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Outline to SNP bioinformatics lecture

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Outline to SNP bioinformatics lecture Brief introduction SNPs in cell biology SNP discovery SNP assessment SNP databases SNPs in genome browsers Single Nucleotide ... – PowerPoint PPT presentation

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Title: Outline to SNP bioinformatics lecture


1
Outline to SNP bioinformatics lecture
  • Brief introduction
  • SNPs in cell biology
  • SNP discovery
  • SNP assessment
  • SNP databases
  • SNPs in genome browsers

2
Single Nucleotide Polymorphisms
  • Must be present in at least 1 of the population
  • Most (90) of the sequence variation between two
    genomes
  • Two humans differ 0.1
  • 1/300 bp in the human genome
  • Lower in coding regions
  • 10 million in the human genome

3
Categories of SNPs
  • Missense/Non-synonymous
  • Changes an amino acid
  • About half of the SNPs in coding sequence
  • Can alter function and or structure of the
    protein
  • Cause of most monogenetic diseases
  • Hemochromatosis (HFE)
  • Cystic fibrosis (CFTR)
  • Hemophilia (F8)
  • Nonsense
  • Introduces a stop codon
  • Same consequences as non-synonymous

4
Categories of SNPs
  • Synonymous
  • Does not alter the coding sequence
  • May alter splicing
  • Non-coding
  • Can be located in promoter or regulatory regions
  • Can impact the expression of the gene
  • All SNPs can be used as markers

5
Use to cell biologist
  • Association studies
  • Use SNPs as markers to find regions associated
    with phenotype
  • Causative SNPs
  • Altered protein
  • Altered expression
  • Regions of altered conservation between
    strains/species/individuals
  • Evolutionary analyses
  • Etc

6
SNP discovery
  • Discovery of SNPs usually from sequencing
  • Discovery is based on separating sequencing
    errors from real differences and assessing the
    frequency in the sequenced population
  • Separation of parologous sequences
  • Validation, genotyping

7
SNP discovery resources
  • Polybayes
  • SNP discovery in redundant sequences
  • Polyphred
  • SNP discovery based on phred/phrap/consed
  • NovoSNP
  • Graphical identification of SNPs

8
Example PolyPhred
  • Detects heterozygotes from chromatograms
  • Runs together with phred/phrap/consed
  • Command line

9
SNP assessment
  • Assess SNPs for functional effects
  • Non-synonymous SNPs
  • Conservation across species
  • Amino acid properties
  • Protein structure
  • Transmembrane regions, signal peptides etc.

10
SNP assessment resources
  • SIFT
  • PolyPhen
  • Pmut
  • SNPs3D
  • PANTHER PSEC
  • TopoSNP
  • MAPP
  • Etc

11
Example SIFT
  • Sorting Intolerant From Tolerant
  • Builds an alignment of similar sequences
  • Calculates a score based on the aa in the
    alignment
  • Takes the environment into account
  • Takes the properties of the aa into account
  • Does not use structure

12
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13
SNP databases
  • Maps of SNPs in human, mouse, etc
  • Haplotype maps
  • Functional SNPs
  • Disease databases

14
SNP databases
  • dbSNP
  • F-SNP
  • HGVBase
  • PolyDoms
  • OMIN
  • Etc

15
Example dbSNP
  • 50 million submissions
  • 18 million clusters
  • 7 million in genes
  • 44 organisms
  • 91 million SNPs submitted

16
dbSNP
  • Search for SNPs, location, etc
  • Information submitted on method, flanking
    sequence, alleles, population, sample size,
    validation etc
  • Information computed on SNPs at same location
    including functional analysis, population
    diversity etc

17
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18
SNPs in genome browsers
  • Ensembl
  • UCSC

19
Example UCSC
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23
HapMap
  • Aim a haplotype map of the human genome
    describing common patterns of sequence variation
  • A haplotype map is based on alleles of SNPs close
    together are inherited together
  • HapMap will identify which SNPs are informative
    in mapping, reducing the number of SNPs to
    genotype by a magnitude
  • Populations from Asia, Europe and Africa
  • 2nd generation map with over 3.1 million SNPs

24
  • Ng PC, Henikoff S.
  • Predicting the effects of amino acid
    substitutions on protein function.
  • Annu Rev Genomics Hum Genet. 2006761-80.
    Review.
  • Bhatti P, Church DM, Rutter JL, Struewing JP,
    Sigurdson AJ.
  • Candidate single nucleotide polymorphism
    selection using publicly available tools a guide
    for epidemiologists.
  • Am J Epidemiol. 2006 Oct 15164(8)794-804. Epub
    2006 Aug 21.
  • Clifford RJ, Edmonson MN, Nguyen C, Scherpbier T,
    Hu Y, Buetow KH.
  • Bioinformatics tools for single nucleotide
    polymorphism discovery and analysis.
  • Ann N Y Acad Sci. 2004 May1020101-9. Review.
  • The International HapMap Consortium.
  • A second generation human haplotype map of over
    3.1 million SNPs.
  • Nature 449, 851-861. 2007.
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