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QTL analysis and candidate gene prediction for seed density per silique by QTL-seq and RNA-seq in spring Brassica napus L.
Seed density per silique (SD) is an important agricultural trait and plays an important role in the yield performance of Brassica napus L. (B. napus). In this study, a genetic linkage map was constructed using a double haploid (DH) population with 213 lines derived from a cross between a low SD line...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9987769/ https://www.ncbi.nlm.nih.gov/pubmed/36877715 http://dx.doi.org/10.1371/journal.pone.0281875 |
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author | Xing, Xiaorong Liu, Haidong Ye, Jingxiu Yao, Yanmei Li, Kaixiang Li, Yanling Du, Dezhi |
author_facet | Xing, Xiaorong Liu, Haidong Ye, Jingxiu Yao, Yanmei Li, Kaixiang Li, Yanling Du, Dezhi |
author_sort | Xing, Xiaorong |
collection | PubMed |
description | Seed density per silique (SD) is an important agricultural trait and plays an important role in the yield performance of Brassica napus L. (B. napus). In this study, a genetic linkage map was constructed using a double haploid (DH) population with 213 lines derived from a cross between a low SD line No. 935 and a high SD line No. 3641, and a total of 1,098,259 SNP (single-nucleotide polymorphisms) markers and 2,102 bins were mapped to 19 linkage groups. Twenty-eight QTLs for SD were detected on chromosomes A02, A04, A05, A09, C02, C03, C06, and C09 of B. napus, of which eight QTLs were on chromosome A09 and explained 5.89%-13.24% of the phenotypic variation. Furthermore, a consistent QTL for SD on chromosome A09, cqSD-A9a, was identified in four environments by QTL meta-analysis, explaining 10.68% of the phenotypic variation. In addition, four pairs of epistatic interactions were detected in the DH population via QTL epistasis analysis, indicating that SD is controlled not only by additive effects but also by epistatic effects that play an important role in spring B. napus., but with little environmental effect. Moreover, 18 closely linked SSR markers for cqSD-A9a were developed, as a result, it was mapped to a 1.86Mb (7.80–9.66 Mb) region on chromosome A09. A total of 13 differentially expressed genes (DEGs) were screened in the candidate interval by RNA-seq analysis, which were differentially expressed in buds, leaves and siliques both between and siliques both between two parents and two pools of extremely high-SD and low-SD lines in the DH population. Three of 13 DEGs were possible candidate genes that might control SD: BnaA09g14070D, which encodes a callose synthase that plays an important role in development and stress responses; BnaA09g14800D, a plant synaptic protein that encodes a membrane component; and BnaA09g18250D, which is responsible for DNA binding, transcriptional regulation, and sequence-specific DNA binding and is involved in the response to growth hormone stimulation. Overall, these results lay a foundation for fine mapping and gene cloning for SD in B. napus. |
format | Online Article Text |
id | pubmed-9987769 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-99877692023-03-07 QTL analysis and candidate gene prediction for seed density per silique by QTL-seq and RNA-seq in spring Brassica napus L. Xing, Xiaorong Liu, Haidong Ye, Jingxiu Yao, Yanmei Li, Kaixiang Li, Yanling Du, Dezhi PLoS One Research Article Seed density per silique (SD) is an important agricultural trait and plays an important role in the yield performance of Brassica napus L. (B. napus). In this study, a genetic linkage map was constructed using a double haploid (DH) population with 213 lines derived from a cross between a low SD line No. 935 and a high SD line No. 3641, and a total of 1,098,259 SNP (single-nucleotide polymorphisms) markers and 2,102 bins were mapped to 19 linkage groups. Twenty-eight QTLs for SD were detected on chromosomes A02, A04, A05, A09, C02, C03, C06, and C09 of B. napus, of which eight QTLs were on chromosome A09 and explained 5.89%-13.24% of the phenotypic variation. Furthermore, a consistent QTL for SD on chromosome A09, cqSD-A9a, was identified in four environments by QTL meta-analysis, explaining 10.68% of the phenotypic variation. In addition, four pairs of epistatic interactions were detected in the DH population via QTL epistasis analysis, indicating that SD is controlled not only by additive effects but also by epistatic effects that play an important role in spring B. napus., but with little environmental effect. Moreover, 18 closely linked SSR markers for cqSD-A9a were developed, as a result, it was mapped to a 1.86Mb (7.80–9.66 Mb) region on chromosome A09. A total of 13 differentially expressed genes (DEGs) were screened in the candidate interval by RNA-seq analysis, which were differentially expressed in buds, leaves and siliques both between and siliques both between two parents and two pools of extremely high-SD and low-SD lines in the DH population. Three of 13 DEGs were possible candidate genes that might control SD: BnaA09g14070D, which encodes a callose synthase that plays an important role in development and stress responses; BnaA09g14800D, a plant synaptic protein that encodes a membrane component; and BnaA09g18250D, which is responsible for DNA binding, transcriptional regulation, and sequence-specific DNA binding and is involved in the response to growth hormone stimulation. Overall, these results lay a foundation for fine mapping and gene cloning for SD in B. napus. Public Library of Science 2023-03-06 /pmc/articles/PMC9987769/ /pubmed/36877715 http://dx.doi.org/10.1371/journal.pone.0281875 Text en © 2023 Xing et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Xing, Xiaorong Liu, Haidong Ye, Jingxiu Yao, Yanmei Li, Kaixiang Li, Yanling Du, Dezhi QTL analysis and candidate gene prediction for seed density per silique by QTL-seq and RNA-seq in spring Brassica napus L. |
title | QTL analysis and candidate gene prediction for seed density per silique by QTL-seq and RNA-seq in spring Brassica napus L. |
title_full | QTL analysis and candidate gene prediction for seed density per silique by QTL-seq and RNA-seq in spring Brassica napus L. |
title_fullStr | QTL analysis and candidate gene prediction for seed density per silique by QTL-seq and RNA-seq in spring Brassica napus L. |
title_full_unstemmed | QTL analysis and candidate gene prediction for seed density per silique by QTL-seq and RNA-seq in spring Brassica napus L. |
title_short | QTL analysis and candidate gene prediction for seed density per silique by QTL-seq and RNA-seq in spring Brassica napus L. |
title_sort | qtl analysis and candidate gene prediction for seed density per silique by qtl-seq and rna-seq in spring brassica napus l. |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9987769/ https://www.ncbi.nlm.nih.gov/pubmed/36877715 http://dx.doi.org/10.1371/journal.pone.0281875 |
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