Function-driven discovery of disease genes in zebrafish using an integrated genomics big data resource

Abstract

Whole exome sequencing (WES) accelerates disease gene discovery using rare genetic variants, but further statistical and functional evidence is required to avoid false-discovery. To complement variant-driven disease gene discovery, here we present function-driven disease gene discovery in zebrafish (Danio rerio), a promising human disease model owing to its high anatomical and genomic similarity to humans. To facilitate zebrafish-based function-driven disease gene discovery, we developed a genome-scale co-functional network of zebrafish genes, DanioNet (www.inetbio.org/danionet), which was constructed by Bayesian integration of genomics big data. Rigorous statistical assessment confirmed the high prediction capacity of DanioNet for a wide variety of human diseases. To demonstrate the feasibility of the function-driven disease gene discovery using DanioNet, we predicted genes for ciliopathies and performed experimental validation for eight candidate genes. We also validated the existence of heterozygous rare variants in the candidate genes of individuals with ciliopathies yet not in controls derived from the UK10K consortium, suggesting that these variants are potentially involved in enhancing the risk of ciliopathies. These results showed that an integrated genomics big data for a model animal of diseases can expand our opportunity for harnessing WES data in disease gene discovery.

MaizeNet: a co‐functional network for network‐assisted systems genetics in Zea mays

“…On the basis of the concept of associalogs (Kim et al ., ), which relates to the functional associations between orthologous genes among species, we inferred the functional linkages between maize genes from seven published co‐functional networks for other species: AraNet v2 ( Arabidopsis thaliana ) (Lee et al ., 2015c; Lee and Lee, ), RiceNet v2 ( O. sativa ) (Lee et al ., 2015b), YeastNet v3 ( Saccharomyces cerevisiae ) (Kim et al ., ), FlyNet ( Drosophila melanogaster ) (Shin et al ., ), MouseNet v2 ( Mus musculus ) (Kim et al ., ; Kim and Lee, ), DanioNet ( Danio rerio ) (Shim et al ., ) and HumanNet ( Homo sapiens ) (Lee et al ., 2011a). The orthology between the genes from maize and other species was identified using Inparanoid software (O'Brien et al ., ).…”

Functional gene networks based on the gene neighborhood in metagenomes

“…We downloaded the gene neighborhood network based on 1748 completely assembled prokaryotic genomes and gold-standard functional links for Arabidopsis thaliana, Danio rerio, and Saccharomyces cerevisiae from AraNet v2 (Lee et al 2015), DanioNet (Shim et al 2016), and YeastNet v3 , respectively. For Staphylococcus aureus, the network was constructed based on the method described in our previous work .…”

Mitotic control by mRNA splicing regulators ensures primary cilia formation

“…Besides the previous analysis that found genes involving G1/S transition and cilia disassembly, we further analyzed the hits to identify genes involving mitosis and cilia assembly here. To find genes regarding the mechanism associated with the coupling of cell cycle progression and ciliogenesis, we analyzed the mRNA processing-related hits by means of Gene ontology and DanioNet (Shim et al 2016). The functional network analysis revealed that SON DNA binding protein (SON) and XPA binding protein 2 (XAB2) within the hits are linked via Polo like kinase 1 (PLK1) and Cyclin-dependent kinase 1 (CDK1), mitosis regulators (Figure 1(b) and (c)).…”