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新方法实现种群尺度结构变异比较与分析
作者:小柯机器人 发布时间:2023/1/29 12:13:23

近日,美国约翰霍普金斯大学Michael C. Schatz等研究人员合作实现种群尺度结构变异比较与分析。该研究于2023年1月19日在线发表于国际一流学术期刊《自然—方法学》。

研究人员表示,长读的可用性正在彻底改变结构变异(SV)的研究。然而,由于SV因人而异,并且是通过不精确的读取技术和方法发现的,因此很难进行比较。

为了解决这个问题,该课题组研究人员提供了Jasmine和Iris(https://github.com/mkirsche/Jasmine/),用于快速准确的SV优化,并比较和总体分析。使用SV接近图,Jasmine优于六种广泛的比较方法,包括将三个数据集中的孟德尔不一致性率降低了五倍以上,并揭示了一组由多种技术确认的高置信度的新SV。研究人员还提出了来自31个不同血统的长读序列样本的122813个SV和82379个indel的统一调用集。研究人员人员用DNA和RNA测序数据对来自千人基因组计划和基因型-组织表达项目的1317个样本进行基因分型,并评估了它们对基因表达的广泛影响,包括在医学相关基因中。

附:英文原文

Title: Jasmine and Iris: population-scale structural variant comparison and analysis

Author: Kirsche, Melanie, Prabhu, Gautam, Sherman, Rachel, Ni, Bohan, Battle, Alexis, Aganezov, Sergey, Schatz, Michael C.

Issue&Volume: 2023-01-19

Abstract: The availability of long reads is revolutionizing studies of structural variants (SVs). However, because SVs vary across individuals and are discovered through imprecise read technologies and methods, they can be difficult to compare. Addressing this, we present Jasmine and Iris (https://github.com/mkirsche/Jasmine/), for fast and accurate SV refinement, comparison and population analysis. Using an SV proximity graph, Jasmine outperforms six widely used comparison methods, including reducing the rate of Mendelian discordance in trio datasets by more than fivefold, and reveals a set of high-confidence de novo SVs confirmed by multiple technologies. We also present a unified callset of 122,813 SVs and 82,379 indels from 31 samples of diverse ancestry sequenced with long reads. We genotype these variants in 1,317 samples from the 1000 Genomes Project and the Genotype-Tissue Expression project with DNA and RNA-sequencing data and assess their widespread impact on gene expression, including within medically relevant genes.

DOI: 10.1038/s41592-022-01753-3

Source: https://www.nature.com/articles/s41592-022-01753-3

期刊信息

Nature Methods:《自然—方法学》,创刊于2004年。隶属于施普林格·自然出版集团,最新IF:47.99
官方网址:https://www.nature.com/nmeth/
投稿链接:https://mts-nmeth.nature.com/cgi-bin/main.plex

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