cincinnati comparative mouse genomics centers consortium: bioinformatics analysis tools for...

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Cincinnati Comparative Mouse Genomics Centers Consortium: Bioinformatics Analysis Tools for Assessment of Human Gene Polymorphisms Anil G Jegga, Sivakumar Gowrisankar, Jing Chen, Rafal Adamczak, Ashima Gupta, Marc A Ramirez, Kalyan SC Andra, James W Carman, Bruce J Aronow University of Cincinnati and Cincinnati Children’s Hospital Medical Center, Cincinnati, OH-45229 A principal goal of the NIEHS Comparative Mouse Genome Centers Consortium (CMGCC) is to systematically evaluate the effect of human genome polymorphisms on critical genes, pathways, and processes that alter the impact of environmental agents on human disease. The evaluation process is to identify polymorphisms, perform sequence analysis, and assess disease association and functional impact using mouse models. Sequence analysis provides an opportunity to prioritize the functional evaluation process in favor of polymorphisms likely to have harmful impact. The University of Cincinnati – CCMGC (Cincinnati Comparative Mouse Genomics Center; http://cmgcc.cchmc.org) has developed several bioinformatics’ analysis tools to improve visualization, assessment, and ranking of polymorphisms. We are now collaborating with the Universities of Washington and Utah and have developed methods to study all of the genes within the EGP and have focused analyses and tools development in three areas: genes, proteins, and pathways. In particular, we have analyzed most of the genes within DNA repair and cell cycle control categories. Support: NIEHS U01 ES11038 Mouse Centers Genomics Consortium Human RefSeq Proteins NCBI-dbSNP (non-EGP Genes) EGP-SNPs Domain Mapping PolyDom Pfam Domain Database Biological Implication •Text Parsing •PolyPhen/SIFT PolyDoms : We have now mapped all non-synonymous SNPs of EGP genes onto the corresponding conserved and known functional protein domains. The potential protein structure altering implications of the coding SNPs have been collected into a general visualizer for the polymorphic proteins (http://polydoms.cchmc.org) using the PolyPhen (Polymorphism Phenotyping; http://tux.embl- heidelberg.de/ramensky/) annotations and SIFT (Sorting Intolerant From Tolerant; http://blocks.fhcrc.org/~pauline/SIFT.html) server. Links to MedLine abstracts referring to the disease implications of any polymorphism of each protein is also provided when available, and are automatically updated for each of the proteins. We are also extending the mapping of the nsSNPs in the context of the 3D structure. TraFaC : To identify gene features potentially susceptible to the effects of polymorphisms, we have developed a system that uses mouse-human comparative genomic sequence feature analysis to identify conserved cis- element clusters that could act as gene regulatory regions. Our current implementation of this tool has focused on the identification and characterization of genomic features that are conserved between mouse and human (http://trafac.chmcc.org). Additional functionalities under development will allow for direct visualization of conserved features altered by insertions, deletions, and non-coding SNPs. V $E TS F/E TS 1_B 8333 -8347 V $S TA T/S TA T1_01 8335 -8355 V $E TS F/P U 1_B 8335 -8350 V $E TS F/G A B P _B 8336 -8347 V $E TS F/N R F2_01 8338 -8347 V $C LO X/C D P C R 3_01 8363 -8377 V$EVI1/E VI1_01 8373 -8388 V $E TS F/E TS 1_B 8880-8894 V $S TA T/S TA T1_01 8881-8901 V $E TS F/P U 1_B 8882-8897 V $E TS F/N R F2_01 8892-8902 V $C LO X/C D P C R 3_01 8908-8922 V$G ATA/G A TA _C 8916-8928 V $FK H D /FR E A C 2_01 8923-8938 >Seq 1 Genomic AGAGAAAATTGCTAGAGCTC AGGAGTTTGAGACCAGCCTG GGCAATAGAGTAAGACTTTG TCTCTATCAAAAATTTAAAA ATTAACTGGGCTTGGCGGTG TGCACCTGTGGTCCAGCTAC TCAGGAGGCTGAGGTGGGAG GATTGCTTGAGCCCAAGAGG TTGAGGCTGCAGTAAGCCGT >Seq 2 Genomic GACTGAGGGCTTGTGAAACA GCAAGAACCTGTCTCAAAAA ACAGTGGGCAGGGAGGGGAT TAATGAATAGGCAGCTACGT TCTGGGACTGGAGGGACTCG AGGTGGCTAGAAAGCAAGAG GTACTGGGAGACAAGGCTGC AGACATTTCTTTTTTTTTTT TTTTTTTTTGAGACAGAGTC Local Alignment Number 5 Similarity Score: 3074 Match Percentage: 51 % Number of Matches: 96 Number of Mismatches: 39 Total Length of Gaps: 52 Begins at (8281,8874) and Ends at (8416,9059) Seq 1 <--> Seq 2 Sim% No. of Nt 8281-8300 <--> 8874-8893 70% (20 nt) 8301-8310 <--> 8902-8911 90% (10 nt) 8311-8324 <--> 8923-8936 57% (14 nt) 8325-8376 <--> 8947-8998 62% (52 nt) 8378-8386 <--> 8999-9007 67% (9 nt) 8387-8416 <--> 9030-9059 90% (30 nt) Blast Z TF Binding Sites TF Binding Sites Seq 1 <--> Seq 2 Sim% Nt Hits 8301-8310 <--> 8902-8911 90% (10 nt) 3 8311-8324 <--> 8923-8936 57% (14 nt) 2 8325-8376 <--> 8947-8998 62% (52 nt) 3 8378-8386 <--> 8999-9007 67% (9 nt) 0 8387-8416 <--> 9030-9059 90% (30 nt) 4 TraFaC CMGCC-UC BIOINFORMATICS TOOLS TraFaC (http://trafac.cchmc.org) SIFT A nalysis G ene G roup N o. of G enes G enes w ith at leastone nsSNP G enes with no nsSNP N o. of nsSN Ps G enesw ith at leastone nsSN P in a Pfam Dom ain N o. of nsSN Psin Pfam Dom ains G enesw ith at leastone PubM ed R eference G enes A nalysed (% /Intolerant=N o. Intolerant/Total analysed nsSN P) CellCycle 76 56 20 159 41 69 31 35 21/82 = 26% CellDivision 17 12 5 52 7 14 10 6 7/34 = 21% CellSignaling 21 18 3 102 11 44 19 10 17/67 = 25% C ellStructure 1 1 0 1 1 1 1 0 0 D N A R epair 70 66 4 445 47 130 40 42 29/274 = 11% G ene Expression 6 3 3 10 2 2 3 2 1/7 = 14% H om eostasis 21 17 4 58 14 36 14 11 11/37 = 30% Metabolism 22 17 5 76 17 55 18 11 12/37 = 32% Total 234 190 44 903 140 351 136 117 98/538 = 26% EGP genes (234): Incidence of SNPs in the context of functional domains PolyDoms (http://polydoms.cchmc.org) PathMaker PathMaker: To represent the presence and impact polymorphisms in the context of biological pathways, we have sought to unify our representation of molecular, biological, and environmental entities such that biological knowledge from experts and biomedical literature could be assembled in a storyboard canvas. For example, the representation of a disease could consist of a biological process that is itself comprised of one or more pathways, within which, entities (gene products, complexes, and cellular and sub-cellular components) are subjected to one or more interactions and transitions to disease term associated states. We have begun the development of an application and database structure that can represent these processes, using a host of publicly available data sources including gene objects and biological ontologies to represent biomedical literature and expert knowledge. Ensembl GenBank Swiss-Prot KEGG OMIM PubMed Molecular Databases Processes & Associated Databases PathMaker Application Layers Search and Browse Organization and Modification Layer Display Layer PathMaker Canvas and Navigator Ontology Categorizer State Changer Ontology Browser Model Viewer Complex Builder Taxonomy Viewer General Search Molecule Search Ontology Explorer Generalized Biological Object Model Molecular Entities & Relationsh ips Pathways Processes & Diseases Biological Ontologies PATHMAKER: A systems biology modeling and data mining tool built on a generalized biological object model able to represent the interaction of genes, biologic processes, environment, oncogenic pathways, and disease. Biomateria l Taxon Developmental Temporal Anatomic body part organ tissue cell subcellular Proces s Physiological gene ontology molecular function biological process cellular localization Temporal Pathologic Toxicologic Injury Genomic damage SNOMED pathology ICD-9/10 OMIM Exposure Xenobiotic Microbiologic Pharmacologic Biologic Clinical Outcome Pathway Biomaterial Process_In Process_out Molecule_in Molecule_ou t Action bind dissociate activate inhibit convert PathMaker uses ontologies PathMaker uses ontologies of specific biological of specific biological domain knowledge to model domain knowledge to model the effects of the effects of environment, genetic environment, genetic variation, and therapy on variation, and therapy on oncogenic molecular oncogenic molecular pathways and disease pathways and disease processes. processes. Molecul e Gene feature promoter cis- element product transcript splice form protein domain polymorphism snp ins / del Chromosome structure damage state Chemical structure reaction Molecular Complex composition modification state Human-Mouse Comparative Genomics Analysis of OGG1 for Coding and Non-Coding Regulatory Region Conservation Genomic Sequence with Exons (red) % sequence identity conserved Cis-element density between human and mouse Regions of sequence similarity between human and mouse conserved cis-elements in 2nd intron of Ogg1 * Disease Implication Esophageal cancer (Xing et al 2001) Lung cancer (Sugimura et al 1999) Prostate cancer (Xu et al 2002) Stomach cancer (Hanaoka et al 2001) Posit.AlleleFreq#Chrom. nonsyn Arg 229 Gln 15804 G/A 0.03 840 nonsyn Ala 288 Val 17566 C/T 0.01 180 nonsyn Asp 322 Asn 18056 G/A 0.01 154 nonsyn Ser 326 Cys 18069 C/G 0.29 756 Implication * OGG1: Mapping Non-Synonymous SNPs onto Conserved Protein Domains & 3D Structure OGG1 Peptide Sequence 345 aa Protein domain-pfam00730, HhH-GPD superfamily base excision DNA repair protein Ala 288 Val Arg 229 Gln Asp 322Asn Clinical/Experimental-GeneChip DataSet Clinical/Experimental-GeneChip DataSet Questions: what are the relevant patterns for disease/biology? Questions: what are the relevant patterns for disease/biology? Controls Poly-Articular JRA Course ... 11113.3, Pauci, 1_Pauci , MTX 0 , XR_unknown 878, Pauci, 2_Poly , MTX 1 , XR_erosions 845, Spond, JAS , MTX 0 , XR_space narrowing 18057, Spond, JAS , MTX 0 , XR_sclerosis 18036, Pauci, 1_Pauci , MTX 0 , XR_normal 7029, Pauci, 1_Pauci , MTX 0 , XR_normal 894, Pauci, 2_Poly , MTX 1 , XR_normal 831, Poly, 2_Poly , MTX 1 , XR_erosions 850, Poly, 2_Poly , MTX 1 , XR_erosions 872, Poly, 2_Poly , MTX 1 , XR_space narrowing 1073, Syst, 2_Poly , MTX 0 , XR_space narrowing 1087PB, Poly, 2_Poly , MTX 1 , XR_space narrowing 9272, Poly, 2_Poly , MTX 1 , XR_unknown 1081, Poly, 2_Poly , MTX 0 , XR_space narrowing 912, Syst, 2_Poly , MTX 1 , XR_space narrowing 19, Pauci, 2_Poly , MTX 1 , XR_space narrowing 9137, Poly, 2_Poly , MTX 0 , XR_space narrowing 993, Syst, 2_Poly , MTX 1 , XR_space narrowing 8003, Pauci, 1_Pauci , MTX 0 , XR_unknown 7177, Spond, JSPA , MTX 1 , XR_space narrowing 9161, Pauci, 1_Pauci , MTX 1 , XR_normal 976, Pauci, 1_Pauci , MTX 1 , XR_normal 1083, Control, na , MTX 0 , XR_na 7145, Pauci, 1_Pauci , MTX 0 , XR_normal 7206, Pauci, 1_Pauci , MTX 0 , XR_unknown 817, Pauci, 1_Pauci , MTX 0 , XR_space narrowing 1082, Control, na , MTX 0 , XR_na 1085, Control, na , MTX 0 , XR_na 1089, Control, na , MTX 0 , XR_na 1095, Control, na , MTX 0 , XR_na 7149.3, Control, na , MTX 0 , XR_na 801, Pauci, 2_Poly , MTX 1 , XR_erosions 1087ctrl, Control, na , MTX 0 , XR_na 9245, Spond, JSPA , MTX 0 , XR_space narrowing 824, Poly, 2_Poly , MTX 0 , XR_normal 9264, Pauci, 1_Pauci , MTX 0 , XR_erosions 7118.3, Control, na , MTX 0 , XR_na 18042, Spond, JAS , MTX 0 , XR_sclerosis 7021.31, Control, na , MTX 0 , XR_na 1084, Control, na , MTX 0 , XR_na 813.3, Control, na , MTX 0 , XR_na 7108, Syst, 3_Systemic , MTX 1 , XR_normal 9150, Spond, JAS , MTX 0 , XR_sclerosis 7113.3, Control, na , MTX 0 , XR_na 242 gene s 105 Genes with Significantly Lower Expression In PolyArticular JRA 137 Genes with Significantly Higher Expression In PolyArticular JRA Individ ual: Individuals (33 patients + 12 controls)

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Page 1: Cincinnati Comparative Mouse Genomics Centers Consortium: Bioinformatics Analysis Tools for Assessment of Human Gene Polymorphisms Anil G Jegga, Sivakumar

Cincinnati Comparative Mouse Genomics Centers Consortium: Bioinformatics Analysis Tools for Assessment of Human Gene PolymorphismsAnil G Jegga, Sivakumar Gowrisankar, Jing Chen, Rafal Adamczak, Ashima Gupta, Marc A Ramirez, Kalyan SC Andra, James W Carman, Bruce J Aronow

University of Cincinnati and Cincinnati Children’s Hospital Medical Center, Cincinnati, OH-45229

A principal goal of the NIEHS Comparative Mouse Genome Centers Consortium (CMGCC) is to systematically evaluate the effect of human genome polymorphisms on critical genes, pathways, and processes that alter the impact of environmental agents on human disease. The evaluation process is to identify polymorphisms, perform sequence analysis, and assess disease association and functional impact using mouse models. Sequence analysis provides an opportunity to prioritize the functional evaluation process in favor of polymorphisms likely to have harmful impact. The University of Cincinnati – CCMGC (Cincinnati Comparative Mouse Genomics Center; http://cmgcc.cchmc.org) has developed several bioinformatics’ analysis tools to improve visualization, assessment, and ranking of polymorphisms. We are now collaborating with the Universities of Washington and Utah and have developed methods to study all of the genes within the EGP and have focused analyses and tools development in three areas: genes, proteins, and pathways. In particular, we have analyzed most of the genes within DNA repair and cell cycle control categories.

Support: NIEHS U01 ES11038 Mouse Centers Genomics Consortium

Human RefSeq Proteins

NCBI-dbSNP(non-EGP Genes)

EGP-SNPsDomain Mapping

PolyDom

Pfam Domain Database

Biological Implication•Text Parsing•PolyPhen/SIFT

PolyDoms: We have now mapped all non-synonymous SNPs of EGP genes onto the corresponding conserved and known functional protein domains. The potential protein structure altering implications of the coding SNPs have been collected into a general visualizer for the polymorphic proteins (http://polydoms.cchmc.org) using the PolyPhen (Polymorphism Phenotyping; http://tux.embl-heidelberg.de/ramensky/) annotations and SIFT (Sorting Intolerant From Tolerant; http://blocks.fhcrc.org/~pauline/SIFT.html) server. Links to MedLine abstracts referring to the disease implications of any polymorphism of each protein is also provided when available, and are automatically updated for each of the proteins. We are also extending the mapping of the nsSNPs in the context of the 3D structure.

TraFaC: To identify gene features potentially susceptible to the effects of polymorphisms, we have developed a system that uses mouse-human comparative genomic sequence feature analysis to identify conserved cis-element clusters that could act as gene regulatory regions. Our current implementation of this tool has focused on the identification and characterization of genomic features that are conserved between mouse and human (http://trafac.chmcc.org). Additional functionalities under development will allow for direct visualization of conserved features altered by insertions, deletions, and non-coding SNPs.

V$ETSF/ETS1_B 8333 - 8347

V$STAT/STAT1_01 8335 - 8355

V$ETSF/PU1_B 8335 - 8350

V$ETSF/GABP_B 8336 - 8347

V$ETSF/NRF2_01 8338 - 8347

V$CLOX/CDPCR3_01 8363 - 8377

V$EVI1/EVI1_01 8373 - 8388

V$ETSF/ETS1_B 8880-8894

V$STAT/STAT1_01 8881-8901

V$ETSF/PU1_B 8882-8897

V$ETSF/NRF2_01 8892-8902

V$CLOX/CDPCR3_01 8908-8922

V$GATA/GATA_C 8916-8928

V$FKHD/FREAC2_01 8923-8938

>Seq 1 Genomic

AGAGAAAATTGCTAGAGCTCAGGAGTTTGAGACCAGCCTGGGCAATAGAGTAAGACTTTGTCTCTATCAAAAATTTAAAAATTAACTGGGCTTGGCGGTGTGCACCTGTGGTCCAGCTACTCAGGAGGCTGAGGTGGGAGGATTGCTTGAGCCCAAGAGGTTGAGGCTGCAGTAAGCCGT

>Seq 2 Genomic

GACTGAGGGCTTGTGAAACAGCAAGAACCTGTCTCAAAAAACAGTGGGCAGGGAGGGGATTAATGAATAGGCAGCTACGTTCTGGGACTGGAGGGACTCGAGGTGGCTAGAAAGCAAGAGGTACTGGGAGACAAGGCTGCAGACATTTCTTTTTTTTTTTTTTTTTTTTGAGACAGAGTC

Local Alignment Number 5 Similarity Score: 3074 Match Percentage: 51 % Number of Matches: 96 Number of Mismatches: 39 Total Length of Gaps: 52 Begins at (8281,8874) and Ends at (8416,9059)

Seq 1 <--> Seq 2 Sim% No. of Nt8281-8300 <--> 8874-8893 70% (20 nt)8301-8310 <--> 8902-8911 90% (10 nt)8311-8324 <--> 8923-8936 57% (14 nt)8325-8376 <--> 8947-8998 62% (52 nt)8378-8386 <--> 8999-9007 67% (9 nt)8387-8416 <--> 9030-9059 90% (30 nt)

BlastZ

TF Binding Sites TF Binding Sites

Seq 1 <--> Seq 2 Sim% Nt Hits8301-8310 <--> 8902-8911 90% (10 nt) 38311-8324 <--> 8923-8936 57% (14 nt) 28325-8376 <--> 8947-8998 62% (52 nt) 38378-8386 <--> 8999-9007 67% (9 nt) 08387-8416 <--> 9030-9059 90% (30 nt) 4

TraFaC

CMGCC-UC BIOINFORMATICS TOOLS CMGCC-UC BIOINFORMATICS TOOLS

TraFaC (http://trafac.cchmc.org) TraFaC (http://trafac.cchmc.org)

SIFT Analysis Gene Group No. of Genes

Genes with at least one nsSNP

Genes with no nsSNP

No. of nsSNPs

Genes with at least one nsSNP in a Pfam Domain

No. of nsSNPs in Pfam Domains

Genes with at least one PubMed Reference

Genes Analysed

(%/Intolerant=No. Intolerant/Total analysed nsSNP)

Cell Cycle 76 56 20 159 41 69 31 35 21/82 = 26% Cell Division 17 12 5 52 7 14 10 6 7/34 = 21% Cell Signaling 21 18 3 102 11 44 19 10 17/67 = 25% Cell Structure 1 1 0 1 1 1 1 0 0 DNA Repair 70 66 4 445 47 130 40 42 29/274 = 11% Gene Expression 6 3 3 10 2 2 3 2 1/7 = 14% Homeostasis 21 17 4 58 14 36 14 11 11/37 = 30% Metabolism 22 17 5 76 17 55 18 11 12/37 = 32% Total 234 190 44 903 140 351 136 117 98/538 = 26%

EGP genes (234): Incidence of SNPs in the context of functional domains

PolyDoms (http://polydoms.cchmc.org) PolyDoms (http://polydoms.cchmc.org) PathMaker PathMaker

PathMaker: To represent the presence and impact polymorphisms in the context of biological pathways, we have sought to unify our representation of molecular, biological, and environmental entities such that biological knowledge from experts and biomedical literature could be assembled in a storyboard canvas. For example, the representation of a disease could consist of a biological process that is itself comprised of one or more pathways, within which, entities (gene products, complexes, and cellular and sub-cellular components) are subjected to one or more interactions and transitions to disease term associated states. We have begun the development of an application and database structure that can represent these processes, using a host of publicly available data sources including gene objects and biological ontologies to represent biomedical literature and expert knowledge.

Ensembl GenBank Swiss-Prot KEGGOMIM PubMed

Molecular Databases Processes & Associated Databases

PathMaker Application Layers

Search and Browse

Organization and Modification Layer

Display Layer

PathMakerCanvas and Navigator

OntologyCategorizer

State ChangerOntologyBrowserModel Viewer

ComplexBuilder

TaxonomyViewer

GeneralSearch

MoleculeSearch

OntologyExplorer

Generalized Biological Object Model

Molecular Entities &

Relationships

Pathways Processes &

Diseases

Biological Ontologies

PATHMAKER: A systems biology modeling and data mining tool built on a generalized biological object model able to represent the interaction of genes, biologic processes, environment, oncogenic pathways, and disease.

BiomaterialTaxon

DevelopmentalTemporalAnatomic

body partorgantissuecellsubcellular

ProcessPhysiologicalgene ontology

molecular functionbiological processcellular localization

TemporalPathologic

Toxicologic Injury Genomic damageSNOMED pathologyICD-9/10OMIM

ExposureXenobioticMicrobiologicPharmacologicBiologic

Clinical Outcome

PathwayBiomaterial

Process_InProcess_outMolecule_inMolecule_outAction

binddissociateactivateinhibitconvert

PathMaker uses ontologies of PathMaker uses ontologies of specific biological domain specific biological domain knowledge to model the knowledge to model the effects of environment, genetic effects of environment, genetic variation, and therapy on variation, and therapy on oncogenic molecular pathways oncogenic molecular pathways and disease processes.and disease processes.

MoleculeGenefeature

promotercis-element

producttranscript

splice formprotein

domainpolymorphism

snpins / del

Chromosomestructuredamage state

Chemicalstructurereaction

Molecular Complexcompositionmodification

state

Human-Mouse Comparative Genomics Analysis of OGG1 for Coding and Non-Coding Regulatory Region Conservation

Genomic Sequence with Exons (red)% sequence

identity

conserved Cis-element density between human and mouse

Regions of sequence similarity between human and mouse

conserved cis-elements in 2nd intron of Ogg1

* Disease Implication

Esophageal cancer (Xing et al 2001)

Lung cancer (Sugimura et al 1999)

Prostate cancer (Xu et al 2002)

Stomach cancer (Hanaoka et al 2001)

Posit. Allele Freq #Chrom.

nonsyn Arg 229 Gln 15804 G/A 0.03 840nonsyn Ala 288 Val 17566 C/T 0.01 180nonsyn Asp 322 Asn 18056 G/A 0.01 154nonsyn Ser 326 Cys 18069 C/G 0.29 756

Implication

*

OGG1: Mapping Non-Synonymous SNPs onto Conserved Protein Domains & 3D Structure

OGG1 Peptide Sequence 345 aa

Protein domain-pfam00730, HhH-GPD superfamily base excision DNA repair protein

Ala 288 Val

Arg 229 Gln Asp 322Asn

Clinical/Experimental-GeneChip DataSetClinical/Experimental-GeneChip DataSet

Questions: what are the relevant patterns for disease/biology?Questions: what are the relevant patterns for disease/biology?

Controls

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105 Genes with Significantly Lower

Expression InPolyArticular

JRA

137 Genes with Significantly

Higher Expression In

PolyArticularJRA

Individual:Individuals (33 patients + 12 controls)