小柯机器人

美国斯坦福大学医学院Thomas J. Montine和Howard Y. Chang研究组合作利用单细胞表观基因组学，分析揭示了与阿尔茨海默氏病和帕金森氏病发病相关变体的遗传风险位点。相关论文发表在2020年10月26日出版的《自然-遗传学》上。

研究人员通过对健康个体中单细胞染色质可及性图谱和成年大脑不同区域的三维染色质相互作用概况的分析，揭示了成年人大脑中多基因组表观遗传图集。研究人员开发了一种机器学习分类器，以整合该多基因组框架并预测与阿尔茨海默氏病和帕金森氏病相关的数十种功能性SNP，并从全基因组关联研究中为先前孤立的基因座指定靶基因和细胞类型。

此外，研究人员解析了MAPT（编码tau）帕金森氏病风险位点的复杂倒置单倍型，确定了可能与这种疾病相关神经元中假定的异位调节相互作用。这项工作扩展了对遗传变异的理解，并为揭示造成疾病发生表观基因组的变异提供了方法。

研究人员表示，神经疾病的全基因组关联研究已经确定了与疾病表型相关的数千种变异。然而，这些变体大多数不改变编码序列，从而难以确定其功能。

附：英文原文

Title: Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer’s and Parkinson’s diseases

Author: M. Ryan Corces, Anna Shcherbina, Soumya Kundu, Michael J. Gloudemans, Laure Frsard, Jeffrey M. Granja, Bryan H. Louie, Tiffany Eulalio, Shadi Shams, S. Tansu Bagdatli, Maxwell R. Mumbach, Boxiang Liu, Kathleen S. Montine, William J. Greenleaf, Anshul Kundaje, Stephen B. Montgomery, Howard Y. Chang, Thomas J. Montine

Issue&Volume: 2020-10-26

Abstract: Genome-wide association studies of neurological diseases have identified thousands of variants associated with disease phenotypes. However, most of these variants do not alter coding sequences, making it difficult to assign their function. Here, we present a multi-omic epigenetic atlas of the adult human brain through profiling of single-cell chromatin accessibility landscapes and three-dimensional chromatin interactions of diverse adult brain regions across a cohort of cognitively healthy individuals. We developed a machine-learning classifier to integrate this multi-omic framework and predict dozens of functional SNPs for Alzheimer’s and Parkinson’s diseases, nominating target genes and cell types for previously orphaned loci from genome-wide association studies. Moreover, we dissected the complex inverted haplotype of the MAPT (encoding tau) Parkinson’s disease risk locus, identifying putative ectopic regulatory interactions in neurons that may mediate this disease association. This work expands understanding of inherited variation and provides a roadmap for the epigenomic dissection of causal regulatory variation in disease. Single-cell chromatin profiling of different brain regions identifies cell-type-specific regulatory elements, and helps to predict functional SNPs for Alzheimer’s and Parkinson’s diseases.

DOI: 10.1038/s41588-020-00721-x

Source: https://www.nature.com/articles/s41588-020-00721-x

Nature Genetics：《自然—遗传学》，创刊于1992年。隶属于施普林格·自然出版集团，最新IF：41.307
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