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Thyssen GN, Jenkins JN, McCarty JC, Zeng L, Campbell BT, Delhom CD, Islam MS, Li P, Jones DC, Condon BD, Fang DD. Whole genome sequencing of a MAGIC population identified genomic loci and candidate genes for major fiber quality traits in upland cotton (Gossypium hirsutum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:989-999. [PMID: 30506522 DOI: 10.1007/s00122-018-3254-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Accepted: 11/27/2018] [Indexed: 05/25/2023]
Abstract
Significant associations between candidate genes and six major cotton fiber quality traits were identified in a MAGIC population using GWAS and whole genome sequencing. Upland cotton (Gossypium hirsutum L.) is the world's major renewable source of fibers for textiles. To identify causative genetic variants that influence the major agronomic measures of cotton fiber quality, which are used to set discount or premium prices on each bale of cotton in the USA, we measured six fiber phenotypes from twelve environments, across three locations and 7 years. Our 550 recombinant inbred lines were derived from a multi-parent advanced generation intercross population and were whole-genome-sequenced at 3× coverage, along with the eleven parental cultivars at 20× coverage. The segregation of 473,517 single nucleotide polymorphisms (SNPs) in this population, including 7506 non-synonymous mutations, was combined with phenotypic data to identify seven highly significant fiber quality loci. At these loci, we found fourteen genes with non-synonymous SNPs. Among these loci, some had simple additive effects, while others were only important in a subset of the population. We observed additive effects for elongation and micronaire, when the three most significant loci for each trait were examined. In an informative subset where the major multi-trait locus on chromosome A07:72-Mb was fixed, we unmasked the identity of another significant fiber strength locus in gene Gh_D13G1792 on chromosome D13. The micronaire phenotype only revealed one highly significant genetic locus at one environmental location, demonstrating a significant genetic by environment component. These loci and candidate causative variant alleles will be useful to cotton breeders for marker-assisted selection with minimal linkage drag and potential biotechnological applications.
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Affiliation(s)
- Gregory N Thyssen
- Cotton Fiber Bioscience Research Unit, USDA-ARS-SRRC, New Orleans, LA, 70124, USA
- Cotton Chemistry and Utilization Unit, USDA-ARS-SRRC, New Orleans, LA, 70124, USA
| | - Johnie N Jenkins
- Genetics and Sustainable Agriculture Research Unit, USDA-ARS, Mississippi State, MS, 39762, USA
| | - Jack C McCarty
- Genetics and Sustainable Agriculture Research Unit, USDA-ARS, Mississippi State, MS, 39762, USA
| | - Linghe Zeng
- Crop Genetics Research Unit, USDA-ARS, Stoneville, MS, 38776, USA
| | - B Todd Campbell
- Coastal Plain Soil, Water and Plant Conservation Research Unit, USDA-ARS, Florence, SC, 29501, USA
| | - Christopher D Delhom
- Cotton Structure and Quality Research Unit, USDA-ARS-SRRC, New Orleans, LA, 70124, USA
| | - Md Sariful Islam
- Sugarcane Production Research Unit, USDA-ARS, Canal Point, FL, 33438, USA
| | - Ping Li
- Cotton Fiber Bioscience Research Unit, USDA-ARS-SRRC, New Orleans, LA, 70124, USA
| | | | - Brian D Condon
- Cotton Chemistry and Utilization Unit, USDA-ARS-SRRC, New Orleans, LA, 70124, USA
| | - David D Fang
- Cotton Fiber Bioscience Research Unit, USDA-ARS-SRRC, New Orleans, LA, 70124, USA.
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QTL analysis for yield and fibre quality traits using three sets of introgression lines developed from three Gossypium hirsutum race stocks. Mol Genet Genomics 2019; 294:789-810. [PMID: 30887144 DOI: 10.1007/s00438-019-01548-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 03/12/2019] [Indexed: 12/31/2022]
Abstract
Upland cotton (Gossypium hirsutum L.) race stocks may possess desirable traits for the genetic improvement of cotton. Quantitative trait locus (QTL) analysis can assist in uncovering new alleles from unadapted race stocks. In this study, three sets of chromosome segment introgression lines (ILs) were developed from three backcrosses (BC3) between three race stocks, G. hirsutum races latifolium accs. TX-34 and TX-48 and punctatum acc. TX-114, as donor parents and Texas Marker-1 (TM-1) as the recurrent parent. Based on a total of 452 polymorphic simple sequence repeat (SSR) markers in BC3F2 genotyping, 149, 150 and 184 ILs were obtained from TM-1 × TX-34, TM-1 × TX-48 and TM-1 × TX-114, respectively. The average introgressed chromosomal segment length was 12.7 cM, and the total genetic distance was 3268 cM covering approximately 73.4% of the Upland cotton genome. The BC3F2, BC3F2:3 and BC3F2:4 progeny, which produced the ILs, were evaluated for yield and fibre quality traits. A total of 128 QTLs were detected, each of which explained 1.6-13.0% of the phenotypic variation. Thirty-five common QTLs related to eight traits were detected. Six QTL clusters were found on five chromosomes. Thirty-eight QTLs were previously unreported, and they may be footprints of cotton domestication. Domestication or artificial selection by humans successfully eliminated most unfavourable QTLs (21/38); however, some favourable QTLs (17/38) are not present in modern cultivars, demonstrating the importance of race stocks for improving cotton cultivars. The 26 elite ILs developed could be used to improve the yield and fibre quality components simultaneously. These results provide information on desirable QTLs for cotton improvement.
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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: 7] [Impact Index Per Article: 1.4] [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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Cui Y, Ma J, Liu G, Wang N, Pei W, Wu M, Li X, Zhang J, Yu J. Genome-Wide Identification, Sequence Variation, and Expression of the Glycerol-3-Phosphate Acyltransferase (GPAT) Gene Family in Gossypium. Front Genet 2019; 10:116. [PMID: 30842789 PMCID: PMC6391866 DOI: 10.3389/fgene.2019.00116] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 02/01/2019] [Indexed: 11/13/2022] Open
Abstract
Cotton is an economically important crop grown for natural fiber and seed oil production. Cottonseed oil ranks third after soybean oil and colza oil in terms of edible oilseed tonnage worldwide. Glycerol-3-phosphate acyltransferase (GPAT) genes encode enzymes involved in triacylglycerol biosynthesis in plants. In the present study, 85 predicted GPAT genes were identified from the published genome data in Gossypium. Among them, 14, 16, 28, and 27 GPAT homologs were identified in G. raimondii, G. arboreum, G. hirsutum, and G. barbadense, respectively. Phylogenetic analysis revealed that a total of 108 GPAT genes from cotton, Arabidopsis and cacao could be classified into three groups. Furthermore, through comparison, the gene structure analyses indicated that GPAT genes from the same group were highly conserved between Arabidopsis and cotton. Segmental duplication could be the major driver for GPAT gene family expansion in the four cotton species above. Expression patterns of GhGPAT genes were diverse in different tissues. Most GhGPAT genes were induced or suppressed after salt or cold stress in Upland cotton. Eight GhGPAT genes were co-localized with oil and protein quantitative trait locus (QTL) regions. Thirty-two single nucleotide polymorphisms (SNPs) were detected from 12 GhGPAT genes, sixteen of which in nine GhGPAT genes were classified as synonymous, and sixteen SNPs in ten GhGPAT genes non-synonymous. Two SNP markers of the GhGPAT16 and GhGPAT26 genes were significantly correlated with cotton oil content in one of the three field tests. This study shed lights on the molecular evolutionary properties of GPAT genes in cotton, and provided reference for improvement of cotton response to abiotic stress and the genetic improvement of cotton oil content.
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Affiliation(s)
- Yupeng Cui
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Jianjiang Ma
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Guoyuan Liu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Nuohan Wang
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Wenfeng Pei
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Xingli Li
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, United States
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, China
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Naoumkina M, Thyssen GN, Fang DD, Jenkins JN, McCarty JC, Florane CB. Genetic and transcriptomic dissection of the fiber length trait from a cotton (Gossypium hirsutum L.) MAGIC population. BMC Genomics 2019; 20:112. [PMID: 30727946 DOI: 10.1186/s12864-019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 01/02/2019] [Indexed: 05/28/2023] Open
Abstract
BACKGROUND Improving cotton fiber length without reducing yield is one of the major goals of cotton breeding. However, genetic improvement of cotton fiber length by breeding has been a challenge due to the narrow genetic diversity of modern cotton cultivars and negative correlations between fiber quality and yield traits. A multi-parent advanced generation inter-cross (MAGIC) population developed through random mating provides an excellent genetic resource that allows quantitative trait loci (QTL) and causal genes to be identified. RESULTS An Upland cotton MAGIC population, consisting of 550 recombinant inbred lines (RILs) derived from eleven different cultivars, was used to identify fiber length QTLs and potential genes that contribute to longer fibers. A genome wide association study (GWAS) identified a cluster of single nucleotide polymorphisms (SNPs) on chromosome (Chr.) D11 that is significantly associated with fiber length. Further evaluation of the Chr. D11 genomic region among lines of the MAGIC population detected that 90% of RILs have a D11 haplotype similar to the reference TM-1 genome (D11-ref), whereas 10% of RILs inherited an alternative haplotype from one of the parents (D11-alt). The average length of fibers of D11-alt RILs was significantly shorter compared to D11-ref RILs, suggesting that alleles in the D11-alt haplotype contributed to the inferior fiber quality. RNAseq analysis of the longest and shortest fiber length RILs from D11-ref and D11-alt populations identified 949 significantly differentially expressed genes (DEGs). Gene set enrichment analysis revealed that different functional categories of genes were over-represented during fiber elongation between the four selected RILs. We found 12 genes possessing non-synonymous SNPs (nsSNPs) significantly associated with the fiber length, and three that were highly significant and were clustered at D11:24-Mb, including D11G1928, D11G1929 and D11G1931. CONCLUSION The results of this study provide insights into molecular aspects of genetic variation in fiber length and suggests candidate genes for genetic manipulation for cotton improvement.
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Affiliation(s)
- Marina Naoumkina
- Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, New Orleans, LA, 70124, USA.
| | - Gregory N Thyssen
- Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, New Orleans, LA, 70124, USA
- Cotton Chemistry and Utilization Research Unit, USDA-ARS-SRRC, 1100 Robert E. Lee Blvd, New Orleans, LA, 70124, USA
| | - David D Fang
- Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, New Orleans, LA, 70124, USA
| | - Johnie N Jenkins
- Genetics and Sustainable Agriculture Research Unit, USDA-ARS, 810 Highway 12 East, Mississippi State, MS, 39762, USA
| | - Jack C McCarty
- Genetics and Sustainable Agriculture Research Unit, USDA-ARS, 810 Highway 12 East, Mississippi State, MS, 39762, USA
| | - Christopher B Florane
- Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, New Orleans, LA, 70124, USA
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Naoumkina M, Thyssen GN, Fang DD, Jenkins JN, McCarty JC, Florane CB. Genetic and transcriptomic dissection of the fiber length trait from a cotton (Gossypium hirsutum L.) MAGIC population. BMC Genomics 2019; 20:112. [PMID: 30727946 PMCID: PMC6366115 DOI: 10.1186/s12864-019-5427-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 01/02/2019] [Indexed: 11/10/2022] Open
Abstract
Background Improving cotton fiber length without reducing yield is one of the major goals of cotton breeding. However, genetic improvement of cotton fiber length by breeding has been a challenge due to the narrow genetic diversity of modern cotton cultivars and negative correlations between fiber quality and yield traits. A multi-parent advanced generation inter-cross (MAGIC) population developed through random mating provides an excellent genetic resource that allows quantitative trait loci (QTL) and causal genes to be identified. Results An Upland cotton MAGIC population, consisting of 550 recombinant inbred lines (RILs) derived from eleven different cultivars, was used to identify fiber length QTLs and potential genes that contribute to longer fibers. A genome wide association study (GWAS) identified a cluster of single nucleotide polymorphisms (SNPs) on chromosome (Chr.) D11 that is significantly associated with fiber length. Further evaluation of the Chr. D11 genomic region among lines of the MAGIC population detected that 90% of RILs have a D11 haplotype similar to the reference TM-1 genome (D11-ref), whereas 10% of RILs inherited an alternative haplotype from one of the parents (D11-alt). The average length of fibers of D11-alt RILs was significantly shorter compared to D11-ref RILs, suggesting that alleles in the D11-alt haplotype contributed to the inferior fiber quality. RNAseq analysis of the longest and shortest fiber length RILs from D11-ref and D11-alt populations identified 949 significantly differentially expressed genes (DEGs). Gene set enrichment analysis revealed that different functional categories of genes were over-represented during fiber elongation between the four selected RILs. We found 12 genes possessing non-synonymous SNPs (nsSNPs) significantly associated with the fiber length, and three that were highly significant and were clustered at D11:24-Mb, including D11G1928, D11G1929 and D11G1931. Conclusion The results of this study provide insights into molecular aspects of genetic variation in fiber length and suggests candidate genes for genetic manipulation for cotton improvement. Electronic supplementary material The online version of this article (10.1186/s12864-019-5427-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Marina Naoumkina
- Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, New Orleans, LA, 70124, USA.
| | - Gregory N Thyssen
- Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, New Orleans, LA, 70124, USA.,Cotton Chemistry and Utilization Research Unit, USDA-ARS-SRRC, 1100 Robert E. Lee Blvd, New Orleans, LA, 70124, USA
| | - David D Fang
- Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, New Orleans, LA, 70124, USA
| | - Johnie N Jenkins
- Genetics and Sustainable Agriculture Research Unit, USDA-ARS, 810 Highway 12 East, Mississippi State, MS, 39762, USA
| | - Jack C McCarty
- Genetics and Sustainable Agriculture Research Unit, USDA-ARS, 810 Highway 12 East, Mississippi State, MS, 39762, USA
| | - Christopher B Florane
- Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, New Orleans, LA, 70124, USA
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Differentially expressed genes between two groups of backcross inbred lines differing in fiber length developed from Upland × Pima cotton. Mol Biol Rep 2019; 46:1199-1212. [DOI: 10.1007/s11033-019-04589-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2018] [Accepted: 01/03/2019] [Indexed: 12/22/2022]
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Li PT, Rashid MHO, Chen TT, Lu QW, Ge Q, Gong WK, Liu AY, Gong JW, Shang HH, Deng XY, Li JW, Li SQ, Xiao XH, Liu RX, Zhang Q, Duan L, Zou XY, Zhang Z, Jiang X, Zhang Y, Peng RH, Shi YZ, Yuan YL. Transcriptomic and biochemical analysis of upland cotton (Gossypium hirsutum) and a chromosome segment substitution line from G. hirsutum × G. barbadense in response to Verticillium dahliae infection. BMC PLANT BIOLOGY 2019; 19:19. [PMID: 30634907 PMCID: PMC6329193 DOI: 10.1186/s12870-018-1619-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Accepted: 12/26/2018] [Indexed: 05/22/2023]
Abstract
BACKGROUND Verticillium wilt (VW), also known as "cotton cancer," is one of the most destructive diseases in global cotton production that seriously impacts fiber yield and quality. Despite numerous attempts, little significant progress has been made in improving the VW resistance of upland cotton. The development of chromosome segment substitution lines (CSSLs) from Gossypium hirsutum × G. barbadense has emerged as a means of simultaneously developing new cotton varieties with high-yield, superior fiber, and resistance to VW. RESULTS In this study, VW-resistant investigations were first conducted in an artificial greenhouse, a natural field, and diseased nursery conditions, resulting in the identification of one stably VW-resistant CSSL, MBI8255, and one VW-susceptible G. hirsutum, CCRI36, which were subsequently subjected to biochemical tests and transcriptome sequencing during V991 infection (0, 1, and 2 days after inoculation). Eighteen root samples with three replications were collected to perform multiple comparisons of enzyme activity and biochemical substance contents. The findings indicated that VW resistance was positively correlated with peroxidase and polyphenol oxidase activity, but negatively correlated with malondialdehyde content. Additionally, RNA sequencing was used for the same root samples, resulting in a total of 77,412 genes, of which 23,180 differentially expressed genes were identified from multiple comparisons between samples. After Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis on the expression profiles identified using Short Time-series Expression Miner, we found that the metabolic process in the biological process, as well as the pathways of phenylpropanoid biosynthesis and plant hormone signal transduction, participated significantly in the response to VW. Gene functional annotation and expression quantity analysis indicated the important roles of the phenylpropanoid metabolic pathway and oxidation-reduction process in response to VW, which also provided plenty of candidate genes related to plant resistance. CONCLUSIONS This study concentrates on the preliminary response to V991 infection by comparing the VW-resistant CSSL and its VW-susceptible recurrent parent. Not only do our findings facilitate the culturing of new resistant varieties with high yield and superior performance, but they also broaden our understanding of the mechanisms of cotton resistance to VW.
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Affiliation(s)
- Peng-tao 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 Science, Anyang, 455000 Henan China
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, 455000 Henan China
| | - Md. Harun or Rashid
- 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 Science, Anyang, 455000 Henan China
| | - Ting-ting Chen
- 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 Science, Anyang, 455000 Henan China
- College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong China
| | - Quan-wei Lu
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, 455000 Henan China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000 Henan China
| | - Wan-kui Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000 Henan China
| | - Ai-ying Liu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000 Henan China
| | - Ju-wu Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000 Henan China
| | - Hai-hong Shang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000 Henan China
| | - Xiao-ying 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 Science, Anyang, 455000 Henan China
| | - Jun-wen 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 Science, Anyang, 455000 Henan China
| | - Shao-qi 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 Science, Anyang, 455000 Henan China
| | - Xiang-hui Xiao
- 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 Science, Anyang, 455000 Henan China
| | - Rui-xian 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 Science, Anyang, 455000 Henan China
| | - Qi 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 Science, Anyang, 455000 Henan China
| | - Li Duan
- 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 Science, Anyang, 455000 Henan China
| | - Xian-yan Zou
- 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 Science, Anyang, 455000 Henan China
| | - Zhen 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 Science, Anyang, 455000 Henan China
| | - Xiao Jiang
- 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 Science, Anyang, 455000 Henan China
| | - Ya Zhang
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, 455000 Henan China
| | - Ren-hai Peng
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, 455000 Henan China
| | - Yu-zhen 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 Science, Anyang, 455000 Henan China
| | - You-lu 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 Science, Anyang, 455000 Henan China
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Li PT, Rashid MHO, Chen TT, Lu QW, Ge Q, Gong WK, Liu AY, Gong JW, Shang HH, Deng XY, Li JW, Li SQ, Xiao XH, Liu RX, Zhang Q, Duan L, Zou XY, Zhang Z, Jiang X, Zhang Y, Peng RH, Shi YZ, Yuan YL. Transcriptomic and biochemical analysis of upland cotton (Gossypium hirsutum) and a chromosome segment substitution line from G. hirsutum × G. barbadense in response to Verticillium dahliae infection. BMC PLANT BIOLOGY 2019; 19:19. [PMID: 30634907 DOI: 10.1186/s12870-018-1619-1614] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Accepted: 12/26/2018] [Indexed: 05/19/2023]
Abstract
BACKGROUND Verticillium wilt (VW), also known as "cotton cancer," is one of the most destructive diseases in global cotton production that seriously impacts fiber yield and quality. Despite numerous attempts, little significant progress has been made in improving the VW resistance of upland cotton. The development of chromosome segment substitution lines (CSSLs) from Gossypium hirsutum × G. barbadense has emerged as a means of simultaneously developing new cotton varieties with high-yield, superior fiber, and resistance to VW. RESULTS In this study, VW-resistant investigations were first conducted in an artificial greenhouse, a natural field, and diseased nursery conditions, resulting in the identification of one stably VW-resistant CSSL, MBI8255, and one VW-susceptible G. hirsutum, CCRI36, which were subsequently subjected to biochemical tests and transcriptome sequencing during V991 infection (0, 1, and 2 days after inoculation). Eighteen root samples with three replications were collected to perform multiple comparisons of enzyme activity and biochemical substance contents. The findings indicated that VW resistance was positively correlated with peroxidase and polyphenol oxidase activity, but negatively correlated with malondialdehyde content. Additionally, RNA sequencing was used for the same root samples, resulting in a total of 77,412 genes, of which 23,180 differentially expressed genes were identified from multiple comparisons between samples. After Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis on the expression profiles identified using Short Time-series Expression Miner, we found that the metabolic process in the biological process, as well as the pathways of phenylpropanoid biosynthesis and plant hormone signal transduction, participated significantly in the response to VW. Gene functional annotation and expression quantity analysis indicated the important roles of the phenylpropanoid metabolic pathway and oxidation-reduction process in response to VW, which also provided plenty of candidate genes related to plant resistance. CONCLUSIONS This study concentrates on the preliminary response to V991 infection by comparing the VW-resistant CSSL and its VW-susceptible recurrent parent. Not only do our findings facilitate the culturing of new resistant varieties with high yield and superior performance, but they also broaden our understanding of the mechanisms of cotton resistance to VW.
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Affiliation(s)
- Peng-Tao 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 Science, Anyang, 455000, Henan, China
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, 455000, Henan, China
| | - Md Harun Or Rashid
- 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 Science, Anyang, 455000, Henan, China
| | - Ting-Ting Chen
- 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 Science, Anyang, 455000, Henan, China
- College of Agriculture, South China Agricultural University, Guangzhou, 510642, Guangdong, China
| | - Quan-Wei Lu
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, 455000, Henan, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Wan-Kui Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Ai-Ying Liu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Ju-Wu Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Hai-Hong Shang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, Henan, China
| | - Xiao-Ying 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 Science, Anyang, 455000, Henan, China
| | - Jun-Wen 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 Science, Anyang, 455000, Henan, China
| | - Shao-Qi 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 Science, Anyang, 455000, Henan, China
| | - Xiang-Hui Xiao
- 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 Science, Anyang, 455000, Henan, China
| | - Rui-Xian 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 Science, Anyang, 455000, Henan, China
| | - Qi 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 Science, Anyang, 455000, Henan, China
| | - Li Duan
- 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 Science, Anyang, 455000, Henan, China
| | - Xian-Yan Zou
- 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 Science, Anyang, 455000, Henan, China
| | - Zhen 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 Science, Anyang, 455000, Henan, China
| | - Xiao Jiang
- 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 Science, Anyang, 455000, Henan, China
| | - Ya Zhang
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, 455000, Henan, China
| | - Ren-Hai Peng
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, 455000, Henan, China
| | - Yu-Zhen 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 Science, Anyang, 455000, Henan, China.
| | - You-Lu 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 Science, Anyang, 455000, Henan, China.
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Ijaz B, Zhao N, Kong J, Hua J. Fiber Quality Improvement in Upland Cotton ( Gossypium hirsutum L.): Quantitative Trait Loci Mapping and Marker Assisted Selection Application. FRONTIERS IN PLANT SCIENCE 2019; 10:1585. [PMID: 31921240 PMCID: PMC6917639 DOI: 10.3389/fpls.2019.01585] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Accepted: 11/12/2019] [Indexed: 05/17/2023]
Abstract
Genetic improvement in fiber quality is one of the main challenges for cotton breeders. Fiber quality traits are controlled by multiple genes and are classified as complex quantitative traits, with a negative relationship with yield potential, so the genetic gain is low in traditional genetic improvement by phenotypic selection. The availability of Gossypium genomic sequences facilitates the development of high-throughput molecular markers, quantitative trait loci (QTL) fine mapping and gene identification, which helps us to validate candidate genes and to use marker assisted selection (MAS) on fiber quality in breeding programs. Based on developments of high density linkage maps, QTLs fine mapping, marker selection and omics, we have performed trait dissection on fiber quality traits in diverse populations of upland cotton. QTL mapping combined with multi-omics approaches such as, RNA sequencing datasets to identify differentially expressed genes have benefited the improvement of fiber quality. In this review, we discuss the application of molecular markers, QTL mapping and MAS for fiber quality improvement in upland cotton.
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Affiliation(s)
- Babar Ijaz
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Nan Zhao
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Jie Kong
- Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, China
| | - Jinping Hua
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
- *Correspondence: Jinping Hua,
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61
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Zhang C, Li L, Liu Q, Gu L, Huang J, Wei H, Wang H, Yu S. Identification of Loci and Candidate Genes Responsible for Fiber Length in Upland Cotton ( Gossypium hirsutum L.) via Association Mapping and Linkage Analyses. FRONTIERS IN PLANT SCIENCE 2019; 10:53. [PMID: 30804954 PMCID: PMC6370998 DOI: 10.3389/fpls.2019.00053] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 01/16/2019] [Indexed: 05/12/2023]
Abstract
Fiber length (FL) is an important fiber quality trait in cotton. Although many fiber quality quantitative trait loci (QTL) responsible for FL have been identified, most cannot be applied to breeding programs, mainly due to unstable environments or large confidence intervals. In this study, we combined a genome-wide association study (GWAS) and linkage mapping to identify and validate high-quality QTLs responsible for FL. For the GWAS, we developed 93,250 high-quality single-nucleotide polymorphism (SNP) markers based on 355 accessions, and the FL was measured in eight different environments. For the linkage mapping, we constructed an F 2 population from two extreme accessions. The high-density linkage maps spanned 3,848.29 cM, with an average marker interval of 1.41 cM. In total, 14 and 13 QTLs were identified in the association and linkage mapping analyses, respectively. Most importantly, a major QTL on chromosome D03 identified in both populations explained more than 10% of the phenotypic variation (PV). Furthermore, we found that a sucrose synthesis-related gene (Gh_D03G1338) was associated with FL in this QTL region. The RNA-seq data showed that Gh_D03G1338 was highly expressed during the fiber development stage, and the qRT-PCR analysis showed significant expression differences between the long fiber and short fiber varieties. These results suggest that Gh_D03G1338 may determine cotton fiber elongation by regulating the synthesis of sucrose. Favorable QTLs and candidate genes should be useful for increasing fiber quality in cotton breeding.
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Affiliation(s)
- Chi Zhang
- College of Agronomy, Northwest A&F University, Yangling, China
- State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Lin’an, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Libei Li
- State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Lin’an, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qibao Liu
- State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Lin’an, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Lijiao Gu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jianqin Huang
- State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Lin’an, China
| | - Hengling Wei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Hantao Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Shuxun Yu
- College of Agronomy, Northwest A&F University, Yangling, China
- State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Lin’an, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- *Correspondence: Shuxun Yu,
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Ma J, Geng Y, Pei W, Wu M, Li X, Liu G, Li D, Ma Q, Zang X, Yu S, Zhang J, Yu J. Genetic variation of dynamic fiber elongation and developmental quantitative trait locus mapping of fiber length in upland cotton (Gossypium hirsutum L.). BMC Genomics 2018; 19:882. [PMID: 30522448 PMCID: PMC6282333 DOI: 10.1186/s12864-018-5309-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 11/25/2018] [Indexed: 02/04/2023] Open
Abstract
Background In upland cotton (Gossypium hirsutum L.), genotypes with the same mature fiber length (FL) might possess different genes and exhibit differential expression of genes related to fiber elongation at different fiber developmental stages. However, there is a lack of information on the genetic variation influencing fiber length and its quantitative trait loci (QTLs) during the fiber elongation stage. In this study, a subset of upland cotton accessions was selected based on a previous GWAS conducted in China and grown in multiple environments to determine the dynamic fiber length at 10, 15, 20, and 25 days post-anthesis (DPA) and maturity. The germplasm lines were genotyped with the Cotton 63 K Illumina single-nucleotide polymorphism (SNP) array for GWAS. Results A total of 25, 38, 57, 89 and 88 SNPs showed significant correlations with fiber length at 10, 15, 20 and 25 DPA and maturity, respectively. In addition, 60 more promising SNPs were detected in at least two tests and two FL developmental time points, and 20 SNPs were located within the confidence intervals of QTLs identified in previous studies. The fastest fiber-length growth rates were obtained at 10 to 15 DPA in 69 upland cotton lines and at 15 to 20 DPA in 14 upland cotton accessions, and 10 SNPs showed significant correlations with the fiber-length growth rate. A combined transcriptome and qRT-PCR analysis revealed that two genes (D10G1008 and D13G2037) showed differential expression between two long-fiber genotypes and two short-fiber genotypes. Conclusions This study provides important new insights into the genetic basis of the time-dependent fiber-length trait and reveals candidate SNPs and genes for improving fiber length in upland cotton. Electronic supplementary material The online version of this article (10.1186/s12864-018-5309-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jianjiang Ma
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shanxi, China.,State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Yanhui Geng
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Wenfeng Pei
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Xingli Li
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Guoyuan Liu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Dan Li
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Qifeng Ma
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - XinShan Zang
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Shuxun Yu
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shanxi, China. .,State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China.
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, 880033, USA.
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China.
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Ali I, Teng Z, Bai Y, Yang Q, Hao Y, Hou J, Jia Y, Tian L, Liu X, Tan Z, Wang W, Kenneth K, Sharkh AYA, Liu D, Guo K, Zhang J, Liu D, Zhang Z. A high density SLAF-SNP genetic map and QTL detection for fibre quality traits in Gossypium hirsutum. BMC Genomics 2018; 19:879. [PMID: 30522437 PMCID: PMC6282304 DOI: 10.1186/s12864-018-5294-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 11/21/2018] [Indexed: 12/17/2022] Open
Abstract
Background Upland Cotton (Gossypium hirsutum) is a very important cash crop known for its high quality natural fiber. Recent advances in sequencing technologies provide powerful tools with which to explore the cotton genome for single nucleotide polymorphism marker identification and high density genetic map construction toward more reliable quantitative trait locus mapping. Results In the present study, a RIL population was developed by crossing a Chinese high fiber quality cultivar (Yumian 1) and an American high fiber quality line (CA3084), with distinct genetic backgrounds. Specific locus amplified fragment sequencing (SLAF-seq) technology was used to discover SNPs, and a genetic map containing 6254 SNPs was constructed, covering 3141.72 cM with an average distance of 0.5 cM between markers. A total of 95 QTL were detected for fiber quality traits in three environments, explaining 5.5-24.6% of the phenotypic variance. Fifty-five QTL found in multiple environments were considered stable QTL. Nine of the stable QTL were found in all three environments. We identified 14 QTL clusters on 13 chromosomes, each containing one or more stable QTL. Conclusion A high-density genetic map of Gossypium hirsutum developed by using specific locus amplified fragment sequencing technology provides detailed mapping of fiber quality QTL, and identification of ‘stable QTL’ found in multiple environments. A marker-rich genetic map provides a foundation for fine mapping, candidate gene identification and marker-assisted selection of favorable alleles at stable QTL in breeding programs. Electronic supplementary material The online version of this article (10.1186/s12864-018-5294-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Iftikhar Ali
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Zhonghua Teng
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Yuting Bai
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Qing Yang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Yongshui Hao
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Juan Hou
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Yongbin Jia
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Lixia Tian
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Xueying Liu
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Zhaoyun Tan
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Wenwen Wang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Kiirya Kenneth
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | | | - Dexin Liu
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Kai Guo
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Jian Zhang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Dajun Liu
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Zhengsheng Zhang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China.
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Liu R, Gong J, Xiao X, Zhang Z, Li J, Liu A, Lu Q, Shang H, Shi Y, Ge Q, Iqbal MS, Deng X, Li S, Pan J, Duan L, Zhang Q, Jiang X, Zou X, Hafeez A, Chen Q, Geng H, Gong W, Yuan Y. GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers. FRONTIERS IN PLANT SCIENCE 2018; 9:1067. [PMID: 30283462 PMCID: PMC6157485 DOI: 10.3389/fpls.2018.01067] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Accepted: 07/02/2018] [Indexed: 05/18/2023]
Abstract
It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18-24.45 and 1.68-28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly "pleiotropic." This study provided important information for MAS and candidate gene functional studies.
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Affiliation(s)
- Ruixian Liu
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Juwu Gong
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xianghui Xiao
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Zhen Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanwei Lu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Yuzhen Shi
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Muhammad S. Iqbal
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Shaoqi Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Li Duan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qi Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiao Jiang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xianyan Zou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Abdul Hafeez
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanjia Chen
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
| | - Hongwei Geng
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Youlu Yuan
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
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Tan Z, Zhang Z, Sun X, Li Q, Sun Y, Yang P, Wang W, Liu X, Chen C, Liu D, Teng Z, Guo K, Zhang J, Liu D, Zhang Z. Genetic Map Construction and Fiber Quality QTL Mapping Using the CottonSNP80K Array in Upland Cotton. FRONTIERS IN PLANT SCIENCE 2018; 9:225. [PMID: 29535744 PMCID: PMC5835031 DOI: 10.3389/fpls.2018.00225] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 02/06/2018] [Indexed: 05/04/2023]
Abstract
Cotton fiber quality traits are controlled by multiple quantitative trait loci (QTL), and the improvement of these traits requires extensive germplasm. Herein, an Upland cotton cultivar from America, Acala Maxxa, was crossed with a local high fiber quality cultivar, Yumian 1, and 180 recombinant inbred lines (RILs) were obtained. In order to dissect the genetic basis of fiber quality differences between these parents, a genetic map containing 12116 SNP markers was constructed using the CottonSNP80K assay, which covered 3741.81 cM with an average distance of 0.31 cM between markers. Based on the genetic map and growouts in three environments, we detected a total of 104 QTL controlling fiber quality traits. Among these QTL, 25 were detected in all three environments and 35 in two environments. Meanwhile, 19 QTL clusters were also identified, and nine contained at least one stable QTL (detected in three environments for a given trait). These stable QTL or QTL clusters are priorities for fine mapping, identifying candidate genes, elaborating molecular mechanisms of fiber development, and application in cotton breeding programs by marker-assisted selection (MAS).
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Zhengsheng Zhang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, China
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Ma Q, Zhao J, Lin H, Ning X, Liu P, Deng F, Si A, Li J. Association between SSR markers and fibre traits in sea island cotton (Gossypium barbadense) germplasm resources. J Genet 2017; 96:e55-e63. [PMID: 29321342 DOI: 10.1007/s12041-017-0849-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Identification of molecular markers associated with fibre traits can accelerate cotton marker-assisted selection (MAS) programmes. In this study, Gossypium barbadense germplasm accessions with diverse origins (n = 123) were used to perform association analysis of fibre traits with 120 polymorphic simple sequence repeat (SSR) markers. In total, 120 polymorphic primer pairs amplified 258 loci with a mean of 2.15 loci per primer. Population structure analysis identified three main clusters for the accessions, which indicated agreement of genetic and predefined populations. Marker-trait associations (n = 58) were detected for 10 fibre traits with 26 SSR markers located on 15 chromosomes. The R² (phenotypic variation explained) ranged from 3.19 to 15.21%. Two markers (NAU5465 and NAU3013) were found to be stably associated with boll number per plant (BNP) and fibre uniformity (UI), respectively. Four markers (BNL252, NAU3424,NAU3324 and CGR5202) associated with fibre quality traits preferentially clustered on the D8 chromosome, which was thus identified as an important candidate region for study molecular mechanisms underlying fibre quality and for use in breeding cotton cultivars for improving fibre quality. This study generated molecular data with a potential for better understanding of the genetic basis of the fibre traits and provided new markers for MAS in G. barbadense breeding programmes.
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Affiliation(s)
- Qi Ma
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science/Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding, Shihezi 832000, People's Republic of China.
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Li PT, Wang M, Lu QW, Ge Q, Rashid MHO, Liu AY, Gong JW, Shang HH, Gong WK, Li JW, Song WW, Guo LX, Su W, Li SQ, Guo XP, Shi YZ, Yuan YL. Comparative transcriptome analysis of cotton fiber development of Upland cotton (Gossypium hirsutum) and Chromosome Segment Substitution Lines from G. hirsutum × G. barbadense. BMC Genomics 2017; 18:705. [PMID: 28886694 PMCID: PMC5591532 DOI: 10.1186/s12864-017-4077-8] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Accepted: 08/21/2017] [Indexed: 12/15/2022] Open
Abstract
Background How to develop new cotton varieties possessing high yield traits of Upland cotton and superior fiber quality traits of Sea Island cotton remains a key task for cotton breeders and researchers. While multiple attempts bring in little significant progresses, the development of Chromosome Segment Substitution Lines (CSSLs) from Gossypium barbadense in G. hirsutum background provided ideal materials for aforementioned breeding purposes in upland cotton improvement. Based on the excellent fiber performance and relatively clear chromosome substitution segments information identified by Simple Sequence Repeat (SSR) markers, two CSSLs, MBI9915 and MBI9749, together with the recurrent parent CCRI36 were chosen to conduct transcriptome sequencing during the development stages of fiber elongation and Secondary Cell Wall (SCW) synthesis (from 10DPA and 28DPA), aiming at revealing the mechanism of fiber development and the potential contribution of chromosome substitution segments from Sea Island cotton to fiber development of Upland cotton. Results In total, 15 RNA-seq libraries were constructed and sequenced separately, generating 705.433 million clean reads with mean GC content of 45.13% and average Q30 of 90.26%. Through multiple comparisons between libraries, 1801 differentially expressed genes (DEGs) were identified, of which the 902 up-regulated DEGs were mainly involved in cell wall organization and response to oxidative stress and auxin, while the 898 down-regulated ones participated in translation, regulation of transcription, DNA-templated and cytoplasmic translation based on GO annotation and KEGG enrichment analysis. Subsequently, STEM software was performed to explicate the temporal expression pattern of DEGs. Two peroxidases and four flavonoid pathway-related genes were identified in the “oxidation-reduction process”, which could play a role in fiber development and quality formation. Finally, the reliability of RNA-seq data was validated by quantitative real-time PCR of randomly selected 20 genes. Conclusions The present report focuses on the similarities and differences of transcriptome profiles between the two CSSLs and the recurrent parent CCRI36 and provides novel insights into the molecular mechanism of fiber development, and into further exploration of the feasible contribution of G. barbadense substitution segments to fiber quality formation, which will lay solid foundation for simultaneously improving fiber yield and quality of upland cotton through CSSLs. Electronic supplementary material The online version of this article (10.1186/s12864-017-4077-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Peng-Tao Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China.,National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Mi Wang
- College of Agriculture, Yangtze University, Jingzhou, Hubei, 434025, China
| | - Quan-Wei Lu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Md Harun Or Rashid
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Ai-Ying Liu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Ju-Wu Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Hai-Hong Shang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Wan-Kui Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Jun-Wen Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Wei-Wu Song
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Li-Xue Guo
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Wei Su
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China.,College of Agriculture, Yangtze University, Jingzhou, Hubei, 434025, China
| | - Shao-Qi Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China
| | - Xiao-Ping Guo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, 430070, China.
| | - Yu-Zhen Shi
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China.
| | - You-Lu Yuan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biologiacl and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, Henan, 455000, China.
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Liu X, Teng Z, Wang J, Wu T, Zhang Z, Deng X, Fang X, Tan Z, Ali I, Liu D, Zhang J, Liu D, Liu F, Zhang Z. Enriching an intraspecific genetic map and identifying QTL for fiber quality and yield component traits across multiple environments in Upland cotton (Gossypium hirsutum L.). Mol Genet Genomics 2017; 292:1281-1306. [PMID: 28733817 DOI: 10.1007/s00438-017-1347-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 06/29/2017] [Indexed: 10/19/2022]
Abstract
Cotton is a significant commercial crop that plays an indispensable role in many domains. Constructing high-density genetic maps and identifying stable quantitative trait locus (QTL) controlling agronomic traits are necessary prerequisites for marker-assisted selection (MAS). A total of 14,899 SSR primer pairs designed from the genome sequence of G. raimondii were screened for polymorphic markers between mapping parents CCRI 35 and Yumian 1, and 712 SSR markers showing polymorphism were used to genotype 180 lines from a (CCRI 35 × Yumian 1) recombinant inbred line (RIL) population. Genetic linkage analysis was conducted on 726 loci obtained from the 712 polymorphic SSR markers, along with 1379 SSR loci obtained in our previous study, and a high-density genetic map with 2051 loci was constructed, which spanned 3508.29 cM with an average distance of 1.71 cM between adjacent markers. Marker orders on the linkage map are highly consistent with the corresponding physical orders on a G. hirsutum genome sequence. Based on fiber quality and yield component trait data collected from six environments, 113 QTLs were identified through two analytical methods. Among these 113 QTLs, 50 were considered stable (detected in multiple environments or for which phenotypic variance explained by additive effect was greater than environment effect), and 18 of these 50 were identified with stability by both methods. These 18 QTLs, including eleven for fiber quality and seven for yield component traits, could be priorities for MAS.
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Affiliation(s)
- Xueying Liu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Zhonghua Teng
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Jinxia Wang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Tiantian Wu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Zhiqin Zhang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Xianping Deng
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Xiaomei Fang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Zhaoyun Tan
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Iftikhar Ali
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Dexin Liu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Jian Zhang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Dajun Liu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Fang Liu
- State Key Laboratory of Cotton Biology/Cotton Research Institute, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
| | - Zhengsheng Zhang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China.
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Abdelraheem A, Liu F, Song M, Zhang JF. A meta-analysis of quantitative trait loci for abiotic and biotic stress resistance in tetraploid cotton. Mol Genet Genomics 2017. [PMID: 28647758 DOI: 10.1007/s00438-017-1342-0] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The number and location of mapped quantitative trait loci (QTL) depend on genetic populations and testing environments. The identification of consistent QTL across genetic backgrounds and environments is a pre-requisite to marker-assisted selection. This study analyzed a total of 661 abiotic and biotic stress resistance QTL based on our previous work and other publications using the meta-analysis software Biomercator. It identified chromosomal regions containing QTL clusters for different resistance traits and hotspots for a particular resistance trait in cotton from 98 QTL for drought tolerance under greenhouse (DT) and 150 QTL in field conditions (FDT), 80 QTL for salt tolerance in the greenhouse conditions (ST), 201 QTL for resistance to Verticillium wilt (VW, Verticillium dahliae), 47 QTL for resistance to Fusarium wilt (FW, Fusarium oxysporum f. sp. vasinfectum), and 85 QTL for resistance to root-knot nematodes (RKN, Meloiodogyne incognita) and reniform nematodes (RN, Rotylenchulus reniformis). The traits used in QTL mapping for abiotic stress tolerance included morphological traits-plant height and fresh and dry shoot and root weights, physiological traits-chlorophyll content, osmotic potential, carbon isotope ratio, stomatal conductance, photosynthetic rate, transpiration, canopy temperature, and leaf area index, agronomic traits-seedcotton yield, lint yield, boll weight, and lint percent, and fiber quality traits-fiber length, uniformity, strength, elongation, and micronaire. The results showed that resistance QTL are not uniformly distributed across the cotton genome; some chromosomes carried disproportionally more QTL, QTL clusters, or hotspots. Twenty-three QTL clusters were found on 15 chromosomes (c3, c4, c5, c6, c7, c11, c14, c15, c16, c19, c20, c23, c24, c25, and c26). Moreover, 28 QTL hotshots were associated with different resistance traits including one hotspot on c4 for Verticillium wilt resistance, two QTL hotspots on c24 for chlorophyll content measured under both drought and salt stress conditions, and three other hotspots on c19 for the resistance to Verticillium wilt and Fusarium wilt, and micronaire under drought stress conditions. This meta-analysis of stress tolerance QTL provides an important foundation for cotton breeding and further studies on the genetic mechanisms of abiotic and biotic stress resistance in cotton.
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Affiliation(s)
- Abdelraheem Abdelraheem
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Feng Liu
- Department of Computer Science, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Mingzhou Song
- Department of Computer Science, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Jinfa F Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA.
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Identification of candidate genes for fiber length quantitative trait loci through RNA-Seq and linkage and physical mapping in cotton. BMC Genomics 2017; 18:427. [PMID: 28569138 PMCID: PMC5452627 DOI: 10.1186/s12864-017-3812-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Accepted: 05/23/2017] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Cotton (Gossypium spp.) fibers are single-celled elongated trichomes, the molecular aspects of genetic variation in fiber length (FL) among genotypes are currently unknown. In this study, two backcross inbred lines (BILs), i.e., NMGA-062 ("Long") and NMGA-105 ("Short") with 32.1 vs. 27.2 mm in FL, respectively, were chosen to perform RNA-Seq on developing fibers at 10 days post anthesis (DPA). The two BILs differed in 4 quantitative trait loci (QTL) for FL and were developed from backcrosses between G. hirsutum as the recurrent parent and G. barbadense. RESULTS In total, 51.7 and 54.3 million reads were obtained and assembled to 49,508 and 49,448 transcripts in the two genotypes, respectively. Of 1551 differentially expressed genes (DEGs) between the two BILs, 678 were up-regulated and 873 down-regulated in "Long"; and 703 SNPs were identified in 339 DEGs. Further physical mapping showed that 8 DEGs were co-localized with the 4 FL QTL identified in the BIL population containing the two BILs. Four SNP markers in 3 DEGs that showed significant correlations with FL were developed. Among the three candidate genes encoding for proline-rich protein, D-cysteine desulfhydrase, and thaumatin-like protein, a SNP of thaumatin-like protein gene showed consistent correlations with FL across all testing environments. CONCLUSIONS This study represents one of the first investigations of positional candidate gene approach of QTL in cotton in integrating transcriptome and SNP identification based on RNA-Seq with linkage and physical mapping of QTL and genes, which will facilitate eventual cloning and identification of genes responsible for FL QTL. The candidate genes may serve as the foundation for further in-depth studies of the molecular mechanism of natural variation in fiber elongation.
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Wang N, Ma J, Pei W, Wu M, Li H, Li X, Yu S, Zhang J, Yu J. A genome-wide analysis of the lysophosphatidate acyltransferase (LPAAT) gene family in cotton: organization, expression, sequence variation, and association with seed oil content and fiber quality. BMC Genomics 2017; 18:218. [PMID: 28249560 PMCID: PMC5333453 DOI: 10.1186/s12864-017-3594-9] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Accepted: 02/15/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Lysophosphatidic acid acyltransferase (LPAAT) encoded by a multigene family is a rate-limiting enzyme in the Kennedy pathway in higher plants. Cotton is the most important natural fiber crop and one of the most important oilseed crops. However, little is known on genes coding for LPAATs involved in oil biosynthesis with regard to its genome organization, diversity, expression, natural genetic variation, and association with fiber development and oil content in cotton. RESULTS In this study, a comprehensive genome-wide analysis in four Gossypium species with genome sequences, i.e., tetraploid G. hirsutum- AD1 and G. barbadense- AD2 and its possible ancestral diploids G. raimondii- D5 and G. arboreum- A2, identified 13, 10, 8, and 9 LPAAT genes, respectively, that were divided into four subfamilies. RNA-seq analyses of the LPAAT genes in the widely grown G. hirsutum suggest their differential expression at the transcriptional level in developing cottonseeds and fibers. Although 10 LPAAT genes were co-localised with quantitative trait loci (QTL) for cottonseed oil or protein content within a 25-cM region, only one single strand conformation polymorphic (SSCP) marker developed from a synonymous single nucleotide polymorphism (SNP) of the At-Gh13LPAAT5 gene was significantly correlated with cottonseed oil and protein contents in one of the three field tests. Moreover, transformed yeasts using the At-Gh13LPAAT5 gene with the two sequences for the SNP led to similar results, i.e., a 25-31% increase in palmitic acid and oleic acid, and a 16-29% increase in total triacylglycerol (TAG). CONCLUSIONS The results in this study demonstrated that the natural variation in the LPAAT genes to improving cottonseed oil content and fiber quality is limited; therefore, traditional cross breeding should not expect much progress in improving cottonseed oil content or fiber quality through a marker-assisted selection for the LPAAT genes. However, enhancing the expression of one of the LPAAT genes such as At-Gh13LPAAT5 can significantly increase the production of total TAG and other fatty acids, providing an incentive for further studies into the use of LPAAT genes to increase cottonseed oil content through biotechnology.
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Affiliation(s)
- Nuohan Wang
- National Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.,College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Jianjiang Ma
- National Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.,College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Wenfeng Pei
- National Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Man Wu
- National Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Haijing Li
- National Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Xingli Li
- National Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Shuxun Yu
- National Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China. .,College of Agronomy, Northwest A&F University, Yangling, 712100, China.
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, 880033, USA.
| | - Jiwen Yu
- National Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
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Ma L, Zhao Y, Wang Y, Shang L, Hua J. QTLs Analysis and Validation for Fiber Quality Traits Using Maternal Backcross Population in Upland Cotton. FRONTIERS IN PLANT SCIENCE 2017; 8:2168. [PMID: 29312408 PMCID: PMC5744017 DOI: 10.3389/fpls.2017.02168] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2017] [Accepted: 12/11/2017] [Indexed: 05/04/2023]
Abstract
Cotton fiber is renewable natural fiber source for textile. Improving fiber quality is an essential goal for cotton breeding project. In present study, F14 recombinant inbred line (RIL) population was backcrossed by the maternal parent to obtain a backcross (BC) population, derived from one Upland cotton hybrid. Three repetitive field trials were performed by randomized complete block design with two replicates in three locations in 2015, together with the BC population, common male parent and the RIL population. Totally, 26 QTLs in BC population explained 5.00-14.17% of phenotype variation (PV) and 37 quantitative trait loci (QTL) were detected in RIL population explaining 5.13-34.00% of PV. Seven common QTLs detected simultaneously in two populations explained PV from 7.69 to 23.05%. A total of 20 QTLs in present study verified the previous results across three environments in 2012. Particularly, qFL-Chr5-2 controlling fiber length on chromosome 5 explained 34.00% of PV, while qFL-Chr5-3 only within a 0.8 cM interval explained 13.93% of PV on average in multiple environments. These stable QTLs explaining great variation offered essential information for marker-assisted selection (MAS) to improve fiber quality traits. Lots of epistasis being detected in both populations acted as one of important genetic compositions of fiber quality traits.
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Affiliation(s)
- Lingling Ma
- Laboratory of Cotton Genetics, Genomics and Breeding, College of Agronomy and Biotechnology/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, China Agricultural University, Beijing, China
| | - Yanpeng Zhao
- Laboratory of Cotton Genetics, Genomics and Breeding, College of Agronomy and Biotechnology/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, China Agricultural University, Beijing, China
| | - Yumei Wang
- Department of Cotton Breeding, Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Lianguang Shang
- Laboratory of Cotton Genetics, Genomics and Breeding, College of Agronomy and Biotechnology/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, China Agricultural University, Beijing, China
| | - Jinping Hua
- Laboratory of Cotton Genetics, Genomics and Breeding, College of Agronomy and Biotechnology/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, China Agricultural University, Beijing, China
- *Correspondence: Jinping Hua
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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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Shang L, Wang Y, Cai S, Ma L, Liu F, Chen Z, Su Y, Wang K, Hua J. Genetic analysis of Upland cotton dynamic heterosis for boll number per plant at multiple developmental stages. Sci Rep 2016; 6:35515. [PMID: 27748451 PMCID: PMC5066282 DOI: 10.1038/srep35515] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Accepted: 09/06/2016] [Indexed: 01/28/2023] Open
Abstract
Yield is an important breeding target. As important yield components, boll number per plant (BNP) shows dynamic character and strong heterosis in Upland cotton. However, the genetic basis underlying the dynamic heterosis is poorly understood. In this study, we conducted dynamic quantitative trait loci (QTL) analysis for BNP and heterosis at multiple developmental stages and environments using two recombinant inbred lines (RILs) and two corresponding backcross populations. By the single-locus analysis, 23 QTLs were identified at final maturity, while 99 QTLs were identified across other three developmental stages. A total of 48 conditional QTLs for BNP were identified for the adjacent stages. QTLs detected at later stage mainly existed in the partial dominance to dominance range and QTLs identified at early stage mostly showed effects with the dominance to overdominance range during plant development. By two-locus analysis, we observe that epistasis played an important role not only in the variation of the performance of the RIL population but also in the expression of heterosis in backcross population. Taken together, the present study reveals that the genetic basis of heterosis is dynamic and complicated, and it is involved in dynamic dominance effect, epistasis and QTL by environmental interactions.
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Affiliation(s)
- Lianguang Shang
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Yumei Wang
- Research Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, Hubei, China
| | - Shihu Cai
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Lingling Ma
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Fang Liu
- Institute of Cotton Research, Chinese Academy of Agricultural Sciences/State Key Laboratory of Cotton Biology, Anyang 455000, Henan, China
| | - Zhiwen Chen
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Ying Su
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Kunbo Wang
- Institute of Cotton Research, Chinese Academy of Agricultural Sciences/State Key Laboratory of Cotton Biology, Anyang 455000, Henan, China
| | - Jinping Hua
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
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Shang L, Wang Y, Wang X, Liu F, Abduweli A, Cai S, Li Y, Ma L, Wang K, Hua J. Genetic Analysis and QTL Detection on Fiber Traits Using Two Recombinant Inbred Lines and Their Backcross Populations in Upland Cotton. G3 (BETHESDA, MD.) 2016. [PMID: 27342735 DOI: 10.1111/pbr.12352] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Cotton fiber, a raw natural fiber material, is widely used in the textile industry. Understanding the genetic mechanism of fiber traits is helpful for fiber quality improvement. In the present study, the genetic basis of fiber quality traits was explored using two recombinant inbred lines (RILs) and corresponding backcross (BC) populations under multiple environments in Upland cotton based on marker analysis. In backcross populations, no significant correlation was observed between marker heterozygosity and fiber quality performance and it suggested that heterozygosity was not always necessarily advantageous for the high fiber quality. In two hybrids, 111 quantitative trait loci (QTL) for fiber quality were detected using composite interval mapping, in which 62 new stable QTL were simultaneously identified in more than one environment or population. QTL detected at the single-locus level mainly showed additive effect. In addition, a total of 286 digenic interactions (E-QTL) and their environmental interactions [QTL × environment interactions (QEs)] were detected for fiber quality traits by inclusive composite interval mapping. QE effects should be considered in molecular marker-assisted selection breeding. On average, the E-QTL explained a larger proportion of the phenotypic variation than the main-effect QTL did. It is concluded that the additive effect of single-locus and epistasis with few detectable main effects play an important role in controlling fiber quality traits in Upland cotton.
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Affiliation(s)
- Lianguang Shang
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Yumei Wang
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China
| | - Xiaocui Wang
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Fang Liu
- Institute of Cotton Research, Chinese Academy of Agricultural Sciences/State Key Laboratory of Cotton Biology, Anyang 455000, Henan, China
| | - Abdugheni Abduweli
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Shihu Cai
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Yuhua Li
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Lingling Ma
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Kunbo Wang
- Institute of Cotton Research, Chinese Academy of Agricultural Sciences/State Key Laboratory of Cotton Biology, Anyang 455000, Henan, China
| | - Jinping Hua
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
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Genetic Analysis and QTL Detection on Fiber Traits Using Two Recombinant Inbred Lines and Their Backcross Populations in Upland Cotton. G3-GENES GENOMES GENETICS 2016; 6:2717-24. [PMID: 27342735 PMCID: PMC5015930 DOI: 10.1534/g3.116.031302] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Cotton fiber, a raw natural fiber material, is widely used in the textile industry. Understanding the genetic mechanism of fiber traits is helpful for fiber quality improvement. In the present study, the genetic basis of fiber quality traits was explored using two recombinant inbred lines (RILs) and corresponding backcross (BC) populations under multiple environments in Upland cotton based on marker analysis. In backcross populations, no significant correlation was observed between marker heterozygosity and fiber quality performance and it suggested that heterozygosity was not always necessarily advantageous for the high fiber quality. In two hybrids, 111 quantitative trait loci (QTL) for fiber quality were detected using composite interval mapping, in which 62 new stable QTL were simultaneously identified in more than one environment or population. QTL detected at the single-locus level mainly showed additive effect. In addition, a total of 286 digenic interactions (E-QTL) and their environmental interactions [QTL × environment interactions (QEs)] were detected for fiber quality traits by inclusive composite interval mapping. QE effects should be considered in molecular marker-assisted selection breeding. On average, the E-QTL explained a larger proportion of the phenotypic variation than the main-effect QTL did. It is concluded that the additive effect of single-locus and epistasis with few detectable main effects play an important role in controlling fiber quality traits in Upland cotton.
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77
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Li C, Dong Y, Zhao T, Li L, Li C, Yu E, Mei L, Daud MK, He Q, Chen J, Zhu S. Genome-Wide SNP Linkage Mapping and QTL Analysis for Fiber Quality and Yield Traits in the Upland Cotton Recombinant Inbred Lines Population. FRONTIERS IN PLANT SCIENCE 2016; 7:1356. [PMID: 27660632 PMCID: PMC5014859 DOI: 10.3389/fpls.2016.01356] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Accepted: 08/25/2016] [Indexed: 05/18/2023]
Abstract
It is of significance to discover genes related to fiber quality and yield traits and tightly linked markers for marker-assisted selection (MAS) in cotton breeding. In this study, 188 F8 recombinant inbred lines (RILs), derived from a intraspecific cross between HS46 and MARCABUCAG8US-1-88 were genotyped by the cotton 63K single nucleotide polymorphism (SNP) assay. Field trials were conducted in Sanya, Hainan Province, during the 2014-2015 cropping seasons under standard conditions. Results revealed significant differences (P < 0.05) among RILs, environments and replications for fiber quality and yield traits. Broad-sense heritabilities of all traits including fiber length, fiber uniformity, micronaire, fiber elongation, fiber strength, boll weight, and lint percentage ranged from 0.26 to 0.66. A 1784.28 cM (centimorgans) linkage map, harboring 2618 polymorphic SNP markers, was constructed, which had 0.68 cM per marker density. Seventy-one quantitative trait locus (QTLs) for fiber quality and yield traits were detected on 21 chromosomes, explaining 4.70∼32.28% phenotypic variance, in which 16 were identified as stable QTLs across two environments. Meanwhile, 12 certain regions were investigated to be involved in the control of one (hotspot) or more (cluster) traits, mainly focused on Chr05, Chr09, Chr10, Chr14, Chr19, and Chr20. Nineteen pairs of epistatic QTLs (e-QTLs) were identified, of which two pairs involved in two additive QTLs. These additive QTLs, e-QTLs, and QTL clusters were tightly linked to SNP markers, which may serve as target regions for map-based cloning, gene discovery, and MAS in cotton breeding.
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Affiliation(s)
- Cong Li
- Department of Agronomy, Zhejiang UniversityHangzhou, China
| | - Yating Dong
- Department of Agronomy, Zhejiang UniversityHangzhou, China
| | - Tianlun Zhao
- Department of Agronomy, Zhejiang UniversityHangzhou, China
| | - Ling Li
- Department of Agronomy, Zhejiang UniversityHangzhou, China
| | - Cheng Li
- Department of Agronomy, Zhejiang UniversityHangzhou, China
| | - En Yu
- Department of Agronomy, Zhejiang UniversityHangzhou, China
| | - Lei Mei
- Department of Agronomy, Zhejiang UniversityHangzhou, China
| | - M. K. Daud
- Department of Biotechnology and Genetic Engineering, Kohat University of Science and TechnologyKohat, Pakistan
| | - Qiuling He
- Department of Agronomy, Zhejiang UniversityHangzhou, China
| | - Jinhong Chen
- Department of Agronomy, Zhejiang UniversityHangzhou, China
| | - Shuijin Zhu
- Department of Agronomy, Zhejiang UniversityHangzhou, China
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Shang L, Liang Q, Wang Y, Zhao Y, Wang K, Hua J. Epistasis together with partial dominance, over-dominance and QTL by environment interactions contribute to yield heterosis in upland cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2016; 129:1429-1446. [PMID: 27138784 DOI: 10.1007/s00122-016-2714-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2015] [Accepted: 04/12/2016] [Indexed: 05/19/2023]
Abstract
QTL mapping based on backcross and RIL populations suggests that epistasis together with partial dominance, over-dominance and their environmental interactions of QTLs play an important role in yield heterosis in upland cotton. A backcross population (BC) was constructed to explore the genetic basis of heterosis in upland cotton (Gossypium hirsutum L.). For yield and yield components, recombinant inbred line (RIL) and BC populations were evaluated simultaneously at three different locations. A total of 35 and 30 quantitative trait loci (QTLs) were detected based on the RILs and BC data, respectively. Six (16.7 %) additive QTLs, 19 (52.8 %) partial dominant QTLs and 11 (30.6 %) over-dominant QTLs were detected by single-locus analysis using composite interval mapping in BC population. QTLs detected for mid-parent heterosis (MPH) were mostly related to those detected in the BC population. No significant correlation was found between marker heterozygosity and performance. It indicated that heterozygosity was not always favorable for performance. Two-locus analysis revealed 46, 25 and 12 QTLs with main effects (M-QTLs), and 55, 63 and 33 QTLs involved in digenic interactions (E-QTLs) were detected for yield and yield components in RIL, BC and MPH, respectively. A large number of M-QTLs and E-QTLs showed QTL by environment interactions (QEs) in three environments. These results suggest that epistasis together with partial dominance, over-dominance and QEs all contribute to yield heterosis in upland cotton.
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Affiliation(s)
- Lianguang Shang
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Qingzhi Liang
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
- The Key Laboratory of Tropical Fruit Biology of Ministry of Agriculture, The South Subtropical Crops Research Institutes, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, 524091, China
| | - Yumei Wang
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
- Research Institute of Cash Crop, Hubei Academy of Agricultural Sciences, Wuhan, 430064, Hubei, China
| | - Yanpeng Zhao
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Kunbo Wang
- Institute of Cotton Research, Chinese Academy of Agricultural Sciences/State Key Laboratory of Cotton Biology, Anyang, 455000, Henan, China
| | - Jinping Hua
- Department of Plant Genetics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China.
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79
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Man W, Zhang L, Li X, Xie X, Pei W, Yu J, Yu S, Zhang J. A comparative transcriptome analysis of two sets of backcross inbred lines differing in lint-yield derived from a Gossypium hirsutum × Gossypium barbadense population. Mol Genet Genomics 2016; 291:1749-67. [PMID: 27256327 DOI: 10.1007/s00438-016-1216-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 05/13/2016] [Indexed: 01/23/2023]
Abstract
Upland cotton (Gossypium hirsutum L.) is the most important fiber crop, and its lint-yield improvement is impeded due to its narrow genetic base and the lack of understanding of the genetic basis of yield. Backcross inbred lines (BILs) or near-isogenic lines (NILs) in the same genetic background differing in lint yield, developed through advanced backcrossing, provide an important genomic resource to study the molecular genetic basis of lint yield. In the present study, a high-yield (HY) group and a low-yield (LY) group each with three BILs were selected from a BIL population between G. hirsutum and G. barbadense. Using a microarray-based comparative transcriptome analysis on developing fibers at 10 days post-anthesis (DPA) between the two groups, 1486 differentially expressed genes (DEGs) were identified. A total of 212 DEGs were further mapped in the regions of 24 yield QTL and 11 yield trait QTL hotspots as reported previously, and 81 DEGs mapped with the 7 lint-yield QTL identified in the BIL population from which the two sets of BILs were selected. Gene Ontology annotations and Blast-Mapping-Annotation-KEGG analysis via Blast2GO revealed that more DEGs were associated with catalytic activity and binding, followed by transporters, nucleic acid binding transcription factors, structural molecules and molecular transducer activities. Six DEGs were chosen for a quantitative RT-PCR assay, and the results were consistent with the microarray analysis. The development of DEGs-based markers revealed that 7 single strand conformation polymorphism-based single nucleotide polymorphic (SSCP-SNP) markers were associated with yield traits, and 3 markers with lint yield. In the present study, we identified a number of yield and yield component QTL-co-localizing DEGs and developed several DEG-based SSCP-SNP markers for the traits, thereby providing a set of candidate genes for molecular breeding and genetic manipulation of lint yield in cotton.
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Affiliation(s)
- Wu Man
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, 455000, Henan, China
| | - Liyuan Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, 455000, Henan, China
| | - Xihua Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, 455000, Henan, China
| | - Xiaobing Xie
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, 455000, Henan, China.,Wuyang A & F Bureau, Luohe, Henan, China
| | - Wenfeng Pei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, 455000, Henan, China
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, 455000, Henan, China.
| | - Shuxun Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, 455000, Henan, China.
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA.
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80
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Dai B, Guo H, Huang C, Zhang X, Lin Z. Genomic heterozygosity and hybrid breakdown in cotton (Gossypium): different traits, different effects. BMC Genet 2016; 17:58. [PMID: 27072350 PMCID: PMC4830075 DOI: 10.1186/s12863-016-0366-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2015] [Accepted: 04/07/2016] [Indexed: 11/25/2022] Open
Abstract
Background Hybrid breakdown has been well documented in various species. Relationships between genomic heterozygosity and traits-fitness have been extensively explored especially in the natural populations. But correlations between genomic heterozygosity and vegetative and reproductive traits in cotton interspecific populations have not been studied. In the current study, two reciprocal F2 populations were developed using Gossypium hirsutum cv. Emian 22 and G. barbadense acc. 3–79 as parents to study hybrid breakdown in cotton. A total of 125 simple sequence repeat (SSR) markers were used to genotype the two F2 interspecific populations. Results To guarantee mutual independence among the genotyped markers, the 125 SSR markers were checked by the linkage disequilibrium analysis. To our knowledge, this is a novel approach to evaluate the individual genomic heterozygosity. After marker checking, 83 common loci were used to assess the extent of genomic heterozygosity. Hybrid breakdown was found extensively in the two interspecific F2 populations particularly on the reproductive traits because of the infertility and the bare seeds. And then, the relationships between the genomic heterozygosity and the vegetative reproductive traits were investigated. The only relationships between hybrid breakdown and heterozygosity were observed in the (Emian22 × 3–79) F2 population for seed index (SI) and boll number per plant (BN). The maternal cytoplasmic environment may have a significant effect on genomic heterozygosity and on correlations between heterozygosity and reproductive traits. Conclusions A novel approach was used to evaluate genomic heterozygosity in cotton; and hybrid breakdown was observed in reproductive traits in cotton. These findings may offer new insight into hybrid breakdown in allotetraploid cotton interspecific hybrids, and may be useful for the development of interspecific hybrids for cotton genetic improvement. Electronic supplementary material The online version of this article (doi:10.1186/s12863-016-0366-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Baosheng Dai
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Huanle Guo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Cong Huang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
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81
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Ma Q, Wu M, Pei W, Wang X, Zhai H, Wang W, Li X, Zhang J, Yu J, Yu S. RNA-Seq-Mediated Transcriptome Analysis of a Fiberless Mutant Cotton and Its Possible Origin Based on SNP Markers. PLoS One 2016; 11:e0151994. [PMID: 26990639 PMCID: PMC4798417 DOI: 10.1371/journal.pone.0151994] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Accepted: 03/07/2016] [Indexed: 01/01/2023] Open
Abstract
As the longest known single-celled trichomes, cotton (Gossypium L.) fibers constitute a classic model system to investigate cell initiation and elongation. In this study, we used a high-throughput transcriptome sequencing technology to identify fiber-initiation-related single nucleotide polymorphism (SNP) markers and differentially expressed genes (DEGs) between the wild-type (WT) Upland cotton (G. hirsutum) Xuzhou 142 and its natural fuzzless-lintless mutant Xuzhou 142 fl. Approximately 700 million high-quality cDNA reads representing over 58 Gb of sequences were obtained, resulting in the identification of 28,610 SNPs--of which 17,479 were novel--from 13,960 expressed genes. Of these SNPs, 50% of SNPs in fl were identical to those of G. barbadense, which suggests the likely origin of the fl mutant from an interspecific hybridization between Xuzhou 142 and an unknown G. barbadense genotype. Of all detected SNPs, 15,555, 12,750, and 305 were classified as non-synonymous, synonymous, and pre-terminated ones, respectively. Moreover, 1,352 insertion/deletion polymorphisms (InDels) were also detected. A total of 865 DEGs were identified between the WT and fl in ovules at -3 and 0 days post-anthesis, with 302 candidate SNPs selected from these DEGs for validation by a high-resolution melting analysis and Sanger sequencing in seven cotton genotypes. The number of genotypic pairwise polymorphisms varied from 43 to 302, indicating that the identified SNPs are reliable. These SNPs should serve as good resources for breeding and genetic studies in cotton.
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Affiliation(s)
- Qifeng Ma
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wenfeng Pei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiaoyan Wang
- College of Biology and Food Technology, Anyang Institute of Technology, Anyang, China
| | - Honghong Zhai
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wenkui Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xingli Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, New Mexico, United States of America
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Shuxun Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
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82
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Jamshed M, Jia F, Gong J, Palanga KK, Shi Y, Li J, Shang H, Liu A, Chen T, Zhang Z, Cai J, Ge Q, Liu Z, Lu Q, Deng X, Tan Y, Or Rashid H, Sarfraz Z, Hassan M, Gong W, Yuan Y. Identification of stable quantitative trait loci (QTLs) for fiber quality traits across multiple environments in Gossypium hirsutum recombinant inbred line population. BMC Genomics 2016. [PMID: 26951621 DOI: 10.1186/s12864‐016‐2560‐2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The identification of quantitative trait loci (QTLs) that are stable and consistent across multiple environments and populations plays an essential role in marker-assisted selection (MAS). In the present study, we used 28,861 simple sequence repeat (SSR) markers, which included 12,560 Gossypium raimondii (D genome) sequence-based SSR markers to identify polymorphism between two upland cotton strains 0-153 and sGK9708. A total of 851 polymorphic primers were finally selected and used to genotype 196 recombinant inbred lines (RIL) derived from a cross between 0 and 153 and sGK9708 and used to construct a linkage map. The RIL population was evaluated for fiber quality traits in six locations in China for five years. Stable QTLs identified in this intraspecific cross could be used in future cotton breeding program and with fewer obstacles. RESULTS The map covered a distance of 4,110 cM, which represents about 93.2 % of the upland cotton genome, and with an average distance of 5.2 cM between adjacent markers. We identified 165 QTLs for fiber quality traits, of which 47 QTLs were determined to be stable across multiple environments. Most of these QTLs aggregated into clusters with two or more traits. A total of 30 QTL clusters were identified which consisted of 103 QTLs. Sixteen clusters in the At sub-genome comprised 44 QTLs, whereas 14 clusters in the Dt sub-genome that included 59 QTLs for fiber quality were identified. Four chromosomes, including chromosome 4 (c4), c7, c14, and c25 were rich in clusters harboring 5, 4, 5, and 6 clusters respectively. A meta-analysis was performed using Biomercator V4.2 to integrate QTLs from 11 environmental datasets on the RIL populations of the above mentioned parents and previous QTL reports. Among the 165 identified QTLs, 90 were identified as common QTLs, whereas the remaining 75 QTLs were determined to be novel QTLs. The broad sense heritability estimates of fiber quality traits were high for fiber length (0.93), fiber strength (0.92), fiber micronaire (0.85), and fiber uniformity (0.80), but low for fiber elongation (0.27). Meta-clusters on c4, c7, c14 and c25 were identified as stable QTL clusters and were considered more valuable in MAS for the improvement of fiber quality of upland cotton. CONCLUSION Multiple environmental evaluations of an intraspecific RIL population were conducted to identify stable QTLs. Meta-QTL analyses identified a common chromosomal region that plays an important role in fiber development. Therefore, QTLs identified in the present study are an ideal candidate for MAS in cotton breeding programs to improve fiber quality.
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Affiliation(s)
- 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.
| | - Fei Jia
- 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. .,College of Agronomy, Xinjiang Agricultural University, Key Laboratory of Agro-Biotechnology, Urumqi, 830052, Xinjiang, China.
| | - Koffi Kibalou Palanga
- 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.
| | - 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.
| | - 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.
| | - 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.
| | - 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.
| | - Tingting Chen
- 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.
| | - Zhen 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.
| | - Juan Cai
- 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.
| | - Zhi Liu
- College of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, Hunan, China.
| | - Quanwei Lu
- Anyang College of Technology, 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.
| | - Yunna Tan
- 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.
| | - Harun Or Rashid
- 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.
| | - Zareen Sarfraz
- 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.
| | - Murtaza Hassan
- Department of Materials Science and Engineering, College of Engineering, Peking University, Beijing, 100871, 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.
| | - 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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Jamshed M, Jia F, Gong J, Palanga KK, Shi Y, Li J, Shang H, Liu A, Chen T, Zhang Z, Cai J, Ge Q, Liu Z, Lu Q, Deng X, Tan Y, Or Rashid H, Sarfraz Z, Hassan M, Gong W, Yuan Y. Identification of stable quantitative trait loci (QTLs) for fiber quality traits across multiple environments in Gossypium hirsutum recombinant inbred line population. BMC Genomics 2016; 17:197. [PMID: 26951621 PMCID: PMC4782318 DOI: 10.1186/s12864-016-2560-2] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2015] [Accepted: 02/29/2016] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND The identification of quantitative trait loci (QTLs) that are stable and consistent across multiple environments and populations plays an essential role in marker-assisted selection (MAS). In the present study, we used 28,861 simple sequence repeat (SSR) markers, which included 12,560 Gossypium raimondii (D genome) sequence-based SSR markers to identify polymorphism between two upland cotton strains 0-153 and sGK9708. A total of 851 polymorphic primers were finally selected and used to genotype 196 recombinant inbred lines (RIL) derived from a cross between 0 and 153 and sGK9708 and used to construct a linkage map. The RIL population was evaluated for fiber quality traits in six locations in China for five years. Stable QTLs identified in this intraspecific cross could be used in future cotton breeding program and with fewer obstacles. RESULTS The map covered a distance of 4,110 cM, which represents about 93.2 % of the upland cotton genome, and with an average distance of 5.2 cM between adjacent markers. We identified 165 QTLs for fiber quality traits, of which 47 QTLs were determined to be stable across multiple environments. Most of these QTLs aggregated into clusters with two or more traits. A total of 30 QTL clusters were identified which consisted of 103 QTLs. Sixteen clusters in the At sub-genome comprised 44 QTLs, whereas 14 clusters in the Dt sub-genome that included 59 QTLs for fiber quality were identified. Four chromosomes, including chromosome 4 (c4), c7, c14, and c25 were rich in clusters harboring 5, 4, 5, and 6 clusters respectively. A meta-analysis was performed using Biomercator V4.2 to integrate QTLs from 11 environmental datasets on the RIL populations of the above mentioned parents and previous QTL reports. Among the 165 identified QTLs, 90 were identified as common QTLs, whereas the remaining 75 QTLs were determined to be novel QTLs. The broad sense heritability estimates of fiber quality traits were high for fiber length (0.93), fiber strength (0.92), fiber micronaire (0.85), and fiber uniformity (0.80), but low for fiber elongation (0.27). Meta-clusters on c4, c7, c14 and c25 were identified as stable QTL clusters and were considered more valuable in MAS for the improvement of fiber quality of upland cotton. CONCLUSION Multiple environmental evaluations of an intraspecific RIL population were conducted to identify stable QTLs. Meta-QTL analyses identified a common chromosomal region that plays an important role in fiber development. Therefore, QTLs identified in the present study are an ideal candidate for MAS in cotton breeding programs to improve fiber quality.
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Affiliation(s)
- 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.
| | - Fei Jia
- 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.
- College of Agronomy, Xinjiang Agricultural University, Key Laboratory of Agro-Biotechnology, Urumqi, 830052, Xinjiang, China.
| | - Koffi Kibalou Palanga
- 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.
| | - 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.
| | - 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.
| | - 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.
| | - 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.
| | - Tingting Chen
- 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.
| | - Zhen 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.
| | - Juan Cai
- 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.
| | - Zhi Liu
- College of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, Hunan, China.
| | - Quanwei Lu
- Anyang College of Technology, 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.
| | - Yunna Tan
- 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.
| | - Harun Or Rashid
- 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.
| | - Zareen Sarfraz
- 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.
| | - Murtaza Hassan
- Department of Materials Science and Engineering, College of Engineering, Peking University, Beijing, 100871, 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.
| | - 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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Partial Dominance, Overdominance, Epistasis and QTL by Environment Interactions Contribute to Heterosis in Two Upland Cotton Hybrids. G3-GENES GENOMES GENETICS 2015; 6:499-507. [PMID: 26715091 PMCID: PMC4777113 DOI: 10.1534/g3.115.025809] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Based on two recombinant inbred line (RIL) populations, two corresponding backcross (BC) populations were constructed to elucidate the genetic basis of heterosis in Upland cotton (Gossypium hirsutum L.). The yield, and yield components, of these populations were evaluated in three environments. At the single-locus level, 78 and 66 quantitative trait loci (QTL) were detected using composite interval mapping in RIL and BC populations, respectively, and 29 QTL were identified based on mid-parental heterosis (MPH) data of two hybrids. Considering all traits together, a total of 50 (64.9%) QTL with partial dominance effect, and 27 (35.1%) QTL for overdominance effect were identified in two BC populations. At the two-locus level, 120 and 88 QTL with main effects (M-QTL), and 335 and 99 QTL involved in digenic interactions (E-QTL), were detected by inclusive composite interval mapping in RIL and BC populations, respectively. A large number of QTL by environment interactions (QEs) for M-QTL and E-QTL were detected in three environments. For most traits, average E-QTL explained a larger proportion of phenotypic variation than did M-QTL in two RIL populations and two BC populations. It was concluded that partial dominance, overdominance, epistasis, and QEs all contribute to heterosis in Upland cotton, and that partial dominance resulting from single loci and epistasis play a relatively more important role than other genetic effects in heterosis in Upland cotton.
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