TRANSDIRE: data-driven direct reprogramming by a pioneer factor-guided trans-omics approach

Author:

Eguchi Ryohei1ORCID,Hamano Momoko1ORCID,Iwata Michio1ORCID,Nakamura Toru1,Oki Shinya2ORCID,Yamanishi Yoshihiro1ORCID

Affiliation:

1. Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology , Fukuoka 820-8502, Japan

2. Department of Drug Discovery Medicine, Graduate School of Medicine, Kyoto University , Kyoto 606-8507, Japan

Abstract

Abstract Motivation Direct reprogramming involves the direct conversion of fully differentiated mature cell types into various other cell types while bypassing an intermediate pluripotent state (e.g. induced pluripotent stem cells). Cell differentiation by direct reprogramming is determined by two types of transcription factors (TFs): pioneer factors (PFs) and cooperative TFs. PFs have the distinct ability to open chromatin aggregations, assemble a collective of cooperative TFs and activate gene expression. The experimental determination of two types of TFs is extremely difficult and costly. Results In this study, we developed a novel computational method, TRANSDIRE (TRANS-omics-based approach for DIrect REprogramming), to predict the TFs that induce direct reprogramming in various human cell types using multiple omics data. In the algorithm, potential PFs were predicted based on low signal chromatin regions, and the cooperative TFs were predicted through a trans-omics analysis of genomic data (e.g. enhancers), transcriptome data (e.g. gene expression profiles in human cells), epigenome data (e.g. chromatin immunoprecipitation sequencing data) and interactome data. We applied the proposed methods to the reconstruction of TFs that induce direct reprogramming from fibroblasts to six other cell types: hepatocytes, cartilaginous cells, neurons, cardiomyocytes, pancreatic cells and Paneth cells. We demonstrated that the methods successfully predicted TFs for most cell conversions with high accuracy. Thus, the proposed methods are expected to be useful for various practical applications in regenerative medicine. Availability and implementation The source code and data are available at the following website: http://figshare.com/s/b653781a5b9e6639972b Supplementary information Supplementary data are available at Bioinformatics online.

Funder

JSPS KAKENHI

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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