Abstracts (first author)


Ignoring heterozygosity biases phylogenomic estimates of divergence times: implications for the evolutionary history of Microtus voles

Author(s): Heckel G, Excoffier L, Lischer HEL


Challenges for the phylogenetic reconstruction of the evolutionary history of closely related organisms may arise from the presence of unsorted lineages and a relatively high proportion of heterozygous sites that are often difficult to incorporate in the analysis. Here we performed a phylogenomic reconstruction of the evolutionary history of the common vole (Microtus arvalis) in Europe with a special focus on the influence of heterozygosity on the estimation of intra-specific divergence. We provide a novel strategy to integrate heterozygous information in existing phylogenetic programs by repeated random haplotype sampling (RRHS) from sequences with multiple unphased heterozygous sites. We evaluate the impact of full, partial or excluded information from heterozygous sites in tree reconstructions on divergence time estimates. All results consistently show four deep and strongly supported evolutionary lineages in our genomic vole sequence data. These lineages diverged at the end of or shortly after the last glacial maximum based on a calibration using radiocarbon-dated archaeological information. However, the incorporation of information from heterozygous sites had a significant impact on absolute and relative branch length estimations. Ignoring heterozygous information led to overestimation of divergence times between the evolutionary lineages of M. arvalis. Computer simulations confirmed the high power of our empirical data set to recover the evolutionary history of the species and allowed to examine potential sources of bias in different analytical approaches. In general, the exclusion of heterozygous sites from evolutionary analysis may cause biased and misleading divergence time estimates particularly in closely related taxa.


Chairman: Octávio S. Paulo
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XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon


Computational Biology & Population Genomics Group