Mapping Quantitative Trait Loci Associated with Toot Traits Using Sequencing-Based Genotyping Chromosome Segment Substitution Lines Derived from 9311 and Nipponbare in Rice (Oryza sativa L.).
Mapping Quantitative Trait Loci Associated with Toot Traits Using Sequencing-Based Genotyping Chromosome Segment Substitution Lines Derived from 9311 and Nipponbare in Rice (Oryza sativa L.).
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使用源自水稻 (Oryza sativa L.) 9311 和日本晴的基于测序的基因分型染色体片段替换系绘制与嘟嘟性状相关的数量性状基因座
DOI：
10.1371/journal.pone.0151796
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Wang Y
中科院分区：
文献类型：
--
作者：
Zhou Y;Dong G;Tao Y;Chen C;Yang B;Wu Y;Yang Z;Liang G;Wang B;Wang Y
水稻根系形态相关的数量性状位点（qtl）的鉴定为灌溉条件下水稻避免干旱胁迫和保持产量提供了有用的信息。本研究以9311为受体，Nipponbare为供体的一组染色体片段代换系对根形态进行了分析。采用基于重测序的bin-map与多元线性回归分析相结合的方法，对水培条件下生长的CSSL群体进行了根数（RN）、总根长（TRL）、根干重（RDW）、最大根长（MRL）、根粗（RTH）、总吸收面积（TAA）和根系活力（RV）的QTL鉴定。共鉴定出38个qtl: TRL 6个，RDW 6个，MRL 8个，RTH 4个，RN 7个，TAA 2个，RV 5个。这些qtl的表型效应解释方差范围为2.23% ~ 37.08%，其中4个qtl对3个根系性状的表型解释均在10%以上。我们还检测了籽粒产量与根系性状之间的相关关系，发现TRL、RTH和MRL与籽粒产量呈显著正相关。TRL、RDW和MRL与生物量产量（BY）呈极显著正相关。在我们的群体中发现的几个qtl与粮食产量或生物量的一些位点共定位。这些信息可立即用于提高水稻水肥利用效率和根系构型分子育种。
Identification of quantitative trait loci (QTLs) associated with rice root morphology provides useful information for avoiding drought stress and maintaining yield production under the irrigation condition. In this study, a set of chromosome segment substitution lines derived from 9311 as the recipient and Nipponbare as donor, were used to analysis root morphology. By combining the resequencing-based bin-map with a multiple linear regression analysis, QTL identification was conducted on root number (RN), total root length (TRL), root dry weight (RDW), maximum root length (MRL), root thickness (RTH), total absorption area (TAA) and root vitality (RV), using the CSSL population grown under hydroponic conditions. A total of thirty-eight QTLs were identified: six for TRL, six for RDW, eight for the MRL, four for RTH, seven for RN, two for TAA, and five for RV. Phenotypic effect variance explained by these QTLs ranged from 2.23% to 37.08%, and four single QTLs had more than 10% phenotypic explanations on three root traits. We also detected the correlations between grain yield (GY) and root traits, and found that TRL, RTH and MRL had significantly positive correlations with GY. However, TRL, RDW and MRL had significantly positive correlations with biomass yield (BY). Several QTLs identified in our population were co-localized with some loci for grain yield or biomass. This information may be immediately exploited for improving rice water and fertilizer use efficiency for molecular breeding of root system architectures.