RT Journal Article
SR Electronic
T1 Predicting gene regulatory networks from cell atlases
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.08.21.261735
DO 10.1101/2020.08.21.261735
A1 Andreas Fønss Møller
A1 Kedar Nath Natarajan
YR 2020
UL http://biorxiv.org/content/early/2020/08/24/2020.08.21.261735.abstract
AB Recent single-cell RNA-sequencing atlases have surveyed and identified major cell-types across different mouse tissues. Here, we computationally reconstruct gene regulatory networks from 3 major mouse cell atlases to capture functional regulators critical for cell identity, while accounting for a variety of technical differences including sampled tissues, sequencing depth and author assigned cell-type labels. Extracting the regulatory crosstalk from mouse atlases, we identify and distinguish global regulons active in multiple cell-types from specialised cell-type specific regulons. We demonstrate that regulon activities accurately distinguish individual cell types, despite differences between individual atlases. We generate an integrated network that further uncovers regulon modules with coordinated activities critical for cell-types, and validate modules using available experimental data. Inferring regulatory networks during myeloid differentiation from wildtype and Irf8 KO cells, we uncover functional contribution of Irf8 regulon activity and composition towards monocyte lineage. Our analysis provides an avenue to further extract and integrate the regulatory crosstalk from single-cell expression data.Summary Integrated single-cell gene regulatory network from three mouse cell atlases captures global and cell-type specific regulatory modules and crosstalk, important for cellular identity.Competing Interest StatementThe authors have declared no competing interest.