Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis

Abstract For a better interpretation of variants, evidence-based databases, such as ClinVar, compile data on the presumed relationships between variants and phenotypes. In this study, we aimed to analyze the pattern of sequencing depth in variants from whole-exome sequencing data in the 1000 Genomes project phase 3, focusing on the variants present in the ClinVar database that were predicted to affect protein-coding regions. We demonstrate that the distribution of the sequencing depth varies across different sequencing centers (pair-wise comparison, p < 0.001). Most importantly, we found that the distribution pattern of sequencing depth is specific to each facility, making it possible to correctly assign 96.9% of the samples to their sequencing center. Thus, indicating the presence of a systematic bias, related to the methods used in the different facilities, which generates significant variations in breadth and depth in whole-exome sequencing data in clinically relevant regions. Our results show that methodological differences, leading to significant heterogeneity in sequencing depth, may potentially influence the accuracy of genetic diagnosis. Furthermore, our findings highlight how it is still challenging to integrate results from different sequencing centers, which may also have an impact on genomic research.

摘要：为更好地解读遗传变异，ClinVar等循证数据库会汇编变异与表型（phenotype）间假定关联的相关数据。本研究旨在分析千人基因组计划第三阶段（1000 Genomes Project Phase 3）全外显子组测序（whole-exome sequencing）数据中变异的测序深度（sequencing depth）分布模式，重点关注ClinVar数据库中被预测会对蛋白质编码区（protein-coding regions）造成影响的变异。研究表明，不同测序中心的测序深度分布存在显著差异（两两比较，p < 0.001）。尤为关键的是，测序深度的分布模式具有测序中心特异性，据此可将96.9%的样本准确归属至其对应的测序中心。这表明不同测序中心所采用的实验方法存在系统性偏差（systematic bias），该偏差会导致临床相关区域的全外显子组测序数据在覆盖广度与深度上出现显著异质性（heterogeneity）。本研究结果显示，方法学差异引发的测序深度异质性，可能会对遗传诊断（genetic diagnosis）的准确性造成潜在影响。此外，研究结果还凸显出整合不同测序中心的测序结果仍颇具挑战，这一问题同样会对基因组研究（genomic research）产生影响。