Human SNPs in microRNA Target Sites
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Human SNPs in microRNA Target Sites

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Human SNPs in microRNA Target Sites by Brian Magnuson and Yasin Senbabaoglu

Human SNPs in microRNA Target Sites by Brian Magnuson and Yasin Senbabaoglu

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    Human SNPs in microRNA Target Sites Human SNPs in microRNA Target Sites Presentation Transcript

    • SNPs in the human genome that lie within predicted miR NA target sites MiR kat Manor presents 19 December, 2007 Yasin “ Yossarian ” Ş enbabaoglu Brian “ Zaphod ” Magnuson . _
    • Introduction to microRNAs
      • subclass of small, non-coding RNA
      • mature miRs: 19-23nt ssRNA
      • regulates gene expression at the level of translation
      • binds to mRNA mRNA degradation (plants) blocks translation (animals)‏
    • miRNA processing
      • transcription of gene (pri-miRNA)
      • pre-processing by Drosha (pre-miRNA)
      • nuclear export
      • post-processing by Dicer (mature miRNA) 5. RISC complex formation 6. target mRNA binding 7. translational inhibition
    • miRNA processing images from Ambion, Inc. (www.ambion.com)‏
    • miRNA processing
    • miRNA processing
    • miRNA processing
    • miRNA processing
    • miRNA processing
    • miRNA processing
    • miRNA processing
    • miRNA structure 5' 3'
      • 8mer seed region
      • highly conserved
      • target site complementation crucial
      • variable-length non-seed region
      • less conserved
      • less complementation
    • Hypotheses 1. If SNPs in human populations exist in miR target sites, there may be a real, functional effect in vivo . 2. Given the importance of the 8mer seed, SNPs in target site may show a bias toward being within the seed region.
    • miR targets (miRBase)‏ SNPs (HapMap)‏ data sources Generating a set of SNPs in miR targets miRBase http://microrna.sanger.ac.uk/ Wellcome Trust Sanger Institute algorithm: miRanda 3.0 targets: v5 (12 November 2007) miR source: miRNA Registry release 9.0 genome source: Ensembl 40 3'UTRs International HapMap Project http://hapmap.org/ Release 22 genome source: NCBI build 36 Populations: YRI – Yoruban in Ibadan, Nigeria CHB – Han Chinese in Beijing JPT – Japanese in Tokyo CEU – European descent in Utah
    • miR targets (miRBase)‏ SNPs (HapMap)‏ filters filters hsa targets hsa miRs unique targets 3'UTR frequency cutoff split by chromosome split by chromosome data sources filtered targets filtered SNPs Generating a set of SNPs in miR targets
    • miR targets (miRBase)‏ SNPs (HapMap)‏ filters filters hsa targets hsa miRs unique targets 3'UTR frequency cutoff split by chromosome split by chromosome data sources filtered targets filtered SNPs merge via chromosomal coordinates tarSNPs Generating a set of SNPs in miR targets
    • miR targets (miRBase)‏ SNPs (HapMap)‏ filters filters hsa targets hsa miRs unique targets 3'UTR frequency cutoff split by chromosome split by chromosome data sources filtered targets filtered SNPs merge via chromosomal coordinates tarSNPs STATISTICS seed non seed Generating a set of SNPs in miR targets 5' 3'
    • Z-scores and Hypothesis Testing For each chromosome of each population, we need to determine whether the target site SNPs have a bias to be inside or outside the seed region (8-mer) We find the proportion of SNPs within seed regions and standardize them using z-scores. But, is the normality assumption valid? Z-score:
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    • Distributional Model Chromosome I for population J X IJK ~ Bernoulli(p)‏
    • Distributional Model Chromosome I for population J X IJK ~ Bernoulli(p)‏
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    •  
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    • miRNA structure 5' 3'
      • 8mer seed region
      • highly conserved
      • target site complimentation crucial
      • variable-length non-seed region
      • less conserved
      • less complimentation
    • Further studies
      • Compare free energy of binding of different allelic variants
      • Compare predicted target sites to experimentally verified sites
      • Compare known genes to predicted genes
      • Compare 3'UTR SNPs in and out of target binding sites
      • Explore conservation across species
      • Group target SNPs intelligently (specific cellular processes, tissue and system specific, human health conditions)‏
      • Apply methods to specialized polymorphism data, such as cancer SNPs
    • Acknowledgments Chris Maher post-doc in Arul Chinnayan's Lab (Pathology)‏ Animal Planet vegetables