PDF(Pubmed)
Abstract：
Pre-messenger RNA splicing is initiated with the recognition of a single-nucleotide intronic branchpoint (BP) within a BP motif by spliceosome elements. Forty-eight rare variants in 43 human genes have been reported to alter splicing and cause disease by disrupting BP. However, until now, no computational approach was available to efficiently detect such variants in massively parallel sequencing data. We established a comprehensive human genome-wide BP database by integrating existing BP data and generating new BP data from RNA sequencing of lariat debranching enzyme DBR1-mutated patients and from machine-learning predictions. We characterized multiple features of BP in major and minor introns and found that BP and BP-2 (two nucleotides upstream of BP) positions exhibit a lower rate of variation in human populations and higher evolutionary conservation than the intronic background, while being comparable to the exonic background. We developed BPHunter as a genome-wide computational approach to systematically and efficiently detect intronic variants that may disrupt BP recognition. BPHunter retrospectively identified 40 of the 48 known pathogenic BP variants, in which we summarized a strategy for prioritizing BP variant candidates. The remaining eight variants all create AG-dinucleotides between the BP and acceptor site, which is the likely reason for missplicing. We demonstrated the practical utility of BPHunter prospectively by using it to identify a novel germline heterozygous BP variant of STAT2 in a patient with critical COVID-19 pneumonia and a novel somatic intronic 59-nucleotide deletion of ITPKB in a lymphoma patient, both of which were validated experimentally. BPHunter is publicly available from https://hgidsoft.rockefeller.edu/BPHunter and https://github.com/casanova-lab/BPHunter.
摘要：
前信使RNA剪接是通过剪接体元件识别BP基序内的单核苷酸内含子分支点（BP）而启动的。据报道，43个人类基因中的48个罕见变体通过破坏BP来改变剪接并导致疾病。然而,直到现在,在大规模平行测序数据中,没有可用的计算方法来有效检测此类变异.我们通过整合现有的BP数据，并从套索脱支酶DBR1突变患者的RNA测序和机器学习预测中生成新的BP数据，建立了一个全面的全人类基因组BP数据库。我们对主要和次要内含子中BP的多个特征进行了表征，发现BP和BP-2（BP上游的两个核苷酸）位置表现出比内含子背景更低的人类种群变异率和更高的进化保守性。同时与异质背景相媲美。我们开发了BPHunter作为一种全基因组计算方法，以系统有效地检测可能破坏BP识别的内含子变体。BPHunter回顾性鉴定了48种已知致病性BP变异中的40种，其中我们总结了优先考虑BP变异候选的策略.其余的八个变体都在BP和受体位点之间产生AG-二核苷酸，这可能是拼接错误的原因。我们通过使用BPHunter在患有严重COVID-19肺炎的患者中鉴定STAT2的新型种系杂合BP变体和在淋巴瘤患者中发现ITPKB的新型体细胞内含子59核苷酸缺失，从而前瞻性地证明了BPHunter的实际实用性。两者都经过实验验证。BPHunter可从https://hgidsoft公开获得。洛克菲勒.edu/BPHunter和https://github.com/casanova-lab/BPHunter。
