The frequent transition from outcrossing to selfing in flowering plants is often accompanied by changes in multiple aspects of floral morphology, termed the "selfing syndrome." While the repeated evolution of these changes suggests a role for natural selection, genetic drift may also be responsible. To determine whether selection or drift shaped different aspects of the pollination syndrome and mating system in the highly selfing morning glory , we performed multivariate and univariate Qst-Fst comparisons using a wide sample of populations of and its mixed-mating sister species . The two species differ in early growth, floral display, inflorescence traits, corolla size, nectar, and pollen number. Our analyses support a role for natural selection driving trait divergence, specifically in corolla size and nectar traits, but not in early growth, display size, inflorescence length, or pollen traits. We also find evidence of selection for reduced herkogamy in , consistent with selection driving both the transition in mating system and the correlated floral changes. Our research demonstrates that while some aspects of the selfing syndrome evolved in response to selection, others likely evolved due to drift or correlated selection, and the balance between these forces may vary across selfing species.
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http://dx.doi.org/10.1002/ece3.5329 | DOI Listing |
Cogn Neuropsychol
January 2025
Department of Psychological Sciences, Rice University, Houston, Texas, USA.
Many aspects of human performance require producing sequences of items in serial order. The current study takes a multiple-case approach to investigate whether the system responsible for serial order is shared across cognitive domains, focusing on working memory (WM) and word production. Serial order performance in three individuals with post-stroke language and verbal WM disorders (hereafter persons with aphasia, PWAs) were assessed using recognition and recall tasks for verbal and visuospatial WM, as well as error analyses in spoken and written production tasks to assess whether there was a tendency to produce the correct phonemes/letters in the wrong order.
View Article and Find Full Text PDFBackground: Imaging and plasma markers are used as key indicators of disease for Alzheimer's disease (AD) but their usefulness in predicting regional tau pathology is relatively understudied. Our objective was to construct predictive models for regional tau pathology measured on postmortem brain tissue using multiple ante-mortem AD biomarkers. We focused on hippocampal and parietal regions that were immunostained with AT8 and 2E9 that reflect early and advanced aspects of tangle maturity, respectively.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, TX, USA.
Background: Epigenetic clocks are biomarkers of biological age based on DNA methylation (DNAm) patterns and are widely used as predictors of health and aging outcomes. Multiple epigenetic clocks have been developed and reflect different aspects of the multidimensional aging process, above and beyond chronological age. To date, no study has examined the relationship of epigenetic aging with circulating biomarkers of Alzheimer's Disease (AD).
View Article and Find Full Text PDFAlzheimers Dement
December 2024
National University of Singapore, Singapore, Singapore, Singapore.
Background: Past studies examining sleep-cognition relationships mostly employed univariate approaches, which are subject to problems such as multicollinearity and multiple comparisons. Further, results from small sample univariate analyses are difficult to compare, precluding the identification of the aspects of sleep health associated with a particular cognitive domain(s). The current study used a multivariate approach to identify key sleep metrics and cognitive domains that contribute to the maximum sleep-cognition covariance in healthy older adults.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Nottingham University Hospital Trust, Nottingham, Nottingham, UK.
Background: Early diagnosis is crucial in Alzheimer's disease (AD) for optimal treatment outcomes. Neuropsychometric assessments, particularly using the Uniform Data Set Neuropsychological Battery (UDSNB3.0) [1], provide insights into cognitive domains in early stages of Alzheimer's disease before significant hippocampal atrophy occurs.
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