Abstract Detail

Population Genetics/Genomics

Verrico, Brittany [1], Capblancq, Thibaut [2], Keller, Stephen [3].

Experimental validation of genetic offset predictions in the coniferous tree, red spruce (Picea rubens Sarg.).

Plant populations frequently display local adaptation in which natural selection has modified their genetic composition to optimize traits and maximize their survival and growth in the local environment. Climate is a common driver of selection, and as a consequence, populations may become vulnerable to changing climates that would disturb local adaptation. One approach to discover the genomic basis of climate adaptation is to model the gene~climate relationship through genotype-environment analyses (GEA) and use this to determine the expected shift in the gene~climate relationship between temporal or spatial climate differences. This allows for a quantitative prediction about the degree of expected maladaptation, a metric termed “genetic offset”. However, genomic assessment of climate change vulnerability has largely remained purely predictive and still lacks empirical validation to test what these predictions mean for the actual performance of populations in the field. Here, we seek to empirically validate genetic offset in the ecologically and economically important coniferous tree, red spruce (Picea rubens Sarg.).
Previous studies have used whole-exome sequencing and high-resolution climate data to characterize the genetic basis of climate adaptation using GEA mapping for red spruce populations located across its entire geographical range. In this study, we will use this gene~climate relationship to derive genetic offset predictions for 12 independent, climatically diverse red spruce populations (from Quebec to North Carolina) that have been established in a 60-year old provenance trail in Colebrook, NH. Using whole-exome sequencing on a sample of surviving trees (N-94), we will compare the modeled adaptive genomic composition between the climate of origin and the climate at Colebrook, NH. Then, the genetic offset estimates will be compared to fitness proxies (i.e., survival, trunk diameter (dbh), height) to empirically test the prediction that a larger genetic offset results in a greater degree of climate maladaptation and thus reduced performance. To supplement the fitness traits, we have collected tree ring cores to further assess climate growth responses, since the record of yearly growth primarily reflects plant response to climate (e.g., drought, heat), and through careful cross-dating, each ring can be associated with a particular year and thus the associated climate data. As a result, we will estimate genetic offset based on yearly climate data and test for associations with growth for each individual year, representing a time series spanning decades. Together, this study produces a robust validation of genetic offset predictions and provides an important step in improving confidence in using genomic data to forecast climate change maladaptation in natural populations.

1 - University of Vermont, Department Of Plant Biology, 111 Jeffords Hall, 63 Carrigan Dr, Burlington, VT, 05401, USA
2 - Université Grenoble Alpes, Laboratoire d’Écologie Alpine , France
3 - University Of Vermont, Department Of Plant Biology, 111 Jeffords Hall, 63 Carrigan Dr, Burlington, VT, 05405, United States

Local adaptation
genotype-environment association
genetic offset
climate change.

Presentation Type: Oral Paper
Number: PGG4001
Abstract ID:881
Candidate for Awards:Margaret Menzel Award

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