Statistical estimates of multiple transcription factors binding in the model plant genomes based on ChIP-seq data

The development of high-throughput genomic sequencing coupled with chromatin immunoprecipitation technologies allows studying the binding sites of the protein transcription factors (TF) in the genome scale. The growth of data volume on the experimentally determined binding sites raises qualitatively new problems for the analysis of gene expression regulation, prediction of transcription factors target genes, and regulatory gene networks reconstruction. Genome regulation remains an insufficiently studied though plants have complex molecular regulatory mechanisms of gene expression and response to environmental stresses. It is important to develop new software tools for the analysis of the TF binding sites location and their clustering in the plant genomes, visualization, and the following statistical estimates. This study presents application of the analysis of multiple TF binding profiles in three evolutionarily distant model plant organisms. The construction and analysis of non-random ChIP-seq binding clusters of the different TFs in mammalian embryonic stem cells were discussed earlier using similar bioinformatics approaches. Such clusters of TF binding sites may indicate the gene regulatory regions, enhancers and gene transcription regulatory hubs. It can be used for analysis of the gene promoters as well as a background for transcription networks reconstruction. We discuss the statistical estimates of the TF binding sites clusters in the model plant genomes. The distributions of the number of different TFs per binding cluster follow same power law distribution for all the genomes studied. The binding clusters in Arabidopsis thaliana genome were discussed here in detail.

A compendium of human genes regulating feeding behavior and body weight, its functional characterization and identification of GWAS genes involved in brain-specific PPI network

Background

Obesity is heritable. It predisposes to many diseases. The objectives of this study were to create a compendium of genes relevant to feeding behavior (FB) and/or body weight (BW) regulation; to construct and to analyze networks formed by associations between genes/proteins; and to identify the most significant genes, biological processes/pathways, and tissues/organs involved in BW regulation.

Results

The compendium of genes controlling FB or BW includes 578 human genes. Candidate genes were identified from various sources, including previously published original research and review articles, GWAS meta-analyses, and OMIM (Online Mendelian Inheritance in Man). All genes were ranked according to knowledge about their biological role in body weight regulation and classified according to expression patterns or functional characteristics. Substantial and overrepresented numbers of genes from the compendium encoded cell surface receptors, signaling molecules (hormones, neuropeptides, cytokines), transcription factors, signal transduction proteins, cilium and BBSome components, and lipid binding proteins or were present in the brain-specific list of tissue-enriched genes identified with TSEA tool. We identified 27 pathways from KEGG, REACTOME and BIOCARTA whose genes were overrepresented in the compendium. Networks formed by physical interactions or homological relationships between proteins or interactions between proteins involved in biochemical/signaling pathways were reconstructed and analyzed. Subnetworks and clusters identified by the MCODE tool included genes/proteins associated with cilium morphogenesis, signal transduction proteins (particularly, G protein–coupled receptors, kinases or proteins involved in response to insulin stimulus) and transcription regulation (particularly nuclear receptors). We ranked GWAS genes according to the number of neighbors in three networks and revealed 22 GWAS genes involved in the brain-specific PPI network. On the base of the most reliable PPIs functioning in the brain tissue, new regulatory schemes interpreting relevance to BW regulation are proposed for three GWAS genes (ETV5, LRP1B, and NDUFS3).

Conclusions

A compendium comprising 578 human genes controlling FB or BW was designed, and the most significant functional groups of genes, biological processes/pathways, and tissues/organs involved in BW regulation were revealed. We ranked genes from the GWAS meta-analysis set according to the number and quality of associations in the networks and then according to their involvement in the brain-specific PPI network and proposed new regulatory schemes involving three GWAS genes (ETV5, LRP1B, and NDUFS3) in BW regulation. The compendium is expected to be useful for pathology risk estimation and for design of new pharmacological approaches in the treatment of human obesity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0466-2) contains supplementary material, which is available to authorized users.