Inferring History of Evolution Using Massive Data of Single-Nucleotide Polymorphism

• Activity Number: 683
• Type: Contributed
• Date/Time: Thursday, August 8, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Yongliang Zhai*+ and Alexandre Bouchard-Côté
• Companies: University of British Columbia and University of British Columbia
• Keywords: phylogenetics ; single-nucleotide polymorphism ; non-symmetric dissimilarity matrix ; neighbour joining algorithm ; population tree ; human evolution

Abstract

We introduce a new likelihood-based inference method to estimate evolutionary distances for any two populations to their most recent common ancestral population using single-nucleotide polymorphism (SNP) allele frequencies. Our model takes fixation into consideration and does not have strict requirements on ancestral frequencies. This model can be applied to both closely related populations and relatively distant populations. Our inference method can be easily generalized to a large number of populations with reasonable computation cost. A new type of non-symmetric dissimilarity matrix for n populations can be obtained using our method. We propose new algorithms to construct a rooted bifurcating non-clock tree based purely on the non-symmetric dissimilarity matrix, without extra information on frequencies of ancestral populations. We obtained a rooted phylogenetic tree for the 53 human populations of the Human Genome Diversity Panel. Our results are obtained without using an outgroup, and are consistent with the prevalent recent single-origin model.