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Abstract Two decades of widespread drought-induced forest mortality events on every forested continent have raised the specter of future unpredictable, rapid ecosystem changes in 21stcentury forests. Yet our ability to predict drought stress, much less drought-induced mortality across the landscape remains limited. This uncertainty stems at least in part from an incomplete understanding of within-species variation in hydraulic physiology, which reflects the interaction of genetic differentiation among populations (ecotypic variation) and phenotypic plasticity in response to growth environment. We examined among-population genetic differentiation in a number of morphological and hydraulic traits in California blue oak (Quercus douglasii) using a 30 year old common garden. We then compared this genetic trait differentiation and trait-trait integration to wild phenotypes in the field from the original source populations. We found remarkably limited among-population genetic differentiation in all traits in the common garden, but considerable site-to-site variation in the field. However, it was difficult to explain trait variation in the field using site climate variables, suggesting that gridded climate data does not capture the drivers of plasticity in drought physiology in this species. Trait-trait relationships were also considerably stronger in the field than in the garden, particularly links between leaf morphology, leaf hydraulic efficiency and stem hydraulic efficiency. Indeed, while twelve of 45 potential trait-trait relationships showed significant wild phenotypic correlations, only four relationships showed both genetic and phenotypic correlations, and five relationships showed significantly different genetic and phenotypic correlations. Collectively, our results demonstrate limited ecotypic variation in drought-related physiology but considerable geographic variation in physiology and phenotypic integration in the wild, both driven largely by plasticity.
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Inferring human neutral genetic variation from craniodental phenotypes
Abstract There is a growing consensus that global patterns of modern human cranial and dental variation are shaped largely by neutral evolutionary processes, suggesting that craniodental features can be used as reliable proxies for inferring population structure and history in bioarchaeological, forensic, and paleoanthropological contexts. However, there is disagreement on whether certain types of data preserve a neutral signature to a greater degree than others. Here, we address this unresolved question and systematically test the relative neutrality of four standard metric and nonmetric craniodental data types employing an extensive computational genotype–phenotype comparison across modern populations from around the world. Our computation draws on the largest existing data sets currently available, while accounting for geographically structured environmental variation, population sampling uncertainty, disparate numbers of phenotypic variables, and stochastic variation inherent to a neutral model of evolution. Our results reveal that the four data types differentially capture neutral genomic variation, with highest signals preserved in dental nonmetric and cranial metric data, followed by cranial nonmetric and dental metric data. Importantly, we demonstrate that combining all four data types together maximizes the neutral genetic signal compared with using them separately, even with a limited number of phenotypic variables. We hypothesize that this reflects a lower level of genetic integration through pleiotropy between, compared to within, the four data types, effectively forming four different modules associated with relatively independent sets of loci. Therefore, we recommend that future craniodental investigations adopt holistic combined data approaches, allowing for more robust inferences about underlying neutral genetic variation.
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- Award ID(s):
- 2131940
- PAR ID:
- 10525529
- Editor(s):
- Milner, George
- Publisher / Repository:
- PNAS
- Date Published:
- Journal Name:
- PNAS Nexus
- Volume:
- 2
- Issue:
- 7
- ISSN:
- 2752-6542
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract ObjectivesMost research in human dental age estimation has focused on point estimates of age, and most research on dental development theories has focused on morphology or eruption. Correlations between developing teeth using ordinal staging have received less attention. The effect of demographic variables on these correlations is unknown. I tested the effect of reference sample demographic variables on the residual correlation matrix using the lens of cooperative genetic interaction (CGI). Materials and MethodsThe sample consisted of Moorrees et al.,Journal of Dental Research, 1963, 42, 1490–1502, scores of left mandibular permanent teeth from panoramic radiographs of 880 London children 3–22.99 years of age stratified by year of age, sex, and Bangladeshi or European ancestry. A multivariate cumulative probit model was fit to each sex/ancestry group (n = 220), each sex or ancestry (n = 440), and all individuals (n = 880). Residual correlation matrices from nine reference sample configurations were compared using Bartlett's tests of between‐sample difference matrices against the identity matrix, hierarchical cluster analysis, and dendrogram cophenetic correlations. ResultsBartlett's test results were inconclusive. Cluster analysis showed clustering by tooth class, position within class, and developmental timing. Clustering patterns and dendrogram correlations showed similarity by sex but not ancestry. DiscussionExpectations of CGI were supported for developmental staging. This supports using CGI as a model for explaining patterns of variation within the dentition. Sex was found to produce consistent patterns of dental correlations, whereas ancestry did not. Clustering by timing of development supports phenotypic plasticity in the dentition and suggests shared environment over genetic ancestry to explain population differences.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1093/pnasnexus/pgad217
