Mapping proximal and distal splicing-regulatory elements

定位近端和远端剪接--调控元件 项目总结 前体mRNA的选择性剪接(AS)是一种允许单基因产生的分子机制 多种转录本和蛋白质异构体，是哺乳动物分子多样性的主要驱动力 包括人类。AS在时间和空间上受到严格调控，以确定蛋白质的类型和水平 在特定细胞环境中表达的产品。这样的监管是由许多拼接监管决定的 由RNA结合剪接因子识别的备选外显子或侧翼内含子中的元件(SRE)。 由SRE中断引起的异常剪接与越来越多的遗传性疾病有关 从神经疾病到癌症，以及人类群体中的表型变异。这一点反映在 最近的研究发现，剪接数量性状基因座(SQTL)与基因表达QTL一样普遍，它们 同样富含与全球遗传多样性研究组织确认的人类疾病相关的遗传变异。尽管 这一领域的显著进展，导致剪接干扰变异体的鉴定受到严重阻碍 由于人类基因组中缺乏全面的SRE注释，与类似的 转录或表观遗传调控元件。为了填补这一巨大的空白，这项研究提出了一种公正、 高通量筛选方法，以定位功能性SRE，包括主要位于远端区域的SRE 被目前的研究忽视了。如果成功，这一平台技术将促进基因组研究 社区研究基因表达调控，了解基因-表型关系，并解释 基因变异对人类疾病的影响。

Mapping proximal and distal splicing-regulatory elements PROJECT SUMMARY Alternative splicing (AS) of precursor mRNA is a molecular mechanism that allows single genes to generate multiple transcript and protein isoforms, providing a major driving force of molecular diversity in mammals including humans. AS is tightly regulated temporally and spatially to determine the types and level of protein products expressed in specific cellular contexts. Such regulation is dictated by numerous splicing-regulatory elements (SREs) in the alternative exon or flanking introns that are recognized by RNA-binding splicing factors. Aberrant splicing caused by disruption of SREs is implicated in an expanding list of genetic diseases ranging from neurological disorders to cancer, as well as phenotypic variation in human populations. This is reflected in recent findings that splicing quantitative trait loci (sQTLs) are as prevalent as gene expression QTLs, and they are similarly enriched in genetic variation associated with human diseases identified by GWAS. Despite the remarkable progress of the field, identification of causal splicing-disrupting variants has been severely impeded by the lack of comprehensive SRE annotations in the human genome, as compared to similar maps of transcriptional or epigenetic regulatory elements. To fill in this tremendous gap, this study proposes an unbiased, high-throughput screening approach to map functional SREs, including those in distal regions that are largely overlooked by current studies. If successful, this platform technology will facilitate the genomic research community to study gene expression regulation, understand genotype-phenotype relationships, and interpret the impact of genetic variation in human diseases.