Functional Annotation Final Results

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2 Unité de Biométrie et d’Intelligence Artificielle (UBIA) INRA

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Functional Annotation Final Results

Annotations : Coding Regions

Pipeline: Coding Regions

Structure annotation Lipo-Protein - LipoP Signal-peptide - SignalP Transmembrane proteins-TMHMM Protein domain identification-Interproscan and CD search

LipoP

Interproscan and CD search The results for the two softwares is similar but we used CD search because the cas genes were highly annotated by CDD database which is not included Interproscan.

Interproscan and CD search The results for the two softwares is similar but we used CD search because the cas genes were highly annotated by CDD which is not included in Interproscan.

Function annotation Specific Annotation : Virulence Factors-VFDB Antibiotic resistance proteins- CARD Overall Annotation : Uniprot Refseq

VFDB and CARD results This table shows the number of virulent and antibiotic resistant genes annotated by each database, these results show that the virulent genes are mostly conserved across the serogroups.

Gene Ontology The table shows the classification of the gene ontologies for our samples

Pathway annotation MetaCyc UniPathway Kobas-KEGG Orthologous Based Annotations

Pathway Results Annotated Genes Kegg orthology based annotation gave us the more annotations than the other two databases, however we wanted to include experimental database too from MetaCyc. MetaCyc is available through Interpro.

Pathway Results Total Number of Genes Annotated genes

Gene Naming E-value<10e-50 Alignment length>100 Coverage>60% Absolute Function All 3 criteria fulfilled E-value<10e-50 Alignment length>100 Coverage>60% Conserved Hypothetical Function All criteria meet with”hypothetical” term Hypothetical Proteins No criteria fulfilled

Number of Genes as per naming

Total Annotated Genes vs Total number of Genes Predicted

1827 834 640 355

Annotations : Non - Coding Regions

RNAs and CRISPRs This table shows the number of RNA elements found in each sample. CRISPRs were fairly difficult to annotate because each software (minced/Rfam/CRISPR finder) had their own algorithm to identify crisprs leading to inconsistency with the results obtained. We concluded to use CRISPR finder through CRISPR DB.

Deliverables Completely annotated gff files uploaded to the server. The annotations included the following information: id=<gene ID>;Name=<gene symbol>;signature=<Gene name>;GO=<GO ID>;Interpro=<Interpro ID>;KEGG=<KEGG ID>;UniPathway=<UniPathway ID>;MetaCyc=<MetaCyc ID>;TMHMM=<Yes/NO>;Coils=<Yes/No>;SignalP=<Yes/No>;LipoP=<Yes/No>;comment=< LOCATION;CATALYTIC ACTIVITY;SIMILARITY;PATHWAY>

Questions???