Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation.
BACKGROUND
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. 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.


METHODS
We 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.


RESULTS
We 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.


CONCLUSIONS
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.
Computer Science Department, University of Missouri, Columbia, Missouri, 65211, USA. rcrg4@mail.missouri.edu.
Renzhi
R
Cao
Computer Science Department, University of Missouri, Columbia, Missouri, 65211, USA. chengji@missouri.edu.|Informatics Institute, University of Missouri, Columbia, Missouri, 65211, USA. chengji@missouri.edu.|Christopher S. Bond Life Science Center, University of Missouri, Columbia, Missouri, 65211, USA. chengji@missouri.edu.
Jianlin
J
Cheng
D002460:Cell Line; D004843:Epistasis, Genetic / Q000235:genetics; D053263:Gene Regulatory Networks / Q000235:genetics*; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D025941:Protein Interaction Mapping