小柯机器人

美国密歇根大学教授Joshua D. Welch团队近期取得重要工作进展，他们通过多组学单细胞速度模拟表观基因组-转录组的相互作用并改善细胞命运预测。相关研究工作2022年10月13日在线发表于《自然—生物技术》杂志上。

据介绍，在多组学单细胞数据集中，多个分子形态被描绘在同一细胞内，为理解表观基因组和转录组之间的时空关系提供了机会。

为了实现这一潜力，研究人员开发了MultiVelo，这是一种基因表达的微分方程模型，它扩展了RNA速度框架，将表观基因组数据纳入其中。MultiVelo采用了概率潜在变量模型来估计染色质可及性和基因表达的切换时间和速率参数，与仅从RNA估计速度相比，提高了细胞命运预测的准确性。对来自大脑、皮肤和血细胞的多组学单细胞数据集的应用揭示了两类不同的基因，其区别在于染色质是否在转录停止之前或之后关闭。

研究人员还发现四种类型的细胞状态：两种表观基因组和转录组耦合的状态和两种不同的解耦状态。最后，研究人员确定了转录因子表达和结合位点可及性之间的时间差，以及疾病相关SNP可及性和相关基因表达之间的时间差。MultiVelo可在PyPI、Bioconda和GitHub (https://github.com/welch-lab/MultiVelo)上使用。

附：英文原文

Title: Multi-omic single-cell velocity models epigenome–transcriptome interactions and improves cell fate prediction

Author: Li, Chen, Virgilio, Maria C., Collins, Kathleen L., Welch, Joshua D.

Issue&Volume: 2022-10-13

Abstract: Multi-omic single-cell datasets, in which multiple molecular modalities are profiled within the same cell, offer an opportunity to understand the temporal relationship between epigenome and transcriptome. To realize this potential, we developed MultiVelo, a differential equation model of gene expression that extends the RNA velocity framework to incorporate epigenomic data. MultiVelo uses a probabilistic latent variable model to estimate the switch time and rate parameters of chromatin accessibility and gene expression and improves the accuracy of cell fate prediction compared to velocity estimates from RNA only. Application to multi-omic single-cell datasets from brain, skin and blood cells reveals two distinct classes of genes distinguished by whether chromatin closes before or after transcription ceases. We also find four types of cell states: two states in which epigenome and transcriptome are coupled and two distinct decoupled states. Finally, we identify time lags between transcription factor expression and binding site accessibility and between disease-associated SNP accessibility and expression of the linked genes. MultiVelo is available on PyPI, Bioconda and GitHub (https://github.com/welch-lab/MultiVelo).

DOI: 10.1038/s41587-022-01476-y

Source: https://www.nature.com/articles/s41587-022-01476-y

Nature Biotechnology：《自然—生物技术》，创刊于1996年。隶属于施普林格·自然出版集团，最新IF：68.164
官方网址：https://www.nature.com/nbt/
投稿链接：https://mts-nbt.nature.com/cgi-bin/main.plex