FertilityOnline, a straight pipeline for functional gene annotation and disease mutation discovery, identifies novel infertility causative mutations in SYCE1 and STAG3

Exploring the genetic basis of human infertility is currently under intensive investigation. However, only a handful of genes are validated in animal models as disease-causing genes in infertile men. Thus, to better understand the genetic basis of spermatogenesis in human and to bridge the knowledge gap between human and other animal species, we have constructed FertilityOnline database, which is a resource that integrates the functional genes reported in literature related to spermatogenesis into an existing spermatogenic database, SpermatogenesisOnline 1.0. Additional features like functional annotation and statistical analysis of genetic variants of human genes, are also incorporated into FertilityOnline. By searching this database, users can focus on the top candidate genes associated with infertility and can perform enrichment analysis to instantly refine the number of candidates in a user-friendly web interface. Clinical validation of this database is established by the identification of novel causative mutations in SYCE1 and STAG3 in azoospermia men. In conclusion, FertilityOnline is not only an integrated resource for analysis of spermatogenic genes, but also a useful tool that facilitates to study underlying genetic basis of male infertility.AvailabilityFertilityOnline can be freely accessed at http://mcg.ustc.edu.cn/bsc/spermgenes2.0/index.html.

Co-Occurrence of Enzyme Domains Guides the Discovery of an Oxazolone Synthetase

Multidomain enzymes are cellular machines that orchestrate two or more catalytic activities to carry out metabolic transformations with increased control and speed. Our understanding of these enzymes’ capabilities drives progress in fundamental metabolic research, biocatalysis, and human health. Here, we report the development of a new genome mining approach for the targeted discovery of novel biochemical transformations through the analysis of co-occurring enzyme domains (CO-ED) in a single protein. CO-ED was designed to identify unannotated multifunctional enzymes for functional characterization and discovery based on the premise that linked enzyme domains have evolved to function collaboratively. Guided by CO-ED, we targeted an unannotated predicted ThiF-nitroreductase di-domain enzyme found in more than 50 proteobacteria. Through heterologous expression and biochemical reconstitution, we discovered a series of new natural products containing the rare oxazolone (azlactone) heterocycle and characterized the di-domain enzyme as the first reported oxazolone synthetase in biology. This enzyme has the potential to become a valuable biocatalyst for the production of versatile oxazolone synthetic intermediates. This proof-of-principle experiment validates CO-ED-guided genome mining as a new method with potential broad utility for both the discovery of novel enzymatic transformations and the functional gene annotation of multidomain enzymes.TOC graphic

Mining approximate frequent dense modules from multiple gene expression datasets

Large amount of gene expression data has been collected for various environmental and biological conditions. Extracting co-expression networks that are recurrent in multiple co-expression networks has been shown promising in functional gene annotation and biomarkers discovery. Frequent subgraph mining reports a large number of subnetworks. In this work, we propose to mine approximate dense frequent subgraphs. Our proposed approach reports representative frequent subgraphs that are also dense. Our experiments on real gene coexpression networks show that frequent subgraphs are biologically interesting as evidenced by the large percentage of biologically enriched frequent dense subgraphs.

Hayai-Annotation Plants: an ultra-fast and comprehensive functional gene annotation system in plants

Summary Hayai-Annotation Plants is a browser-based interface for an ultra-fast and accurate functional gene annotation system for plant species using R. The pipeline combines the sequence-similarity searches, using USEARCH against UniProtKB (taxonomy Embryophyta), with a functional annotation step. Hayai-Annotation Plants provides five layers of annotation: i) protein name; ii) gene ontology terms consisting of its three main domains (Biological Process, Molecular Function and Cellular Component); iii) enzyme commission number; iv) protein existence level; and v) evidence type. It implements a new algorithm that gives priority to protein existence level to propagate GO and EC information and annotated Arabidopsis thaliana representative peptide sequences (Araport11) within 5 min at the PC level. Availability and implementation The software is implemented in R and runs on Macintosh and Linux systems. It is freely available at https://github.com/kdri-genomics/Hayai-Annotation-Plants under the GPLv3 license. Supplementary information Supplementary data are available at Bioinformatics online.

EnTAP: Bringing Faster and Smarter Functional Annotation to Non-Model Eukaryotic Transcriptomes

ABSTRACTEnTAP (Eukaryotic Non-Model Transcriptome Annotation Pipeline) was designed to improve the accuracy, speed, and flexibility of functional gene annotation for de novo assembled transcriptomes in non-model eukaryotes. This software package addresses the fragmentation and related assembly issues that result in inflated transcript estimates and poor annotation rates, while focusing primarily on protein-coding transcripts. Following filters applied through assessment of true expression and frame selection, open-source tools are leveraged to functionally annotate the translated proteins. Downstream features include fast similarity search across three repositories, protein domain assignment, orthologous gene family assessment, and Gene Ontology term assignment. The final annotation integrates across multiple databases and selects an optimal assignment from a combination of weighted metrics describing similarity search score, taxonomic relationship, and informativeness. Researchers have the option to include additional filters to identify and remove contaminants, identify associated pathways, and prepare the transcripts for enrichment analysis. This fully featured pipeline is easy to install, configure, and runs significantly faster than comparable annotation packages. EnTAP is optimized to generate extensive functional information for the gene space of organisms with limited or poorly characterized genomic resources.