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Principles of Pharmacogenetics: Types of Genetic Variants

Principles of Pharmacogenetics: Types of Genetic Variants

The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...

Polygenic Traits

Polygenic Traits

Polygenic Traits

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...

Genetic Variation

Genetic Variation

Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles,...

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Genetic Variant Selection: Learning Across Traits and Sites.

Laurel Stell¹, Chiara Sabatti²

¹Department of Health Research and Policy, Stanford University, Stanford, California 94305 lstell@stanford.edu.

|December 19, 2015

Summary

This study introduces a Bayesian framework for prioritizing genetic variants in resequencing studies. It enhances functional follow-up by accounting for multiple gene effects and learning variant roles across phenotypes.

Keywords:

Bayesian variant selection fine mapping pleiotropy rare variants

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Area of Science:

Genetics
Statistical Genetics
Bioinformatics

Background:

Resequencing studies identify genetic variants associated with traits.
Prioritizing variants for functional validation is a key challenge.
Understanding the joint effects of multiple genes is crucial.

Purpose of the Study:

To develop a statistical framework for prioritizing sequence variants.
To account for joint genetic effects using multivariate linear regression.
To incorporate all available information about variant function using a Bayesian approach.

Main Methods:

Utilized a multivariate linear regression framework.
Adopted a Bayesian approach to calculate posterior probabilities.
Developed two novel prior distributions for variant analysis.

Main Results:

The proposed Bayesian method coherently incorporates all information about variant function.
Novel priors facilitate learning variant roles by borrowing evidence across phenotypes and genes.
Simulations and reanalysis of sequencing data demonstrated the approach's advantages.

Conclusions:

The Bayesian framework provides a robust method for prioritizing sequence variants.
The novel priors improve the ability to identify functionally relevant sites.
This approach aids in the efficient follow-up of genetic discoveries.