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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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A phylogeny-based sampling strategy and power calculator informs genome-wide associations study design for microbial
Maha R Farhat1, B Jesse Shapiro2, Samuel K Sheppard3
1Department of Pulmonary and Critical Care, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA ; Department of Global Health and Social Medicine, Harvard Medical School, 641 Huntington Avenue Suite 4A, Boston, MA 02115 USA.
Genome Medicine
|December 9, 2014
Summary
Selecting pathogen strains for genomic studies is crucial for understanding disease traits. This study proposes a matched sampling strategy and a phylogenetic power calculator for efficient genotype-phenotype association in pathogens like Mycobacterium tuberculosis.
Area of Science:
- Microbial genomics
- Population genetics
- Infectious disease research
Background:
- Whole genome sequencing (WGS) is vital for studying pathogen phenotypic variation, including transmissibility, virulence, and immunogenicity.
- Limited guidance exists on optimal pathogen strain selection for genotype-phenotype association studies, especially in structured bacterial populations.
Purpose of the Study:
- To address methodological questions regarding pathogen strain sampling and analysis for genotype-phenotype associations.
- To propose an efficient study design for clonal to moderately recombining pathogens.
- To introduce a power calculator for assessing study design efficiency based on phylogenetic convergence.
Main Methods:
- Consideration of general methodological questions for sampling and analysis in bacterial pathogens.
- Proposal of a matched sampling scheme as an efficient study design.
- Development of a power calculator utilizing phylogenetic convergence.
Main Results:
- A matched sampling scheme is proposed as an efficient approach for genotype-phenotype association studies.
- A novel power calculator based on phylogenetic convergence is provided.
- The proposed methodology was applied to genomic data from Mycobacterium tuberculosis and Campylobacter species.
Conclusions:
- The study provides a framework for optimizing pathogen strain selection in genomic association studies.
- The proposed matched sampling design and power calculator can enhance the efficiency and power of such research.
- This approach is applicable to diverse microbial pathogens with varying recombination rates.
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