Overview
I am interested in evolution within natural systems and the role of the local environment in manipulating evolution at the gene level. More recently this has led me to genomics, in which I am interested in the predictability and convergence of adaptive genomic evolution in response to common selection pressures. I am currently researching these questions as part of the Fraser Lab, investigating the convergent genomic changes in natural populations of Trinidadian guppies that have repeatedly adapted to low-predation environments from high-predation sources. My specialisms include evolutionary genetics and genomics, bioinformatics, statistics and R-coding.
Qualifications
M.BiolSci (University of Sheffield), Ph.D (University of Nottingham)
Career
PhD with Dr Andrew MacColl, University of Nottingham 2013-2017
Research group links
Publications
Key publications | Publications by category | Publications by year
Publications by category
Journal articles
Whiting JR, Fraser BA (2019). Contingent Convergence: the Ability to Detect Convergent Genomic Evolution is Dependent on Population Size and Migration.
G3: Genes|Genomes|Genetics,
10(2), 677-693.
Abstract:
Contingent Convergence: the Ability to Detect Convergent Genomic Evolution is Dependent on Population Size and Migration
Outlier scans, in which the genome is scanned for signatures of selection, have become a prominent tool in studies of local adaptation, and more recently studies of genetic convergence in natural populations. However, such methods have the potential to be confounded by features of demographic history, such as population size and migration, which are considerably varied across natural populations. In this study, we use forward-simulations to investigate and illustrate how several measures of genetic differentiation commonly used in outlier scans (FST, DXY and Δπ) are influenced by demographic variation across multiple sampling generations. In a factorial design with 16 treatments, we manipulate the presence/absence of founding bottlenecks (N of founding individuals), prolonged bottlenecks (proportional size of diverging population) and migration rate between two populations with ancestral and diverged phenotypic optima. Our results illustrate known constraints of individual measures associated with reduced population size and a lack of migration; but notably we demonstrate how relationships between measures are similarly dependent on these features of demography. We find that false-positive signals of convergent evolution (the same simulated outliers detected in independent treatments) are attainable as a product of similar population size and migration treatments (particularly for DXY), and that outliers across different measures (for e.g. FST and DXY) can occur with little influence of selection. Taken together, we show how underappreciated, yet quantifiable measures of demographic history can influence commonly employed methods for detecting selection.
Abstract.
Full text.
Publications by year
2019
Whiting JR, Fraser BA (2019). Contingent Convergence: the Ability to Detect Convergent Genomic Evolution is Dependent on Population Size and Migration.
G3: Genes|Genomes|Genetics,
10(2), 677-693.
Abstract:
Contingent Convergence: the Ability to Detect Convergent Genomic Evolution is Dependent on Population Size and Migration
Outlier scans, in which the genome is scanned for signatures of selection, have become a prominent tool in studies of local adaptation, and more recently studies of genetic convergence in natural populations. However, such methods have the potential to be confounded by features of demographic history, such as population size and migration, which are considerably varied across natural populations. In this study, we use forward-simulations to investigate and illustrate how several measures of genetic differentiation commonly used in outlier scans (FST, DXY and Δπ) are influenced by demographic variation across multiple sampling generations. In a factorial design with 16 treatments, we manipulate the presence/absence of founding bottlenecks (N of founding individuals), prolonged bottlenecks (proportional size of diverging population) and migration rate between two populations with ancestral and diverged phenotypic optima. Our results illustrate known constraints of individual measures associated with reduced population size and a lack of migration; but notably we demonstrate how relationships between measures are similarly dependent on these features of demography. We find that false-positive signals of convergent evolution (the same simulated outliers detected in independent treatments) are attainable as a product of similar population size and migration treatments (particularly for DXY), and that outliers across different measures (for e.g. FST and DXY) can occur with little influence of selection. Taken together, we show how underappreciated, yet quantifiable measures of demographic history can influence commonly employed methods for detecting selection.
Abstract.
Full text.
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