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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!.

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  1. 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”.

  2. 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 yibuchen@belen.hsc.usc.edu Dec. 6, 2007

  3. 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

  4. Polymorphisms: How different are we? Human vs. Chimp ~96% overall (~99% similar in terms of SNPs) Human vs. Human ~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

  5. 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

  6. 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

  7. How many variations are presentin 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)areover 100,000across the human genome • The short insertion/deletions are very difficult to quantify and the number is likely to fallin between SNPs and VNTR.

  8. 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.

  9. 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.

  10. From a Mutation to a SNP

  11. 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.)

  12. Coding Region SNPs • Synonymous • Non-Synonymous • Missense – amino acid change • Nonsense – changes amino acid to stop codon. Geospiza Green Arrow™ tutorial by Sandra Porter, Ph.D.

  13. 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.

  14. 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.

  15. 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/

  16. 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 Initiativehttp://www.hgvs.org/dblist/dblist.html

  17. 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).

  18. dbSNP Data Stats (build 128, Oct, 2007) http://www.ncbi.nlm.nih.gov/SNP/snp_summary.cgi

  19. 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)

  20. 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

  21. From Submitted Record to Reference SNP Cluster SNP position mapped to the reference genomic contigs SNPs records submitted by researchers 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

  22. 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.

  23. Search SNPs from dbSNP Web Page • dbSNP Web site http://www.ncbi.nlm.nih.gov/SNP/index.html

  24. 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.

  25. 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=

  26. 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

  27. Entrez SNP Search Results Example 1

  28. 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

  29. dbSNP Ref SNP Record Example 1: SNP position and the flank region

  30. 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.

  31. 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.

  32. 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.

  33. 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.

  34. dbSNP Ref SNP Record Example 1: GeneVeiw and SequenceView of ALL SNPs

  35. dbSNP Ref SNP Record Example 1: Links to View SNPs on 3D Structure, Conserved Domains, and Multiple Sequence Alignment

  36. 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

  37. Search dbSNP: SNP Links from Entrez Gene Record

  38. Search dbSNP: SNP Display Using NCBI Map Viewer

  39. Search dbSNP: Configure Map Viewer to Display other Relevant Data

  40. 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

  41. SNPs Display in Map Viewer: Legend

  42. 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.

  43. Online Mendelian Inheritance in Man Stats • http://www.ncbi.nlm.nih.gov/Omim/mimstats.html

  44. 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.

  45. 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 disease-producing 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

  46. Sequence variations view in UniProt Beta http://beta.uniprot.org/uniprot/P38398

  47. 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

  48. 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 identifythe 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

  49. Assessing Polymorphisms: Linkage Disequilibrium, Haplotype Block, and Tag SNPs Adapted from Nature 426, 6968: 789-796 (2003) • 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.

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