Genome Annotation and Databases Genomic DNA sequence Genomic

Genome Annotation and Databases Genomic DNA sequence Genomic annotation Reading Ch 9, Ch 10 BIO 520 Bioinformatics Jim Lund

Genome Annotation • Find known repeats • Search for new repeated sequences • Predict Genes – BLASTX – Genewise, Fgenes, Genscan… • Integrate other data sources. Accuracy highest in “high homology” class

Genome annotation servers • Integrate information from several maps – DNA sequence (contigs, quality). – Physical (cytogenetic, STS content). – Genes (show gene annotations and evidence). • Several prediction programs. • Expressed sequence tags (ESTs, Unigene clusters) • Evidence (Predicted, confirmed) • Non-coding RNA (nc. RNA) transcripts. – Variation (e. g. , SNPs) – Regions of shared synteny.

Data Release • Human genome sequence released under 1996 Bermuda rules – Assembled sequence greater than 1000 bp long is deposited in public database (Gen. Bank/EMBL/DDBJ) every 24 hours – No patents are filed • Bermuda principles reaffirmed at January 2003 WT/NIH meeting – Pre-release of data for all “community projects” – Nature 421 , 875 (2003) – NHGRI: • http: //www. genome. gov/page. cfm? page. ID=10506376 – WT: • http: //www. wellcome. ac. uk/About-us/Policy-and-positionstatements/WTD 002751. htm • Benefits of Open Data Access supported by OECD report – http: //dataaccess. ucsd. edu

Accessing the Genome • Genomes sequences are becoming available very rapidly – Large and difficult to handle computationally – Everyone expects to be able to access them immediately • Bench Biologists – – Has my gene been sequenced? What are the genes in this region? Where all the GPCRs Connect the genome to other resources. • Research Bioinformatics – Give me a dataset of human genomic DNA. – Give me a protein dataset.

Getting information out • Search/browse to find the gene or region. • Export formats: – Screen shot – FASTA seq. – Genbank file with features annotated – Feature list (Gff, tab-delimited text) – Pip (plot of sequence identity between organisms).

Challenges • Scale and data flow – Presentation, ease of use. – Engineering problems. – User interface design. • Algorithmic – Partly engineering (pre-compute hard computations, etc. ) – Partly research.

NCBI sequence assembly (sequence chromosome) • Remove contaminants • Bin by chromosome arms • Sequence Layout • Sequence Building • Place on chromosomes http: //www. ncbi. nlm. nih. gov/genome/guide/build. shtml

NCBI sequence assembly - a modified greedy approach Sequence Layout • Curated Finished Regions • Curated assembly instructions • Mega. BLAST hits • Consider clone order • BAC chromosome assignment • annotation • STS markers • personal communication • Remove conflicting overlaps, redundant BACs Sequence Building • Consider fragment: fragment sequence overlaps for each BAC pair in layout • Meld overlapping sequence • Order and Orient (o+o ): • alignments (m. RNA, EST) • BAC annotation • paired plasmid reads BAC Sequence Fragments Assemble Order NCBI Contig

NCBI Genome Build Process db. SNP STS Clones Genome. Scan Collaboration Curation Gen. Bank Locus. Link Ref. Seq Locus. Link Assembly Contig Build & Release Freeze Input Data: Sequences Curated NTs TPF BLAST hits Exclude Problem accessions Annotation Update: Links gi’s Prepare for release Resource Updates Public Release Analysis & Review Corrections for next build Sequences (contig m. RNA protein) Map Viewer FTP BLAST Input Resources

What is being annotated? Feature Genes: Method By alignment, by prediction Markers: By e. PCR Variation: By alignment Clones/Cytogenetic location: Phenotype (MIM): Cytogenetic Position: By alignment (BAC ends) Via Gene identification, associated markers By annotated BAC-END sequenced clones By FISH-mapped clones used in assembly

Ref. Seq: a reagent for Contig Annotation genome Ref. Seq m. RNAs Gen. Bank m. RNAs ESTs TBLASTN RPSBLAST Genome. Scan Potential Problems With ESTs: • Gene Families • Partial • Chimeric • Intron read-through • Linker • Vector • Wrong organism Ref. Seq Advantages: • Separate Gene Families • Not Partial • Means to correct problem sequences Ref. Seq process results in excluding problem Gen. Bank sequences from annotation pipeline

NCBI: Products of annotation • • Ref. Seqs (transcripts, proteins) Gene id (Locus. ID) features in chromosome coordinates features in contig (NT accession) coordinates Available in: • Map Viewer – Graphical display – Tabular display – Sequence downloads • FTP – Ref. Seqs (contigs, transcripts, proteins) – Mapping Data – Locus. Link & Other resources

NCBI Map Viewer

NCBI Map Viewer: Tabular report

Genes in regions of conserved synteny Anchored by human gene order Anchored by mouse gene order

Chromosomal segments in dog conserved with human and mouse Dog: 38 autosomes + sex chr

Query by sequence: Review the alignment A click away: • Alignments (BLAST hit) • Gene Description (Locus. Link) • Report of all features in the region • Contig sequence • Sequence in the region • other m. RNAs aligning in the region • Define your own gene model based on alignments in the region

Quality Control - Genome review • • Is the sequence correct? Is the feature correctly placed? Is there a feature that should be placed? Are the attributes of the feature correct? Approaches: • In-house analysis & review (manual curation) • Shared information (UCSC/Ensembl) • Solicited review by experts in local regions

Ensembl Annotation pipeline • Set of high quality gene predictions – From known human m. RNAs aligned against genome – From similar protein and m. RNAs aligned against genome – From Genscan predictions confirmed via BLAST of Protein, c. DNA, ESTs databases. • Initial functional annotation from Interpro • Integration with external resources (SNPs, SAGE, OMIM) • Comparative analysis between mouse/human – DNA sequence alignment – Protein orthologs

Ensembl gene prediction pipeline DNA Repeat. Masker Genscan Blast genscan peptides v Protein, unigene, est, vert mrna Mini. Genewise Mini. Est 2 genome Genes Pmatch all human Proteins and cdnas

Genome Annotation The generic structure of an automatic genome annotation pipeline and delivery system

Chromosome Overview Genes and Markers 1 Mb Configuration Detailed View Genes, ESTs, Cp. G etc. 100 kb

Useful genomic annotation and browser URLs EBI/Sanger Institute Ensembl Project: http: //www. ensembl. org/Homo_sapiens/ NCBI Human Genome Browser: http: //www. ncbi. nlm. nih. gov/mapview/map_search. cgi? chr=hum_chr. inf&query The Oak Ridge National Laboratories Genome Channel: http: //compbio. ornl. gov/channel/ UCSC Human Genome Browser: http: //genome. ucsc. edu/cgi-bin/hg. Gateway The Institute for Genomic Research (TIGR): http: //www. tigr. org/

Genome annotation -things still being worked out- • Annotation servers. • Pro: make genomics information accessible to biologists without expert bioinformatics skills. • Con: makes it difficult to perform large-scale data mining. • Solution: enable more experienced users to retrieve the data they require and to run analyses locally. • Open annotation systems. • Biologists need to have access to annotations available in the community and to share their own contributions with the community. • A common protocol between systems that enables genome data to be freely exchanged • AGAVE (Architecture for Genomic Annotation, Visualization and Exchange) • Distributed Annotation System (DAS) projects

Genome annotation servers • Several ways to find information: – Search by clone, gene, EST, marker. – Browse sequence. – BLAST searches. – Homology, start in one organism, jump to the syntenic region of another.

UCSC Genome Browser http: //genome. ucsc. edu/cgi-bin/hg. Gateway