Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers.

Huge efforts have been invested in the last two decades to dissect the genetic bases of complex traits including yields of many crop plants, through quantitative trait locus (QTL) analyses. However, almost all the studies were based on linkage maps constructed using low-throughput molecular markers,...

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Main Authors: Huihui Yu, Weibo Xie, Jia Wang, Yongzhong Xing, Caiguo Xu, Xianghua Li, Jinghua Xiao, Qifa Zhang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3048400?pdf=render
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author Huihui Yu
Weibo Xie
Jia Wang
Yongzhong Xing
Caiguo Xu
Xianghua Li
Jinghua Xiao
Qifa Zhang
author_facet Huihui Yu
Weibo Xie
Jia Wang
Yongzhong Xing
Caiguo Xu
Xianghua Li
Jinghua Xiao
Qifa Zhang
author_sort Huihui Yu
collection DOAJ
description Huge efforts have been invested in the last two decades to dissect the genetic bases of complex traits including yields of many crop plants, through quantitative trait locus (QTL) analyses. However, almost all the studies were based on linkage maps constructed using low-throughput molecular markers, e.g. restriction fragment length polymorphisms (RFLPs) and simple sequence repeats (SSRs), thus are mostly of low density and not able to provide precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, we constructed an ultra-high density genetic map based on high quality single nucleotide polymorphisms (SNPs) from low-coverage sequences of a recombinant inbred line (RIL) population of rice, generated using new sequencing technology. The quality of the map was assessed by validating the positions of several cloned genes including GS3 and GW5/qSW5, two major QTLs for grain length and grain width respectively, and OsC1, a qualitative trait locus for pigmentation. In all the cases the loci could be precisely resolved to the bins where the genes are located, indicating high quality and accuracy of the map. The SNP map was used to perform QTL analysis for yield and three yield-component traits, number of tillers per plant, number of grains per panicle and grain weight, using data from field trials conducted over years, in comparison to QTL mapping based on RFLPs/SSRs. The SNP map detected more QTLs especially for grain weight, with precise map locations, demonstrating advantages in detecting power and resolution relative to the RFLP/SSR map. Thus this study provided an example for ultra-high density map construction using sequencing technology. Moreover, the results obtained are helpful for understanding the genetic bases of the yield traits and for fine mapping and cloning of QTLs.
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spelling doaj.art-14e8bd8fc342487b9d177f17394e76d72022-12-22T03:10:49ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-0163e1759510.1371/journal.pone.0017595Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers.Huihui YuWeibo XieJia WangYongzhong XingCaiguo XuXianghua LiJinghua XiaoQifa ZhangHuge efforts have been invested in the last two decades to dissect the genetic bases of complex traits including yields of many crop plants, through quantitative trait locus (QTL) analyses. However, almost all the studies were based on linkage maps constructed using low-throughput molecular markers, e.g. restriction fragment length polymorphisms (RFLPs) and simple sequence repeats (SSRs), thus are mostly of low density and not able to provide precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, we constructed an ultra-high density genetic map based on high quality single nucleotide polymorphisms (SNPs) from low-coverage sequences of a recombinant inbred line (RIL) population of rice, generated using new sequencing technology. The quality of the map was assessed by validating the positions of several cloned genes including GS3 and GW5/qSW5, two major QTLs for grain length and grain width respectively, and OsC1, a qualitative trait locus for pigmentation. In all the cases the loci could be precisely resolved to the bins where the genes are located, indicating high quality and accuracy of the map. The SNP map was used to perform QTL analysis for yield and three yield-component traits, number of tillers per plant, number of grains per panicle and grain weight, using data from field trials conducted over years, in comparison to QTL mapping based on RFLPs/SSRs. The SNP map detected more QTLs especially for grain weight, with precise map locations, demonstrating advantages in detecting power and resolution relative to the RFLP/SSR map. Thus this study provided an example for ultra-high density map construction using sequencing technology. Moreover, the results obtained are helpful for understanding the genetic bases of the yield traits and for fine mapping and cloning of QTLs.http://europepmc.org/articles/PMC3048400?pdf=render
spellingShingle Huihui Yu
Weibo Xie
Jia Wang
Yongzhong Xing
Caiguo Xu
Xianghua Li
Jinghua Xiao
Qifa Zhang
Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers.
PLoS ONE
title Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers.
title_full Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers.
title_fullStr Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers.
title_full_unstemmed Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers.
title_short Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers.
title_sort gains in qtl detection using an ultra high density snp map based on population sequencing relative to traditional rflp ssr markers
url http://europepmc.org/articles/PMC3048400?pdf=render
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