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Qi G, Si Z, Xuan L, Han Z, Hu Y, Fang L, Dai F, Zhang T. Unravelling the genetic basis and regulation networks related to fibre quality improvement using chromosome segment substitution lines in cotton. PLANT BIOTECHNOLOGY JOURNAL 2024; 22:3135-3150. [PMID: 39046162 PMCID: PMC11500987 DOI: 10.1111/pbi.14436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 07/02/2024] [Accepted: 07/06/2024] [Indexed: 07/25/2024]
Abstract
The elucidation of genetic architecture and molecular regulatory networks underlying complex traits remains a significant challenge in life science, largely due to the substantial background effects that arise from epistasis and gene-environment interactions. The chromosome segment substitution line (CSSL) is an ideal material for genetic and molecular dissection of complex traits due to its near-isogenic properties; yet a comprehensive analysis, from the basic identification of substitution segments to advanced regulatory network, is still insufficient. Here, we developed two cotton CSSL populations on the Gossypium hirsutum background, representing wide adaptation and high lint yield, with introgression from G. barbadense, representing superior fibre quality. We sequenced 99 CSSLs that demonstrated significant differences from G. hirsutum in fibre, and characterized 836 dynamic fibre transcriptomes in three crucial developmental stages. We developed a workflow for precise resolution of chromosomal substitution segments; the genome sequencing revealed substitutions collectively representing 87.25% of the G. barbadense genome. Together, the genomic and transcriptomic survey identified 18 novel fibre-quality-related quantitative trait loci with high genetic contributions and the comprehensive landscape of fibre development regulation. Furthermore, analysis determined unique cis-expression patterns in CSSLs to be the driving force for fibre quality alteration; building upon this, the co-expression regulatory network revealed biological relationships among the noted pathways and accurately described the molecular interactions of GhHOX3, GhRDL1 and GhEXPA1 during fibre elongation, along with reliable predictions for their interactions with GhTBA8A5. Our study will enhance more strategic employment of CSSL in crop molecular biology and breeding programmes.
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Affiliation(s)
- Guoan Qi
- Hainan Institute of Zhejiang University, Yazhou Bay Science and Technology CitySanyaHainanChina
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang UniversityHangzhouZhejiangChina
| | - Zhanfeng Si
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang UniversityHangzhouZhejiangChina
| | - Lisha Xuan
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang UniversityHangzhouZhejiangChina
| | - Zegang Han
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang UniversityHangzhouZhejiangChina
| | - Yan Hu
- Hainan Institute of Zhejiang University, Yazhou Bay Science and Technology CitySanyaHainanChina
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang UniversityHangzhouZhejiangChina
| | - Lei Fang
- Hainan Institute of Zhejiang University, Yazhou Bay Science and Technology CitySanyaHainanChina
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang UniversityHangzhouZhejiangChina
| | - Fan Dai
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang UniversityHangzhouZhejiangChina
| | - Tianzhen Zhang
- Hainan Institute of Zhejiang University, Yazhou Bay Science and Technology CitySanyaHainanChina
- The Advanced Seed Institute, College of Agriculture and Biotechnology, Zhejiang UniversityHangzhouZhejiangChina
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Zhang B, Liu G, Song J, Jia B, Yang S, Ma J, Liu J, Shahzad K, Wang W, Pei W, Wu M, Zhang J, Yu J. Analysis of the MIR396 gene family and the role of MIR396b in regulating fiber length in cotton. PHYSIOLOGIA PLANTARUM 2022; 174:e13801. [PMID: 36258652 DOI: 10.1111/ppl.13801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 09/12/2022] [Accepted: 10/13/2022] [Indexed: 06/16/2023]
Abstract
Cotton fiber is one of the most important natural raw materials in the world textile industry. Improving fiber yield and quality has always been the main goal. MicroRNAs, as typical small noncoding RNAs, could affect fiber length during different stages of fiber development. Based on differentially expressed microRNA in the two interspecific backcross inbred lines (BILs) with a significant difference in fiber length, we identified the miR396 gene family in the two tetraploid cotton genomes and found MIR396b_D13 as the functional precursor to produce mature miR396 during the fiber elongation stage. Among 46 target genes regulated by miR396b, the GROWTH-REGULATING FACTOR 5 gene (GRF5, Gh_A10G0492) had a differential expression level in the two BILs during fiber elongation stage. The expression patterns indicated that the miR396b-GRF5 regulatory module has a critical role in fiber development. Furthermore, virus-induced gene silencing (VIGS) of miR396b significantly produced longer fiber than the wild type, and the expression level of GRF5 showed the reverse trends of the miR396b expression level. The analysis of co-expression network for the GRF5 gene suggested that a cytochrome P450 gene functions as an allene oxide synthase (Gh_D06G0089, AOS), which plays a critical role in jasmonate biosynthetic pathway. In conclusion, our results revealed that the miR396b-GRF5 module has a critical role in fiber development. These findings provide a molecular foundation for fiber quality improvement in the future.
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Affiliation(s)
- Bingbing Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
| | - Guoyuan Liu
- School of Life Science, Nantong University, Nantong, China
| | - Jikun Song
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
| | - Bing Jia
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
| | - Shuxian Yang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jianjiang Ma
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
| | - Ji Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
| | - Kashif Shahzad
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wenkui Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wenfeng Pei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, New Mexico, USA
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, China
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Revealing Genetic Differences in Fiber Elongation between the Offspring of Sea Island Cotton and Upland Cotton Backcross Populations Based on Transcriptome and Weighted Gene Coexpression Networks. Genes (Basel) 2022; 13:genes13060954. [PMID: 35741716 PMCID: PMC9222338 DOI: 10.3390/genes13060954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 05/20/2022] [Accepted: 05/24/2022] [Indexed: 02/05/2023] Open
Abstract
Fiber length is an important indicator of cotton fiber quality, and the time and rate of cotton fiber cell elongation are key factors in determining the fiber length of mature cotton. To gain insight into the differences in fiber elongation mechanisms in the offspring of backcross populations of Sea Island cotton Xinhai 16 and land cotton Line 9, we selected two groups with significant differences in fiber length (long-fiber group L and short-fiber group S) at different fiber development stages 0, 5, 10 and 15 days post-anthesis (DPA) for transcriptome comparison. A total of 171.74 Gb of clean data was obtained by RNA-seq, and eight genes were randomly selected for qPCR validation. Data analysis identified 6055 differentially expressed genes (DEGs) between two groups of fibers, L and S, in four developmental periods, and gene ontology (GO) term analysis revealed that these DEGs were associated mainly with microtubule driving, reactive oxygen species, plant cell wall biosynthesis, and glycosyl compound hydrolase activity. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis indicated that plant hormone signaling, mitogen-activated protein kinase (MAPK) signaling, and starch and sucrose metabolism pathways were associated with fiber elongation. Subsequently, a sustained upregulation expression pattern, profile 19, was identified and analyzed using short time-series expression miner (STEM). An analysis of the weighted gene coexpression network module uncovered 21 genes closely related to fiber development, mainly involved in functions such as cell wall relaxation, microtubule formation, and cytoskeletal structure of the cell wall. This study helps to enhance the understanding of the Sea Island–Upland backcross population and identifies key genes for cotton fiber development, and these findings will provide a basis for future research on the molecular mechanisms of fiber length formation in cotton populations.
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Pei W, Song J, Wang W, Ma J, Jia B, Wu L, Wu M, Chen Q, Qin Q, Zhu H, Hu C, Lei H, Gao X, Hu H, Zhang Y, Zhang J, Yu J, Qu Y. Quantitative Trait Locus Analysis and Identification of Candidate Genes for Micronaire in an Interspecific Backcross Inbred Line Population of Gossypium hirsutum × Gossypium barbadense. FRONTIERS IN PLANT SCIENCE 2021; 12:763016. [PMID: 34777444 PMCID: PMC8579039 DOI: 10.3389/fpls.2021.763016] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 09/22/2021] [Indexed: 05/08/2023]
Abstract
Cotton is the most important fiber crop and provides indispensable natural fibers for the textile industry. Micronaire (MIC) is determined by fiber fineness and maturity and is an important component of fiber quality. Gossypium barbadense L. possesses long, strong and fine fibers, while upland cotton (Gossypium hirsutum L.) is high yielding with high MIC and widely cultivated worldwide. To identify quantitative trait loci (QTLs) and candidate genes for MIC in G. barbadense, a population of 250 backcross inbred lines (BILs), developed from an interspecific cross of upland cotton CRI36 × Egyptian cotton (G. barbadense) Hai7124, was evaluated in 9 replicated field tests. Based on a high-density genetic map with 7709 genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) markers, 25 MIC QTLs were identified, including 12 previously described QTLs and 13 new QTLs. Importantly, two stable MIC QTLs (qMIC-D03-2 on D03 and qMIC-D08-1 on D08) were identified. Of a total of 338 genes identified within the two QTL regions, eight candidate genes with differential expression between TM-1 and Hai7124 were identified. Our research provides valuable information for improving MIC in cotton breeding.
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Affiliation(s)
- Wenfeng Pei
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Jikun Song
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Wenkui Wang
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jianjiang Ma
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Bing Jia
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Luyao Wu
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanjia Chen
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
| | - Qin Qin
- Western Agriculture Research Centre, Chinese Academy of Agricultural Sciences, Changji, China
| | - Haiyong Zhu
- Western Agriculture Research Centre, Chinese Academy of Agricultural Sciences, Changji, China
| | - Chengcheng Hu
- Western Agriculture Research Centre, Chinese Academy of Agricultural Sciences, Changji, China
| | - Hai Lei
- Seed Management Station, Department of Agriculture and Rural Affairs of Xinjiang, Urumqi, China
| | - Xuefei Gao
- Join Hope Seed Co., Ltd., Changji, China
| | - Haijun Hu
- Join Hope Seed Co., Ltd., Changji, China
| | - Yu Zhang
- Join Hope Seed Co., Ltd., Changji, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, United States
- Jinfa Zhang,
| | - Jiwen Yu
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
- *Correspondence: Jiwen Yu,
| | - Yanying Qu
- Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
- Yanying Qu,
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Wang F, Zhang J, Chen Y, Zhang C, Gong J, Song Z, Zhou J, Wang J, Zhao C, Jiao M, Liu A, Du Z, Yuan Y, Fan S, Zhang J. Identification of candidate genes for key fibre-related QTLs and derivation of favourable alleles in Gossypium hirsutum recombinant inbred lines with G. barbadense introgressions. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:707-720. [PMID: 31446669 PMCID: PMC7004909 DOI: 10.1111/pbi.13237] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 08/15/2019] [Indexed: 05/02/2023]
Abstract
Fine mapping QTLs and identifying candidate genes for cotton fibre-quality and yield traits would be beneficial to cotton breeding. Here, we constructed a high-density genetic map by specific-locus amplified fragment sequencing (SLAF-seq) to identify QTLs associated with fibre-quality and yield traits using 239 recombinant inbred lines (RILs), which was developed from LMY22 (a high-yield Gossypium hirsutumL. cultivar) × LY343 (a superior fibre-quality germplasm with G. barbadenseL. introgressions). The genetic map spanned 3426.57 cM, including 3556 SLAF-based SNPs and 199 SSR marker loci. A total of 104 QTLs, including 67 QTLs for fibre quality and 37 QTLs for yield traits, were identified with phenotypic data collected from 7 environments. Among these, 66 QTLs were co-located in 19 QTL clusters on 12 chromosomes, and 24 QTLs were detected in three or more environments and determined to be stable. We also investigated the genomic components of LY343 and their contributions to fibre-related traits by deep sequencing the whole genome of LY343, and we found that genomic components from G. hirsutum races (which entered LY343 via its G. barbadense parent) contributed more favourable alleles than those from G. barbadense. We further identified six putative candidate genes for stable QTLs, including Gh_A03G1147 (GhPEL6), Gh_D07G1598 (GhCSLC6) and Gh_D13G1921 (GhTBL5) for fibre-length QTLs and Gh_D03G0919 (GhCOBL4), Gh_D09G1659 (GhMYB4) and Gh_D09G1690 (GhMYB85) for lint-percentage QTLs. Our results provide comprehensive insight into the genetic basis of the formation of fibre-related traits and would be helpful for cloning fibre-development-related genes as well as for marker-assisted genetic improvement in cotton.
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Affiliation(s)
- Furong Wang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Jingxia Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Yu Chen
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Chuanyun Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Juwu Gong
- State Key Laboratory of Cotton BiologyKey Laboratory of Biological and Genetic Breeding of CottonMinistry of AgricultureInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangChina
| | - Zhangqiang Song
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Juan Zhou
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Jingjing Wang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Chengjie Zhao
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Mengjia Jiao
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Aiying Liu
- State Key Laboratory of Cotton BiologyKey Laboratory of Biological and Genetic Breeding of CottonMinistry of AgricultureInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangChina
| | - Zhaohai Du
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
| | - Youlu Yuan
- State Key Laboratory of Cotton BiologyKey Laboratory of Biological and Genetic Breeding of CottonMinistry of AgricultureInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangChina
| | - Shoujin Fan
- College of Life SciencesShandong Normal UniversityJinanChina
| | - Jun Zhang
- Key Laboratory of Cotton Breeding and Cultivation in Huang‐Huai‐Hai PlainMinistry of AgricultureCotton Research Center of Shandong Academy of Agricultural SciencesJinanChina
- College of Life SciencesShandong Normal UniversityJinanChina
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Zhang Z, Li J, Jamshed M, Shi Y, Liu A, Gong J, Wang S, Zhang J, Sun F, Jia F, Ge Q, Fan L, Zhang Z, Pan J, Fan S, Wang Y, Lu Q, Liu R, Deng X, Zou X, Jiang X, Liu P, Li P, Iqbal MS, Zhang C, Zou J, Chen H, Tian Q, Jia X, Wang B, Ai N, Feng G, Wang Y, Hong M, Li S, Lian W, Wu B, Hua J, Zhang C, Huang J, Xu A, Shang H, Gong W, Yuan Y. Genome-wide quantitative trait loci reveal the genetic basis of cotton fibre quality and yield-related traits in a Gossypium hirsutum recombinant inbred line population. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:239-253. [PMID: 31199554 PMCID: PMC6920336 DOI: 10.1111/pbi.13191] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 05/30/2019] [Accepted: 06/11/2019] [Indexed: 05/02/2023]
Abstract
Cotton is widely cultivated globally because it provides natural fibre for the textile industry and human use. To identify quantitative trait loci (QTLs)/genes associated with fibre quality and yield, a recombinant inbred line (RIL) population was developed in upland cotton. A consensus map covering the whole genome was constructed with three types of markers (8295 markers, 5197.17 centimorgans (cM)). Six fibre yield and quality traits were evaluated in 17 environments, and 983 QTLs were identified, 198 of which were stable and mainly distributed on chromosomes 4, 6, 7, 13, 21 and 25. Thirty-seven QTL clusters were identified, in which 92.8% of paired traits with significant medium or high positive correlations had the same QTL additive effect directions, and all of the paired traits with significant medium or high negative correlations had opposite additive effect directions. In total, 1297 genes were discovered in the QTL clusters, 414 of which were expressed in two RNA-Seq data sets. Many genes were discovered, 23 of which were promising candidates. Six important QTL clusters that included both fibre quality and yield traits were identified with opposite additive effect directions, and those on chromosome 13 (qClu-chr13-2) could increase fibre quality but reduce yield; this result was validated in a natural population using three markers. These data could provide information about the genetic basis of cotton fibre quality and yield and help cotton breeders to improve fibre quality and yield simultaneously.
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Qin Y, Sun H, Hao P, Wang H, Wang C, Ma L, Wei H, Yu S. Transcriptome analysis reveals differences in the mechanisms of fiber initiation and elongation between long- and short-fiber cotton (Gossypium hirsutum L.) lines. BMC Genomics 2019; 20:633. [PMID: 31382896 PMCID: PMC6683361 DOI: 10.1186/s12864-019-5986-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Accepted: 07/19/2019] [Indexed: 12/27/2022] Open
Abstract
Background Improving the yield and fiber quality of upland cotton is a goal of plant breeders. However, increasing the yield and quality of cotton fibers is becoming more urgent. While the growing human population needs more cotton fiber, climate change is reducing the amount of land on which cotton can be planted, or making it difficult to ensure that water and other resources will be available in optimal quantities. The most logical means of improving yield and quality is understanding and manipulating the genes involved. Here, we used comparative transcriptomics to explore differences in gene expression between long- and short-fiber cotton lines to identify candidate genes useful for cotton improvement. Results Light and electron microscopy revealed that the initial fiber density was significantly greater in our short-fiber group (SFG) than in our long-fiber group (LFG). Compared with the SFG fibers, the LFG fibers were longer at all developmental stages. Comparison of the LFG and SFG transcriptomes revealed a total of 3538 differentially expressed genes (DEGs). Notably, at all three developmental stages examined, two expression patterns, consistently downregulated (profile 0) and consistently upregulated (profile 7), were identified, and both were significantly enriched in the SFG and LFG. Twenty-two DEGs known to be involved in fiber initiation were detected in profile 0, while 31 DEGs involved in fiber elongation were detected in profile 7. Functional annotation suggested that these DEGs, which included ERF1, TUA2, TUB1, and PER64, affect fiber elongation by participating in the ethylene response, microtubule synthesis, and/or the peroxidase (POD) catalytic pathway. qRT-PCR was used to confirm the RNA sequencing results for select genes. Conclusions A comparison of SFG and LFG transcription profiles revealed modest but important differences in gene expression between the groups. Notably, our results confirm those of previous studies suggesting that genes involved in ethylene, tubulin, and POD pathways play important roles in fiber development. The 22 consistently downregulated DEGs involved in fiber initiation and the 31 consistently upregulated genes involved in fiber elongation are seemingly good candidate genes for improving fiber initiation and elongation in cotton. Electronic supplementary material The online version of this article (10.1186/s12864-019-5986-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yuan Qin
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, China
| | - Huiru Sun
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, China
| | - Pengbo Hao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, China
| | - Hantao Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, China
| | - Congcong Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, China
| | - Liang Ma
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, China
| | - Hengling Wei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, China.
| | - Shuxun Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, 455000, China.
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