4.7 Article

m 6 Aexpress-BHM: predicting m6A regulation of gene expression in multiple-groups context by a Bayesian hierarchical mixture model

Journal

BRIEFINGS IN BIOINFORMATICS
Volume 23, Issue 4, Pages -

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbac295

Keywords

m(6)A regulatory gene expression; multiple groups context; Bayesian hierarchical mixture model; immune system

Funding

  1. Nationa lNatural Science Foundation of China [61873202,62173271, 61473232]

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This study proposes a Bayesian hierarchical mixture model (m(6)Aexpress-BHM) to predict m(6)A regulation of gene expression in multiple groups of MeRIP-seq experiments. The model demonstrates high predicting precision and robustness based on evaluations on simulated data. The application of m(6)Aexpress-BHM on real-world datasets reveals the regulatory function of m(6)A in immune response and suggests its potential role in influencing the expression of PD-1/PD-L1 through regulating interacting genes.
As the most abundant RNA modification, N-6-methyladenosine (m(6)A) plays an important role in various RNA activities including gene expression and translation. With the rapid application of MeRIP-seq technology, samples of multiple groups, such as the involved multiple viral/ bacterial infection or distinct cell differentiation stages, are extracted from same experimental unit. However, our current knowledge about how the dynamic m(6)A regulating gene expression and the role in certain biological processes (e.g. immune response in this complex context) is largely elusive due to lack of effective tools. To address this issue, we proposed a Bayesian hierarchical mixture model (called m(6)Aexpress-BHM) to predict m(6)A regulation of gene expression (m(6)A-reg-exp) in multiple groups of MeRIP-seq experiment with limited samples. Comprehensive evaluations of m(6)Aexpress-BHM on the simulated data demonstrate its high predicting precision and robustness. Applying m(6)Aexpress-BHM on three real-world datasets (i.e. Flaviviridae infection, infected time-points of bacteria and differentiation stages of dendritic cells), we predicted more m(6)A-reg-exp genes with positive regulatory mode that significantly participate in innate immune or adaptive immune pathways, revealing the underlying mechanism of the regulatory function of m(6)A during immune response. In addition, we also found that m(6)A may influence the expression of PD-1/PD-L1 via regulating its interacted genes. These results demonstrate the power of m(6)Aexpress-BHM, helping us understand the m(6)A regulatory function in immune system.

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