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Mapping intron retention events contributing to complex traits using splice quantitative trait locus
BACKGROUND: Alternative splicing (AS) of mRNA plays an important roles in transcriptome diversity, involving regulation of plant growth and stress response. Understanding the variation of AS events underlying GWAS loci in a crop population can provide insight into the molecular mechanisms of complex...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362629/ https://www.ncbi.nlm.nih.gov/pubmed/37480119 http://dx.doi.org/10.1186/s13007-023-01048-4 |
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author | Wang, Siyuan Wu, Hongyu Zhao, Yongyan Wang, Luyao Guan, Xueying Zhao, Ting |
author_facet | Wang, Siyuan Wu, Hongyu Zhao, Yongyan Wang, Luyao Guan, Xueying Zhao, Ting |
author_sort | Wang, Siyuan |
collection | PubMed |
description | BACKGROUND: Alternative splicing (AS) of mRNA plays an important roles in transcriptome diversity, involving regulation of plant growth and stress response. Understanding the variation of AS events underlying GWAS loci in a crop population can provide insight into the molecular mechanisms of complex agronomic traits. To date, genome-wide association studies relating AS events to agronomic traits have rarely been conducted at the population level in crops. RESULTS: Here, a pipeline was constructed to identify candidate AS events related to complex traits. Firstly, ovule transcriptome data were used to characterize intron retention (IR), the predominant type of AS in plants, on a genome-wide scale. This was done in a natural population consisting of 279 upland cotton lines. Secondly, splice quantitative trait locus (sQTL) analysis was carried out, which yielded a total of 2295 sQTLs involving 1607 genes. Of these, 14.25% (n = 427) were cis-regulatory loci. Integration with expression quantitative trait loci (eQTL) revealed that 53 (21.4%) cis-sGenes were regulated by both cis-sQTLs and cis-eQTLs. Finally, co-localization analysis integrated with GWAS loci in this population showed 32 cis-QTLs to be co-located with genetic regulatory loci related to fiber yield and quality traits, indicating that sQTLs are likely to participate in regulating cotton fiber yield and quality. An in-depth evaluation confirmed that differences in the IR rates of sQTL-regulated candidate genes such as GhLRRK1 and GhGC1 are associated with lint percentage (LP), which has potential in breeding applications. CONCLUSION: This study provides a clue that AS of mRNA has an impact on crop yield, along with functional sQTLs are new genetic resources for cotton precision breeding. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-023-01048-4. |
format | Online Article Text |
id | pubmed-10362629 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103626292023-07-23 Mapping intron retention events contributing to complex traits using splice quantitative trait locus Wang, Siyuan Wu, Hongyu Zhao, Yongyan Wang, Luyao Guan, Xueying Zhao, Ting Plant Methods Research BACKGROUND: Alternative splicing (AS) of mRNA plays an important roles in transcriptome diversity, involving regulation of plant growth and stress response. Understanding the variation of AS events underlying GWAS loci in a crop population can provide insight into the molecular mechanisms of complex agronomic traits. To date, genome-wide association studies relating AS events to agronomic traits have rarely been conducted at the population level in crops. RESULTS: Here, a pipeline was constructed to identify candidate AS events related to complex traits. Firstly, ovule transcriptome data were used to characterize intron retention (IR), the predominant type of AS in plants, on a genome-wide scale. This was done in a natural population consisting of 279 upland cotton lines. Secondly, splice quantitative trait locus (sQTL) analysis was carried out, which yielded a total of 2295 sQTLs involving 1607 genes. Of these, 14.25% (n = 427) were cis-regulatory loci. Integration with expression quantitative trait loci (eQTL) revealed that 53 (21.4%) cis-sGenes were regulated by both cis-sQTLs and cis-eQTLs. Finally, co-localization analysis integrated with GWAS loci in this population showed 32 cis-QTLs to be co-located with genetic regulatory loci related to fiber yield and quality traits, indicating that sQTLs are likely to participate in regulating cotton fiber yield and quality. An in-depth evaluation confirmed that differences in the IR rates of sQTL-regulated candidate genes such as GhLRRK1 and GhGC1 are associated with lint percentage (LP), which has potential in breeding applications. CONCLUSION: This study provides a clue that AS of mRNA has an impact on crop yield, along with functional sQTLs are new genetic resources for cotton precision breeding. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-023-01048-4. BioMed Central 2023-07-21 /pmc/articles/PMC10362629/ /pubmed/37480119 http://dx.doi.org/10.1186/s13007-023-01048-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wang, Siyuan Wu, Hongyu Zhao, Yongyan Wang, Luyao Guan, Xueying Zhao, Ting Mapping intron retention events contributing to complex traits using splice quantitative trait locus |
title | Mapping intron retention events contributing to complex traits using splice quantitative trait locus |
title_full | Mapping intron retention events contributing to complex traits using splice quantitative trait locus |
title_fullStr | Mapping intron retention events contributing to complex traits using splice quantitative trait locus |
title_full_unstemmed | Mapping intron retention events contributing to complex traits using splice quantitative trait locus |
title_short | Mapping intron retention events contributing to complex traits using splice quantitative trait locus |
title_sort | mapping intron retention events contributing to complex traits using splice quantitative trait locus |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362629/ https://www.ncbi.nlm.nih.gov/pubmed/37480119 http://dx.doi.org/10.1186/s13007-023-01048-4 |
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