Related Experiment Video
Updated: Sep 2, 2025
08:03
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
2.3K
A Phylogeny-aware GWAS Framework to Correct for Heritable Pathogen Effects on Infectious Disease Traits
Sarah Nadeau1,2, Christian W Thorball3, Roger Kouyos4,5
1Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Molecular Biology and Evolution
|August 3, 2022
Summary
Genome-wide association studies (GWAS) for infectious diseases can be improved by accounting for pathogen ancestry. A new method removes heritable pathogen effects, increasing power to detect host genetic variants when pathogen effects are strongly correlated.
Area of Science:
- Genetics
- Evolutionary Biology
- Infectious Diseases
Background:
- Genome-wide association studies (GWAS) traditionally assume sample independence.
- Infectious diseases present unique challenges for GWAS due to combined host and pathogen genetic influences.
- Pathogen transmission chains can introduce heritable effects and violate independence assumptions in host GWAS.
Purpose of the Study:
- To develop and validate a novel method for estimating and removing heritable pathogen effects prior to host GWAS.
- To enhance the power of GWAS for detecting host genetic variants by restoring sample independence.
- To assess the impact of accounting for pathogen phylogeny on host GWAS results in real-world systems.
Main Methods:
- Proposed a computational framework to model pathogen phylogeny and estimate heritable pathogen effects.
- Simulated data to evaluate the method's performance under varying degrees of heritability and phylogenetic correlation.
- Applied the framework to host-pathogen systems: Human Immunodeficiency Virus (HIV) in humans and *Xanthomonas arboricola* in *Arabidopsis thaliana*.
Main Results:
- Simulations demonstrated increased GWAS power to detect host genetic variants when pathogen effects were highly heritable and phylogenetically correlated.
- Application to HIV and *X. arboricola* systems revealed low heritability and phylogenetic correlations.
- Qualitative GWAS outcomes remained unchanged in these specific systems after correcting for shared pathogen ancestry.
Conclusions:
- The proposed method can improve GWAS power for host genetic studies of infectious diseases, particularly when pathogen effects exhibit strong phylogenetic structure.
- Previous GWAS results for HIV and *X. arboricola* are unlikely to be biased by uncorrected shared pathogen ancestry due to low heritability.
- The framework offers insights into the evolutionary dynamics of traits within pathogen populations.
Related Concept Videos
01:11Genome-wide Association Studies-GWAS
14.1K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
14.1K
02:39Gene Flow
35.5K
Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.
35.5K
01:09Mutation, Gene Flow, and Genetic Drift
59.3K
In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
59.3K
02:54Evolutionary Relationships through Genome Comparisons
6.1K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.1K
03:33Genetic Drift
40.6K
Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
40.6K
01:06Heritability
292
Heritability is a statistical concept that measures the degree to which genetic differences among individuals contribute to trait variations within a population. It is a fundamental idea in genetics, often prone to misinterpretation. Heritability is expressed as a percentage, reflecting the proportion of variation in a specific trait across a population that can be linked to genetic differences. However, it's important to understand that heritability does not determine how "genetic"...
292