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Target Enrichment Improves Mapping of Complex Traits by Deep Sequencing

机译:目标富集通过深度测序改善了复杂性状的定位

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摘要

Complex traits such as crop performance and human diseases are controlled by multiple genetic loci, many of which have small effects and often go undetected by traditional quantitative trait locus (QTL) mapping. Recently, bulked segregant analysis with large F2 pools and genome-level markers (named extreme-QTL or X-QTL mapping) has been used to identify many QTL. To estimate parameters impacting QTL detection for X-QTL mapping, we simulated the effects of population size, marker density, and sequencing depth of markers on QTL detectability for traits with differing heritabilities. These simulations indicate that a high (>90%) chance of detecting QTL with at least 5% effect requires 5000× sequencing depth for a trait with heritability of 0.4−0.7. For most eukaryotic organisms, whole-genome sequencing at this depth is not economically feasible. Therefore, we tested and confirmed the feasibility of applying deep sequencing of target-enriched markers for X-QTL mapping. We used two traits in Arabidopsis thaliana with different heritabilities: seed size (H2 = 0.61) and seedling greening in response to salt (H2 = 0.94). We used a modified G test to identify QTL regions and developed a model-based statistical framework to resolve individual peaks by incorporating recombination rates. Multiple QTL were identified for both traits, including previously undiscovered QTL. We call our method target-enriched X-QTL (TEX-QTL) mapping; this mapping approach is not limited by the genome size or the availability of recombinant inbred populations and should be applicable to many organisms and traits.
机译:复杂的性状(如作物生长性能和人类疾病)受多个遗传基因座控制,其中许多基因座作用不大,而传统的数量性状基因座(QTL)作图通常无法检测到。最近,具有大量F2库和基因组水平标记物(称为Extreme-QTL或X-QTL定位图)的大量分离物分析已用于鉴定许多QTL。为了估计影响X-QTL定位的QTL检测的参数,我们模拟了种群大小,标记密度和标记测序深度对不同遗传性状QTL可检测性的影响。这些模拟表明,对于遗传力为0.4-0.7的性状,检测QTL至少有5%效果的可能性很高(> 90%),需要5000倍的测序深度。对于大多数真核生物,在此深度进行全基因组测序在经济上不可行。因此,我们测试并确认了对X-QTL定位应用富含靶标的标记进行深度测序的可行性。我们在拟南芥中使用了两个具有不同遗传力的性状:种子大小(H 2 = 0.61)和幼苗对盐的响应(H 2 = 0.94)。我们使用改良的G检验来识别QTL区域,并开发了基于模型的统计框架以通过合并重组率来解析单个峰。针对这两个性状都鉴定了多个QTL,包括以前未发现的QTL。我们称此方法为目标丰富的X-QTL(TEX-QTL)映射;这种定位方法不受基因组大小或重组近交种群可用性的限制,应适用于许多生物和性状。

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