Biology subjects

Conner, J. K.

Publications and source records attributed to Conner, J. K..

6 recordsLinked to original sources

bioRxiv2026

Shared QTLs underlie loss of a conserved trait in replicate mapping populations of Arabidopsis thaliana

The evolutionary mechanisms leading to nonfunctional trait loss are not well understood. Some Arabidopsis thaliana populations display incomplete loss of short stamens, floral organs that do not contribute significantly to seed set in this species. In nature, short stamen number is correlated with ovule number and flowering time, suggesting that pleiotropy with these traits could drive stamen number evolution. To investigate the role of pleiotropy in short stamen number evolution, we performed QTL mapping of stamen number and ovule number and examined previously published QTL analyses of flowering time for two sets of RILs, Belm-12 x Roda-47 and Tsu-1 x Kas-1. Flowering time, ovule number, and short stamen loss were correlated in Belm-12 x Roda-47 RILs, but not Tsu-1 x Kas-1 RILs. For both stamen and ovule number, some QTLs were unique to each RIL set and others were shared. Notably, for Belm-12 x Roda-47 RILs, we mapped QTLs affecting ovule and short stamen number to a region of chromosome 5 that also affects flowering time. For Tsu-1 x Kas-1 RILs, we identified the same chromosome 5 region as a short stamen number QTL, but ovule number and flowering time QTLs map to other genomic regions. While some genetic architectures of short stamen number and traits that are correlated in nature suggest linked or pleiotropic loci on chromosome 5, other architectures allow for recombination between QTLs that affect stamen number, ovule number, and flowering time. The role of pleiotropy in short stamen number evolution is therefore context dependent.

genetics↗

bioRxiv2026

Differentiation for drought strategy but conserved plasticity to heat and drought in locally adapted populations of Arabidopsis thaliana

Background and AimsAdaptive plasticity may be crucial for plants to survive rapid environmental changes long enough for evolutionary adaptation to occur. Heat and drought are both abiotic stresses projected to increase globally and their individual impact on plant growth and function is well-characterized. However, to understand potential responses to climate change, we must manipulate multiple stressors simultaneously. MethodsWe measured heat- and drought-related traits as well as fitness in two locally adapted populations of Arabidopsis thaliana from Rod[a]sen, Sweden and Castelnuovo di Porto, Italy. We used chamber common gardens that simulate the current fall and spring climate in Sweden and a hotter and drier climate to identify population differentiation for trait means, trait plasticity, and fitness. Key ResultsPopulation differentiation in both treatments suggests that the Swedish population avoids drought by investing in stress-tolerant leaves while the Italian population escapes drought by flowering early. Despite these differences, there is little evidence for genetic differentiation of plasticity; when experiencing heat and drought, both populations shift their traits in the direction expected to avoid drought. Further, both populations have greatly decreased fitness in heat and drought. ConclusionsThese results highlight that locally adapted populations with genetic differentiation for traits within a single environment can respond to the same stressors with plasticity in the same direction. Further, the combination of heat and drought will be extremely damaging to plant populations. Lay SummaryPlant populations respond to environmental stress in different ways, and their response can determine their survival. We found that plant populations that have evolved different drought responses in their native environments still have the same drought response in an experimental hot and dry environment. Both populations also make many fewer fruits, indicating they may decline in future climates.

evolutionary biology↗

bioRxiv2025

Seed vernalization and gibberellic acid interact to affect life cycle type in facultative winter annual Canadian horseweed (Erigeron canadensis)

Background and AimsPlants display enormous variation in the phenological traits that make up their life cycle both within and between populations. Facultative winter annual species are particularly interesting because they can adopt either a fall-emerging/spring-flowering or spring-emerging/summer-flowering life cycle at the population level via evolution or at the individual level via within-generation and transgenerational plasticity. Responses of phenological traits to the environment have often been found to be mediated by changes in hormone levels, especially the growth hormone gibberellic acid (GA). MethodsWe conducted growth chamber and greenhouse experiments using the facultative winter annual agricultural weed Erigeron canadensis (horseweed) to investigate the interactive effects of genetic variation; parent plant life cycle; and plastic responses to temperature, light, and GA treatments. Key ResultsWe found that contrary to a prior report, exposing imbibed seeds to 3-4 weeks of cold (i.e., seed vernalization) does not always result in summer annual type growth, with considerable variation found among field-collected seeds from 10 populations. Further, we found that seed vernalization and exogenous application of GA both tended to increase summer annual characteristics, interacting in ways that were largely consistent with the hypothesis that GA is a mechanism for cold-induced life cycle differentiation. Light treatment did not significantly affect life cycle traits, while parent life cycle type had marginal effects on offspring life cycle type. Finally, genetic variation among and within sites explained far less of the variation in life cycle traits than the plastic responses to seed vernalization and GA treatments. ConclusionsOur study proposes that the seasonality of this harmful agricultural weed is influenced by a GA-mediated response to vernalization of seeds during winter, yet highlights the need for further study, given the variability in this response.

plant biology↗

bioRxiv2024

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↗

bioRxiv2021

High throughput measurement of Arabidopsis thaliana fitness traits using transfer learning

O_LIRevealing the contributions of genes to plant phenotype is frequently challenging because the effects of loss of gene function may be subtle or be masked by genetic redundancy. Such effects can potentially be detected by measuring plant fitness, which reflects the cumulative effects of genetic changes over the lifetime of a plant. However, fitness is challenging to measure accurately, particularly in species with high fecundity and relatively small propagule sizes such as Arabidopsis thaliana. C_LIO_LIAn image segmentation-based (ImageJ) and a Faster Region Based Convolutional Neural Network (R-CNN) approach were used for measuring two Arabidopsis fitness traits: seed and fruit counts. C_LIO_LIAlthough straightforward to use, ImageJ was error-prone (correlation between true and predicted seed counts, r2=0.849) because seeds touching each other were undercounted. In contrast, Faster R-CNN yielded near perfect seed counts (r2=0.9996) and highly accurate fruit counts (r2=0.980). C_LIO_LIBy examining seed counts, we were able to reveal fitness effects for genes that were previously reported to have no or condition-specific loss-of-function phenotypes. C_LIO_LIOur study provides models to facilitate the investigation of Arabidopsis fitness traits and demonstrates the importance of examining fitness traits in the study of gene functions. C_LI

bioinformatics↗

bioRxiv2020

Genome-wide predictions of genetic redundancy in Arabidopsis thaliana

Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studies have identified some characteristics common among redundant gene pairs, but a predictive model of genetic redundancy incorporating a wide variety of features has not yet been established. In addition, the relative importance of these characteristics for genetic redundancy remains unclear. Here, we establish machine learning models for predicting whether a gene pair is likely redundant or not in the model plant Arabidopsis thaliana. Benchmark gene pairs were classified based on six feature categories: functional annotations, evolutionary conservation including duplication patterns and mechanisms, epigenetic marks, protein properties including post-translational modifications, gene expression, and gene network properties. The definition of redundancy, data transformations, feature subsets, and machine learning algorithms used affected model performance significantly. Among the most important features in predicting gene pairs as redundant were having a paralog(s) from recent duplication events, annotation as a transcription factor, downregulation during stress conditions, and having similar expression patterns under stress conditions. Predictions were then tested using phenotype data withheld from model building and validated using well-characterized, redundant and nonredundant gene pairs. This genetic redundancy model sheds light on characteristics that may contribute to long-term maintenance of paralogs that are seemingly functionally redundant, and will ultimately allow for more targeted generation of functionally informative double mutants, advancing functional genomic studies.

evolutionary biology↗