美国纪念斯隆-凯特琳癌症中心Christina S. Leslie和Kushal K. Dey团队合作取得一项新成果。经过不懈努力，他们利用单细胞多组回归模型识别功能和疾病相关的增强子，并实现染色质潜力分析。这一研究成果于2024年3月21日发表在国际学术期刊《自然-遗传学》上。

研究人员提出了一种基因水平的调控模型-单细胞ATAC+RNA连接（SCARlink），它能预测单细胞基因表达，并利用多组（scRNA-seq和scATAC-seq共测）测序数据将增强子与目标基因连接起来。该方法在平级可及性数据上使用正向化泊松回归，对基因位点的所有调控效应进行联合建模，避免了成对基因-峰值相关的局限性和对峰值调用的依赖性。

在高覆盖率多组数据集的染色质可及性推算基因表达方面，SCARlink的表现优于现有的基因评分方法，同时在低覆盖率数据集上的表现也与现有方法平分秋色，甚至有所提高。对成熟模型进行的夏普利值分析确定了细胞类型特异性基因增强子，这些增强子经启动子捕获Hi-C验证，在精细映射的eQTL和精细映射的全基因组关联研究（GWAS）变异中分别富集了11倍至15倍和5倍至12倍。进一步研究表明，SCARlink预测的和观察到的基因表达矢量，为计算染色质势能矢量场提供了一种稳定的方法，可用于发育轨迹分析。

附：英文原文

Title: Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis

Author: Mitra, Sneha, Malik, Rohan, Wong, Wilfred, Rahman, Afsana, Hartemink, Alexander J., Pritykin, Yuri, Dey, Kushal K., Leslie, Christina S.

Issue&Volume: 2024-03-21

Abstract: We present a gene-level regulatory model, single-cell ATAC+RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and scATAC–seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene–peak correlations and dependence on peak calling. SCARlink outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across high-coverage multi-ome datasets while giving comparable to improved performance on low-coverage datasets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 11× to 15× and 5× to 12× enriched in fine-mapped eQTLs and fine-mapped genome-wide association study (GWAS) variants, respectively. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.

DOI: 10.1038/s41588-024-01689-8

Source: https://www.nature.com/articles/s41588-024-01689-8