Interspecies gene function prediction using semantic similarity.
BACKGROUND
Gene Ontology (GO) is a collaborative project that maintains and develops controlled vocabulary (or terms) to describe the molecular function, biological roles and cellular location of gene products in a hierarchical ontology. GO also provides GO annotations that associate genes with GO terms. GO consortium independently and collaboratively annotate terms to gene products, mainly from model organisms (or species) they are interested in. Due to experiment ethics, research interests of biologists and resources limitations, homologous genes from different species currently are annotated with different terms. These differences can be more attributed to incomplete annotations of genes than to functional difference between them.


RESULTS
Semantic similarity between genes is derived from GO hierarchy and annotations of genes. It is positively correlated with the similarity derived from various types of biological data and has been applied to predict gene function. In this paper, we investigate whether it is possible to replenish annotations of incompletely annotated genes by using semantic similarity between genes from two species with homology. For this investigation, we utilize three representative semantic similarity metrics to compute similarity between genes from two species. Next, we determine the k nearest neighborhood genes from the two species based on the chosen metric and then use terms annotated to k neighbors of a gene to replenish annotations of that gene. We perform experiments on archived (from Jan-2014 to Jan-2016) GO annotations of four species (Human, Mouse, Danio rerio and Arabidopsis thaliana) to assess the contribution of semantic similarity between genes from different species. The experimental results demonstrate that: (1) semantic similarity between genes from homologous species contributes much more on the improved accuracy (by 53.22%) than genes from single species alone, and genes from two species with low homology; (2) GO annotations of genes from homologous species are complementary to each other.


CONCLUSIONS
Our study shows that semantic similarity based interspecies gene function annotation from homologous species is more prominent than traditional intraspecies approaches. This work can promote more research on semantic similarity based function prediction across species.
College of Computer and Information Sciences, Southwest University, Chongqing, China. gxyu@swu.edu.cn.
Guoxian
G
Yu
College of Computer and Information Sciences, Southwest University, Chongqing, China.
Wei
W
Luo
College of Computer and Information Sciences, Southwest University, Chongqing, China.
Guangyuan
G
Fu
College of Computer and Information Sciences, Southwest University, Chongqing, China.
Jun
J
Wang
D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D063990:Gene Ontology; D006801:Humans; D051379:Mice; D058977:Molecular Sequence Annotation; D009323:Natural Language Processing; D012441:Saccharomyces cerevisiae / Q000235:genetics; D012660:Semantics; D013045:Species Specificity; D015027:Zebrafish / Q000235:genetics
GO annotations; Gene function prediction; Interspecies; Semantic similarity