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通过选择性重组基因分型对数量性状基因座进行高分辨率定位。

High-resolution mapping of quantitative trait loci by selective recombinant genotyping.

作者信息

Ronin Y, Korol A, Shtemberg M, Nevo E, Soller M

机构信息

Institute of Evolution, University of Haifa, Mount Carmel, 31095 Haifa, Israel.

出版信息

Genetics. 2003 Aug;164(4):1657-66. doi: 10.1093/genetics/164.4.1657.

Abstract

Selective recombinant genotyping (SRG) is a three-stage procedure for high-resolution mapping of a QTL that has previously been mapped to a known confidence interval (target C.I.). In stage 1, a large mapping population is accessed and phenotyped, and a proportion, P, of the high and low tails is selected. In stage 2, the selected individuals are genotyped for a pair of markers flanking the target C.I., and a group of R individuals carrying recombinant chromosomes in the target interval are identified. In stage 3, the recombinant individuals are genotyped for a set of M markers spanning the target C.I. Extensive simulations showed that: (1) Standard error of QTL location (SEQTL) decreased when QTL effect (d) or population size (N) increased, but was constant for given "power factor" (PF = d(2)N); (2) increasing the proportion selected in the tails beyond 0.25 had only a negligible effect on SEQTL; and (3) marker spacing in the target interval had a remarkably powerful effect on SEQTL, yielding a reduction of up to 10-fold in going from highest (24 cM) to lowest (0.29 cM) spacing at given population size and QTL effect. At the densest marker spacing, SEQTL of 1.0-0.06 cM were obtained at PF = 500-16,000. Two new genotyping procedures, the half-section algorithm and the golden section/half-section algorithm, allow the equivalent of complete haplotyping of the target C.I. in the recombinant individuals to be achieved with many fewer data points than would be required by complete individual genotyping.

摘要

选择性重组基因分型(SRG)是一种用于对先前已定位到已知置信区间(目标置信区间)的数量性状基因座(QTL)进行高分辨率定位的三阶段程序。在第一阶段,获取一个大型作图群体并进行表型分析,然后从高值和低值尾部中选择比例为P的个体。在第二阶段,对目标置信区间两侧的一对标记进行所选个体的基因分型,并识别出一组在目标区间携带重组染色体的R个个体。在第三阶段,对跨越目标置信区间的一组M个标记进行重组个体的基因分型。广泛的模拟表明:(1)当QTL效应(d)或群体大小(N)增加时,QTL定位的标准误差(SEQTL)会降低,但对于给定的“功率因子”(PF = d²N)则保持不变;(2)将尾部选择的比例增加到超过0.25对SEQTL的影响可忽略不计;(3)目标区间内的标记间距对SEQTL有显著强大的影响,在给定群体大小和QTL效应的情况下,从最高间距(24 cM)到最低间距(0.29 cM),SEQTL可降低多达10倍。在最密集的标记间距下,当PF = 500 - 16,000时,SEQTL为1.0 - 0.06 cM。两种新的基因分型程序,即半段算法和黄金分割/半段算法,允许在重组个体中实现目标置信区间的等效完整单倍型分型,所需的数据点比完整个体基因分型所需的数据点少得多。

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