Abstract

BackgroundA number of factors have been investigated in the context of gene function prediction and analysis, such as sequence identity, gene expressions, and gene co-evolution. However, three-dimensional (3D) conformation of the genome has not been tapped to analyse gene function, probably largely due to lack of genome conformation data until recently.MethodsWe construct the genome-wide spatial gene-gene interaction networks for three different human B-cells or cell lines from their chromosomal contact data generated by the Hi-C chromosome conformation capturing technique. The G-SESAME and Fast-SemSim are used to calculate function similarity between interacted / non-interacted genes. The Gene Ontology statistics computed from the gene-gene interaction networks is used for gene function prediction.ResultsWe compare the function similarity of gene pairs that do not spatially interact and that have interactions. We find that genes that have strong spatial interactions tend to have highly similar function in terms of biological process, molecular function and cellular component of the Gene Ontology. And even though the level of gene-gene interactions generally have no or weak correlation with either sequential genomic distance or sequence identity between genes, the interacted genes with high function similarity tend to have stronger interactions, somewhat shorter genomic distance and significantly higher sequence identity. And combining genomic distance or sequence identity with spatial gene-gene interaction information informs gene-gene function similarity much better than using either one of them alone, suggesting gene-gene interaction information is largely complementary with genomic distance and sequence identity in the context of gene function analysis. We develop and evaluate a new gene function prediction method based on gene-gene interacting networks, which can predict gene function well for a large number of human genes.ConclusionsIn this work, we demonstrate that the spatial conformation of the human genome is relevant to gene function similarity and is useful for gene function prediction.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2093-0) contains supplementary material, which is available to authorized users.

Highlights

  • A number of factors have been investigated in the context of gene function prediction and analysis, such as sequence identity, gene expressions, and gene co-evolution

  • In this work, we demonstrate that the spatial conformation of the human genome is relevant to gene function similarity and is useful for gene function prediction

  • A number of factors potentially related to gene function such as sequence identity, gene phylogenetic profiles, sequential genomic co-localizations, gene expressions, and proteinprotein interaction have been investigated in the context of gene function prediction and analysis [3,4,5,6,7,8]

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Summary

Introduction

A number of factors have been investigated in the context of gene function prediction and analysis, such as sequence identity, gene expressions, and gene co-evolution. A number of factors potentially related to gene function such as sequence identity, gene phylogenetic profiles, sequential genomic co-localizations, gene expressions, and proteinprotein interaction have been investigated in the context of gene function prediction and analysis [3,4,5,6,7,8]. Since the Hi-C technique [9] that can determine the genome-wide chromosomal interaction/contact data was invented in 2009, it has been applied to generate the largescale genome-wide chromosomal conformation data for a number of genomes such as human B-cells [10, 11], yeast [12], bacteria [13], and Arabidopsis [14], which provides valuable data for studying the relationships between spatial gene-gene interactions and gene function. From the Hi-C contact data, we generated the spatial genegene interactions for these cells or cell lines in order to investigate if the spatially interacting genes tend to have similar functions

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