Genome Browser. Background and Strategy. 12 April 2010

Transcription

1 Genome Browser Background and Strategy 12 April 2010 I. Background 1. Project definition 2. Survey of genome browsers II. Strategy Alejandro Caro, Chandni Desai, Neha Gupta, Jay Humphrey, Chengwei Luo, Sandeep Namburi, Aarthi Talla

2 I. Background Project definition

3 Project definition We have been directed: to build a genome browser featuring strains M13519 and M to build on the work of previous groups to make a significant contribution beyond what has already been achieved.

4 Project definition-introduction A genome browser is a website that provides access to an organism-specific genomic database. There are different visualization programs and databases for genome browser, but many of them provide similar tools for the users, such as: Interactive graphical map of the genome regions of interest and features search tools for relevant tags or sequence homology (BLAST)

5 Project definition General Description GENERAL Genome data in our genome browser will include : 1. The assembled genome sequence from N. meningiditis M16917 and M Features (genes, srnas,) identified by homology (BLAST) and ab-initio gene predictors. 3. Functional annotation of predicted genes, operon prediction and metabolic pathway reconstruction 4. Ontological linkages between features.

6 Project definition Specific Description SPECIFIC Our genome browser will explore the findings of the functional annotation and comparative genomic group related to: 1. Phylogenetic relation of the strains Whole genome tree ANI Intra-contig local syntheny 2. Genomic basis of pathogenicity Capsule genes (capsule polymerase) Opa, Opc, (recognition of different host receptors ) 3. Genomic basis for non- groupability (M16917) (polyaglutinator) but serogroup B 4. Genomic basis for discrepancy on test results (M13519): Serogroup C SGS-PCR (serogroup-specific PCR assays) but serogroup W135 agglutination test.

7 I. Background 2. Survey of genome browsers

8 Scale of a genome browser One model genome, or a few representatives of one species Flybase, Wormbase Several genomes of a certain type GenoList (microbial genomes) Psuedomonas (7 species, 18 strains) Hundreds or thousands Separated into organism families GenoScope (the platform shared by NeMeSys) UCSC

9 genolist home

10 genolist search

11 genolist results

12 genolist analysis tools

13 genolist alignment

14 genolist seqlogo

15 genolist jalview

16 microbes home

17 microbes genome info top

18 microbes genome info foot

19 microbes browser

20 microbes phylo tree

21 NeMeSys

22 nemesys circular genome viewer

23 nemesys details

24 UCSC browser MC58

25 Psuedomonas aeruginosa - search

26 Psuedo tools

27 Psuedo tools

28 Psuedo synteny

29 NBase

30 Database models How are the databases for these web applications implemented? Flat files - plain text tables examples include GBrowse, CGView RDBMS May be standard (like Chado, an extensive model organism db schema) May be created in-house, which is probably the case with many of these multiple genome online databases

31 NBase has a hybrid schema The next few slides show it Bio::DB::GFF which is the GBrowse default

32 Bio::DB::GFF

33 InterProScan

34 Blast, SignalP, Tmhmm, etc.

35 Chado

36 Survey Conclusions Genome browsers generally provide Search forms for querying the database, including BLAST Detailed profile for each genome feature hyperlinks to more detailed information in external databases such as KEGG,... Graphical viewer Analysis tools Genome data downloads

37 Survey Conclusions Backend implementation, the database design of these genome browsers, is kind of a mystery, we don't have access to their schemas unless they are using a standard one like Chado, GFF, BioSQL They might be using a home-built or modified schema customized for their purposes

38 III. Strategy 1. Data Collation 2. Browser Design

39 DATA COLLATION 1) Assembly, Prediction, Annotation and Comparative Genomics provide us with data which are compiled into a searchable database. 2)Along with that we will also compile this data in special formats used by other tools like BLAST and the SYNTENY VIEWER.

40 BASIC BROWSER DESIGN While using our website, the user may follow certain paths in their workflow, starting with the home page. From Home access is provided to a genome viewer (to a selected contig in a selected genome) Search forms for querying the database From search results, access to Feature Details A BLAST search From BLAST results, access to Feature Details An MLST typing tool Comparative genomics data ( Synteny, Phylogeny, Genome characteristics profiles)

41 From the viewer : In the viewer, you see a positional overview of selected feature types. Feature Details: a page where all data in the database on a feature is shown From Details, link back to the viewer From Details, links to external databases (KEGG, Pubmed) From Details, link to a BLAST search (homology search)

42 Information Flow ASSEMB LY GENE PREDICTIO N FUNCTIONA L ANNOTATIO N COMPARITIV E GENOMICS NEMO SEARCH DOWNLOA D VIEWE R MLST BLAST FEATU RE DETAIL S

43 TASK DECOMPOSITION: SEARCH SEARCH Contig Gene Protein GO Others

44 CONTIG GENE Strain Name Length Type PROTEIN Name Uniprot ID GO OTHERS Name Type KEGG Pubmed ID E.C Interpro ID

45 TASK DECOMPOSITION:VIEWER VIEWER CONTIG VIEWER CG VIEWER BLAST VISUALIZATI ON PHYLOGENY SYNTENY HGT

46 DOWNLOAD Neisseria GENOMES This is the overview of the strategy we plan to follow for presenting Neisseriagenome database (NeMO) that will provide graphical interface of M13519 & M16917 Neisseria strains and a comprehensive search tool.

47 Questions / Feedback Next: 14 April 2010 Preliminary Results Data Collation Implementation of browser applications Lab Exercise Data Collation and provisioning GBrowse with FAM18 (Tentative)