Global prediction of chromatin accessibility using small-cell-number and single-cell RNA-seq.

Weiqiang Zhou,Hongkai Ji,Zhicheng Ji,Weixiang Fang

doi:10.1093/nar/gkz716

Abstract

Conventional high-throughput genomic technologies for mapping regulatory element activities in bulk samples such as ChIP-seq, DNase-seq and FAIRE-seq cannot analyze samples with small numbers of cells. The recently developed low-input and single-cell regulome mapping technologies such as ATAC-seq and single-cell ATAC-seq (scATAC-seq) allow analyses of small-cell-number and single-cell samples, but their signals remain highly discrete or noisy. Compared to these regulome mapping technologies, transcriptome profiling by RNA-seq is more widely used. Transcriptome data in single-cell and small-cell-number samples are more continuous and often less noisy. Here, we show that one can globally predict chromatin accessibility and infer regulatory element activities using RNA-seq. Genome-wide chromatin accessibility predicted by RNA-seq from 30 cells can offer better accuracy than ATAC-seq from 500 cells. Predictions based on single-cell RNA-seq (scRNA-seq) can more accurately reconstruct bulk chromatin accessibility than using scATAC-seq. Integrating ATAC-seq with predictions from RNA-seq increases the power and value of both methods. Thus, transcriptome-based prediction provides a new tool for decoding gene regulatory circuitry in samples with limited cell numbers.

Highlights

Decoding gene regulatory network in developmental systems and precious clinical samples often requires measuring transcriptome and regulome in samples with small numbers of cells or in single cells
We have shown that genome-wide chromatin accessibility predicted from gene expression is practically useful in many applications including predicting transcription factor (TF) binding sites (TFBSs) and differential regulatory element activities between different biological conditions [19]
Our analyses show that predicting chromatin accessibility using RNA sequencing (RNA-seq) can provide a new approach for regulome mapping in bulk, small-cell-number, and singlecell samples

Summary

Introduction

Decoding gene regulatory network in developmental systems and precious clinical samples often requires measuring transcriptome (i.e. genes’ transcriptional activities) and regulome (i.e. regulatory element activities) in samples with small numbers of cells or in single cells. Conventional high-throughput regulome mapping technologies such as chromatin immunoprecipitation followed by sequencing (ChIP-seq) [4], sequencing of DNase I hypersensitive sites (DNase-seq) [5], and Formaldehyde-Assisted Isolation of Regulatory Elements coupled with sequencing (FAIRE-seq) [6] require large amounts of input material (∼106 cells). These ‘bulk’ technologies cannot analyze samples with small numbers of cells. Other recent low-input methods, such as microfluidic oscillatory washing-based ChIP-seq (MOWChIP-seq) for measuring histone modifications [8], remain noisy when the cell number is below a few hundreds

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