Temporal Mitogenomics of the Galapagos Giant Tortoise from Pinzón Reveals Potential Biases in Population Genetic Inference
Author(s) -
Evelyn L. Jensen,
Joshua M. Miller,
Danielle L. Edwards,
Ryan C. Garrick,
Washington Tapia,
Adalgisa Caccone,
Michael A. Russello
Publication year - 2018
Publication title -
journal of heredity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 92
eISSN - 1471-8505
pISSN - 0022-1503
DOI - 10.1093/jhered/esy016
Subject(s) - biology , coalescent theory , evolutionary biology , population , demographic history , effective population size , genetic diversity , inference , tortoise , population size , population genetics , genome , approximate bayesian computation , spurious relationship , sampling (signal processing) , genetics , genetic variation , statistics , zoology , phylogenetics , gene , demography , mathematics , philosophy , epistemology , filter (signal processing) , sociology , computer science , computer vision
Empirical population genetic studies generally rely on sampling subsets of the population(s) of interest and of the nuclear or organellar genome targeted, assuming each is representative of the whole. Violations of these assumptions may impact population-level parameter estimation and lead to spurious inferences. Here, we used targeted capture to sequence the full mitochondrial genome from 123 individuals of the Galapagos giant tortoise endemic to Pinzón Island (Chelonoidis duncanensis) sampled at 2 time points pre- and postbottleneck (circa 1906 and 2014) to explicitly assess differences in diversity estimates and demographic reconstructions based on subsets of the mitochondrial genome versus the full sequences and to evaluate potential biases associated with diversity estimates and demographic reconstructions from postbottlenecked samples alone. Haplotypic diversities were equal between the temporal samples based on the full mitochondrial genome, but single gene estimates suggested either decreases or increases in diversity depending upon the region. Demographic reconstructions based on the full sequence were more similar between the temporal samples than those based on the control region alone, or a subset of 3 regions, where the trends in population size changes shifted in magnitude and direction between the temporal samples. In all cases, the estimated coalescent point was more distant for the historical than contemporary sample. In summary, our results empirically demonstrate the influence of sampling bias when interpreting population genetic patterns and punctuate the need for careful consideration of potentially conflicting evolutionary signal across the mitochondrial genome.
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