Comparative phylogeographic inference with genome-wide data from aggregated population pairs

Xue, Alexander T, Hickerson, Michael J (May 2020) Comparative phylogeographic inference with genome-wide data from aggregated population pairs. Evolution, 74 (5). pp. 808-830. ISSN 0014-3820

URL: https://www.ncbi.nlm.nih.gov/pubmed/32129472
DOI: 10.1111/evo.13945

Abstract

Comparing divergences across multiple sister population pairs has been a focus in phylogeography since its inception. Initial approaches used organelle genetic data and involved qualitative comparisons of phylogenetic patterns to evaluate hypotheses of shared and variable evolutionary responses. This endeavor has progressed with coalescent model-based statistical techniques and advances in next-generation sequencing, yet there remains a need for methods that can exploit aggregated genomic-scale data within a unified analytical framework. To this end, we introduce the aggregate joint site frequency spectrum (ajSFS) by validating its use within a hierarchical Bayesian framework through several in silico experiments. Subsequently, we applied our method against two published restriction site-associated DNA marker datasets consisting of eight local replicates of a lamprey species pair and six co-distributed passerine taxon pairs, respectively, with the aim of inferring variability in co-divergence and co-migration histories. We found that the lamprey population pairs exhibited temporal synchrony in both co-divergence and collective secondary contact times, yet an idiosyncratic pattern in secondary migration intensities. In contrast, the bird population pairs displayed thoroughly asynchronous co-divergence histories. Our results demonstrate that the ajSFS can be exploited for complex and flexible co-demographic inference, opening up new possibilities for comparative phylogeography and population genomic studies.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics
evolution
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > genomes
CSHL Authors:
Communities: CSHL labs > Siepel lab
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: May 2020
Date Deposited: 03 May 2023 23:08
Last Modified: 01 Feb 2024 19:38
Related URLs:
URI: https://repository.cshl.edu/id/eprint/40885

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