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通过超深度全基因组测序,直接估计黑猩猩亲代-子代三人间的从头突变率。

Direct estimation of de novo mutation rates in a chimpanzee parent-offspring trio by ultra-deep whole genome sequencing.

机构信息

Department of Brain Sciences, Center for Novel Science Initiatives, National Institutes of Natural Sciences, Okazaki, Aichi, 444-8585, Japan.

Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Aichi, 444-8585, Japan.

出版信息

Sci Rep. 2017 Nov 1;7(1):13561. doi: 10.1038/s41598-017-13919-7.

DOI:10.1038/s41598-017-13919-7
PMID:29093469
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5666008/
Abstract

Mutations generate genetic variation and are a major driving force of evolution. Therefore, examining mutation rates and modes are essential for understanding the genetic basis of the physiology and evolution of organisms. Here, we aim to identify germline de novo mutations through the whole-genome surveyance of Mendelian inheritance error sites (MIEs), those not inherited through the Mendelian inheritance manner from either of the parents, using ultra-deep whole genome sequences (>150-fold) from a chimpanzee parent-offspring trio. We identified such 889 MIEs and classified them into four categories based on the pattern of inheritance and the sequence read depth: [i] de novo single nucleotide variants (SNVs), [ii] copy number neutral inherited variants, [iii] hemizygous deletion inherited variants, and [iv] de novo copy number variants (CNVs). From de novo SNV candidates, we estimated a germline de novo SNV mutation rate as 1.48 × 10 per site per generation or 0.62 × 10 per site per year. In summary, this study demonstrates the significance of ultra-deep whole genome sequencing not only for the direct estimation of mutation rates but also for discerning various mutation modes including de novo allelic conversion and de novo CNVs by identifying MIEs through the transmission of genomes from parents to offspring.

摘要

突变产生遗传变异,是进化的主要驱动力。因此,研究突变率和突变模式对于理解生物的生理和进化的遗传基础至关重要。在这里,我们旨在通过对孟德尔遗传错误位点(MIEs)的全基因组检测,从父本或母本一方未通过孟德尔遗传方式遗传的突变来识别生殖系新生突变。我们使用来自黑猩猩亲子三人组的超深度全基因组序列(>150 倍),鉴定了 889 个这样的 MIEs,并根据遗传模式和测序深度将其分为四类:[i]新生单核苷酸变异(SNV),[ii]拷贝数中性遗传变异,[iii]半合子缺失遗传变异,和 [iv]新生拷贝数变异(CNV)。从新生 SNV 候选者中,我们估计生殖系新生 SNV 突变率为每代每个位点 1.48×10 或每年每个位点 0.62×10。总之,这项研究表明,超深度全基因组测序不仅对于直接估计突变率具有重要意义,而且还可以通过从父母到后代的基因组传递来识别 MIEs,从而区分各种突变模式,包括新生等位基因转换和新生 CNV。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/d54aab3efdba/41598_2017_13919_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/89fc42cd2825/41598_2017_13919_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/9ef7238fa375/41598_2017_13919_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/685f25b3fa29/41598_2017_13919_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/001021b54a43/41598_2017_13919_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/d54aab3efdba/41598_2017_13919_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/89fc42cd2825/41598_2017_13919_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/9ef7238fa375/41598_2017_13919_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/685f25b3fa29/41598_2017_13919_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/001021b54a43/41598_2017_13919_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d6/5666008/d54aab3efdba/41598_2017_13919_Fig5_HTML.jpg

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