Senckenberg Research

Session 2







17. January 2018, 1.30 - 3.00 pm


1.30-2.00 pm

Dr. Christian Rellstab, WSL Swiss Federal Research Institute, Birmensdorf, Switzerland

Towards predictive genomics – Adaptation of oaks (Quercus spp.) to present and future climatic conditions

Testing how populations are adapted to their local habitat and predicting their response to their future environment is of key importance in view of climate change. This is particularly relevant for long-lived forest trees, because their long generation time may hamper keeping up with the pace of climatic change. Landscape genomics is a powerful research field that combines environmental and genomic data for investigating genes and environmental factors involved in local adaptation. The main methodological approach of landscape genomics, environmental association analysis, results in gene–environment models describing the current association. These models may then be used to predict the potential fate of populations under future climatic scenarios. However, almost no studies exist that have tackled such a predictive genomic approach. Here I present such an analysis using a large set of populations of the three most common oak species (Quercus spp.) in Switzerland. We first tested genetic variation in 95 candidate genes for associations with abiotic factors related to local topography, climate, and soil characteristics. We then used the obtained results to calculate the risk of non-adaptedness (RONA), which represents the average change in allele frequency at climate-associated loci theoretically required to match future climatic conditions. RONA was considerably large for some populations and species (up to 48% in single populations) and strongly differed among species, depending on the environmental factor considered. Given the long generation time of oaks, some of the required allele frequency changes might not be realistic to be achieved based on standing genetic variation. Hence, future adaptedness may require gene flow or planting of individuals carrying beneficial alleles from habitats currently matching their future climatic conditions (assisted gene flow). I discuss the pros and cons of such a predictive genomic approach. Moreover, I show some limitations of landscape genomic analyses like the problem of finding similar signatures of adaptation in independent population sets. Finally, I highlight that studying the environment–genotype–phenotype triangle in combination with reciprocal transplant experiments should become the gold standard for studying local adaptation at the genomic level.

2.00-2.20 pm

Moises Exposito-Alonso, Weigel Lab, MPI Developmental Biology, Tübingen, Germany

Genomic basis and evolutionary potential for extreme drought adaptation in Arabidopsis thaliana

Because earth is currently experiencing dramatic climate change, it is of critical interest to understand how species will respond to it. The chance of a species to withstand climate change will likely depend on the diversity within the species and, particularly, whether there are subpopulations that are already adapted to extreme environments. However, most predictive studies ignore that species comprise genetically diverse individuals. We have identified genetic variants in Arabidopsis thaliana that are associated with survival of an extreme drought event, a major consequence of global warming. Subsequently, we determined how these variants are distributed across the native range of the species. Genetic alleles conferring higher drought survival showed signatures of polygenic adaptation, and were more frequently found in Mediterranean and Scandinavian regions. Using geo-environmental models, we predicted that Central European, but not Mediterranean, populations might lag behind in adaptation by the end of the 21st century. Further analyses showed that a population decline could nevertheless be compensated by natural selection acting efficiently over standing variation or by migration of adapted individuals from populations at the margins of the species’ distribution. These findings highlight the importance of within-species genetic heterogeneity in facilitating an evolutionary response to a changing climate.

2.20-2.40 pm

Dr. Stefan Laurent, Max Planck Institute for Plant Breeding, Cologne, Germany

Recent adaptation to a new environment in the presence of high gene flow. A case study in North American populations of the deer mouse Peromyscus maniculatus

Stefan Laurent; Susanne Pfeifer; Vitor Sousa, Ricardo Mallarino; Catherine R. Linnen; Laurent Excoffier; Hopi E. Hoekstra, Rowan Barrett, Jeffrey D. Jensen

Cryptic coat color evolution in the Nebraskan deer mice occurred as a response to the formation of a dune field (Sand Hills) around 12000 years ago. On the Sand Hills, dark-coated wild-type mice are subject to higher predation by visually hunting predators. Light-coated mutants increase their fitness by improving their camouflage, which explains the observed correlation between substrate color and coat color. I will present new results from a population genomic analysis conducted on 280 mice from 12 populations sampled on and off the Sand Hills. We collected data from a 200kb region around Agouti and from random genomic regions. I will also present new results from a manipulative field experiment in which survival rates and genome-wide allele frequency changes (before/after predation) have been measured in controlled populations of dark and light mice in both environments. The population genomic analysis identified the selective sweep on Agouti and several mutation and recombination events responsible for this adaptive event. The results of the field experiment highlight the reproducibility of positive selection on Agouti in this system. Finally, I will discuss statistical issues related to the estimation of fitness from allele frequency change data obtained from such field experiments.

2.40-3.00 pm

Gerrit Kuhn, Pacific Biosciences

PacBio Application Updates and coming advances

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