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利用分子标记估计数量性状基因座参数:非重复和重复后代的功效及遗传方差

Using molecular markers to estimate quantitative trait locus parameters: power and genetic variances for unreplicated and replicated progeny.

作者信息

Knapp S J, Bridges W C

机构信息

Department of Crop Science, Oregon State University, Corvallis 97731.

出版信息

Genetics. 1990 Nov;126(3):769-77. doi: 10.1093/genetics/126.3.769.

DOI:10.1093/genetics/126.3.769
PMID:2249768
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC1204230/
Abstract

Many of the progeny types used to estimate quantitative trait locus (QTL) parameters can be replicated, e.g., recombinant inbred, doubled haploid, and F3 lines. These parameters are estimated using molecular markers or QTL genotypes estimated from molecular markers as independent variables. Experiment designs for replicated progeny are functions of the number of replications per line (r) and the number of replications per QTL genotype (n). The value of n is determined by the size of the progeny population (N), the progeny type, and the number of simultaneously estimated QTL parameters (q - 1). Power for testing hypotheses about means of QTL genotypes is increased by increasing r and n, but the effects of these factors have not been quantified. In this paper, we describe how power is affected by r, n, and other factors. The genetic variance between lines nested in QTL genotypes (sigma 2n:q) is the fraction of the genetic variance between lines (sigma 2n) which is not explained by simultaneously estimated intralocus and interlocus QTL parameters (phi 2Q); thus, sigma 2n:q = sigma 2n - phi 2Q. If sigma 2n:q not equal to 0, then power is not efficiently increased by increasing r and is maximized by maximizing n and using r = 1; however, if sigma 2n:q = 0, then r and n affect power equally and power is efficiently increased by increasing r and is maximized by maximizing N.r. Increasing n efficiently increases power for a wide range of values of sigma 2n:q.sigma 2n:q = 0 when the genetic variance between lines is fully explained by QTL parameters (sigma 2n = phi 2Q).(ABSTRACT TRUNCATED AT 250 WORDS)

摘要

许多用于估计数量性状基因座(QTL)参数的后代类型都可以重复,例如重组近交系、双单倍体和F3代系。这些参数是使用分子标记或根据分子标记估计的QTL基因型作为自变量来估计的。重复后代的实验设计是每行重复次数(r)和每个QTL基因型重复次数(n)的函数。n的值由后代群体大小(N)、后代类型以及同时估计的QTL参数数量(q - 1)决定。通过增加r和n,可以提高检验QTL基因型均值假设的功效,但这些因素的影响尚未量化。在本文中,我们描述了功效是如何受到r、n和其他因素影响的。嵌套在QTL基因型中的品系间遗传方差(sigma 2n:q)是品系间遗传方差(sigma 2n)中未被同时估计的基因座内和基因座间QTL参数(phi 2Q)解释的部分;因此,sigma 2n:q = sigma 2n - phi 2Q。如果sigma 2n:q不等于0,那么增加r并不能有效提高功效,通过最大化n并使用r = 1可使功效最大化;然而,如果sigma 2n:q = 0,那么r和n对功效的影响相同,通过增加r可有效提高功效,通过最大化N.r可使功效最大化。对于广泛的sigma 2n:q值范围,增加n能有效提高功效。当品系间遗传方差完全由QTL参数解释时(sigma 2n = phi 2Q),sigma 2n:q = 0。(摘要截短于250字)

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