Functional characterization of prostate cancer risk loci by high throughput sequencing

摘要 尽管人类癌症的原因有许多因素，但有大量证据表明 遗传学可能起着关键作用。以前的研究使用了基于群体的方法，例如基因组- 广谱关联研究(GWAS)，以确定癌症相关遗传易感变异(单核苷酸 人类基因组中的SNPs)。尽管GWAS报告了数千个SNP基因座 与癌症风险增加相关，这些风险-SNP的功能效应在很大程度上仍不清楚。因为 许多Risk-SNPs位于没有已知蛋白质编码基因的基因组区域，有些位于 几百个碱基对，人们相信这些SNP中的许多，如果不是大多数的话，都有 对导致这些癌症的基因的调控作用。确定导致这种疾病的调节性SNPs 风险，我们建议应用两种新的高通量测序技术来筛选数千个候选 前列腺癌高危基因的SNPs。目的1是确定SNP依赖的转录因子(TF)的结合 前列腺癌风险基因通过IP-SNPs-seq的差异目标2是确定其生物学意义。 通过CRISPRi-SNPs-seq.目标3是 从功能上表征一组选定的SNPs及其目标基因。圆满完成拟议中的 研究将进一步了解GWAS相关的SNPs的功能作用。刻画人物形象 癌症风险基因座的功能效应将有助于将基于人群的发现转化为生物学 机制，并最终将有益于临床实践。

SUMMARY Although the causes of human cancers are attributable to many factors, there is substantial evidence that genetics likely plays a key role. Previous studies have used population-based approaches, such as genome- wide association studies (GWASs), to identify cancer-associated genetic susceptibility variants (single nucleotide polymorphisms or SNPs) in the human genome. Although GWASs have reported thousands of SNP loci associated with an increased cancer risk, functional effects of these risk-SNPs remain largely unknown. Because many of the risk-SNPs are located in genomic regions without known protein-coding genes and some reside several hundred kilobases from any nearby gene, it is believed that many, if not most, of these SNPs have regulatory effects on the genes that cause these cancers. To identify regulatory SNPs responsible for the disease risk, we propose to apply two novel high-throughput sequencing technologies to screen thousands of candidate SNPs at prostate cancer risk loci. Aim 1 is to determine SNP-dependent transcription factor (TF) binding differences at prostate cancer risk loci through IP-SNPs-seq. Aim 2 is to determine biological significance of SNP-dependent sequence variants at prostate cancer risk loci through CRISPRi-SNPs-seq. Aim 3 is to functionally characterize a set of selected SNPs and their target genes. Successful completion of the proposed study will gain further understanding of the functional role of GWAS-implicated SNPs. Characterization of the functional effects of cancer risk loci will facilitate the translation of population-based discovery into biological mechanisms and will eventually benefit clinical practice.