颜林林 (2022-06-16 00:40):
#paper doi:10.1038/s41588-022-01075-2 Nature Genetics, 2022, Allelic imbalance of chromatin accessibility in cancer identifies candidate causal risk variants and their mechanisms. 这又是一篇只有两位作者署名的论文。如今,司空见惯了一篇文章动辄好几十位甚至成百上千位作者的情况,见到这类一两位作者“单打独斗”的作品,还是挺佩服的。从这篇文章,我学到个新词“调节组(regulome)”;相应地,其关联分析方法,被称为“regulome-wide associations study (RWAS)”。这篇文章还有个特点,它并未通过湿实验产出新数据,而是完全使用公开数据进行分析,包括结果验证,也是在公共数据库中进行。从概念到方法上进行创新,而成果发表到Nature子刊上,挺值得学习的。作者使用了来自TCGA的406例ATAC-seq数据,涵盖23个不同癌种,识别出7262个胚系allele-specific accessibility QTLs (as-aQTLs),即把染色质开放程度当做一种数量性状来研究,这个aQTL也是仿照eQTL提出的概念,的确很有意思。而通过RWAS,在各个癌种中鉴别出与癌症发生风险相关的as-aQTL位点,且发现它们在癌症风险遗传力方面的富集度甚至优于其他功能注释。这不仅实现了对非编码的“垃圾DNA(junk DNA)”区间的功能研究和解释,也开辟了肿瘤治疗的新思路,即针对这些调控区间及其相关机制来开展治疗。
IF:31.700Q1 Nature genetics, 2022-06. DOI: 10.1038/s41588-022-01075-2 PMID: 35697866
Allelic imbalance of chromatin accessibility in cancer identifies candidate causal risk variants and their mechanisms
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Abstract:
While many germline cancer risk variants have been identified through genome-wide association studies (GWAS), the mechanisms by which these variants operate remain largely unknown. Here we used 406 cancer ATAC-Seq samples across 23 cancer types to identify 7,262 germline allele-specific accessibility QTLs (as-aQTLs). Cancer as-aQTLs had stronger enrichment for cancer risk heritability (up to 145 fold) than any other functional annotation across seven cancer GWAS. Most cancer as-aQTLs directly altered transcription factor (TF) motifs and exhibited differential TF binding and gene expression in functional screens. To connect as-aQTLs to putative risk mechanisms, we introduced the regulome-wide associations study (RWAS). RWAS identified genetically associated accessible peaks at >70% of known breast and prostate loci and discovered new risk loci in all examined cancer types. Integrating as-aQTL discovery, motif analysis and RWAS identified candidate causal regulatory elements and their probable upstream regulators. Our work establishes cancer as-aQTLs and RWAS analysis as powerful tools to study the genetic architecture of cancer risk.
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