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新方法实现对植物表型变化背后遗传变异的鉴定
作者:小柯机器人 发布时间:2020/4/16 11:58:06

德国马克斯-普朗克发育生物学研究所Detlef Weigel研究团队,通过不使用完整基因组实现对植物表型变化背后遗传变异的鉴定。相关论文于2020年4月13日在线发表于《自然—遗传学》。

研究人员扩展了在全基因组关联研究(GWAS)中检测到的遗传变异的类型,将主要的缺失、插入和重排包含其中。他们首先直接使用原始测序数据来推导短序列k-mers,这些短序列独立于参考基因组而标志着广泛的多态性。然后,他们将与表型相关的k-mers联系到特定的基因组区域。
 
使用这种方法,研究人员重新分析了拟南芥、番茄和玉米种群中的2,000个性状。用k-mers鉴定的关联概括了用SNP发现的关联,但具有更强的统计学支撑。重要的是,他们发现了与结构变异和参考基因组缺失区域的新关联。
 
这些结果证明了在将序列读数联系到特定基因组区域之前执行GWAS的效力,这使得可以检测到影响表型变化的大量遗传变异。
 
据了解,结构变异和存在/不存在多态性在植物基因组中很常见,但在GWAS中通常被忽略。
 
附:英文原文

Title: Identifying genetic variants underlying phenotypic variation in plants without complete genomes

Author: Yoav Voichek, Detlef Weigel

Issue&Volume: 2020-04-13

Abstract: Structural variants and presence/absence polymorphisms are common in plant genomes, yet they are routinely overlooked in genome-wide association studies (GWAS). Here, we expand the type of genetic variants detected in GWAS to include major deletions, insertions and rearrangements. We first use raw sequencing data directly to derive short sequences, k-mers, that mark a broad range of polymorphisms independently of a reference genome. We then link k-mers associated with phenotypes to specific genomic regions. Using this approach, we reanalyzed 2,000 traits in Arabidopsis thaliana, tomato and maize populations. Associations identified with k-mers recapitulate those found with SNPs, but with stronger statistical support. Importantly, we discovered new associations with structural variants and with regions missing from reference genomes. Our results demonstrate the power of performing GWAS before linking sequence reads to specific genomic regions, which allows the detection of a wider range of genetic variants responsible for phenotypic variation.

DOI: 10.1038/s41588-020-0612-7

Source: https://www.nature.com/articles/s41588-020-0612-7

期刊信息

Nature Genetics:《自然—遗传学》,创刊于1992年。隶属于施普林格·自然出版集团,最新IF:25.455
官方网址:https://www.nature.com/ng/
投稿链接:https://mts-ng.nature.com/cgi-bin/main.plex