An-Yuan Guo

GSDS 2.0: an upgraded gene feature visualization server

Summary: Visualizing genes’ structure and annotated features helps biologists to investigate their function and evolution intuitively. The Gene Structure Display Server (GSDS) has been widely used by more than 60 000 users since its first publication in 2007. Here, we reported the upgraded GSDS 2.0 with a newly designed interface, supports for more types of annotation features and formats, as well as an integrated visual editor for editing the generated figure. Moreover, a user-specified phylogenetic tree can be added to facilitate further evolutionary analysis. The full source code is also available for downloading. Availability and implementation: Web server and source code are freely available at http://gsds.cbi.pku.edu.cn. Contact: gaog@mail.cbi.pku.edu.cn or gsds@mail.cbi.pku.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Genome‐wide identification of SNPs in microRNA genes and the SNP effects on microRNA target binding and biogenesis

MicroRNAs (miRNAs) are studied as key regulators of gene expression involved in different diseases. Several single nucleotide polymorphisms (SNPs) in miRNA genes or target sites (miRNA‐related SNPs) have been proved to be associated with human diseases by affecting the miRNA‐mediated regulatory function. To systematically analyze miRNA‐related SNPs and their effects, we performed a genome‐wide scan for SNPs in human pre‐miRNAs, miRNA flanking regions, target sites, and designed a pipeline to predict the effects of them on miRNA–target interaction. As a result, we identified 48 SNPs in human miRNA seed regions and thousands of SNPs in 3′ untranslated regions with the potential to either disturb or create miRNA–target interactions. Furthermore, we experimentally confirmed seven loss‐of‐function SNPs and one gain‐of‐function SNP by luciferase assay. This is the first case of experimental validation of an SNP in an miRNA creating a novel miRNA target binding. All useful data were complied into miRNASNP, a user‐friendly free online database (http://www.bioguo.org/miRNASNP/). These data will be a useful resource for studying miRNA function, identifying disease‐associated miRNAs, and further personalized medicine. Hum Mutat 33:254–263, 2012.

AnimalTFDB: a comprehensive animal transcription factor database

Transcription factors (TFs) are proteins that bind to specific DNA sequences, thereby playing crucial roles in gene-expression regulation through controlling the transcription of genetic information from DNA to RNA. Transcription cofactors and chromatin remodeling factors are also essential in the gene transcriptional regulation. Identifying and annotating all the TFs are primary and crucial steps for illustrating their functions and understanding the transcriptional regulation. In this study, based on manual literature reviews, we collected and curated 72 TF families for animals, which is currently the most complete list of TF families in animals. Then, we systematically characterized all the TFs in 50 animal species and constructed a comprehensive animal TF database, AnimalTFDB. To better serve the community, we provided detailed annotations for each TF, including basic information, gene structure, functional domain, 3D structure hit, Gene Ontology, pathway, protein–protein interaction, paralogs, orthologs, potential TF-binding sites and targets. In addition, we collected and annotated transcription cofactors and chromatin remodeling factors. AnimalTFDB has a user-friendly web interface with multiple browse and search functions, as well as data downloading. It is freely available at http://www.bioguo.org/AnimalTFDB/.

PlantTFDB: a comprehensive plant transcription factor database

Transcription factors (TFs) play key roles in controlling gene expression. Systematic identification and annotation of TFs, followed by construction of TF databases may serve as useful resources for studying the function and evolution of transcription factors. We developed a comprehensive plant transcription factor database PlantTFDB (http://planttfdb.cbi.pku.edu.cn), which contains 26 402 TFs predicted from 22 species, including five model organisms with available whole genome sequence and 17 plants with available EST sequences. To provide comprehensive information for those putative TFs, we made extensive annotation at both family and gene levels. A brief introduction and key references were presented for each family. Functional domain information and cross-references to various well-known public databases were available for each identified TF. In addition, we predicted putative orthologs of those TFs among the 22 species. PlantTFDB has a simple interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis.

DRTF: a database of rice transcription factors

SUMMARY DRTF contains 2025 putative transcription factors (TFs) in Oryza sativa L. ssp. indica and 2384 in ssp. japonica, distributed in 63 families, identified by computational prediction and manual curation. It includes detailed annotations of each TF including sequence features, functional domains, Gene Ontology assignment, chromosomal localization, EST and microarray expression information, as well as multiple sequence alignment of the DNA-binding domains for each TF family. The database can be browsed and searched with a user-friendly web interface. AVAILABILITY DRTF is available at http://drtf.cbi.pku.edu.cn

Genome-wide identification and evolutionary analysis of the plant specific SBP-box transcription factor family.

We made genome-wide analyses to explore the evolutionary process of the SBP-box gene family. We identified 120 SBP-box genes from nine species representing the main green plant lineages: green alga, moss, lycophyte, gymnosperm and angiosperm. A maximum-likelihood phylogenetic tree was constructed using the protein sequences of the DNA-binding domain of SBP-box genes (SBP-domain). Our results revealed that all SBP-box genes of green alga clustered into a single clade (CR group), while all genes from land-plants fell into two distinct groups. Group I had a single copy in each species except for poplar while group II had several members in each species and can be divided into several subgroups. The SBP-domain encoded by all SBP-box genes possesses two zinc fingers. The C-terminal zinc finger of both group I and group II had the same C2HC motif while their N-terminal zinc finger showed different signatures, C4 in group I and C3H in group II. The patterns of exon-intron structure in Arabidopsis and rice SBP-box genes were consistent with the phylogenetic results. A target site of microRNA miR156 was highly conserved among land-plant SBP-box genes. Our results suggested that the SBP-box gene family might have originated from a common ancestor of green plants, followed by duplication and divergence in each lineage including exon-intron loss processes.

A Novel microRNA and transcription factor mediated regulatory network in schizophrenia

BackgroundSchizophrenia is a complex brain disorder with molecular mechanisms that have yet to be elucidated. Previous studies have suggested that changes in gene expression may play an important role in the etiology of schizophrenia, and that microRNAs (miRNAs) and transcription factors (TFs) are primary regulators of this gene expression. So far, several miRNA-TF mediated regulatory modules have been verified. We hypothesized that miRNAs and TFs might play combinatory regulatory roles for schizophrenia genes and, thus, explored miRNA-TF regulatory networks in schizophrenia.ResultsWe identified 32 feed-forward loops (FFLs) among our compiled schizophrenia-related miRNAs, TFs and genes. Our evaluation revealed that these observed FFLs were significantly enriched in schizophrenia genes. By converging the FFLs and mutual feedback loops, we constructed a novel miRNA-TF regulatory network for schizophrenia. Our analysis revealed EGR3 and hsa-miR-195 were core regulators in this regulatory network. We next proposed a model highlighting EGR3 and miRNAs involved in signaling pathways and regulatory networks in the nervous system. Finally, we suggested several single nucleotide polymorphisms (SNPs) located on miRNAs, their target sites, and TFBSs, which may have an effect in schizophrenia gene regulation.ConclusionsThis study provides many insights on the regulatory mechanisms of genes involved in schizophrenia. It represents the first investigation of a miRNA-TF regulatory network for a complex disease, as demonstrated in schizophrenia.

The dystrobrevin-binding protein 1 gene: features and networks

The dystrobrevin-binding protein 1 (DTNBP1) gene has been one of the most studied and promising schizophrenia susceptibility genes since it was first reported to be associated with schizophrenia in the Irish Study of High Density Schizophrenia Families (ISHDSF). Although many studies have been performed both at the functional level and in association with psychiatric disorders, there has been no systematic review of the features of the DTNBP1 gene, protein or the relationship between function and phenotype. Using a bioinformatics approach, we identified the DTNBP1 gene in 13 vertebrate species. The comparison of these genes revealed a conserved gene structure, protein-coding sequence and dysbindin domain, but a diverse noncoding sequence. The molecular evolutionary analysis suggests the DTNBP1 gene probably originated in chordates and matured in vertebrates. No signature of recent positive selection was seen in any primate lineage. The DTNBP1 gene likely has many more alternative transcripts than the current three major isoforms annotated in the NCBI database. Our examination of risk haplotypes revealed that, although the frequency of a single nucleotide polymorphism (SNP) or haplotype might be significantly different in cases from controls, difference between major geographic populations was even larger. Finally, we constructed the first DTNBP1 interactome and explored its network features. Besides the biogenesis of lysosome-related organelles complex 1 and dystrophin-associated protein complex, several molecules in the DTNBP1 network likely provide insight into the role of DTNBP1 in biological systems: retinoic acid, β-estradiol, calmodulin and tumour necrosis factor. Studies of these subnetworks and pathways may provide opportunities to deepen our understanding of the mechanisms of action of DTNBP1 variants.

lncRNASNP: a database of SNPs in lncRNAs and their potential functions in human and mouse

Long non-coding RNAs (lncRNAs) play key roles in various cellular contexts and diseases by diverse mechanisms. With the rapid growth of identified lncRNAs and disease-associated single nucleotide polymorphisms (SNPs), there is a great demand to study SNPs in lncRNAs. Aiming to provide a useful resource about lncRNA SNPs, we systematically identified SNPs in lncRNAs and analyzed their potential impacts on lncRNA structure and function. In total, we identified 495 729 and 777 095 SNPs in more than 30 000 lncRNA transcripts in human and mouse, respectively. A large number of SNPs were predicted with the potential to impact on the miRNA–lncRNA interaction. The experimental evidence and conservation of miRNA–lncRNA interaction, as well as miRNA expressions from TCGA were also integrated to prioritize the miRNA–lncRNA interactions and SNPs on the binding sites. Furthermore, by mapping SNPs to GWAS results, we found that 142 human lncRNA SNPs are GWAS tagSNPs and 197 827 lncRNA SNPs are in the GWAS linkage disequilibrium regions. All these data for human and mouse lncRNAs were imported into lncRNASNP database (http://bioinfo.life.hust.edu.cn/lncRNASNP/), which includes two sub-databases lncRNASNP-human and lncRNASNP-mouse. The lncRNASNP database has a user-friendly interface for searching and browsing through the SNP, lncRNA and miRNA sections.

DPTF: a database of poplar transcription factors

The database of poplar transcription factors (DPTF) is a plant transcription factor (TF) database containing 2576 putative poplar TFs distributed in 64 families. These TFs were identified from both computational prediction and manual curation. We have provided extensive annotations including sequence features, functional domains, GO assignment and expression evidence for all TFs. In addition, DPTF contains cross-links to the Arabidopsis and rice transcription factor databases making it a unique resource for genome-scale comparative studies of transcriptional regulation in model plants. Availiability: DPTF is available at http://dptf.cbi.pku.edu.cn.