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Whole-genome mapping identified novel “QTL hotspots regions” for seed storability in soybean (Glycine max L.)

BACKGROUND: Seed aging in soybean is a serious challenge for agronomic production and germplasm preservation. However, its genetic basis remains largely unclear in soybean. Unraveling the genetic mechanism involved in seed aging, and enhancing seed storability is an imperative goal for soybean breed...

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Autores principales: Zhang, Xi, Hina, Aiman, Song, Shiyu, Kong, Jiejie, Bhat, Javaid Akhter, Zhao, Tuanjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580613/
https://www.ncbi.nlm.nih.gov/pubmed/31208334
http://dx.doi.org/10.1186/s12864-019-5897-5
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author Zhang, Xi
Hina, Aiman
Song, Shiyu
Kong, Jiejie
Bhat, Javaid Akhter
Zhao, Tuanjie
author_facet Zhang, Xi
Hina, Aiman
Song, Shiyu
Kong, Jiejie
Bhat, Javaid Akhter
Zhao, Tuanjie
author_sort Zhang, Xi
collection PubMed
description BACKGROUND: Seed aging in soybean is a serious challenge for agronomic production and germplasm preservation. However, its genetic basis remains largely unclear in soybean. Unraveling the genetic mechanism involved in seed aging, and enhancing seed storability is an imperative goal for soybean breeding. The aim of this study is to identify quantitative trait loci (QTLs) using high-density genetic linkage maps of soybean for seed storability. In this regard, two recombinant inbred line (RIL) populations derived from Zhengyanghuangdou × Meng 8206 (ZM6) and Linhefenqingdou × Meng 8206 (LM6) crosses were evaluated for three seed-germination related traits viz., germination rate (GR), normal seedling length (SL) and normal seedling fresh weight (FW) under natural and artificial aging conditions to map QTLs for seed storability. RESULTS: A total of 34 QTLs, including 13 QTLs for GR, 11 QTLs for SL and 10 QTLs for FW, were identified on 11 chromosomes with the phenotypic variation ranged from 7.30 to 23.16% under both aging conditions. All these QTLs were novel, and 21 of these QTLs were clustered in five QTL-rich regions on four different chromosomes viz., Chr3, Chr5, Chr17 &Chr18, among them the highest concentration of seven and six QTLs were found in “QTL hotspot A” (Chr17) and “QTL hotspot B” (Chr5), respectively. Furthermore, QTLs within all the five QTL clusters are linked to at least two studied traits, which is also supported by highly significant correlation between the three germination-related traits. QTLs for seed-germination related traits in “QTL hotspot B” were found in both RIL populations and aging conditions, and also QTLs underlying “QTL hotspot A” are identified in both RIL populations under artificial aging condition. These are the stable genomic regions governing the inheritance of seed storability in soybean, and will be the main focus for soybean breeders. CONCLUSION: This study uncovers the genetic basis of seed storability in soybean. The newly identified QTLs provides valuable information, and will be main targets for fine mapping, candidate gene identification and marker-assisted breeding. Hence, the present study is the first report for the comprehensive and detailed investigation of genetic architecture of seed storability in soybean. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5897-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-65806132019-06-24 Whole-genome mapping identified novel “QTL hotspots regions” for seed storability in soybean (Glycine max L.) Zhang, Xi Hina, Aiman Song, Shiyu Kong, Jiejie Bhat, Javaid Akhter Zhao, Tuanjie BMC Genomics Research Article BACKGROUND: Seed aging in soybean is a serious challenge for agronomic production and germplasm preservation. However, its genetic basis remains largely unclear in soybean. Unraveling the genetic mechanism involved in seed aging, and enhancing seed storability is an imperative goal for soybean breeding. The aim of this study is to identify quantitative trait loci (QTLs) using high-density genetic linkage maps of soybean for seed storability. In this regard, two recombinant inbred line (RIL) populations derived from Zhengyanghuangdou × Meng 8206 (ZM6) and Linhefenqingdou × Meng 8206 (LM6) crosses were evaluated for three seed-germination related traits viz., germination rate (GR), normal seedling length (SL) and normal seedling fresh weight (FW) under natural and artificial aging conditions to map QTLs for seed storability. RESULTS: A total of 34 QTLs, including 13 QTLs for GR, 11 QTLs for SL and 10 QTLs for FW, were identified on 11 chromosomes with the phenotypic variation ranged from 7.30 to 23.16% under both aging conditions. All these QTLs were novel, and 21 of these QTLs were clustered in five QTL-rich regions on four different chromosomes viz., Chr3, Chr5, Chr17 &Chr18, among them the highest concentration of seven and six QTLs were found in “QTL hotspot A” (Chr17) and “QTL hotspot B” (Chr5), respectively. Furthermore, QTLs within all the five QTL clusters are linked to at least two studied traits, which is also supported by highly significant correlation between the three germination-related traits. QTLs for seed-germination related traits in “QTL hotspot B” were found in both RIL populations and aging conditions, and also QTLs underlying “QTL hotspot A” are identified in both RIL populations under artificial aging condition. These are the stable genomic regions governing the inheritance of seed storability in soybean, and will be the main focus for soybean breeders. CONCLUSION: This study uncovers the genetic basis of seed storability in soybean. The newly identified QTLs provides valuable information, and will be main targets for fine mapping, candidate gene identification and marker-assisted breeding. Hence, the present study is the first report for the comprehensive and detailed investigation of genetic architecture of seed storability in soybean. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5897-5) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-17 /pmc/articles/PMC6580613/ /pubmed/31208334 http://dx.doi.org/10.1186/s12864-019-5897-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zhang, Xi
Hina, Aiman
Song, Shiyu
Kong, Jiejie
Bhat, Javaid Akhter
Zhao, Tuanjie
Whole-genome mapping identified novel “QTL hotspots regions” for seed storability in soybean (Glycine max L.)
title Whole-genome mapping identified novel “QTL hotspots regions” for seed storability in soybean (Glycine max L.)
title_full Whole-genome mapping identified novel “QTL hotspots regions” for seed storability in soybean (Glycine max L.)
title_fullStr Whole-genome mapping identified novel “QTL hotspots regions” for seed storability in soybean (Glycine max L.)
title_full_unstemmed Whole-genome mapping identified novel “QTL hotspots regions” for seed storability in soybean (Glycine max L.)
title_short Whole-genome mapping identified novel “QTL hotspots regions” for seed storability in soybean (Glycine max L.)
title_sort whole-genome mapping identified novel “qtl hotspots regions” for seed storability in soybean (glycine max l.)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580613/
https://www.ncbi.nlm.nih.gov/pubmed/31208334
http://dx.doi.org/10.1186/s12864-019-5897-5
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