遗传学
生物
索引
杂交基因组组装
DNA测序
深度测序
INDEL突变
基因组
基因组学
参考基因组
纳米孔测序
顺序装配
计算生物学
Illumina染料测序
生殖系
全基因组测序
结构变异
作者
Michelle D Noyes,William T Harvey,David Porubsky,Arvis Sulovari,Ruiyang Li,Nicholas R Rose,Peter A Audano,Katherine M Munson,Alexandra P Lewis,Kendra Hoekzema,Tuomo Mantere,Tina A Graves-Lindsay,Ashley D Sanders,Sara Goodwin,Melissa Kramer,Younes Mokrab,Michael C Zody,Alexander Hoischen,Jan O Korbel,W Richard McCombie,Evan E Eichler
标识
DOI:10.1016/j.ajhg.2022.02.014
摘要
Summary
Studies of de novo mutation (DNM) have typically excluded some of the most repetitive and complex regions of the genome because these regions cannot be unambiguously mapped with short-read sequencing data. To better understand the genome-wide pattern of DNM, we generated long-read sequence data from an autism parent-child quad with an affected female where no pathogenic variant had been discovered in short-read Illumina sequence data. We deeply sequenced all four individuals by using three sequencing platforms (Illumina, Oxford Nanopore, and Pacific Biosciences) and three complementary technologies (Strand-seq, optical mapping, and 10X Genomics). Using long-read sequencing, we initially discovered and validated 171 DNMs across two children—a 20% increase in the number of de novo single-nucleotide variants (SNVs) and indels when compared to short-read callsets. The number of DNMs further increased by 5% when considering a more complete human reference (T2T-CHM13) because of the recovery of events in regions absent from GRCh38 (e.g., three DNMs in heterochromatic satellites). In total, we validated 195 de novo germline mutations and 23 potential post-zygotic mosaic mutations across both children; the overall true substitution rate based on this integrated callset is at least 1.41 × 10−8 substitutions per nucleotide per generation. We also identified six de novo insertions and deletions in tandem repeats, two of which represent structural variants. We demonstrate that long-read sequencing and assembly, especially when combined with a more complete reference genome, increases the number of DNMs by >25% compared to previous studies, providing a more complete catalog of DNM compared to short-read data alone.
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