PT  - JOURNAL ARTICLE
AU  - Andreas Fønss Møller
AU  - Kedar Nath Natarajan
TI  - Predicting gene regulatory networks from cell atlases
AID  - 10.26508/lsa.202000658
DP  - 2020 Nov 01
TA  - Life Science Alliance
PG  - e202000658
VI  - 3
IP  - 11
4099  - https://www.life-science-alliance.org/content/3/11/e202000658.short
4100  - https://www.life-science-alliance.org/content/3/11/e202000658.full
SO  - Life Sci. Alliance2020 Nov 01; 3
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 three 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 wild-type 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.