Comprehensive network modeling from single cell RNA sequencing of human and mouse reveals well conserved transcription regulation of hematopoiesis

Shouguo Gao,Neal S Young,Zhijie Wu,Xingmin Feng,Xujing Wang,Sachiko Kajigaya

doi:10.1186/s12864-020-07241-2

Abstract

BackgroundPresently, there is no comprehensive analysis of the transcription regulation network in hematopoiesis. Comparison of networks arising from gene co-expression across species can facilitate an understanding of the conservation of functional gene modules in hematopoiesis.ResultsWe used single-cell RNA sequencing to profile bone marrow from human and mouse, and inferred transcription regulatory networks in each species in order to characterize transcriptional programs governing hematopoietic stem cell differentiation. We designed an algorithm for network reconstruction to conduct comparative transcriptomic analysis of hematopoietic gene co-expression and transcription regulation in human and mouse bone marrow cells. Co-expression network connectivity of hematopoiesis-related genes was found to be well conserved between mouse and human. The co-expression network showed “small-world” and “scale-free” architecture. The gene regulatory network formed a hierarchical structure, and hematopoiesis transcription factors localized to the hierarchy’s middle level.ConclusionsTranscriptional regulatory networks are well conserved between human and mouse. The hierarchical organization of transcription factors may provide insights into hematopoietic cell lineage commitment, and to signal processing, cell survival and disease initiation.

Highlights

There is no comprehensive analysis of the transcription regulation network in hematopoiesis
In order to characterize the early stages of hematopoiesis, we sorted lineage-CD34+ cells to enrich for Hematopoietic Stem and Progenitor Cell (HSPC)
CD34+ cells could be computationally assigned to the following subpopulations: multipotent progenitor Hematopoietic Stem Cell (HSC), megakaryocyte-erythroid progenitors (MEPs), granulocyte-monocyte progenitors (GMPs), B lymphocyte progenitors (ProBs), and early T lineage progenitors (ETPs) (Figure S2A)

Summary

Introduction

There is no comprehensive analysis of the transcription regulation network in hematopoiesis. Differentiation versus maintenance, proliferation versus quiescence, lineage specificity and maturation of cells are mainly determined by transcription factors (TFs) and their target genes (TGs) within complex transcriptional regulatory networks. Single-cell RNA-sequencing (scRNA-seq) has developed as a powerful discovery tool to characterize global regulatory programs in hematopoiesis [5]. Interactions were much more enriched in single-cell specific co-expressed genes with a 5-fold enrichment compared to the expectation [7]. Compared with bulk expression data, the co-expressed genes in single cells encode proteins that are more likely to physically interact with each other. Single-cell data are limited due to dropout events (expressed genes undetected by scRNA-seq) and noise (technical issues such as PCR amplification bias [8]), which often make reliable inferences of regulatory networks difficult. The algorithm bigScale is advantageous as it clusters cells and calculates z-scores for each gene in terms of differential expression between pairs of clusters, and uses z-scores to calculate gene-pair correlations [9]. bigScale circumvents dropout and can detect gene-to-gene correlations that are often otherwise missed

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Results

Conclusion