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Cited by 22Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and AnimalsGenetic and phenotypic traits in livestock

DNA Sequence‐Based Phenotypic Association Analysis

Schork, Nicholas J., Wessel, Jennifer, Malo, Nathalie·2008·Advances in Genetics
DOI 10.1016/s0065-2660(07)00409-9
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Abstract

The availability of cost-effective, high-throughput genotyping technologies has generated a tremendous amount of interest in genetic association studies. This interest has led to the belief that one could possibly test thousands to millions of representative polymorphic sites on the genome for association with a trait or disease in order to identify the few sites that may be of relevance to the expression of that trait or disease. The choice of which polymorphic sites are "representative" and to be interrogated in such studies is problematic and has involved considerations of the putative functional significance of the sites as well as the linkage disequilibrium relationships between variations at those sites and other neighboring sites. We consider an obvious alternative to genotyping-based strategies and settings for association studies for which decisions about which variations to interrogate are obviated. Essentially, we anticipate a time when cost-effective, high-throughput DNA sequencing technologies are available and researchers will have actual sequence information on the individuals under study rather than information about what variations they possess at a few well-chosen polymorphic genomic sites. We consider Multivariate Distance Matrix Regression analysis to evaluate associations between DNA sequence information and quantitative traits such as blood pressure and cholesterol level. We evaluate the potential of the method in a few (albeit contrived) settings via simulation studies. Ultimately, we show that the procedure has promise and argue that consideration of DNA sequence-based association data should usher in a new era in genetic association study designs and methodologies.

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  • Multiple rare variants, both within the same gene and across different genes, collectively influence the expression and prevalence of traits and diseases in the population.

    “There are many reasons to believe that multiple rare variants, both within the same gene and across different genes, collectively influence the expression and prevalence of traits and diseases in the population at large.”

    From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [20]

  • The identification of multiple functional variants within the same gene and their association with in vitro and clinical phenotypes indicates that multiple rare variants could influence general clinical phenotypic expression.

    “Fourth, the identification of multiple functional variants within the same gene and the association of these variants with both in vitro and clinical phenotypes indicates that multiple rare variants could influence general clinical phenotypic expression20.”

    From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [20]

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Authors
Schork, N. J., Wessel, J., & Malo, N.
Affiliations
Scripps Research Institute (US)
ORCID
Venue
Advances in Genetics
Publisher
Elsevier
Published
2008
Volume
60
Pages
195-217
ISSN
0065-2660 (ISSN-L)
DOI
10.1016/s0065-2660(07)00409-9
OpenAlex
W1607581234
Cited by
22
References
52
Citations by year
2025: 1 · 2016: 1 · 2014: 2 · 2013: 3 · 2012: 2
FWCI
7.07
Type
book chapter
Language
en
Open access
closed
Locations
  • Advances in genetics (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institute on Aging (U19AG023122)
  • National Heart, Lung, and Blood Institute (5R01 HL/MH 065571-02, U01HL064777, R01HL070137, R01HL074730)
  • National Institute of Mental Health (R01MH065571)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
Keywords
genetic association studies, quantitative traits, blood pressure, cholesterol levels, next-generation sequencing, linkage disequilibrium, polymorphic sites
MeSH terms
Animals, Humans, Models, Genetic, Phenotype, Sequence Analysis, DNA, Computational Biology

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