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Understanding Genome

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Understanding genome through biological databases and their usages.

Understanding genome through biological databases and their usages.

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  • 1. Understanding Genome -Biological Database Overview Part-1 DAY-2, SESSION-1 (25-10-2010) Rajendra K. Labala Biomedical Informatics Centre, NICED, ICMR, Kolkata
  • 2. Major Challenges with Genomes Scientific challenge of decoding a genome from its nucleotides to a set of functional elements Development of software which is capable of storing, manipulating, and evaluating genomes Challenge of providing comprehensive and informative access to a large amount of data in a user friendly way
  • 3. The Genome Problem The problem with the genome (particularly human) is that it is “large, complicated, and opaque to analysis” Genome features to identify include:  Genes: protein coding, RNA, pseudogenes  Regulatory elements  SNPs, repeats, etc….
  • 4. Solutions Ensembl NCBI PATRIC  You will learn  Detailed overview  Sequence related information/data mining!
  • 5. The Ensembl Project Ensembl is a joint project between 3 organizations to develop a software system which produces and maintains automatic annotation on selected eukaryotic genomes  EMBL- European Molecular Biology Laboratory  EBI- European Bioinformatics Institute  WTSI – Wellcome Trust Sanger Institute
  • 6. What is Ensembl Ensembl is one of 3 main systems that are currently available that annotate and display genomic information  Ensembl  http://www.ensembl.org  UCSC Genome Browser  http://genome.ucsc.edu  NCBI Genome Browser  http://www.ncbi.nlm.nih.gov Public annotation of mammalian and other genomes Open source software Relational database system
  • 7. Genomes and Annotation Ensembl does not assembly any genome project directly  Works in relation with the sequencing centers that generate the genome assembly Ensembl provides high quality annotation for genomes that do not have existing annotation  Works in relation with genomes that do have high quality annotation
  • 8. Utilizes raw DNAsequence data from publicsourcesCreates a trackingdatabase (The “Ensembldatabase”)Joins the sequences -based on a sequencescaffold or “Golden Path”Automatically findsgenes and other featuresof the sequenceAssociates sequenceand features with datafrom other sourcesProvides a publicly Ensembl Genome Annotationaccessible web basedinterface to the database
  • 9. Ensemblgenomes57
  • 10. Species tree
  • 11. Ensembl Software System Uses extensively BioPerl (www.bioperl.org) The free MySQL database Entire Ensembl code base is freely available under Apache open source license. Mainly written in Perl, extensions in C. Some viewers have been written in Java (e.g. Apollo). Software can be accessed by FTP Possible to set up a mirror of the entire Ensembl system.
  • 12. Ensembl Databases 4 Main Databases  Ensembl Core Database  Ensembl EST Database  Ensembl Compara Database  Ensembl Variation Database Ensembl uses MySQL to store information in relational databases Ensembl also utilizes APIs (Application Programme Interfaces)  Serve as a connection between the databases and specific application programs  Ensembl has Perl API and Java API  Perl API more “complete” than Java API
  • 13. Ensembl Databases Ensembl Core Databases  Species specific Ensembl core databases that store genome sequence and annotation information  Gene, transcript, and protein models that are annotated by the Ensembl automated genome analysis  Databases also stores information about cDNA and protein alignments, as well as external references  Ex. - NCBI Numbers AB012211
  • 14. Ensembl Databases Ensembl Compara Database  Is a multi-species database that stores the results of genome wide species comparisons  The comparative genomic dataset allows for pairwise whole genome alignments  The comparative proteomics dataset allows for orthologue predictions and protein family clusters Ensembl EST  Species-specific Ensembl EST databases hold an independent EST gene set provided for all well-characterised species with a suitable amount of biological evidence. The layout of Ensembl EST Databases is identical to the Ensembl Core Database schema so that schema descriptions and API access are equally applicable Variation  The large amount of genetic variation information is organised in a set of species-specific Ensembl Variation databases.
  • 15. Data Mining with Ensembl BioMart  Generic data management system built specifically for use in Ensembl  Ensembl provide users the ability to conduct fast and powerful searches  It simplifies the task of integrating external data sets (provided by the user) with the Ensembl databases Help & Documentation Link  http://asia.ensembl.org/info/index.html
  • 16. Data mining through BioMart Choose dataset Choose data to be retrieved (attributes) Narrow your dataset (filters)
  • 17. BioMartDatasetSelect your datasetthrough the dropdownlist
  • 18. FiltersFilter your query by thegiven options
  • 19. AttributesNarrow your searchthrough these attributes
  • 20. Try Yourself Retrieve all SNPs for „novel‟ human G-protein coupled receptor genes (GPCRs – IPR000276) on chromosome 2. Retrieve the sequences of the exons of the human MEFV gene in FASTA format. Retrieve the gene structure (i.e. start and end coordinates of exons) of the mouse gene ENSMUSG00000042351. Retrieve all human disease genes containing transmembrane domains located between p11.2 and q22. The file contains a list of probeset IDs from a microarray experiment using the Affymetrix array HG-U133 Plus 2.0 (human). Retrieve the 500 bp upstream of the transcripts matching these probeset IDs. Retrieve the sequences 5kb upstream of all human „known‟ genes between D1S2806 and D1S464. Retrieve all human SNPs that have an ID from The SNP Consortium (TSC), from chromosome 6 between 15 Mb and 15.2 Mb, with 200 bases flanking sequence. Retrieve the mouse homologues of Homo sapiens genes CASP1, CASP2, CASP3, and CASP4.
  • 21. NCBI Genome projects  After DNA sequencing, several contigs were generated and are submitted to NCBI through WGS Submissions Whole Genome Shotgun Sequences WGS List Download (GenBank format  WGS  FASTA)
  • 22. NCBI GenomeProjectGo for WGS Sequences
  • 23. WGSHome Page of WGSwhere you can find theWGS project lists
  • 24. GenBankformat file forthe WGSClick on the link fordetailed view of thedata
  • 25. WGS projectpageCheck out the FASTAformat
  • 26. NCBI FTP For downloading the sequences/genomes in different required formats.  FAA (amino acid file in fasta format)  FNA (nucleic acid file in fasta format)  FFN (Coding Sequences in fasta format)  GBK (GenBank format)  PTT (CDS file in tab delimited format)
  • 27. NCBI FTP
  • 28. Genome filesin differentformatsFAA (amino acid file infasta format)FNA (nucleic acid file infasta format)FFN (Coding Sequencesin fasta format)GBK (GenBank format)PTT (CDS file in tabdelimited format)
  • 29. PATRIC WGS annotations download For details visit the website and the FAQ page http://www.patricbrc.org/portal/portal/patric/Hom e
  • 30. PATRIChome/searchpagehttp://www.patricbrc.org/portal/portal/patric/Home
  • 31. CDS linksCheck out the CDS linksfor the searchedorganism
  • 32. DownloadingCheck out differentdownloading options
  • 33. Exercise Check out all the databases thoroughly according to the given problem mentioned in “part-1.doc” file of “day-2” folder (in desktop).

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