Brief Funct Genomics. 2020 Jul 29;19(4):243-258. doi: 10.1093/bfgp/elaa009.
Next generation sequencing (NGS) has revolutionised rare disease diagnostics. Concomitant with advancing technologies has been a rise in the number of new gene disorders discovered and diagnoses made for patients and their families. However, despite the trend towards whole exome and whole genome sequencing, diagnostic rates remain suboptimal. On average, only ~30% of patients receive a molecular diagnosis. National sequencing projects launched in the last 5 years are integrating clinical diagnostic testing with research avenues to widen the spectrum of known genetic disorders. Consequently, efforts to diagnose genetic disorders in a clinical setting are now often shared with efforts to prioritise candidate variants for the detection of new disease genes. Herein we discuss some of the biggest obstacles precluding molecular diagnosis and discovery of new gene disorders. We consider bioinformatic and analytical challenges faced when interpreting next generation sequencing data and showcase some of the newest tools available to mitigate these issues. We consider how incomplete penetrance, non-coding variation and structural variants are likely to impact diagnostic rates, and we further discuss methods for uplifting novel gene discovery by adopting a gene-to-patient-based approach.
下一代测序(NGS)彻底改变了罕见病的诊断。随着技术的不断进步,新发现的基因疾病数量以及对患者及其家属的诊断数量不断增加。然而,尽管全外显子组和全基因组测序的趋势不断发展,但诊断率仍不理想。平均而言,只有约 30%的患者接受了分子诊断。在过去 5 年中启动的国家测序项目将临床诊断测试与研究途径相结合,以扩大已知遗传疾病的范围。因此,在临床环境中诊断遗传疾病的努力现在通常与优先考虑候选变体以检测新疾病基因的努力共享。本文讨论了一些导致分子诊断和新基因疾病发现受阻的最大障碍。我们考虑了解读下一代测序数据时面临的生物信息学和分析挑战,并展示了一些可用的最新工具来减轻这些问题。我们考虑了不完全外显率、非编码变异和结构变异如何可能影响诊断率,我们还进一步讨论了通过采用基于基因到患者的方法来提升新基因发现的方法。