Paper presentation @DILS'07
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Accelerating Disease Gene Identification Through Integrated SNP Data Analysis
![Overall goal ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Build a flexible data infrastructure to support current biology research involving gene polymorphism (SNP)](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Paper presentation @DILS'07
- 1. Accelerating Disease Gene Identification Through Integrated SNP Data Analysis Paolo Missier , S. Embury, C. Hedeler, M. Greenwood School of Computer Science, University of Manchester, UK J. Pennock, A. Brass School of Biological Sciences, University of Manchester, UK DILS ’07, Philadelphia, USA
- 8. Group strain score model Strains Corresponding alleles For each SNP : Common, distinct non-null alleles Distinct non-null alleles in A 1 , A 2 : Penalties:
- 9. Example
- 16. SNPit access from a workflow
- 17. SNP DB dependencies Ensembl Mouse (407,000) NCBI dbSNP Perlegen Public submission from multiple sources join rsId rsId ssId ssId join SNPs Strain alleles SNP Provenance Multiple SNPs strains Load Load Load Sanger institute Primary sources Updates Updates Tot 407,000 Tot 420,000 147,000 146,000 14,000 133,000 132,000 (420,000) (all figures relative to chromosome 12)
- 19. Missing strains – chr 17
- 20. Effect of source selection Ensembl Perlegen
- 24. DB overlaps Perlegen 291,718 Ensembl 253,862 dbSNP (Chromosome 17) 50,564 122,938 105,265 243,702
Hinweis der Redaktion
- QTL mapping is a powerful tool to determine the role of host genetics in disease phenotypes. In theory the genes involved in any trait that is measurable can be determined, eg weight, height etc. aswell as disease.
- When studied in detail, this QTL turned out to be two separate peaks associated with different disease phenotypes, however each region was very large. The number of genes in this region is XX – sequencing the whole area would take a long time and a lot of resources. Is this necessary with the information publicly available? BY comparing parental strain SNPs, is it possible to pinpoint the areas of greatest difference between parental strains in order to prioritise the candidate gene search? After all, although 1 SNP in a gene can make a significant difference, 50 SNPs will make more!
- Inbred strains are genetically similar The arrangement of SNPs across the mouse genome falls into blocks which are common among strains ( haplotypes ) One of the arguments for this being a good strategy is previous work which suggests that inbred strains are not as genetically diverse as previously thought. In fact the arrangement of SNPs across the mouse genome falls into blocks which are common among strains. These blocks define haplotypes (patterns) across the genome, and areas of high or low diversity. This can be demonstrated by the QTL area of chromosome 12 just shown (click for red box). It can be clearly seen that the susceptible mouse (top row – purple box) is different from the two resistant strains (AJ and BALBc – yellow blocks). This is useful because if an offspring inherits a block of susceptible DNA, which is 80% similar to the resistant strain, then the only point of interest will be the 20% that is different (click for blue block as example).
- A SNP in which the allele for the selected strain is different from that observed in all the others supports the hypothesis that the SNP plays a role in the phenotype associated with the selected strain; the SNP should therefore receive a high score
- One of the arguments for this being a good strategy is previous work which suggests that inbred strains are not as genetically diverse as previously thought. In fact the arrangement of SNPs across the mouse genome falls into blocks which are common among strains. These blocks define haplotypes (patterns) across the genome, and areas of high or low diversity. This can be demonstrated by the QTL area of chromosome 12 just shown (click for red box). It can be clearly seen that the susceptible mouse (top row – purple box) is different from the two resistant strains (AJ and BALBc – yellow blocks). This is useful because if an offspring inherits a block of susceptible DNA, which is 80% similar to the resistant strain, then the only point of interest will be the 20% that is different (click for blue block as example).