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Buysse, S. F.

Publications and source records attributed to Buysse, S. F..

2 recordsLinked to original sources

The Roles of Drift and Selection on Short Stamen Loss in Arabidopsis thaliana along an Elevational Gradient in the Spanish Pyrenees

Traits that have lost function sometimes persist through evolutionary time. These traits may persist if there is not enough standing genetic variation for the trait to allow a response to selection, if selection against the trait is weak relative to drift, or if the trait has a residual function. To determine the evolutionary processes shaping whether nonfunctional traits are retained or lost, we investigated short stamens in 16 populations of Arabidopsis thaliana along an elevational cline in northeast Spain. We found a cline in short stamen number from retention of short stamens in high elevation populations to incomplete loss in low elevation populations. We did not find evidence that limited genetic variation constrains the loss of short stamens at high elevations, nor evidence for divergent selection on short stamens between high and low elevations. Finally, we identified loci associated with short stamens in northeast Spain that are different from loci associated with variation in short stamen number across latitudes from a previous study. Overall, we did not identify the evolutionary mechanisms contributing to an elevational cline in short stamen number but did identify different genetic loci underlying variation in short stamen along similar phenotypic clines. Teaser textThe evolutionary mechanisms underlying loss or retention of traits that have lost function are poorly understood. Short stamens in Arabidopsis thaliana provide a compelling system to investigate the roles of genetic drift and selection in trait loss across latitudinal and elevational clines. This study investigates how drift and selection shape short stamen loss in 16 populations of A. thaliana along an elevational gradient in Northeast Spain. An investigation of the loci underlying variation in short stamen number suggests variants in different genes may cause trait loss in similar phenotypic clines within a species.

evolutionary biology↗

A data-driven evaluation of Arabidopsis-centric research and the model species concept

The selection of Arabidopsis as a model organism played a pivotal role in advancing genomic science, firmly establishing the cornerstone of today s plant molecular biology. Competing frameworks to select an agricultural- or ecological-based model species, or to decentralize plant science and study a multitude of diverse species, were selected against in favor of building core knowledge in a species that would facilitate genome-enabled research that could assumedly be transferred to other plants. Here, we examine the ability of models based on Arabidopsis gene expression data to predict tissue identity in other flowering plant species. Comparing different machine learning algorithms, models trained and tested on Arabidopsis data achieved near perfect precision and recall values using the K-Nearest Neighbor method, whereas when tissue identity is predicted across the flowering plants using models trained on Arabidopsis data, precision values range from 0.69 to 0.74 and recall from 0.54 to 0.64, depending on the algorithm used. Below-ground tissue is more predictable than other tissue types, and the ability to predict tissue identity is not correlated with phylogenetic distance from Arabidopsis. This suggests that gene expression signatures rather than marker genes are more valuable to create models for tissue and cell type prediction in plants. Our data-driven results highlight that, in hindsight, the assertion that knowledge from Arabidopsis is translatable to other plants is not always true. Considering the current landscape of abundant sequencing data and computational resources, it may be prudent to reevaluate the scientific emphasis on Arabidopsis and to prioritize the exploration of plant diversity.

plant biology↗