Dataset Information

Multi-Phenotype Association Decomposition: Unraveling Complex Gene-Phenotype Relationships.

ABSTRACT: Various patterns of multi-phenotype associations (MPAs) exist in the results of Genome Wide Association Studies (GWAS) involving different topologies of single nucleotide polymorphism (SNP)-phenotype associations. These can provide interesting information about the different impacts of a gene on closely related phenotypes or disparate phenotypes (pleiotropy). In this work we present MPA Decomposition, a new network-based approach which decomposes the results of a multi-phenotype GWAS study into three bipartite networks, which, when used together, unravel the multi-phenotype signatures of genes on a genome-wide scale. The decomposition involves the construction of a phenotype powerset space, and subsequent mapping of genes into this new space. Clustering of genes in this powerset space groups genes based on their detailed MPA signatures. We show that this method allows us to find multiple different MPA and pleiotropic signatures within individual genes and to classify and cluster genes based on these SNP-phenotype association topologies. We demonstrate the use of this approach on a GWAS analysis of a large population of 882 Populus trichocarpa genotypes using untargeted metabolomics phenotypes. This method should prove invaluable in the interpretation of large GWAS datasets and aid in future synthetic biology efforts designed to optimize phenotypes of interest.

SUBMITTER: Weighill D

PROVIDER: S-EPMC6522845 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Multi-Phenotype Association Decomposition: Unraveling Complex Gene-Phenotype Relationships.

Weighill Deborah D Jones Piet P Bleker Carissa C Ranjan Priya P Shah Manesh M Zhao Nan N Martin Madhavi M DiFazio Stephen S Macaya-Sanz David D Schmutz Jeremy J Sreedasyam Avinash A Tschaplinski Timothy T Tuskan Gerald G Jacobson Daniel D

Frontiers in genetics 20190510

Various patterns of multi-phenotype associations (MPAs) exist in the results of Genome Wide Association Studies (GWAS) involving different topologies of single nucleotide polymorphism (SNP)-phenotype associations. These can provide interesting information about the different impacts of a gene on closely related phenotypes or disparate phenotypes (pleiotropy). In this work we present MPA Decomposition, a new network-based approach which decomposes the results of a multi-phenotype GWAS study into ...[more]

PMID: 31134130

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Project description:Rates of infection with hospital-acquired Acinetobacter baumannii have exploded over the past decade due to our inability to limit persistence and effectively treat disease. A. baumannii quickly acquires antibiotic resistance, and its genome encodes mechanisms to tolerate biocides and desiccation, which enhance its persistence in hospital settings. With depleted antibiotic options, new methods to treat A. baumannii infections are desperately needed. A comprehensive understanding detailing A. baumannii cellular factors that contribute to its resiliency at genetic and mechanistic levels is vital to the development of new treatment options. Tools to rapidly dissect the A. baumannii genome will facilitate this goal by quickly advancing our understanding of A. baumannii gene-phenotype relationships. We describe here a recombination-mediated genetic engineering (recombineering) system for targeted genome editing of A. baumannii. We have demonstrated that this system can perform directed mutagenesis on wide-ranging genes and operons and is functional in various strains of A. baumannii, indicating its broad application. We utilized this system to investigate key gene-phenotype relationships in A. baumannii biology important to infection and persistence in hospitals, including oxidative stress protection, biocide resistance mechanisms, and biofilm formation. In addition, we have demonstrated that both the formation and movement of type IV pili play an important role in A. baumannii biofilm. Importance: Acinetobacter baumannii is the causative agent of hospital-acquired infections, including pneumonia and serious blood and wound infections. A. baumannii is an emerging pathogen and has become a threat to public health because it quickly develops antibiotic resistance, making treatment difficult or impossible. While the threat of A. baumannii is well recognized, our understanding of even its most basic biology lags behind. Analysis of A. baumannii cellular functions to identify potential targets for drug development has stalled due in part to laborious genetic techniques. Here we have pioneered a novel recombineering system that facilitates efficient genome editing in A. baumannii by single PCR products. This technology allows for rapid genome editing to quickly ascertain gene-phenotype relationships. To demonstrate the power of recombineering in dissecting A. baumannii biology, we use this system to establish key gene-phenotype relationships important to infection and persistence in hospitals, including oxidative stress protection, biocide resistance, and biofilm formation.

Dataset Information

Multi-Phenotype Association Decomposition: Unraveling Complex Gene-Phenotype Relationships.

Publications

Multi-Phenotype Association Decomposition: Unraveling Complex Gene-Phenotype Relationships.

Similar Datasets

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