MDHITS-tfh

Integrative analysis of human Tfh cell differentiation using a multilayered gene regulatory network approach

Abstract: Analysis of gene regulatory networks (GRNs) across cell differentiation can offer novel insights into the regulators of lineage specification and immune cell development. Many variations of ranking algorithms like Personalized PageRank and Hyperlink-Induced Topic Search (HITS) that rank node centrality measures have been applied to identify pivotal genes and transcription factors (TFs) in GRNs. However, these algorithms have limitations in modeling global regulatory dynamics across a differentiation trajectory and do not capture information about gene expression dynamics that arise in response to changes in TF activity across differentiation. To address these challenges, we propose using a multilayered network framework for analyzing GRNs across a trajectory of cell differentiation that can be analyzed using the Multi-Dimensional HITS (MD-HITS) algorithm, a globally convergent nonlinear extension of the original HITS algorithm. We utilized this analytical framework on a dataset of chromatin accessibility and gene expression levels across human T follicular helper (Tfh) cell development, revealing critical hub and authority nodes governing human Tfh cell differentiation. This approach is amenable to incorporating additional priors such as mRNA expression and protein-protein interaction networks. These findings underscore the value of a multilayered approach in the identification of hubs and authorities for elucidating complex regulatory networks underlying cell differentiation.