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Online Resources for Genetic Variation Study – Part One Workshop Attendees: Please complete the workshop sign-in form. To help us develop bioinformatics workshops that are more relevant to your research, please take our online User Needs Survey, thanks! NML Bioinformatics Service User Needs Survey: From the NML-Bioinformatics Web Page Click the NML Support Requests under the “Support Request Section” Click the “this online user needs survey” under the “Tell us how to serve your information needs better! Section”. Online Resources for Genetic Variation Study – Part One Yi-Bu Chen, Ph.D. Bioinformatics Specialist Norris Medical Library University of Southern California 323-442-3309 [email protected] Dec. 6, 2007 Workshop Outline Overview of Bioinformatics Support Program at NML Human Genetic Variation Overview Main types of genetic variations Basics of the single nucleotide polymorphisms (SNPs) NCBI Genetic Variation Resources: dbSNP and OMIM dbSNP overview dbSNP search examples OMIM overview International HapMap Project The HapMap project: overview and major findings HapMap search examples The Perlegen Genetic Variation Database Genome Variation Server (SeattleSNPs) Ensembl SNPs Hands-on Search Question Polymorphisms: How different are we? Human vs. Chimp Human vs. Human ~96% overall (~99% similar in terms of SNPs) ~99.9% similar with around 3.2 million single nucleotide differences (account for up to 90% of all genomic variations, total possible SNPs near 12 millions) Adapted from a lecture slide by Jonathan Wren, NYU Why do we care about genetic variations? 1. Genetic variations underlie phenotypic differences among different individuals 2. Genetic variations determine our predisposition to complex diseases and responses to drugs and environmental factors 3. Genetic variations reveal clues of ancestral human migration history Main Types of Genetic Variations A. Single nucleotide mutation Resulting in single nucleotide polymorphisms (SNPs) Accounts for up to 90% of human genetic variations Majority of SNPs do NOT directly or significantly contribute to any phenotypes B. Insertion or deletion of one or more nucleotide(s) 1. Tandem repeat polymorphisms Tandem repeats are genomic regions consisting of variable length of sequence motifs repeating in tandem with variable copy number. Used as genetic markers for DNA finger printing (forensic, parentage testing) Many cause genetic diseases Microsatelites (Short Tandem Repeats): repeat unit 1-6 bases long Minisatelites: repeat unit 11-100 bases long 2. Insertion/Deletion (INDEL or DIPS) polymorphisms Often resulted from localized rearrangements between homologous tandem repeats. C. Gross chromosomal aberration Deletions, inversions, or translocation of large DNA fragments Rare but often causing serious genetic diseases How many variations are present in human genome? SNPs appear once per 0.1-1 kb interval or on average 1 per 300 bp. Considering the size of entire human genome (3.2 x109 bp), the total number of SNPs is well above 11 million. The high density and relatively easier assay make SNPs the ideal genomic markers. In sillico estimation of potentially polymorphic variable number tandem repeats (VNTR) are over 100,000 across the human genome The short insertion/deletions are very difficult to quantify and the number is likely to fall in between SNPs and VNTR. Types of Single Base Substitutions Transitions Change of one purine (A,G) for another purine, or a pyrimidine (C,T) for another pyrimidine Transversions Change of a purine (A,G) for a pyrimidine (C,T), or vice versa. The cytosine to thymine (C>T) transition accounts for approximately 2 out of every 3 SNPs in human genome. SNP or Mutation? Call it a SNP IF the single base change occurs in a population at a frequency of 1% or higher. Call it a mutation IF the single base change occurs in less than 1% of a population. A SNP is a polymorphic position where the point mutation has been fixed in the population. From a Mutation to a SNP SNPs Classification SNPs can occur anywhere on a genome, they are classified based on their locations. Intergenic region Gene region can be further classified as promoter region, and coding region (intronic, exonic, promoter region, UTR, etc.) Coding Region SNPs Missense – amino acid change Nonsense – changes amino acid to stop codon. Geospiza Green Arrow™ tutorial by Sandra Porter, Ph.D. Synonymous Non-Synonymous The Consequences of SNPs The phenotypic consequence of a SNP is significantly affected by the location where it occurs, as well as the nature of the mutation. No consequence Affect gene transcription quantitatively or qualitatively. Affect gene translation quantitatively or qualitatively. Change protein structure and functions. Change gene regulation at different steps. Simple/Complex Genetic Diseases and SNPs Simple genetic diseases (Mendelian diseases) are often caused by mutations in a single gene. -- e.g. Huntington’s, Cystic fibrosis, PKU, etc. Many complex diseases are the result of mutations in multiple genes, the interactions among them as well as between the environmental factors. -- e.g. cancers, heart diseases, Alzheimer's, diabetes, asthmas, etc. Majority of SNPS may not directly cause any diseases. SNPs are ideal genomic markers (dense and easy to assay) for locating disease loci in association studies. Main Genetic Variation Resources NCBI dbSNP http://www.ncbi.nlm.nih.gov/SNP/index.html NCBI Online Mendelian Inheritance in Man (OMIM) http://www.ncbi.nlm.nih.gov/sites/entrez?db=OMIM International HapMap Project http://www.hapmap.org/ Perlegen http://genome.perlegen.com Genome Variation Server (Seattle SNPs) http://gvs.gs.washington.edu/GVS/ Where to Find Bioinformatics Resources for Genetic Variation Studies? OBRC: Online Bioinformatics Resources Collection (Univ. of Pittsburgh) http://www.hsls.pitt.edu/guides/genetics/obrc The most comprehensive annotated bioinformatics databases and software tools collection on the Web, with over 200 resources relevant to genetic variation studies. HUGO Mutation Database Initiative http://www.hgvs.org/dblist/dblist.html NCBI dbSNP Database: Overview URL: http://www.ncbi.nlm.nih.gov/SNP/index.html The NCBI’s Single Nucleotide Polymorphism database (dbSNP) is the largest and primary public-domain archive for simple genetic variation data. The polymorphisms data in dbSNP includes: Single-base nucleotide substitutions (SNPs) Small-scale multi-base deletions or insertions variations (also called deletion insertion polymorphisms or DIPs or INDELs) Microsatellite tandem repeat variations (also called short tandem repeats or STRs). dbSNP Data Stats (build 128, Oct, 2007) http://www.ncbi.nlm.nih.gov/SNP/snp_summary.cgi dbSNP Data Types The dbSNP contains two classes of records: Submitted record The original observations of sequence variation; submitted SNPs (SS) records started with ss (ss5586300) Computationally annotated record Generated during the dbSNP "build" cycle by computation based the original submitted data, Reference SNP Clusters (ref SNP) start with rs (rs4986582) dbSNP Submitted Record Provides information on the SNP and conditions under which it was collected. Provides links to collection methods (assay technique), submitter information (contact data, individual submitter), and variation data (frequencies, genotypes). ss5586300 From Submitted Record to Reference SNP Cluster SNPs records submitted by researchers SNP position mapped to the reference genomic contigs If the SNP position not unique, it will be assigned to the existing RefSNP cluster If the SNP position is unique, a new RS# is assigned Different Ways to Search SNPs in dbSNP dbSNP Web site http://www.ncbi.nlm.nih.gov/SNP/index.html Direct search of SS record; batch search; allow SNP record submission; NO search limits Entrez SNP http://www.ncbi.nlm.nih.gov/sites/entrez?db=Snp Search limits options allows precise retrieval Entrez Gene Record’s SNP Links Out Feature Direct links to corresponding SNP records; access to genotype and linkage disequilibrium data NCBI’s MapViewer Visualize SNPs in the genomic context along with other types of genetic data. Search SNPs from dbSNP Web Page dbSNP Web site http://www.ncbi.nlm.nih.gov/SNP/index.html Search SNPs from Entrez SNP Web Page Entrez SNP http://www.ncbi.nlm.nih.gov/sites/entrez?db=Snp The dbSNP is a part of the Entrez integrated information retrieval system and may be searched using either qualifiers (aliases) or a combination search limits from 14 different categories. Entrez SNP Search Limits Organisms Chromosome (including W and Z for non-mammals) Chromosome Ranges Map Weight (how many times in genome) Function Class (coding non-synonymous; intron; etc.) SNP Class (types of variations) Method Class (methods for determining the variations) Validation Status (if and how the data is validated) Variation Alleles (using IUPAC- codes) Annotation (Records with links to other NCBI database) Heterozygosity (% of heterozygous genotype) Success Rate (likelihood that the SNP is real) Created Build ID Updated Build ID http://www.ncbi.nlm.nih.gov/portal/query.fcgi?db=Snp http://www.ensembl.org/common/helpview?kw=snpview;ref= Search dbSNP: Example 1 Some mutations on human BRCA1 gene have been reported to be involved in the early onset of breast cancer. Retrieve all validated non-synonymous coding reference SNPs for BRCA1 from dbSNP. Hint: starting from the Entrez SNP: http://www.ncbi.nlm.nih.gov/sites/entrez?db=Snp Entrez SNP Search Results Example 1 dbSNP Ref SNP Record Example 1: Summery http://www.ncbi.nlm.nih.gov/SNP/snp_ref.cgi?rs=4986852 This Ref SNP cluster contains multiple submitted SNP records from different groups dbSNP Ref SNP Record Example 1: SNP position and the flank region dbSNP Ref SNP Record Example 1: GeneView of an individual SNP Because of alternative splicing, the very same SNP can locate in different region of the transcripts. dbSNP Ref SNP Record Example 1: TableView of an individual SNP Notice that the individual SNP is mapped to the same position on the reference genomic contig, but different positions on mRNAs and proteins due to alternative splicing. dbSNP Ref SNP Record Example 1: Links to Various Annotated NCBI Databases Link to the OMIM record where documented clinical and genetic data of this SNP can be found. Warning: the lack of OMIM link does not necessary mean that this SNP is unrelated to any OMIM record. dbSNP Ref SNP Record Example 1: Population Allele Frequency, Genotype and Heterozygosity Data Link to the detailed population genotype data. Data from National Cancer Institute. Data from The NIH Polymorphism Discovery Resource Data from Centre d'Etude du Polymorphisme Human (CEPH). Data from the International HapMap Project. dbSNP Ref SNP Record Example 1: GeneVeiw and SequenceView of ALL SNPs dbSNP Ref SNP Record Example 1: Links to View SNPs on 3D Structure, Conserved Domains, and Multiple Sequence Alignment Search dbSNP: Example 2 Mutations in Dopamine Receptor 5 (DRD5) gene have been observed in patients with various neurological disorders. Find how many refSNP records have been reported for DRD5. Show all refSNPs in the context of a chromosome. Hint: starting from the Entrez Gene: http://www.ncbi.nlm.nih.gov/sites/entrez?db=gene Search dbSNP: SNP Links from Entrez Gene Record Search dbSNP: SNP Display Using NCBI Map Viewer Search dbSNP: Configure Map Viewer to Display other Relevant Data SNPs Display in Map Viewer: Legend Click on any column headings to see the refSNPs legend. http://www.ncbi.nlm.nih.gov/SNP/get_html.cgi?whichHtml=verbose SNPs Display in Map Viewer: Legend Online Mendelian Inheritance in Man (OMIM): A Brief Overview URL: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=OMIM OMIM is a human genetic disorders database built and curated using results from published studies. Each OMIM record provides a summary of the current state of knowledge of the genetic basis of a disorder, which contains the following information: description and clinical features of a disorder or a gene involved in genetic disorders; biochemical and other features; cytogenetics and mapping; molecular and population genetics; diagnosis and clinical management; animal models for the disorder; allelic variants. OMIM is searchable via NCBI Entrez, and its records are cross-linked to other NCBI resources. Online Mendelian Inheritance in Man Stats •http://www.ncbi.nlm.nih.gov/Omim/mimstats.html OMIM: Allelic Variants The OMIM database includes genetic disorders caused by various mutation/variation, from SNPs to large-scale chromosomal abnormalities. The listed allelic variants are searchable through the "Allelic Variants" field. Single nucleotide substitutions (SNPs); small insertions and deletions (INDEL/DIPS); frame shifts caused by these INDELs. Allelic variants are represented by a 10-digit OMIM number, and can be searched in two ways: Search for a gene or a disease, when retrieved, view its allelic variants. Use the Limits to narrow your search to: -- retrieve only records that contain allelic variant information; -- search for particular terms within the allelic variants field. Notes on OMIM Allelic Variants For most genes, only selected mutations are included Criteria for inclusion include: the first mutation to be discovered, high population frequency, distinctive phenotype, historic significance, unusual mechanism of mutation, unusual pathogenetic mechanism, and distinctive inheritance. Most of the allelic variants represent diseaseproducing mutations, NOT polymorphisms. A few polymorphisms are included, many of which show a positive statistical correlation with particular common disorders. Few neutral polymorphisms are included in OMIM. Some SNPs in the dbSNP records are not linked to the corresponding OMIM records. http://www.ncbi.nlm.nih.gov/entrez/dispomim.cgi?id=113705 Sequence variations view in UniProt Beta http://beta.uniprot.org/uniprot/P38398 Assessing Polymorphisms: Genotypes and Genotyping Genotype: Each person has two copies of all chromosomes except the sex chromosomes. The set of alleles at a given locus forms the genotype. Genotyping: the process of identifying what genotype a person has for any given locus (loci). Whole-genome genotyping of all SNPs in a human genome? (11.8 million and counting) Technologically daunting Prohibitively expensive and time consuming Assessing Polymorphisms: the Origin of Haplotype Two ancestral chromosomes scrambled through recombination over many generations to yield different descendant chromosomes. If a genetic variant marked by the X on the ancestral chromosome increases the risk of a particular disease, the two descendants who inherit that part of the ancestral chromosome will be at increased risk. Adjacent to the variant marked by the X are many SNPs that can be used to identify the location of the variant. Haplotype: A particular combination of alleles along a chromosome that tends to be inherited as a unit. http://www.hapmap.org/originhaplotype.html Adapted from Nature 426, 6968: 789-796 (2003) Assessing Polymorphisms: Linkage Disequilibrium, Haplotype Block, and Tag SNPs Linkage Disequilibrium (LD): If two alleles tend to be inherited together more often than would be predicted, then the alleles are in linkage disequilibrium. If most SNPs have highly significant correlation to one or more of neighbors, these correlations can be used to generate haplotypes, which represent excellent proxies for individual SNP. Because haplotypes may be identified by a much small number of SNPs (tag SNPs), assessing polymorphisms via haplotypes dramatically reduces genotyping work. Assessing Polymorphisms: Tag SNPs Tag SNP: a representative SNP enabling to infer (or predict) other SNPs of its “neighborhood” (both distance and genealogically wise). An r2 of 0.8 or greater is sufficient for tag SNP mapping to obtain a good coverage of untyped SNPs. Tag SNPs allow genotyping of a lower number of marker SNPs with very small losses in power. If LD between SNPs is low, almost every SNP might have to be genotyped to get all variation information. 51 Goals Create a public genome-wide database of common human genetic variation in the context of geographic distribution Provide such information to guide genetic studies of clinical phenotypes Phase I (Oct. 2002) One million common SNPs (every 5 kb across the genome) were genotyped in 269 DNA samples from four populations. Common SNPs : Minor Allele Frequency ≥ 0.05 YRI : Yoruba in Nigeria (30 trios), CEU : Utah with European ancestry (30 trios), CHB : 45 Han Chinese, JPT: 44 Japanese Phase II An additional 4.6 million SNPs are genotyped. ENCODE (Encyclopedia of DNA Elements) Collection of ten regions, each 500kb in length. Each 500 kb region was re-sequenced and all SNPs were genotyped. HapMap Progress PHASE I – completed 1,000,000 SNPs successfully typed in all 269 HapMap samples At least one common SNP every 5 kb across the genome ENCODE variation reference resource available PHASE II – data generation complete, about 4.6 million SNPs typed in total. ENCODE-HAPMAP – A much more detailed variation resource 48 samples sequenced All discovered SNPs (and any others in dbSNP) typed in all 270 HapMap samples Current data set – average 1 SNP every 279 bp HapMap Data Overview Basic Data: genotypes of the 270 individual samples (frequencies of SNP alleles and genotypes in each population) Recent data release (Full Data Set): January 11, 2007, NCBI B35 (includes both Phase I&II data, genotypes from Illumina 100k and 300k genotyping arrays and the Affymetrix nsSNPs) Phase I: 600,000 common SNPs in 270 individuals Phase II: 4-5 million SNPs in the same individuals Available for bulk download: All genotype data, haplotype phasing data (from PHASE) Pedigree trio files Raw LD data (D’, R2), recombination rates and hotspots Allele and genotype frequencies SNP assays and protocols Allocated SNPs (dbSNP reference clusters chosen for genotyping) Adapted from Alanna Morrison, Human Genetics Center, Feb. 2007 lecture Major Findings of the HapMap Project Extensive Redundancy of SNP: over 90% of all SNPs on the map have highly statistically significant correlation to one or more neighbors. Confirmed the generality of recombination hotspots and long segments of strong LD (Haplotype blocks), with the average length ranging from 7.3 (YRI) to 16.3 kb (CEU), and between 65-85% of human genome presented in such blocks. Revealed limited haplotype diversity: while each haplotype block contains 30-70 SNPs, on average only 4-5.6 common haplotype blocks exist, which can be further identified by a smaller number of SNPs (tag SNPs). The density of common SNPs can be reduced by 75–90% with essentially no loss of information. That is, the genotyping burden can be reduced from one common SNP every 500 bp to one SNP every 2 kb (YRI) to 5 kb (CEU and CHB/JPT). What can you do from the HapMap Web Site? Search for SNPs in a gene or any region of interest (ROI). View patterns of LD in the ROI. Select tagSNPs in the ROI. Download information on the SNPs in ROI for genotype/haplotype data analysis and visualization in Haploview or other software. Generate and retrieve customized subset data. Download the entire data set in bulk. Search HapMap: Example 1 SNPs in human BRCA1 gene have been reported to be involved in the early onset of breast cancer. Find all available genotype and LD data for SNPs documented for BRCA1 in HapMap database. http://www.hapmap.org/ HapMap Search Example 1 Step 1: Open the Genome Browser with the Latest Full Data Set Click “HapMap Genome Browser (B35 full data set)” HapMap Search Example 1 Step 2: Specify the landmark/region of interests Enter gene name “brca1” to specify the region of your interest When there are multiple transcripts, click one of your choice HapMap Search Example 1 Step 3: Examine and determine the desired region for display The mRNA Examine the region for display using different scales Genotype frequency Genotyped SNPs in the region, pie chart shows allelic frequencies (ref vs other) HapMap Search Example 1 Step 4: display genotype data for each refSNP HapMap Search Example 1 Step 5: Select the desired tracks for display Select the desired analysis results for display Click “Update Image” once the configuration is done HapMap Search Example 1 Step 6: Configure the tag SNP Picker Select the desired population Select the desired tagging methods Select r2 value to set desired stringency Set MAF for the lowest threshold of alleles to be captured by the tagged SNPs Specify SNPs to be included/excluded as tagged SNPs HapMap Search Example 1 Step 7: Configure the LD Plot Configure LD plot display Select LD measurement and range Select desired populations Customize the color display for LD value HapMap Search Example 1 Step 8: Tag SNPS and LD Plot Genotyped SNPs in the region LD plot shows LD between different pairs of SNPs Tagged SNPs based on your criteria HapMap Search Example 1 Step 9: Download various data and files Click “Go” The genotype data can be used for in depth LD and Haplotype analysis with the free Haploview program. Select desired data or file for download Haploview-http://www.broad.mit.edu/mpg/haploview/ Haploview Screenshots HapMap Data Extraction using HapMart Select desired population www.hapmap.org HapMap Data Extraction using HapMart: Data filter and export Perlegen Sciences Found in 2000 with the mission of identifying clinically relevant patterns of genetic variation. Over 1.6 millions common SNPs genotyped from 71 individuals from 3 American populations of European, African and Asian ancestry (about 1 SNP/1871 bp) GWA studies on over 100,000 different human individual. Re-sequenced the nuclear DNA genomes of 15 inbred laboratory mouse strains and generated genotype data. Specialized Mouse Genome Brower allows users visualize the SNPs and LR-PCR primer pairs and access the SNP genotypes for the 15 strains http://mouse.perlegen.com/mouse/browser.html Perlegen Human Genotype Brower http://genome.perlegen.com/cgi-bin/gbrowse/ Perlegen Human Genotype Brower Hosting raw genotyping data for 4.5 million human SNPs from HapMap, Perlegen, and other projects. Generated SNPs data on candidate genes involved in cardiovascular diseases and inflammatory process. Tools for searching, visualization and analysis of genotype data for association studies. Merging SNP data sets from different populations. Using Genome Variation Server http://gvs.gs.washington.edu/GVS/index.jsp Select the search type to start the search upload your genotype data for analysis Detailed online tutorial GVS Search Example: rs9939609 (FTO gene) Step 1: select query type 1 2 GVS Search Example: rs9939609 (FTO gene) Step 2: Select population(s) GVS Search Example: rs9939609 (FTO gene) Step 3: Configure parameters GVS Search Example: rs9939609 (FTO gene) Step 4: Display Results—Genotype data GVS Search Example: rs9939609 (FTO gene) Step 4: Display Results—Genotype data rs9939609 SNP ID Sample GVS Search Example: rs9939609 (FTO gene) Step 5: Display results—TagSNPs TagSNPs Table Display GVS Search Example: rs9939609 (FTO gene) Step 5: Display results—TagSNPs Bin TagSNPs Graphic Display GVS Search Example: rs9939609 (FTO gene) Step 6: Display results—LD GVS Search Example: rs9939609 (FTO gene) Step 7: Display results—Summary SNPs in Ensembl http://www.ensembl.org/index.html • Most SNPs imported from dbSNP (rs……): • Imported data: alleles, flanking sequences, frequencies, …. • Calculated data: position, synonymous status, peptide shift, …. • For human also: • • • • HGVbase TSC Affy GeneChip 100K and 500K Mapping Array Ensembl-called SNPs (from Celera reads) • For mouse and rat also: • Sanger- and Ensembl-called SNPs SNPs in Ensembl MapView: SNP density on chromosome SNPs in Ensembl ContigView: SNPs in genomic context SNPs in Ensembl GeneSeqView: SNPs in genomic sequence SNPs in Ensembl TransView & ProtView: SNPs in transcript/ protein SNPs in Ensembl What SNPs does my gene contain? > GeneSNPView SNPs in Ensembl Info about one specific SNP? > SNPView: • SNP Report • Genotype and allele frequencies per population • Located in transcripts • SNP Context • Individual genotypes https://www.pharmgkb.org/index.jsp User Question A recent report (Frayling et al. Science 2007) found a common variant (rs9939609, A>T) in the FTO gene (fat mass and obesity associated) is associated with body mass index and predisposes to obesity and diabetes. The adults (16%) carrying homozygous risk allele A weighed 3 kg more and had 1.67 fold increased odds of obesity compared to those without the risk allele. Use the HapMap and dbSNP to find the genotype data of this SNP in different populations. Answer 1: Searching HapMap Use the refSNP# (must starts with rs) as the landmark for the search Click on the pie chart for detailed population genotype data Answer 1: Searching HapMap Population genotype data of the homozygous risk allele A Retrieve detailed genotyping data Answer 2: Searching NCBI’s dbSNP http://www.ncbi.nlm.nih.gov/sites/entrez?db=Snp Click on the rs record for detailed SNP data report Answer 2: Searching NCBI’s dbSNP Genotype data from Perlegen’s project with different population samples Acknowledgement In addition to those already stated, some slides of this workshop were adapted from the sources below: 1. Chattopadhyay A. and M.R. Tennant. “Genetic Variation Resources”. Lecture slides for 2007 NCBI Advanced Workshop for Bioinformatics Information Specialists. 2. Stein L. “Using HapMap.org: A tutorial”. Presentation slides as part of the Official HapMap Tutorial. 3. Overduin B. “Sequence Variation in Ensembl”. Lecture slides for “Ensembl Courses and Workshops” Recommend Topics for the Second Part of “Online Resources for Genetic Variation Study” Functional analysis of SNPs Tools for SNP discovery and genotyping Tools for TagSNPs selection Tools for genome wide association study Genetic association databases Others?? Please evaluate this workshop to help me improving future presentations: http://www.zoomerang.com/survey.zgi?p=WEB226GJV4RJWR Have questions or comments about this workshop? Please contact: Yi-Bu Chen, Ph.D. Bioinformatics Specialist Norris Medical Library University of Southern California 323-442-3309 [email protected]