PAST: The Pathway Association Studies Tool to Infer Biological Meaning from GWAS Datasets

Thrash, Adam; Tang, Juliet D.; DeOrnellis, Mason; Peterson, Daniel G.; Warburton, Marilyn L.

doi:10.3390/plants9010058

Cited by 21 publications

(33 citation statements)

References 22 publications

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“…The R Package Pathway Association Study Tool (PAST) version 1.0.1 [105] was used to detect high-confidence genes surrounding (±200 kb) the peak SNPs. Gene sites were aligned and downloaded from the ViroBLAST database (https://urgi.versailles.inra.fr/blast/docs/aboutviroblast.html).…”

Section: Candidate Gene Analysismentioning

confidence: 99%

Appraising the Genetic Architecture of Kernel Traits in Hexaploid Wheat Using GWAS

Ali

et al. 2020

IJMS

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Kernel morphology is one of the major yield traits of wheat, the genetic architecture of which is always important in crop breeding. In this study, we performed a genome-wide association study (GWAS) to appraise the genetic architecture of the kernel traits of 319 wheat accessions using 22,905 single nucleotide polymorphism (SNP) markers from a wheat 90K SNP array. As a result, 111 and 104 significant SNPs for Kernel traits were detected using four multi-locus GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, and pLARmEB) and three single-locus models (FarmCPU, MLM, and MLMM), respectively. Among the 111 SNPs detected by the multi-locus models, 24 SNPs were simultaneously detected across multiple models, including seven for kernel length, six for kernel width, six for kernels per spike, and five for thousand kernel weight. Interestingly, the five most stable SNPs (RAC875_29540_391, Kukri_07961_503, tplb0034e07_1581, BS00074341_51, and BobWhite_049_3064) were simultaneously detected by at least three multi-locus models. Integrating these newly developed multi-locus GWAS models to unravel the genetic architecture of kernel traits, the mrMLM approach detected the maximum number of SNPs. Furthermore, a total of 41 putative candidate genes were predicted to likely be involved in the genetic architecture underlining kernel traits. These findings can facilitate a better understanding of the complex genetic mechanisms of kernel traits and may lead to the genetic improvement of grain yield in wheat.

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Section: Candidate Gene Analysismentioning

confidence: 99%

Appraising the Genetic Architecture of Kernel Traits in Hexaploid Wheat Using GWAS

Ali

et al. 2020

IJMS

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“…The Pathway Association Study Tool (PAST) 10 Bioconductor for R3.6, and PAST can be installed from Github for users with R3.5. R installation instructions can be downloaded from the following link: https://www.rproject.org/.…”

Section: Introductionmentioning

confidence: 99%

“…10 shows the rugplot produced from the pathway analysis of GWAS results created with a maize panel of 288 inbred lines that had been phenotyped for grain color. This simplistic example, where the phenotypes were either "white" or "yellow", was used because the pathway responsible for creating the bright yellow carotenoid pigments is known and should be responsible for most of the phenotype.…”

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confidence: 99%

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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Thrash

Warburton

2020

JoVE

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Recently, a new implementation of a previously described method for interpreting genome-wide association study (GWAS) data using metabolic pathway analysis has been developed and released. The Pathway Association Study Tool (PAST) was developed to address concerns with user-friendliness and slow-running analyses. This new user-friendly tool has been released on Bioconductor and Github. In testing, PAST ran analyses in less than one hour that previously required twenty-four or more hours. In this article, we present the protocol for using either the Shiny application or the R console to run PAST.

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“…Traits that confer enhanced food safety are likely complex and controlled by multiple genes, presenting challenges to breeding efforts, especially for human pathogen-plant interactions. A starting point could be genome-wide association studies followed by metabolic pathway analysis (Li et al, 2019;Thrash et al, 2020) or functional analysis of mapped intervals (Korte and Farlow, 2013;Bartoli and Roux, 2017). For instance, one could predict various biochemical pathways needed for the synthesis of secondary metabolites with antioxidant and antimicrobial properties that could influence plant-microbe interactions and plant responses to associated microbiota.…”

Section: Multidisciplinary Approach To Understanding Plant Genotype ×mentioning

confidence: 99%

Breeding Crops for Enhanced Food Safety

et al. 2020

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An increasing global population demands a continuous supply of nutritious and safe food. Edible products can be contaminated with biological (e.g., bacteria, virus, protozoa), chemical (e.g., heavy metals, mycotoxins), and physical hazards during production, storage, transport, processing, and/or meal preparation. The substantial impact of foodborne disease outbreaks on public health and the economy has led to multidisciplinary research aimed to understand the biology underlying the different contamination processes and how to mitigate food hazards. Here we review the knowledge, opportunities, and challenges of plant breeding as a tool to enhance the food safety of plant-based food products. First, we discuss the significant effect of plant genotypic and phenotypic variation in the contamination of plants by heavy metals, mycotoxin-producing fungi, and human pathogenic bacteria. In addition, we discuss the various factors (i.e., temperature, relative humidity, soil, microbiota, cultural practices, and plant developmental stage) that can influence the interaction between plant genetic diversity and contaminant. This exposes the necessity of a multidisciplinary approach to understand plant genotype × environment × microbe × management interactions. Moreover, we show that the numerous possibilities of crop/hazard combinations make the definition and identification of high-risk pairs, such as Salmonella-tomato and Escherichia coli-lettuce, imperative for breeding programs geared toward improving microbial safety of produce. Finally, we discuss research on developing effective assays and approaches for selecting desirable breeding germplasm. Overall, it is recognized that although breeding programs for some human pathogen/toxin systems are ongoing (e.g., Fusarium in wheat), it would be premature to start breeding when targets and testing systems are not well defined. Nevertheless, current research is paving the way toward this goal and this review highlights advances in the field and critical points for the success of this initiative that were discussed during the Breeding Crops for Enhanced Food Safety workshop held 5-6 June 2019 at University of California, Davis.

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PAST: The Pathway Association Studies Tool to Infer Biological Meaning from GWAS Datasets

Cited by 21 publications

References 22 publications

Appraising the Genetic Architecture of Kernel Traits in Hexaploid Wheat Using GWAS

Appraising the Genetic Architecture of Kernel Traits in Hexaploid Wheat Using GWAS

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Breeding Crops for Enhanced Food Safety

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