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对具有重复基因组障碍缺失的个体基因组进行测序:一种用于描述常染色体隐性罕见疾病特征的基因的方法。

Sequencing individual genomes with recurrent genomic disorder deletions: an approach to characterize genes for autosomal recessive rare disease traits.

机构信息

Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA.

Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.

出版信息

Genome Med. 2022 Sep 30;14(1):113. doi: 10.1186/s13073-022-01113-y.

Abstract

BACKGROUND

In medical genetics, discovery and characterization of disease trait contributory genes and alleles depends on genetic reasoning, study design, and patient ascertainment; we suggest a segmental haploid genetics approach to enhance gene discovery and molecular diagnostics.

METHODS

We constructed a genome-wide map for nonallelic homologous recombination (NAHR)-mediated recurrent genomic deletions and used this map to estimate population frequencies of NAHR deletions based on large-scale population cohorts and region-specific studies. We calculated recessive disease carrier burden using high-quality pathogenic or likely pathogenic variants from ClinVar and gnomAD. We developed a NIRD (NAHR deletion Impact to Recessive Disease) score for recessive disorders by quantifying the contribution of NAHR deletion to the overall allele load that enumerated all pairwise combinations of disease-causing alleles; we used a Punnett square approach based on an assumption of random mating. Literature mining was conducted to identify all reported patients with defects in a gene with a high NIRD score; meta-analysis was performed on these patients to estimate the representation of NAHR deletions in recessive traits from contemporary human genomics studies. Retrospective analyses of extant clinical exome sequencing (cES) were performed for novel rare recessive disease trait gene and allele discovery from individuals with NAHR deletions.

RESULTS

We present novel genomic insights regarding the genome-wide impact of NAHR recurrent segmental variants on recessive disease burden; we demonstrate the utility of NAHR recurrent deletions to enhance discovery in the challenging context of autosomal recessive (AR) traits and biallelic variation. Computational results demonstrate new mutations mediated by NAHR, involving recurrent deletions at 30 genomic regions, likely drive recessive disease burden for over 74% of loci within these segmental deletions or at least 2% of loci genome-wide. Meta-analyses on 170 literature-reported patients implicate that NAHR deletions are depleted from the ascertained pool of AR trait alleles. Exome reanalysis of personal genomes from subjects harboring recurrent deletions uncovered new disease-contributing variants in genes including COX10, ERCC6, PRRT2, and OTUD7A.

CONCLUSIONS

Our results demonstrate that genomic sequencing of personal genomes with NAHR deletions could dramatically improve allele and gene discovery and enhance clinical molecular diagnosis. Moreover, results suggest NAHR events could potentially enable human haploid genetic screens as an approach to experimental inquiry into disease biology.

摘要

背景

在医学遗传学中,疾病特征基因和等位基因的发现和特征取决于遗传推理、研究设计和患者确定;我们建议采用片段单倍型遗传学方法来增强基因发现和分子诊断。

方法

我们构建了一个用于非等位同源重组(NAHR)介导的复发性基因组缺失的全基因组图谱,并使用该图谱基于大规模人群队列和特定区域的研究来估计 NAHR 缺失的人群频率。我们使用 ClinVar 和 gnomAD 中的高质量致病性或可能致病性变体计算隐性疾病携带者负担。我们通过量化 NAHR 缺失对枚举所有致病等位基因对的总体等位基因负荷的贡献,为隐性疾病开发了 NIRD(NAHR 缺失对隐性疾病的影响)评分;我们使用基于随机交配假设的 Punnett 方格方法。进行文献挖掘以确定具有高 NIRD 评分的基因中所有报道的患者;对这些患者进行荟萃分析,以从当代人类基因组学研究中估计隐性性状中 NAHR 缺失的代表性。对存在的临床外显子组测序 (cES) 进行回顾性分析,以从具有 NAHR 缺失的个体中发现新的罕见隐性疾病性状基因和等位基因。

结果

我们提供了关于 NAHR 复发性片段变体对隐性疾病负担的全基因组影响的新的基因组见解;我们证明了 NAHR 复发性缺失在常染色体隐性 (AR) 性状和双等位基因变异的具有挑战性的情况下增强发现的实用性。计算结果表明,涉及 30 个基因组区域的 NAHR 介导的新突变,可能导致这些片段缺失内超过 74%的基因座或至少 2%的基因座内的隐性疾病负担。对 170 篇文献报道的患者的荟萃分析表明,NAHR 缺失从 AR 性状等位基因的确定池中被耗尽。对携带复发性缺失的个体的个人基因组进行外显子重新分析,发现了 COX10、ERCC6、PRRT2 和 OTUD7A 等基因中的新疾病贡献变体。

结论

我们的结果表明,对具有 NAHR 缺失的个人基因组进行基因组测序可以极大地改善等位基因和基因发现,并增强临床分子诊断。此外,结果表明,NAHR 事件可能能够使人类单倍体遗传筛选成为一种疾病生物学实验研究的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9508/9526336/2ae5b3805c00/13073_2022_1113_Fig1_HTML.jpg

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