Abstract
Detecting loci under selection is an important task in evolutionary biology. In conservation genetics detecting selection is key to investigating adaptation to the spread of infectious disease. Loci under selection can be detected on a spatial scale, accounting for differences in demographic history among populations, or on a temporal scale, tracing changes in allele frequencies over time. Here we use these two approaches to investigate selective responses to the spread of an infectious cancer—devil facial tumor disease (DFTD)—that since 1996 has ravaged the Tasmanian devil (Sarcophilus harrisii). Using time-series ‘restriction site associated DNA’ (RAD) markers from populations pre- and post DFTD arrival, and DFTD free populations, we infer loci under selection due to DFTD and investigate signatures of selection that are incongruent among methods, populations, and times. The lack of congruence among populations influenced by DFTD with respect to inferred loci under selection, and the direction of that selection, fail to implicate a consistent selective role for DFTD. Instead genetic drift is more likely driving the observed allele frequency changes over time. Our study illustrates the importance of applying methods with different performance optima e.g. accounting for population structure and background selection, and assessing congruence of the results.
Highlights
Identification of genetic variants that are advantageous to a population is of immense interest in evolutionary biology, but disentangling whether a change in allele frequency of a genetic variant is driven by selection or genetic drift poses a problem
We found no evidence of change in genetic diversity over time in relation to devil facial tumor disease (DFTD) (Fig 1; S1 File)
Using genome-wide restriction site associated DNA’ (RAD) markers for hundreds of individuals sampled across time, in multiple DFTD affected populations, and non-infected control populations, we investigated possible selective responses to DFTD, an infectious cancer causing severe declines in Tasmanian devil populations
Summary
Identification of genetic variants that are advantageous to a population is of immense interest in evolutionary biology, but disentangling whether a change in allele frequency of a genetic variant is driven by selection or genetic drift poses a problem. Novel ‘multiple time points’ methods have been developed that rely on sampling a population through time—investigating temporal changes in allele frequencies. The ideal way to identify loci under selection—in response to disease—is to have samples from before and after the disease enters a population, and to sample multiple populations along with replicates and non-affected populations, the latter to act as controls against other environmental changes that may be influential We accomplish this by investigating thousands of Restrictionsite associated DNA (RAD) markers from six Tasmanian devil populations sampled from 1999 to 2013, spanning both pre- and post DTFD arrival, as well as non-infected control populations. Our sampling enables more rigorous assessments of selection, in that we can test for (i) an increase in the number of outlier loci with increasing duration of exposure to disease at a population, (ii) congruence in the outlier loci identified among multiple DFTD-affected populations, and (iii) congruence between the loci identified as being under selection with ‘single time point’ (BAYESCAN v2.1 [5]) and ‘multiple time points’ (WFABC v1.0 [8, 9]) approaches
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