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TSABL: Trait Specific Annotation Based Locus predictor.

Kim Lorenz1,2, Christopher S Thom1,2,3, Sanjana Adurty4

  • 1Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

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|June 15, 2022
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Summary
This summary is machine-generated.

Identifying causal variants in non-coding DNA is challenging. Trait Specific Annotation Based Locus (TSABL) predictors successfully identified biologically relevant regulatory features for various traits, aiding genetic study interpretation.

Keywords:
GWAS interpretationPleiotropyTissue specificVariant prediction

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Area of Science:

  • Genomics
  • Bioinformatics
  • Human Genetics

Background:

  • Most Genome Wide Association Study (GWAS) loci are in non-coding regions, complicating causal variant identification.
  • Regulatory elements influencing genetic traits are hypothesized to be biologically specific and distinct across unrelated traits.

Purpose of the Study:

  • To develop predictive models for identifying trait-specific regulatory features in GWAS loci.
  • To differentiate regulatory architectures associated with distinct phenotypic trait groups.

Main Methods:

  • Utilized publicly available GWAS loci and genomic annotations.
  • Developed 17 Trait Specific Annotation Based Locus (TSABL) predictors using penalized binomial logistic regression.
  • Validated models on an independent holdout set of loci.

Main Results:

  • Successfully built TSABL models for autoimmune, electrocardiogram, lipid, platelet, red blood cell, and white blood cell trait groups.
  • Models prioritized variants within existing loci and identified novel genomic regions.
  • Identified biologically relevant regulatory features specific to different trait groups.

Conclusions:

  • TSABL models effectively pinpoint biologically relevant regulatory features.
  • These models are anticipated to improve the design and interpretation of genetic studies.
  • The approach aids in understanding trait-specific genetic architectures.