Discovering Splicing Defects in Human Genes

目前，小型研究小组可以对单个基因组进行测序， 对成千上万的个体进行测序。不幸的是，我们识别 影响表型的变异没有跟上我们的测序能力。这是 尤其是非编码变体。该提案提出了一项对4，972种疾病的试点筛查， 显示10%外显子突变的等位基因影响剪接。试点研究还显示， 剪接突变在疾病基因中的分布并不均匀。初步结果 确定了64种疾病，这些疾病更有可能是由剪接突变引起的。这项建议 将利用报告系统来测试置换和插入/缺失对剪接的影响， 注释医学相关基因中的剪接元件。通过这种方法创建的数据集 将用于训练在线剪接突变预测工具。该项目还将筛选所有 在130个“可操作基因”的集合中，位于剪接位点的75个核苷酸内的变体。的 研究将利用反映不同来源组织的多种细胞系，并确定 剪接体组装阶段被破坏以提供这些变体的更好表征。 最后，Geisinger HealthCare System GHS与Regeneron（RGN）合作 Pharmaceuticals创建了一个独特的配对基因型和表型数据集。的 GHS MyCode项目已招募超过16万名患者并完成了整个外显子组 测序（WES）对超过60，000例患者样本进行了检测。这一组将用于识别 (and验证）变异的携带者预测改变剪接。对患者进行深度的重新分型， 评估剪接缺陷对EHR QTL的贡献，发病年龄，严重程度， 跨多个器官系统的差异接合）。

It is currently feasible for small research groups to sequence individual genomes and for larger groups to sequence tens of thousands of individuals. Unfortunately, our ability to identify variants that impact phenotype has not kept pace with our sequencing capacity. This is particularly true of non-coding variants. This proposal presents a pilot screen of 4,972 disease alleles that revealed 10% of exonic mutations affect splicing. The pilot study also revealed that splicing mutations are not uniformly distributed across disease genes. Preliminary results identify 64 diseases significantly more likely to be caused by a splicing mutation. This proposal will utilize a reporter system to test the effect of substitutions and in/dels on splicing and to annotate splicing element in medically relevant genes. The data set created by this approach will be used to train an online splicing mutation prediction tool. This project will also screen all variants that fall within 75nucleotides of a splice site in the set of 130 “actionable genes”. The study will utilize a variety of cell lines reflecting distinct tissues of origin and determine which stage of spliceosome assembly is disrupted to provide better characterization of these variants. Finally, Geisinger HealthCare System GHS in partnership with Regeneron (RGN) Pharmaceuticals has created a unique dataset of paired genotypic and phenotypic data. The GHS MyCode project has enrolled over 160,000 patients and completed whole exome sequencing (WES) on over 60,000 of those patient samples. This set will be used to identify (and verify) carriers of variants predict to alter splicing. A deep re-phenotyping of patients to asses the contribution of splicing defects to EHR QTLs, age of onset, severity, penetrance and differential engagement across multiple organ systems).