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Beissinger, T. M.

Publications and source records attributed to Beissinger, T. M..

3 recordsLinked to original sources

Subset-based genomic prediction provides insights into the genetic architecture of free amino acid levels in dry Arabidopsis thaliana seeds

Plant growth, development, and nutritional quality depends upon amino acid homeostasis, especially in seeds. However, our understanding of the underlying genetics influencing amino acid content and composition remains limited, with only a few candidate genes and quantitative trait loci identified to date. Improved knowledge of the genetics and biological processes that determine amino acid levels will enable researchers to use this information for plant breeding and biological discovery. Towards this goal, we used genomic prediction to identify biological processes that are associated with, and therefore potentially influence, free amino acid (FAA) composition in seeds of the model plant Arabidopsis thaliana. Markers were split into categories based on metabolic pathway annotations and fit using a genomic partitioning model to evaluate the influence of each pathway on heritability explained, model fit, and predictive ability. Selected pathways included processes known to influence FAA composition, albeit to an unknown degree, and spanned four categories: amino acid, core, specialized, and protein metabolism. Using this approach, we identified associations for pathways containing known variants for FAA traits, in addition to finding new trait-pathway associations. Markers related to amino acid metabolism, which are directly involved in the FAA regulation, improved predictive ability for branched chain amino acids and histidine. The use of genomic partitioning also revealed patterns across biochemical families, in which serine-derived FAAs were associated with protein related annotations and aromatic FAAs were associated with specialized metabolic pathways. Taken together, these findings provide evidence that genomic partitioning is a viable strategy to uncover the relative contributions of biological processes to FAA traits in seeds, offering a promising framework to guide hypothesis testing and narrow the search space for candidate genes.

genetics

A simple test identifies selection on complex traits in breeding and experimentally-evolved populations

Important traits in agricultural, natural, and human populations are increasingly being shown to be under the control of many genes that individually contribute only a small proportion of genetic variation. However, the majority of modern tools in quantitative and population genetics, including genome wide association studies and selection mapping protocols, are designed to identify individual genes with large effects. We have developed an approach to identify traits that have been under selection and are controlled by large numbers of loci. In contrast to existing methods, our technique utilizes additive effects estimates from all available markers, and relates these estimates to allele frequency change over time. Using this information, we generate a composite statistic, denoted[G] , which can be used to test for significant evidence of selection on a trait. Our test requires pre- and post-selection genotypic data but only a single time point with phenotypic information. Simulations demonstrate that[G] is powerful for identifying selection, particularly in situations where the trait being tested is controlled by many genes, which is precisely the scenario where classical approaches for selection mapping are least powerful. We apply this test to breeding populations of maize and chickens, where we demonstrate the successful identification of selection on traits that are documented to have been under selection.

evolutionary biology

The interplay of demography and selection during maize domestication and expansion

The history of maize has been characterized by major demographic events including changes in population size associated with domestication and range expansion as well as gene flow with wild relatives. The interplay between demographic history and selection has shaped diversity across maize populations and genomes. Here, we investigate these processes based on high-depth resequencing data from 31 maize landraces spanning the pre-Columbian distribution of maize as well as four wild progenitor individuals (Zea mays ssp. parviglumis) from the Balsas River Valley in Mexico. Genome-wide demographic analyses reveal that maize domestication and spread resulted in pronounced declines in effective population size due to both a protracted bottleneck and serial founder effects, while, concurrently, parviglumis experienced population growth. The cost of maize domestication and spread was an increase in deleterious alleles in the domesticate relative to its wild progenitor. This cost is particularly pronounced in Andean maize, which appears to have experienced a more dramatic founder event when compared to other maize populations. Introgression from the wild teosinte Zea mays ssp. mexicana into maize in the highlands of Mexico and Guatemala is found found to decrease the prevalence of deleterious alleles, likely due to the higher long-term effective population size of wild maize. These findings underscore the strong interaction between historical demography and the efficiency of selection species- and genome-wide and suggest domesticated species with well-characterized histories may be particularly useful for understanding this interplay.

evolutionary biology