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An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice
Development and use of genome-wide informative simple sequence repeat (SSR) markers and novel integrated genomic strategies are vital to drive genomics-assisted breeding applications and for efficient dissection of quantitative trait loci (QTLs) underlying complex traits in rice. The present study d...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5080349/ https://www.ncbi.nlm.nih.gov/pubmed/27833617 http://dx.doi.org/10.3389/fpls.2016.01535 |
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author | Daware, Anurag Das, Sweta Srivastava, Rishi Badoni, Saurabh Singh, Ashok K. Agarwal, Pinky Parida, Swarup K. Tyagi, Akhilesh K. |
author_facet | Daware, Anurag Das, Sweta Srivastava, Rishi Badoni, Saurabh Singh, Ashok K. Agarwal, Pinky Parida, Swarup K. Tyagi, Akhilesh K. |
author_sort | Daware, Anurag |
collection | PubMed |
description | Development and use of genome-wide informative simple sequence repeat (SSR) markers and novel integrated genomic strategies are vital to drive genomics-assisted breeding applications and for efficient dissection of quantitative trait loci (QTLs) underlying complex traits in rice. The present study developed 6244 genome-wide informative SSR markers exhibiting in silico fragment length polymorphism based on repeat-unit variations among genomic sequences of 11 indica, japonica, aus, and wild rice accessions. These markers were mapped on diverse coding and non-coding sequence components of known cloned/candidate genes annotated from 12 chromosomes and revealed a much higher amplification (97%) and polymorphic potential (88%) along with wider genetic/functional diversity level (16–74% with a mean 53%) especially among accessions belonging to indica cultivar group, suggesting their utility in large-scale genomics-assisted breeding applications in rice. A high-density 3791 SSR markers-anchored genetic linkage map (IR 64 × Sonasal) spanning 2060 cM total map-length with an average inter-marker distance of 0.54 cM was generated. This reference genetic map identified six major genomic regions harboring robust QTLs (31% combined phenotypic variation explained with a 5.7–8.7 LOD) governing grain weight on six rice chromosomes. One strong grain weight major QTL region (OsqGW5.1) was narrowed-down by integrating traditional QTL mapping with high-resolution QTL region-specific integrated SSR and single nucleotide polymorphism markers-based QTL-seq analysis and differential expression profiling. This led us to delineate two natural allelic variants in two known cis-regulatory elements (RAV1AAT and CARGCW8GAT) of glycosyl hydrolase and serine carboxypeptidase genes exhibiting pronounced seed-specific differential regulation in low (Sonasal) and high (IR 64) grain weight mapping parental accessions. Our genome-wide SSR marker resource (polymorphic within/between diverse cultivar groups) and integrated genomic strategy can efficiently scan functionally relevant potential molecular tags (markers, candidate genes and alleles) regulating complex agronomic traits (grain weight) and expedite marker-assisted genetic enhancement in rice. |
format | Online Article Text |
id | pubmed-5080349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-50803492016-11-10 An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice Daware, Anurag Das, Sweta Srivastava, Rishi Badoni, Saurabh Singh, Ashok K. Agarwal, Pinky Parida, Swarup K. Tyagi, Akhilesh K. Front Plant Sci Plant Science Development and use of genome-wide informative simple sequence repeat (SSR) markers and novel integrated genomic strategies are vital to drive genomics-assisted breeding applications and for efficient dissection of quantitative trait loci (QTLs) underlying complex traits in rice. The present study developed 6244 genome-wide informative SSR markers exhibiting in silico fragment length polymorphism based on repeat-unit variations among genomic sequences of 11 indica, japonica, aus, and wild rice accessions. These markers were mapped on diverse coding and non-coding sequence components of known cloned/candidate genes annotated from 12 chromosomes and revealed a much higher amplification (97%) and polymorphic potential (88%) along with wider genetic/functional diversity level (16–74% with a mean 53%) especially among accessions belonging to indica cultivar group, suggesting their utility in large-scale genomics-assisted breeding applications in rice. A high-density 3791 SSR markers-anchored genetic linkage map (IR 64 × Sonasal) spanning 2060 cM total map-length with an average inter-marker distance of 0.54 cM was generated. This reference genetic map identified six major genomic regions harboring robust QTLs (31% combined phenotypic variation explained with a 5.7–8.7 LOD) governing grain weight on six rice chromosomes. One strong grain weight major QTL region (OsqGW5.1) was narrowed-down by integrating traditional QTL mapping with high-resolution QTL region-specific integrated SSR and single nucleotide polymorphism markers-based QTL-seq analysis and differential expression profiling. This led us to delineate two natural allelic variants in two known cis-regulatory elements (RAV1AAT and CARGCW8GAT) of glycosyl hydrolase and serine carboxypeptidase genes exhibiting pronounced seed-specific differential regulation in low (Sonasal) and high (IR 64) grain weight mapping parental accessions. Our genome-wide SSR marker resource (polymorphic within/between diverse cultivar groups) and integrated genomic strategy can efficiently scan functionally relevant potential molecular tags (markers, candidate genes and alleles) regulating complex agronomic traits (grain weight) and expedite marker-assisted genetic enhancement in rice. Frontiers Media S.A. 2016-10-26 /pmc/articles/PMC5080349/ /pubmed/27833617 http://dx.doi.org/10.3389/fpls.2016.01535 Text en Copyright © 2016 Daware, Das, Srivastava, Badoni, Singh, Agarwal, Parida and Tyagi. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Daware, Anurag Das, Sweta Srivastava, Rishi Badoni, Saurabh Singh, Ashok K. Agarwal, Pinky Parida, Swarup K. Tyagi, Akhilesh K. An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice |
title | An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice |
title_full | An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice |
title_fullStr | An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice |
title_full_unstemmed | An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice |
title_short | An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice |
title_sort | efficient strategy combining ssr markers- and advanced qtl-seq-driven qtl mapping unravels candidate genes regulating grain weight in rice |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5080349/ https://www.ncbi.nlm.nih.gov/pubmed/27833617 http://dx.doi.org/10.3389/fpls.2016.01535 |
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