Biology subjects

Warburton, M. L.

Publications and source records attributed to Warburton, M. L..

3 recordsLinked to original sources

bioRxiv2026

Genotypic and multi-environment phenotypic evaluation of the lima bean USDA National Plant Germplasm System collection

Lima bean (Phaseolus lunatus L.) is an economically and agronomically important grain legume. Lima beans (or limas) show a range of climatic adaptations with independent domestications in the Andes (large-seeded) and Mesoamerica (small- or medium-seeded). We generated and integrated genotypic and comprehensive field- and laboratory-based phenotypic information for the available accessions in the USDA National Plant Germplasm System collection across multiple environments to inform germplasm utilization in breeding. A total of 810 accessions were genotyped using short-read, low-coverage sequencing. Accession geographic origin and domestication explained population structure. A partially overlapping subset of the panel (n=141-308) was field-evaluated across two years in each of Davis, CA, Central Ferry, WA, and Coachella Valley, CA (the latter was fall-planted for evaluation of photoperiod-sensitive accessions) to assess trait performance in contrasting environments. Agronomic traits such as determinacy and flowering time, and seed traits such as seed coat color and hundred-seed weight, were scored. Macronutrient traits (protein, starch, fat, and ash content) were measured on dry (mature) harvested grain via near-infrared spectroscopy. Genome-wide association analyses identified loci significantly associated with descriptive, agronomic, and seed traits, including orthologs of known genes in common bean and novel candidate regions. Genomic predictive abilities were moderate to high for key traits. Finally, we established a conditional core collection that was constrained to include 211 extensively phenotyped accessions and for which 91 supplemental accessions were selected to maximize genetic diversity from among the genotyped accessions. Overall, these resources provide a foundation to support genomics-assisted breeding of limas.

plant biology↗

bioRxiv2021

Portrait of a genus: the genetic diversity of Zea

Maize is a globally valuable commodity and one of the most extensively studied genetic model organisms. However, we know surprisingly little about the extent and potential utility of the genetic variation found in the wild relatives of maize. Here, we characterize a high-density genomic variation map from ~700 genomes encompassing maize and all wild taxa of the genus Zea, identifying over 65 million single nucleotide polymorphisms (SNPs), 8 million Insertion/Deletion (InDel) polymorphisms, and over one thousand novel inversions. The variation map reveals evidence of selection within taxa displaying novel adaptations such as perenniality and regrowth. We focus in detail on evidence of convergent adaptation in highland teosinte and temperate maize. This study not only indicates the key role of hormone related pathways in highland adaptation and flowering time related pathways in high latitude adaptation, but also identifies significant overlap in the genes underlying adaptations to both environments. To show how this data can identify useful genetic variants, we generated and characterized novel mutant alleles for two flowering time candidate genes. This work provides the most extensive sampling to date of the genetic diversity inherent in the genus Zea, resolving questions on evolution and identifying adaptive variants for direct use in modern breeding.

evolutionary biology↗

bioRxiv2019

PAST: Pathway Association Studies Tool

BackgroundIn recent years, a bioinformatics method for interpreting GWAS data using metabolic pathway analysis has been developed and successfully used to find significant pathways and mechanisms explaining phenotypic traits of interest in plants. However, the many scripts implementing this method were not straightforward to use, had to be customized for each project, required user supervision, and took more than 24 hours to process data. PAST (Pathway Association Study Tool), a new implementation of this method, has been developed to address these concerns.\n\nResultsPAST is implemented as a package for the R language. Two user-interfaces are provided; PAST can be run by loading the package in R and calling its methods, or by using an R Shiny guided user interface. In testing, PAST completed analyses in approximately one hour by processing data in parallel. PAST has many user-specified options for maximum customization. PAST produces the same results as the previously developed method.\n\nConclusionsIn order to promote a powerful new method of pathway analysis that interprets GWAS data to find biological mechanisms associated with traits of interest, we developed a more accessible and user friendly tool. This tool is more efficient and requires less knowledge of programming languages to use than previous methods. Moreover, it produces similar results in significantly less time. These attributes make PAST accessible to researchers interested in associating metabolic pathways with GWAS datasets to better understand the genetic architecture and mechanisms affecting phenotype.

bioinformatics↗