Discovering Splicing Defects in Human Genes

目前，小型研究小组对单个基因组进行测序是可行的，而对较大的研究小组则是可行的 对数以万计的个体进行排序。不幸的是，我们辨认的能力 影响表型的变异没有跟上我们的测序能力。这是 对于非编码变体尤其如此。这项提案展示了4972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。初步研究还显示， 剪接突变并不均匀地分布在疾病基因上。初步结果 确定疾病明显更有可能是由剪接突变引起的。这项建议 将利用报告系统测试替换和插入/缺失对剪接的影响，并 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“可作用基因”的剪接点的75个核苷酸范围内的变异。这个 这项研究将利用反映不同起源组织的各种细胞系，并确定哪些 剪接体组装的阶段被破坏，以提供对这些变体的更好的特征。 最后，盖辛格医疗系统GHS与Regeneron(RGN)合作 制药公司已经创建了配对的基因和表型数据的独特数据集。这个 GHS MyCode项目已招募了超过16万名患者，并完成了整个外显子组 对其中60,000多个患者样本进行测序(WES)。此集合将用于识别 (和验证)变异的携带者预测会改变剪接。对患者进行深入的重新表型分析 评估剪接缺陷对EHR QTL、发病年龄、严重程度、外显性和 跨多个器官系统的不同参与)。

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).