Genome Annotation

Genome Annotation Daniel Lawson VectorBase @ EBI Bioinformatics tools for Comparative Genomics of Vectors

Genome annotation - building a pipeline Genome sequence Map repeats Map ESTs Map Peptides Genefinding nc-RNAs Protein-coding genes Functional annotation Release Bioinformatics tools for Comparative Genomics of Vectors

Repeat features • Genomes contain repetitive sequences Bioinformatics tools for Comparative Genomics of Vectors

Repeat features: Tandem repeats • Pattern of two or more nucleotides repeated where the repetitions are directly adjacent to each other • Polymorphic between individuals/populations • Example programs: Tandem, TRF Bioinformatics tools for Comparative Genomics of Vectors

Repeat features: Interspersed elements • Transposable elements (TEs) • Transposons, Retrotransposons etc • Entire research field in itself • Example programs: Repeatscout, RECON Bioinformatics tools for Comparative Genomics of Vectors

Finding repeats as a preliminary to gene prediction • Repeat discovery • Literature and public databanks • Automated approaches (e.g. RepeatScout or RECON) • Generate a library of example repeat sequences (FASTA file with a defined header line format) • Use RepeatMasker to search the genome and mask the sequence Bioinformatics tools for Comparative Genomics of Vectors

Masked sequence • Repeatmasked sequence is an artificial construction where those regions which are thought to be repetitive are marked with X’s • Widely used to reduce the overhead of subsequent computational analyses and to reduce the impact of TE’s in the final annotation set >my sequence atgagcttcgatagcgatcagctagcgatcaggctactattggcttctctagactcgtctatctctattagctatcatctcgatagcgatcagctagcgatcaggctactattggcttcgatagcgatcagctagcgatcaggctactattggcttcgatagcgatcagctagcgatcaggctactattggctgatcttaggtcttctgatcttct >my sequence (repeatmasked) atgagcttcgatagcgatcagctagcgatcaggctactattxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxatctcgatagcgatcagctagcgatcaggctactattxxxxxxxxxxxxxxxxxxxtagcgatcaggctactattggcttcgatagcgatcagctagcgatcaggctxxxxxxxxxxxxxxxxxxxtcttctgatcttct Bioinformatics tools for Comparative Genomics of Vectors

Masked sequence - Hard or Soft? • Sometimes we want to mark up repetitive sequence but not to exclude it from downstream analyses. This is achieved using a format known as soft-masked >my sequence ATGAGCTTCGATAGCGCATCAGCTAGCGATCAGGCTACTATTGGCTTCTCTAGACTCGTCTATCTCTATTAGTATCATCTCGATAGCGATCAGCTAGCGATCAGGCTACTATTGGCTTCGATAGCGATCAGCTAGCGATCAGGCTACTATTGGCTTCGATAGCGATCAGCTAGCGATCAGGCTACTATTGGCTGATCTTAGGTCTTCTGATCTTCT >my sequence (softmasked) ATGAGCTTCGATAGCGCATCAGCTAGCGATCAGGCTACTATTggcttctctagactcgtctatctctattagtatcATCTCGATAGCGATCAGCTAGCGATCAGGCTACTATTggcttcgatagcgatcagcTAGCGATCAGGCTACTATTggcttcgatagcgatcagcTAGCGATCAGGCTACTATTGGCTGATCTTAGGTCTTCTGATCTTCT Bioinformatics tools for Comparative Genomics of Vectors

Genome annotation - building a pipeline Genome sequence Map Repeats Map ESTs Map Peptides Genefinding nc-RNAs Protein-coding genes Functional annotation Release Bioinformatics tools for Comparative Genomics of Vectors

More terminology • Gene prediction Predicted exon structure for the primary transcript of a gene • CDS Coding sequence for a protein-coding gene prediction (not necessarily continuous in a genomic context) • ORF Open reading frame, sequence devoid of stop codons • Similarity Similarity between sequences which does not necessarily infer any evolutionary linkage • ab initio prediction Prediction of gene structure from first principles using only the genome sequence • Hidden Markov Model (HMM) Statistical model (dynamic Baysian network) which can be used as a sensitive statistically robust search algorithm. Use of profile HMMs to search sequence data is widespread Bioinformatics tools for Comparative Genomics of Vectors

Eukaryote genome annotation Find locus Genome Transcription Primary Transcript RNA processing Find exons using transcripts ATG STOP Processed mRNA m7G AAAn Translation Find exons using peptides Polypeptide Protein folding Folded protein Find function Enzyme activity A B Functional activity Bioinformatics tools for Comparative Genomics of Vectors

Prokaryote genome annotation Find locus Genome Transcription Primary Transcript RNA processing Find CDS START STOP START STOP Processed RNA Translation Polypeptide Protein folding Folded protein Find function Enzyme activity A B Functional activity Bioinformatics tools for Comparative Genomics of Vectors

Genefinding ab initio similarity Bioinformatics tools for Comparative Genomics of Vectors

Genefinding resources • Transcript • cDNA sequences • EST sequences • Other (MPSS, SAGE, ditags) • Peptide • Non-redundant (nr) protein database • Protein sequence data, Mass spectrometry data • Genome • Other genomic sequence Bioinformatics tools for Comparative Genomics of Vectors

ab initio prediction Genome Transcription Primary Transcript RNA processing ATG STOP Processed mRNA m7G AAAn Translation Polypeptide Protein folding Folded protein Enzyme activity A B Functional activity Bioinformatics tools for Comparative Genomics of Vectors

Genefinding - ab initio predictions • Use compositional features of the DNA sequence to define coding segments (essentially exons) • ORFs • Coding bias • Splice site consensus sequences • Start and stop codons • Each feature is assigned a log likelihood score • Use dynamic programming to find the highest scoring path • Need to be trained using a known set of coding sequences • Examples: Genefinder, Augustus, Glimmer, SNAP, fgenesh Bioinformatics tools for Comparative Genomics of Vectors

ab initio prediction Genome Coding potential ATG & Stop codons Splice sites ATG & Stop codons Coding potential Bioinformatics tools for Comparative Genomics of Vectors

ab initio prediction Genome Coding potential ATG & Stop codons Splice sites ATG & Stop codons Coding potential Find best prediction Bioinformatics tools for Comparative Genomics of Vectors

Similarity prediction Genome Transcription Primary Transcript RNA processing ATG STOP Processed mRNA m7G AAAn Translation Polypeptide Protein folding Folded protein Enzyme activity A B Functional activity Bioinformatics tools for Comparative Genomics of Vectors

Similarity prediction Genome Transcription Primary Transcript RNA processing Find exons using transcripts ATG STOP Processed mRNA m7G AAAn Translation Find exons using peptides Polypeptide Protein folding Folded protein Enzyme activity A B Functional activity Bioinformatics tools for Comparative Genomics of Vectors

Genefinding - similarity • Use known coding sequence to define coding regions • EST sequences • Peptide sequences • Needs to handle fuzzy alignment regions around splice sites • Needs to attempt to find start and stop codons • Examples: EST2Genome, exonerate, genewise Bioinformatics tools for Comparative Genomics of Vectors

Similarity-based prediction Genome Align cDNA/peptide Create prediction Bioinformatics tools for Comparative Genomics of Vectors

Genefinding - comparative • Use 2 or more genomic sequences to predict genes based on conservation of exon sequences • Examples: Twinscan and SLAM Bioinformatics tools for Comparative Genomics of Vectors

Genefinding - manual • Manual annotation is time consuming • Annotators use specialized utilities to view genomic regions with tiers/columns of data from which they construct a gene prediction • Most decisions are subjective and tedious to document • Avoids the systematic problems of ab initio predictors and automated annotation pipeline Bioinformatics tools for Comparative Genomics of Vectors

Manual prediction EST similarity Coding potential ATG & Stop codons Splice sites ATG & Stop codons Coding potential Bioinformatics tools for Comparative Genomics of Vectors

Manual prediction EST similarity Coding potential ATG & Stop codons Splice sites ATG & Stop codons Coding potential Predict structure Bioinformatics tools for Comparative Genomics of Vectors

Genefinding - non-coding RNA genes • Non-coding RNA genes can be predicted using knowledge of their structure or by similarity with known examples • tRNAscan - uses an HMM and co-variance model for prediction of tRNA genes • Rfam - a suite of HMM’s trained against a large number of different RNA genes Bioinformatics tools for Comparative Genomics of Vectors

Overview of current annotation system Assembled genome Sequencing centre gene predictions VectorBase gene predictions Merge into canonical set Protein analysis Display on genome browser Release to GenBank/EMBL/DDBJ Bioinformatics tools for Comparative Genomics of Vectors

Canonical predictions VectorBase gene prediction pipeline Blessed predictions Manual annotations Community submissions (Apollo) (Genewise, Exonerate, Apollo) Similarity predictions Species-specific predictions (Genewise) (Genewise) Protein family HMMs ncRNA predictions (Genewise) (Rfam) Transcript based predictions Ab initio gene predictions (Exonerate) (SNAP) Bioinformatics tools for Comparative Genomics of Vectors

VectorBase curation database pipeline for manual/community annotation Community annotation (Community representatives) Manual annotation (Harvard) Curation warehouse db Chado-XML Chado-XML Apollo Chado Apollo Community annotation GFF3 Ensembl Gene build db Bioinformatics tools for Comparative Genomics of Vectors

Genefinding - Review • Gene prediction relies heavily on similarity data • EST/cDNA sequences are vital for genefinding • Training for ab initio approaches • Similarity builds • Validating predictions • Protein data is the predominant supporting evidence for prediction in most vector genomes • Need to be wary of predicting from predictions • Genefinding is still something of a dark art • Efforts to standardize and document supporting evidence for prediction and modifications are ongoing Bioinformatics tools for Comparative Genomics of Vectors

Genefinding omissions • Alternative splice forms • Currently there is no good method for predicting alternative isoforms • Only created where supporting transcript evidence is present • Pseudogenes • Each genome project has a fuzzy definition of pseudogenes • Badly curated/described across the board • Promoters • Rarely a priority for a genome project • Some algorithms exist but usually not integrated into an annotation set Bioinformatics tools for Comparative Genomics of Vectors

Functionalannotation Bioinformatics tools for Comparative Genomics of Vectors

Functional annotation • Utilise known structure/function information to infer facts related to the predicted protein sequence • Provide users with results from a number of standard algorithms/searches • Provide users with cross-references (dbxrefs) to other resources • Assign a simple one line description for each gene product • This will never be comprehensive • This will always be somewhat general Bioinformatics tools for Comparative Genomics of Vectors

Genome annotation Genome Transcription Primary Transcript RNA processing ATG STOP Processed mRNA m7G AAAn Translation Polypeptide Protein folding Folded protein Find function Enzyme activity A B Functional activity Bioinformatics tools for Comparative Genomics of Vectors

Functional annotation - protein similarities • Predicted proteins are searched against the non-redundant protein database to look for similarities • Visually assess the top 5-10 hits to identify whether these have been assigned a function • It is important to check how the function of the top hits has been assigned in order not to transfer erroneous annotations Bioinformatics tools for Comparative Genomics of Vectors

Functional annotation - Protein domains • Protein domains have a number of definitions based on their size, folding and function/evolution. • Domains are a part of protein structure description • Domains with a similar structure are likely to be related evolutionarily and have a similar function • We can use this to infer function (& structure) for an unknown protein be comparison to known proteins • The tool of choice here is a Hidden Markov Model (HMM) Bioinformatics tools for Comparative Genomics of Vectors

Protein Domain databases • InterPro • UniProt - protein database • Prosite - database of regular expressions • Pfam - profile HMMs • PRINTS - conserved protein signatures • Prodom - collection of multiple sequence alignments • SMART - HMMs • TIGRfams - HMMs • PIRSF • Superfamily • Gene3D • Panther - HMMs Bioinformatics tools for Comparative Genomics of Vectors

Functional annotation - Other features • Other features which can be determined • Signal peptides • Transmembrane domains • Low complexity regions • Various binding sites, glycosylation sites etc. See http://expasy.org/tools/ for a good list of possible prediction algorithms Bioinformatics tools for Comparative Genomics of Vectors

Signal peptides • Short peptide sequence found at the N-terminus of a pre-protein which mark the peptide for transport across one or more membranes • e.g. SignalP Bioinformatics tools for Comparative Genomics of Vectors

Transmembrane domains • Simple hydrophobic regions which sit inside a membrane • Transmembrane domains anchor proteins in a membrane and can orient other domains in the protein correctly • Examples: Receptors, transporters, ion channels • Identified based on the protein composition using a simple sliding window algorithm or an HMM • e.g. Tmpred, TMHMM Bioinformatics tools for Comparative Genomics of Vectors

Ontologies • Use of ontologies to annotate gene products • Gene Ontology (GO) • Cellular component • Molecular function • Biological process • Sequence Ontology (SO) Bioinformatics tools for Comparative Genomics of Vectors

Other data to look at • Enzyme classification (EC) numbers • Phenotype information • Alleles • Gene knockouts • RNAi knockdowns • Expression data • EST libraries (source of RNA material) • Microarrays • SAGE tags Bioinformatics tools for Comparative Genomics of Vectors

Functional assignment • The assignment of a function to a gene product can be made by a human curator by assessing all of the data (similarities, protein domains, signal peptide etc) • This is a labour intensive process and like gene prediction is subjective • There are automated approaches (based on family and domain databases such as Panther or InterPro) but these are under-developed • Large number of predictions from a genome project remain ‘hypothetical protein’ or ‘conserved hypothetical protein’. Bioinformatics tools for Comparative Genomics of Vectors

Caveats to genome annotation • Annotation accuracy is only as good as the available supporting data at the time of annotation • Gene predictions will change over time as new data becomes available (ESTs, related genomes) • Functional assignments will change over time as new data becomes available (characterisation of hypothetical proteins) • Gene predictions are ‘best guess’ • Functional annotations are not definitive and only a guide • If you want the annotation to improve you should get involved with whoever is (or has) sequenced your genome of interest. • For vectors you can mail info@vectorbase.org with suggestions and corrections. Bioinformatics tools for Comparative Genomics of Vectors

Genome Annotation