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SUMMARY:“A genetic study of type 2 diabetes - fine mapping\, targeted se
 quencing and subsequent functional analyses” - Seminar by Dr Toby Andrew
    Genomics of Common Disease Department of Medicine Imperial College
DTSTART:20170706T120000Z
DTEND:20170706T130000Z
UID:TALK73391@talks.cam.ac.uk
CONTACT:48007
DESCRIPTION:Numerous empirical genomic studies and long established geneti
 c theory show that complex traits - including many common diseases - are l
 ikely to be polygenic with numerous non-coding variants conferring risk of
  disease via the regulation of gene expression and post-translational modi
 fication. While ever increasing sample size and imputation are presented a
 s the solution to relatively underpowered genome-wide association studies\
 , improved study design (for example to minimise disease and genetic heter
 ogeneity) and the importance of genetic marker coverage continue to be neg
 lected. Here we use genetic maps and multi-marker method of association ba
 sed upon the Malécot-Morton model to map a total of 173 type 2 diabetes d
 isease (T2D) susceptibility loci in European and African American samples.
  In addition\, we use the same mapping methods and adipose expression data
  to show that approximately 2/3 of these disease loci appear to act as exp
 ression Quantitative Trait Loci regulating neighbouring genes (cis-eQTLs)\
 , thereby posing testable molecular mechanisms and pathways for conferring
  risk of T2D disease.\n \nThe use of genetic maps provide the following ad
 vantages over single SNP tests of association: 1) additional power by the 
 inclusion of  “out-of-sample” high-coverage linkage disequilibrium (LD
 ) information with gene mapping methods being more efficient using markers
  located upon genetic rather than physical maps\; 2) the model is more sen
 sitive than single SNP tests to detect functional variants that are potent
 ially in LD with a combination of neighbouring genotyped markers\, but not
  necessarily in high LD with any single genotyped marker\; 3) greater comm
 ensurability between different SNP array platforms and a biologically mean
 ingful integration of functional annotation upon genetic maps\; 4) the mod
 el is highly interpretable\, both in terms of population genetic theory an
 d in the context of association mapping by providing precise genetic locat
 ion estimates for putative functional variant(s) in a region.\n
LOCATION:Seminar Room\, Strangeways Research Laboratory\, Worts Causeway\,
  CB18RN
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