Efficiency of low heritability QTL mapping under high SNP density

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• 作者：José Marcelo Soriano Viana ; Fabyano Fonseca e Silva ; Gabriel Borges Mundim…
• 关键词：F2 design ; Power of QTL detection ; False discovery rate ; Bias in QTL position
• 刊名：Euphytica
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：213
• 期：1
• 全文大小：
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Plant Sciences; Plant Genetics & Genomics; Plant Pathology; Plant Physiology; Biotechnology;
• 出版者：Springer Netherlands
• ISSN：1573-5060
• 卷排序：213

文摘

The efficiency of quantitative trait locus (QTL) mapping methods needs to be investigated assuming high single nucleotide polymorphism (SNP) density and low heritability QTLs. This study assessed the efficiency of the least squares, maximum likelihood, and Bayesian approaches for QTL mapping assuming high SNP density and low heritability QTLs. We simulated 50 samples of 400 F₂ individuals, which were genotyped for 1000 SNPs (average density of one SNP/centiMorgan) and phenotyped for three traits controlled by 12 QTLs and 88 minor genes. The genes were randomly distributed in the regions covered by the SNPs along ten chromosomes. The QTL heritabilities ranged from approximately 1–2% and the sample sizes were 200 and 400. The power of QTL detection ranged from 30 to 60%, the false discovery rate (FDR) ranged from only 0.5–1.2%, and the bias in the QTL position ranged from 4 to 6 cM. The QTL mapping efficiency was not influenced by the degree of dominance. The statistical approaches were comparable regarding the FDR. Regression-based and simple interval mapping methods showed equivalent power of QTL detection and mapping precision. Compared to interval mapping, the inclusive composite interval mapping provided slightly greater QTL detection power and mapping precision only for the intermediate and high heritability QTLs. By maximizing the prior number of QTLs, the Bayesian analysis provided the greatest power of QTL detection. No method proved to be superior.