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全基因组标记效应异质性与冬大麦麦芽休眠的一个大效应位点相关。

Genome-wide marker effect heterogeneity is associated with a large effect dormancy locus in winter malting barley.

作者信息

Rooney Travis E, Kunze Karl H, Sorrells Mark E

机构信息

Plant Breeding and Genetics Section, School of Integrative Plant Sciences, Cornell Univ., Ithaca, NY, 14853, USA.

出版信息

Plant Genome. 2022 Dec;15(4):e20247. doi: 10.1002/tpg2.20247. Epub 2022 Aug 16.

DOI:10.1002/tpg2.20247
PMID:35971877
Abstract

Prediction of trait values in plant breeding populations typically relies on assumptions about marker effect homogeneity across populations. Evidence is presented for winter malting barley (Hordeum vulgare L.) germination traits that a single, causative, large-effect gene in the Seed dormancy 1 region on Chromosome 5H, HvAlaAT1 (Qsd1), leads to heterogeneous estimated marker effects genome wide between groups of otherwise related individuals carrying different Qsd1 alleles. This led to reduced prediction accuracy across alleles when a model was trained either on individuals carrying both alleles or one allele. Several genomic prediction models were tested to increase prediction accuracy within the Qsd1 allele groups. Small gains (5-12%) in prediction accuracy were realized using structured genomic best linear unbiased predictor models when information about the Qsd1 allele was used to stratify the population. We concluded that a single large-effect locus can lead to heterogeneous marker effects in the same breeding family. Variance partitioning based on large-effect loci can be used to inform best practices in designing genomic prediction models; however, there are likely few cases for which it may be practical to do this. For malting barley, if germination traits are highly associated with malting quality traits, then similar steps should be considered for malting quality trait prediction.

摘要

植物育种群体中性状值的预测通常依赖于关于群体间标记效应同质性的假设。有证据表明,对于冬性制麦大麦(Hordeum vulgare L.)的发芽性状,位于5H染色体种子休眠1区域的一个单一的、具有因果关系的、大效应基因HvAlaAT1(Qsd1),导致在携带不同Qsd1等位基因的其他相关个体组之间,全基因组估计的标记效应存在异质性。当模型在携带两个等位基因或一个等位基因的个体上进行训练时,这导致了等位基因间预测准确性的降低。测试了几种基因组预测模型,以提高Qsd1等位基因组内的预测准确性。当使用关于Qsd1等位基因的信息对群体进行分层时,使用结构化基因组最佳线性无偏预测模型可实现预测准确性的小幅提高(5%-12%)。我们得出结论,单个大效应基因座可导致同一育种家族中标记效应的异质性。基于大效应基因座的方差划分可用于为设计基因组预测模型提供最佳实践信息;然而,可能很少有实际可行的情况。对于制麦大麦,如果发芽性状与制麦品质性状高度相关,那么对于制麦品质性状预测应考虑类似步骤。

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