Qiu P, Pei L, Xu Z, Wang T, Gao E, Liu J, Liu S, Hu Q, Miao Y, Lindsey K, Tu L, Zhu L, Zhang X. Long noncoding RNAs involve in resistance to Verticillium dahliae, a fungal disease in cotton. PLANT BIOTECHNOLOGY JOURNAL 2018; 16:1172-1185. [PMID: 29149461 PMCID: PMC5978870 DOI: 10.1111/pbi.12861] [Citation(s) in RCA: 99] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Revised: 10/13/2017] [Accepted: 11/01/2017] [Indexed: 05/20/2023]
Abstract
Long noncoding RNAs (lncRNAs) have several known functions in plant development, but their possible roles in responding to plant disease remain largely unresolved. In this study, we described a comprehensive disease-responding lncRNA profiles in defence against a cotton fungal disease Verticillium dahliae. We further revealed the conserved and specific characters of disease-responding process between two cotton species. Conservatively for two cotton species, we found the expression dominance of induced lncRNAs in the Dt subgenome, indicating a biased induction pattern in the co-existing subgenomes of allotetraploid cotton. Comparative analysis of lncRNA expression and their proposed functions in resistant Gossypium barbadense cv. '7124' versus susceptible Gossypium hirsutum cv. 'YZ1' revealed their distinct disease response mechanisms. Species-specific (LS) lncRNAs containing more SNPs displayed a fiercer inducing level postinfection than the species-conserved (core) lncRNAs. Gene Ontology enrichment of LS lncRNAs and core lncRNAs indicates distinct roles in the process of biotic stimulus. Further functional analysis showed that two core lncRNAs, GhlncNAT-ANX2- and GhlncNAT-RLP7-silenced seedlings, displayed an enhanced resistance towards V. dahliae and Botrytis cinerea, possibly associated with the increased expression of LOX1 and LOX2. This study represents the first characterization of lncRNAs involved in resistance to fungal disease and provides new clues to elucidate cotton disease response mechanism.
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Affiliation(s)
- Lin Zhang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Maojun Wang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Nannan Li
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Honglei Wang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Ping Qiu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Liuling Pei
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Zheng Xu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Tianyi Wang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Erlin Gao
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Junxia Liu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Shiming Liu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Qin Hu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Yuhuan Miao
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Keith Lindsey
- Integrative Cell Biology LaboratorySchool of Biological and Biomedical SciencesDurham UniversityDurhamUK
| | - Lili Tu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Longfu Zhu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanHubeiChina
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Li T, Ma X, Li N, Zhou L, Liu Z, Han H, Gui Y, Bao Y, Chen J, Dai X. Genome-wide association study discovered candidate genes of Verticillium wilt resistance in upland cotton (Gossypium hirsutum L.). PLANT BIOTECHNOLOGY JOURNAL 2017; 15:1520-1532. [PMID: 28371164 PMCID: PMC5698051 DOI: 10.1111/pbi.12734] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 03/16/2017] [Accepted: 03/21/2017] [Indexed: 05/03/2023]
Abstract
Verticillium wilt (VW), caused by infection by Verticillium dahliae, is considered one of the most yield-limiting diseases in cotton. To examine the genetic architecture of cotton VW resistance, we performed a genome-wide association study (GWAS) using a panel of 299 accessions and 85 630 single nucleotide polymorphisms (SNPs) detected using the specific-locus amplified fragment sequencing (SLAF-seq) approach. Trait-SNP association analysis detected a total of 17 significant SNPs at P < 1.17 × 10-5 (P = 1/85 630, -log10 P = 4.93); the peaks of SNPs associated with VW resistance on A10 were continuous and common in three environments (RDIG2015, RDIF2015 and RDIF2016). Haplotype block structure analysis predicted 22 candidate genes for VW resistance based on A10_99672586 with a minimum P-value (-log10 P = 6.21). One of these genes (CG02) was near the significant SNP A10_99672586 (0.26 Mb), located in a 372-kb haplotype block, and its Arabidopsis AT3G25510 homologues contain TIR-NBS-LRR domains that may be involved in disease resistance response. Real-time quantitative PCR and virus-induced gene silencing (VIGS) analysis showed that CG02 was specific to up-regulation in the resistant (R) genotype Zhongzhimian2 (ZZM2) and that silenced plants were more susceptible to V. dahliae. These results indicate that CG02 is likely the candidate gene for resistance against V. dahliae in cotton. The identified locus or gene may serve as a promising target for genetic engineering and selection for improving resistance to VW in cotton.
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Affiliation(s)
- Tinggang Li
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Xuefeng Ma
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Nanyang Li
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Lei Zhou
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Zheng Liu
- Xinjiang Academy of Agricultural and Reclamation ScienceXinjiangChina
| | - Huanyong Han
- Xinjiang Academy of Agricultural and Reclamation ScienceXinjiangChina
| | - Yuejing Gui
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Yuming Bao
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Jieyin Chen
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Xiaofeng Dai
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
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Zhao Y, Wang H, Chen W, Zhao P, Gong H, Sang X, Cui Y. Regional association analysis-based fine mapping of three clustered QTL for verticillium wilt resistance in cotton (G. hirsutum. L). BMC Genomics 2017; 18:661. [PMID: 28841857 PMCID: PMC6389109 DOI: 10.1186/s12864-017-4074-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Accepted: 08/16/2017] [Indexed: 11/21/2022] Open
Abstract
Background Verticillium wilt is one of the most destructive diseases affecting global cotton production. The most effective way to control wilt disease has been the development of new cotton varieties that are resistant to VW. VW-resistant Upland cotton cultivars have been created in both the USA and China by Gossypium barbadense introgression. More than 100 VW resistance quantitative trait loci have been detected. Results Three clustered VW resistance-related QTL were detected in a 120-line association population and assigned to a genome region of 14,653,469–55,190,112 bp in Dt_chr9. A regional association analysis-based fine-mapping strategy was developed to narrow down the confidence intervals of the above QTL. The estimated LD decay of the genome region of interest was much faster than those of the Dt_chr9 chromosome and the whole genome, suggesting the existence of a recombination hotspot. Thirty-seven haplotype blocks were detected. The confidence intervals of the three clustered QTL were narrowed down to a region of 937,906 bp involving QTL-i23734Gh and a region of 1,389,417 bp involving QTL- i10740Gh, respectively. Each region contained the strongest association signal. Comparative analysis redefined the confidence intervals of the other three QTLs, qDL52T2-c19, QTL-BNL4069, and QTL-JESPR0001. The broad-spectrum VW resistance QTL qVW-D9–1 was demonstrated to be closely linked with the three redefined QTL, QTL-i23734Gh, QTL- i10740Gh and QTL-JESPR0001. Twelve functional genes were detected to be located within the redefined confidence intervals of VW resistance QTL. The mRNA CotAD_60243, encoding E3 ubiquitin-protein ligase UPL2-like, responsible for plant innate immunity and broad-spectrum disease resistance, was found to be overlapped with the strongest association signal i10740Gh. Six mRNAs encoding putative disease-resistance proteins were within the redefined confidence interval of QTL-JESPR0001, suggesting a tandem arrangement of R genes. Conclusions Our results proved that the VW resistance effect related to three clustered VW resistance-related QTL was actually controled by two redefined major QTL and severlal minor loci. The broad-spectrum VW resistance QTL qVW-D9–1 may be closely linked with the two redefined major QTLs. The tandem arrangement of R genes were detected in the redefined confidence interval of QTL-JESPR0001. The candidate genes obtained should be helpful in identifying and characterizing defense genes related to VW resistance QTL. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-4074-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yunlei Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
| | - Hongmei Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China.
| | - Wei Chen
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
| | - Pei Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
| | - Haiyan Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
| | - Xiaohui Sang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
| | - Yanli Cui
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
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10
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Palanga KK, Jamshed M, Rashid MHO, Gong J, Li J, Iqbal MS, Liu A, Shang H, Shi Y, Chen T, Ge Q, Zhang Z, Dilnur T, Li W, Li P, Gong W, Yuan Y. Quantitative Trait Locus Mapping for Verticillium wilt Resistance in an Upland Cotton Recombinant Inbred Line Using SNP-Based High Density Genetic Map. FRONTIERS IN PLANT SCIENCE 2017; 8:382. [PMID: 28424708 PMCID: PMC5380748 DOI: 10.3389/fpls.2017.00382] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 03/06/2017] [Indexed: 05/20/2023]
Abstract
Verticillium wilt (VW) caused by Verticillium dahlia Kleb is one of the most destructive diseases of cotton. Numerous efforts have been made to improve the resistance of upland cotton against VW, with little progress achieved due to the paucity of upland cotton breeding germplasms with high level of resistance to VW. Gossypium barbadense was regarded as more resistant compared to upland cotton; however, it is difficult to apply the resistance from G. barbadense to upland cotton improvement because of the hybrid breakdown and the difficulty to fix resistant phenotype in their interspecific filial. Here we reported QTLs related to VW resistance identified in upland cotton based on 1 year experiment in greenhouse with six replications and 4 years investigations in field with two replications each year. In total, 119 QTLs of disease index (DI) and of disease incidence (DInc) were identified on 25 chromosome of cotton genome except chromosome 13 (c13). For DI, 62 QTLs explaining 3.7-12.2% of the observed phenotypic variations were detected on 24 chromosomes except c11 and c13. For DInc, 59 QTLs explaining 2.3-21.30% of the observed PV were identified on 19 chromosomes except c5, c8, c12-c13, c18-c19, and c26. Seven DI QTLs were detected to be stable in at least environments, among which six have sGK9708 alleles, while 28 DInc QTLs were detected to be stable in at least environments. Eighteen QTL clusters containing 40 QTLs were identified on 13 chromosomes (c1-c4, c6-c7, c10, c14, c17 c20-c22, and c24-c25). Most of the stable QTLs aggregated into these clusters. These QTLs and clusters identification can be an important step toward Verticillium wilt resistant gene cloning in upland cotton and provide useful information to understand the complex genetic bases of Verticillium wilt resistance.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - 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 SciencesAnyang, 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 SciencesAnyang, China
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11
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Quantitative trait loci analysis of Verticillium wilt resistance in interspecific backcross populations of Gossypium hirsutum × Gossypium barbadense. BMC Genomics 2016; 17:877. [PMID: 27814678 PMCID: PMC5097350 DOI: 10.1186/s12864-016-3128-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2015] [Accepted: 09/27/2016] [Indexed: 11/17/2022] Open
Abstract
Background Verticillium wilt (VW) caused by Verticillium dahliae (Kleb) is one of the most destructive diseases of cotton. The identification of highly resistant QTLs or genes in the whole cotton genome is quite important for developing a VW-resistant variety and for further molecular design breeding. Results In the present study, BC1F1, BC1S1, and BC2F1 populations derived from an interspecific backcross between the highly resistant line Hai1 (Gossypium barbadense L.) and the susceptible variety CCRI36 (G. hirsutum L.) as the recurrent parent were constructed. Quantitative trait loci (QTL) related to VW resistance were detected in the whole cotton genome using a high-density simple sequence repeat (SSR) genetic linkage map from the BC1F1 population, with 2292 loci covering 5115.16 centiMorgan (cM) of the cotton (AD) genome, and the data concerning VW resistance that were obtained from four dates of BC2F1 in the artificial disease nursery and one date of BC1S1 and BC2F1 in the field. A total of 48 QTLs for VW resistance were identified, and 37 of these QTLs had positive additive effects, which indicated that the G. barbadense alleles increased resistance to VW and decreased the disease index (DI) by about 2.2–10.7. These QTLs were located on 19 chromosomes, in which 33 in the A subgenome and 15 QTLs in the D subgenome. The 6 QTLs were found to be stable. The 6 QTLs were consistent with those identified previously, and another 42 were new, unreported QTLs, of which 31 QTLs were from G. barbadense. By meta-analysis, 17 QTL hotspot regions were identified and 10 of them were new, unreported hotspot regions. 29 QTLs in this paper were in 12 hotspot regions and were all from G. barbadense. Conclusions These stable or consensus QTL regions warrant further investigation to better understand the genetics and molecular mechanisms underlying VW resistance. This study provides useful information for further comparative analysis and marker-assisted selection in the breeding of disease-resistant cotton. It may also lay an important foundation for gene cloning and further molecular design breeding for the entire cotton genome. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3128-x) contains supplementary material, which is available to authorized users.
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12
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Nie X, Huang C, You C, Li W, Zhao W, Shen C, Zhang B, Wang H, Yan Z, Dai B, Wang M, Zhang X, Lin Z. Genome-wide SSR-based association mapping for fiber quality in nation-wide upland cotton inbreed cultivars in China. BMC Genomics 2016; 17:352. [PMID: 27177443 PMCID: PMC4866303 DOI: 10.1186/s12864-016-2662-x] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Accepted: 04/23/2016] [Indexed: 12/04/2022] Open
Abstract
Background Since upland cotton was introduced into China during the 1920s–1950s, hundreds of inbreed cultivars have been developed. To explore the molecular diversity, population structure and elite alleles, 503 inbred cultivars developed in China and some foreign cultivars from the United States and the Soviet Union were collected and analyzed by 494 genome-wide SSRs (Simple Sequence Repeats). Methods Four hundred and ninety-four pairs of SSRs with high polymorphism and uniform distribution on 26 chromosomes were used to scan polymorphisms in 503 nation-wide upland cottons. The programming language R was used to make boxplots for the phenotypic traits in different environments. Molecular marker data and 6 fiber quality traits were analyzed by the method of MLM (mixed linear model) (P + G + Q + K) in the TASSEL software package on the basis of the population structure and linkage disequilibrium analysis. The loci of elite allelic variation and typical materials carrying elite alleles were identified based on phenotypic effect values. Results A total of 179 markers were polymorphic and generated 426 allele loci; the population based on molecular diversity was classified into seven subpopulations corresponding to pedigree origin, ecological and geographical distribution. The attenuation distance of linkage disequilibrium dropped significantly up to 0–5 cM. Association mapping for fiber quality showed that 216 marker loci were associated with fiber quality traits (P < 0.05) explaining 0.58 % ~ 5.12 % of the phenotypic variation, with an average of 2.70 %. Thirteen marker loci were coincident with other studies, and three were detected for the same trait. Seven quantitative trait loci were related to known genes in fiber development. Based on phenotypic effects, 48 typical materials that contained the elite allele loci related to fiber quality traits were identified and are widely used in practical breeding. Conclusions The molecular diversity and population structure of 503 nation-wide upland cottons in China were evaluated by 494 genome-wide SSRs, and association mapping for fiber quality revealed known and novel elite alleles. The molecular diversity provides a guide for parental mating in cotton breeding, and the association mapping results will aid in the fine-mapping genes related to fiber quality traits and facilitate further studies on candidate genes. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2662-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xinhui Nie
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.,Cotton Research Institute, Shihezi Academy of Agriculture Science, Shihezi, 832011, Xinjiang, China
| | - Cong Huang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Chunyuan You
- Cotton Research Institute, Shihezi Academy of Agriculture Science, Shihezi, 832011, Xinjiang, China
| | - Wu Li
- Economic Crop Research Institute, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, Henan, China
| | - Wenxia Zhao
- 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
| | - Beibei Zhang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Hantao Wang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Zhenhua Yan
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Baoshen Dai
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Maojun Wang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, 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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13
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Zhang J, Yu J, Pei W, Li X, Said J, Song M, Sanogo S. Genetic analysis of Verticillium wilt resistance in a backcross inbred line population and a meta-analysis of quantitative trait loci for disease resistance in cotton. BMC Genomics 2015; 16:577. [PMID: 26239843 PMCID: PMC4524102 DOI: 10.1186/s12864-015-1682-2] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Accepted: 06/01/2015] [Indexed: 12/12/2022] Open
Abstract
Background Verticillium wilt (VW) and Fusarium wilt (FW), caused by the soil-borne fungi Verticillium dahliae and Fusarium oxysporum f. sp. vasinfectum, respectively, are two most destructive diseases in cotton production worldwide. Root-knot nematodes (Meloidogyne incognita, RKN) and reniform nematodes (Rotylenchulus reniformis, RN) cause the highest yield loss in the U.S. Planting disease resistant cultivars is the most cost effective control method. Numerous studies have reported mapping of quantitative trait loci (QTLs) for disease resistance in cotton; however, very few reliable QTLs were identified for use in genomic research and breeding. Results This study first performed a 4-year replicated test of a backcross inbred line (BIL) population for VW resistance, and 10 resistance QTLs were mapped based on a 2895 cM linkage map with 392 SSR markers. The 10 VW QTLs were then placed to a consensus linkage map with other 182 VW QTLs, 75 RKN QTLs, 27 FW QTLs, and 7 RN QTLs reported from 32 publications. A meta-analysis of QTLs identified 28 QTL clusters including 13, 8 and 3 QTL hotspots for resistance to VW, RKN and FW, respectively. The number of QTLs and QTL clusters on chromosomes especially in the A-subgenome was significantly correlated with the number of nucleotide-binding site (NBS) genes, and the distribution of QTLs between homeologous A- and D- subgenome chromosomes was also significantly correlated. Conclusions Ten VW resistance QTL identified in a 4-year replicated study have added useful information to the understanding of the genetic basis of VW resistance in cotton. Twenty-eight disease resistance QTL clusters and 24 hotspots identified from a total of 306 QTLs and linked SSR markers provide important information for marker-assisted selection and high resolution mapping of resistance QTLs and genes. The non-overlapping of most resistance QTL hotspots for different diseases indicates that their resistances are controlled by different genes. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1682-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA.
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of China, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China.
| | - Wenfeng Pei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of China, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China.
| | - Xingli Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of China, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China.
| | - Joseph Said
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA.
| | - Mingzhou Song
- Department of Computer Science, New Mexico State University, Las Cruces, NM, 88003, USA.
| | - Soum Sanogo
- Department of Entomology, Plant Pathology and Weed Science, New Mexico State University, Las Cruces, NM, 88003, USA.
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Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations. Mol Genet Genomics 2015. [PMID: 25758743 DOI: 10.1007/s00438‐015‐1021‐y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
KEY MESSAGE A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.
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15
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Said JI, Knapka JA, Song M, Zhang J. Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations. Mol Genet Genomics 2015; 290:1615-25. [PMID: 25758743 DOI: 10.1007/s00438-015-1021-y] [Citation(s) in RCA: 83] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2014] [Accepted: 02/24/2015] [Indexed: 11/29/2022]
Abstract
KEY MESSAGE A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.
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Affiliation(s)
- Joseph I Said
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, USA,
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