Abstract Detail

Population Genetics/Genomics

Capblancq, Thibaut [1], Lachmuth, Susanne [2], Fitzpatrick, Matt [2], Keller, Stephen [3].

From common gardens to candidate genes: exploring local adaptation to climate in red spruce.

Local adaptation to climate is common in plant species and has noticeably been investigated in forestry, with motivations ranging from improving crop yields to predicting population maladaptation to future conditions. The genomic era has brought new tools to study this process, which was historically explored through common garden experiments and quantitative genetics perspectives. In this study, we follow both approaches to investigate local adaptation to climate in red spruce and identify environmental gradients and loci involved in climate adaptation. We first use climate transfer functions to estimate the impact of climate change on seedling performance in three common gardens. We then explore the use of multivariate gene-environment association (GEA) methods to identify genes underlying climate adaptation, with particular attention to the implications of conducting genome scans with and without correction for neutral population structure. This integrative approach uncovered phenotypic evidence of adaptation to climate, confirming the presence of local adaptation across red spruce range, and identified a set of putatively adaptive genes that segregated into two different “modules” associated with different environmental gradients. Finally, we show that accounting for population structure when conducting GEAs is not always beneficial and provide new insights for methodological development in this field.

Related Links:
Keller Lab website

1 - Université Grenoble Alpes, Laboratoire d’Écologie Alpine , France
2 - University of Maryland Center for Environmental Science, Appalachian Lab, 301 Braddock Rd, Frostburg, MD, 21532, USA
3 - University Of Vermont, Department Of Plant Biology, 111 Jeffords Hall, 63 Carrigan Dr, Burlington, VT, 05405, United States

Keywords:
Cliimate transfer distance
Genome scan
Exome
conifer
genotype-environment association
Local adaptation
Gradient Forest
RDA.

Presentation Type: Oral Paper
Number: PGG2002
Abstract ID:486
Candidate for Awards:None