Gene3D: comprehensive structural and functional annotation of genomes

Gene3D provides comprehensive structural and functional annotation of most available protein sequences, including the UniProt, RefSeq and Integr8 resources. The main structural annotation is generated through scanning these sequences against the CATH structural domain database profile-HMM library. CATH is a database of manually derived PDB-based structural domains, placed within a hierarchy reflecting topology, homology and conservation and is able to infer more ancient and divergent homology relationships than sequence-based approaches. This data is supplemented with Pfam-A, other non-domain structural predictions (i.e. coiled coils) and experimental data from UniProt. In order to enhance the investigations possible with this data, we have also incorporated a variety of protein annotation resources, including protein–protein interaction data, GO functional assignments, KEGG pathways, FUNCAT functional descriptions and links to microarray expression data. All of this data can be accessed through a newly re-designed website that has a focus on flexibility and clarity, with searches that can be restricted to a single genome or across the entire sequence database. Currently Gene3D contains over 3.5 million domain assignments for nearly 5 million proteins including 527 completed genomes. This is available at: http://gene3d.biochem.ucl.ac.uk

Non-homology-based prediction of gene functions in maize (\u3ci\u3eZea mays\u3c/i\u3e ssp. \u3ci\u3emays\u3c/i\u3e)

Advances in genome sequencing and annotation have eased the difficulty of identifying new gene sequences. Predicting the functions of these newly identified genes remains challenging. Genes descended from a common ancestral sequence are likely to have common functions.As a result, homology is widely used for gene function prediction. This means functional annotation errors also propagate from one species to another. Several approaches based on machine learning classification algorithms were evaluated for their ability to accurately predict gene function from non-homology gene features. Among the eight supervised classification algorithms evaluated, random forest-based prediction consistently provided the most accurate gene function prediction. Non-homology-based functional annotation provides complementary strengths to homology-based annotation, with higher average performance in Biological Process GO terms, the domain where homology-based functional annotation performs the worst, and weaker performance in Molecular Function GO terms, the domain where the accuracy of homology-based functional annotation is highest. GO prediction models trained with homology-based annotations were able to successfully predict annotations from a manually curated “gold standard” GO annotation set. Non-homology-based functional annotation based on machine learning may ultimately prove useful both as a method to assign predicted functions to orphan genes which lack functionally characterized homologs, and to identify and correct functional annotation errors which were propagated through homology-based functional annotations

A Genome-Wide Screening and SNPs-to-Genes Approach to Identify Novel Genetic Risk Factors Associated with Frontotemporal Dementia

Frontotemporal dementia (FTD) is the second most prevalent form of early onset dementia after Alzheimer’s disease (AD). We performed a case-control association study in an Italian FTD cohort (n = 530) followed by the novel SNPs-to-genes approach and functional annotation analysis. We identified two novel potential loci for FTD. Suggestive SNPs reached p-values ~10-7 and OR > 2.5 (2p16.3) and 1.5 (17q25.3). Suggestive alleles at 17q25.3 identified a disease-associated haplotype causing decreased expression of -cis genes such as RFNG and AATK involved in neuronal genesis and differentiation, and axon outgrowth, respectively. We replicated this locus through the SNPs-to-genes approach. Our functional annotation analysis indicated significant enrichment for functions of the brain (neuronal genesis, differentiation and maturation), the synapse (neurotransmission and synapse plasticity), and elements of the immune system, the latter supporting our recent international FTD-GWAS. This is the largest genome-wide study in Italian FTD to date. Although our results are not conclusive, we set the basis for future replication studies and identification of susceptible molecular mechanisms involved in FTD pathogenesis

Escherichia coli EHEC Germany outbreak preliminary functional annotation using BG7 system

We have annotated the European outbreak E. coli EHEC genome sequenced by BGI (6-2-2011) and assembled with MIRA by Nick Loman (6-2-2011 ). Our system BG7, Bacterial Genome annotation of Era7 Bioinformatics, predicts ORFs and annotates them based on fragments of similarity with Uniprot proteins. We have predicted 6327 genes, 6156 encoding proteins y 171 corresponding to ribosomal and tRNA. Based on the preliminary results of our semi-automated method of annotation we have selected some predicted proteins with potential implications in pathogenicity and virulence.
There are 33 predicted genes annotated as toxins and we have found three putative hemolysins: Hemolysin E, a putative hemolysin expression modulating protein and a channel protein, hemolysin III family. We have found 31 predicted genes that could be related to specific antibiotic resistance: beta-lactamic, aminoglycoside, macrolide, polymyxin, tetracycline, fosfomycin and deoxycholate, novobiocin, chloramphenicol, bicyclomycin, norfloxacin and enoxacin and 6-mercaptopurine. This strain is rich in adhesion, secretion systems, pathogenicity and virulence related proteins. It seems to have a restriction-modification system, many proteins involved in Fe transport and utilization (siderophores as aerobactin and enterobactin), lysozyme, one inhibitor of pancreatic serine proteases, proteins involved in anaerobic respiration, antimicrobial peptides, and proteins involved in quorum sensing and biofilm formation that could confer competitive advantage to this strain

Target identification in Fusobacterium nucleatum by subtractive genomics approach and enrichment analysis of host-pathogen protein-protein interactions

Homology based HP-PPIs predicted from HPIDB. Table S9. Pathway enrichment analysis of host genes from DAVID functional annotation tool. Table S10. Gene ontology report of host genes. Table S11. Disease enrichment analysis of host genes participated in HP-PPIs. Table S12. Total functional annotation cluster analysis of host genes. (XLSX 99 kb

miRDB: An online resource for microRNA target prediction and functional annotations

functional annotation

Transcriptomic comparison of the self-pollinated and cross-pollinated flowers of Erigeron breviscapus to analyze candidate self-incompatibility-associated genes

Table S1. Functional annotation of E.breviscapus transcriptome. (XLSX 4281 kb