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Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules

Title: Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules
Authors: Xiao, X
Moreno-Moral, A
Rotival, M
Bottolo, L
Petretto, E
Item Type: Journal Article
Abstract: Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states). Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks) that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted) networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based) and humans (mRNA-sequencing-based) and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi-tissue subnetwork of co-expressed heat shock protein (Hsp) and cardiomyopathy genes (Bag3, Cryab, Kras, Emd, Plec), which was significantly replicated using separate failing heart and liver gene expression datasets in humans, thus revealing a conserved functional role for Hsp genes in cardiovascular disease.
Issue Date: 1-Jan-2014
Date of Acceptance: 22-Oct-2013
URI: http://hdl.handle.net/10044/1/57209
DOI: https://dx.doi.org/10.1371/journal.pgen.1004006
ISSN: 1553-7390
Publisher: Public Library of Science (PLoS)
Journal / Book Title: PLoS Genetics
Volume: 10
Issue: 1
Copyright Statement: © 2014 Xiao et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited (https://creativecommons.org/licenses/by/4.0/).
Sponsor/Funder: British Heart Foundation
Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: FS/11/25/28740
EP/I019111/1
Keywords: Science & Technology
Life Sciences & Biomedicine
Genetics & Heredity
GENE-EXPRESSION SIGNATURES
HEAT-SHOCK PROTEINS
R-PACKAGE
DATA SETS
DISEASE
GENOMICS
CARDIOMYOPATHY
RESPONSES
MATRIX
FAMILY
Algorithms
Animals
Cardiomyopathies
Cell Cycle Proteins
Gene Expression
Gene Expression Profiling
Gene Regulatory Networks
Genome, Human
Humans
Organ Specificity
Rats
Signal Transduction
Transcription, Genetic
0604 Genetics
Developmental Biology
Publication Status: Published
Article Number: ARTN e1004006
Appears in Collections:Clinical Sciences
Molecular Sciences
Faculty of Medicine
Faculty of Natural Sciences



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