Group Leader

Angela Hancock, PhD
Angela Hancock, PhD
Max Planck Research Group Leader
Phone:+49 221 5062-285

Molecular basis of adaptive evolution (Angela Hancock)

Molecular basis of adaptive evolution

Adaptation to different local environments can result in extreme phenotypic diversity across a species’ range. Determining how this variation is produced and maintained is a central goal of evolutionary biology.

But to understand how diversity evolves, it is necessary to identify the molecular bases of variation in natural populations. Our research aims to elucidate the molecular mechanisms that produce phenotypic variation in nature and connect this variation back to the native local environments to gain a holistic understanding of the adaptive process. To accomplish these goals, we use a range of approaches, including population genetic analysis, modeling, bioinformatics, and trait mapping.


1. Spatially-explicit population genomics

In some cases, it is possible to identify adaptive loci using genetic polymorphism data alone. However, this approach is limited because it requires strong assumptions about the particular model of adaptation. When these assumptions are violated, this class of methods has low power. A classic and intuitive approach to identify signals of adaptation is based on spatial patterns of traits or allele frequencies, also called ‘clines’. Following this logic, we develop and apply approaches that incorporate spatial and environmental information into the search for adaptive loci.

Concordance between allele frequency (left) and temperature (right) at the TTG1 locus
Concordance between allele frequency (left) and temperature (right) at the TTG1 locus

2. Mapping traits and reconstructing adaptive histories

Producing a comprehensive understanding of how adaptation progressed in specific cases is a daunting task because it requires knowledge of adaptive phenotypes, the genetic basis for phenotypic variation, and evidence that differences in this genetic basis equate to fitness differentials in the natural population. In most organisms, due to long life spans and inadequate genetic tools, this is currently not possible. However, ecologically interesting populations of well-studied model organisms can provide both the background knowledge and tools necessary to overcome this challenge.

Islands can be particularly powerful systems and have been likened to natural laboratories where complexity is reduced relative to mainland populations and natural processes can be studied in relative isolation.

Arabidopsis thaliana plant growing in the Cape Verde Islands Zoom Image
Arabidopsis thaliana plant growing in the Cape Verde Islands

With support from a major European Research Council grant, our group is using populations of the model plant Arabidopsis thaliana we collected from several Macaronesian Islands to dissect phenotypic variation and reconstruct detailed adaptive histories. Specific projects focus on identifying adaptive and functional genetic variants, modeling their evolutionary histories and testing for fitness differentials in simulated and natural environments. Approaches we use include population genetic analysis and modeling, GWAS, QTL mapping, molecular genetics and fieldwork in the Cape Verde and Canary Islands.

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