Abstract Detail

Population Genetics/Genomics

Shastry, Vivaswat [1].

Model-based genotype and ancestry estimation for potential hybrids with mixed-ploidy.

Non-random mating among individuals can lead to spatial clustering of genetically similar individuals and population stratification. This deviation from panmixia is commonly observed in natural populations. Consequently, individuals can have parentage in single populations or involving hybridization between differentiated populations. Accounting for this mixture and structure is important when mapping the genetics of traits and learning about the formative evolutionary processes that shape genetic variation among individuals and populations. Stratified genetic relatedness among individuals is commonly quantified using estimates of ancestry that are derived from a statistical model. Development of these models for polyploid and mixed-ploidy individuals and populations has lagged behind those for diploids. Here, we extend and test a hierarchical Bayesian model, called entropy, which can utilize low-depth sequence data to estimate genotype and ancestry parameters in autopolyploid and mixed-ploidy individuals. We present the effect of average sequence depth at a locus, coverage across the genome, evolutionary divergence in parental populations, and ploidy of individuals on the ability of our model to accurately estimate genotype and ancestry from simulated data. We also reanalyzed an empirical mixed-ploidy data set of individuals from diploid and autotetraploid populations of Arabidopsis arenosa across Europe to estimate admixture proportions. We found that the model has high accuracy and sensitivity in estimating genotype and ancestry as verified with simulated data and provides new insight into empirical data from a diploid-tetraploid hybrid zone.

Related Links:
Repository containing the source code for the model
Conda package to install entropy on your machine

1 - University of Wyoming, Department of Botany, 1000 E University Ave, Laramie, WY, 82071, USA

genotype likelihoods

Presentation Type: Oral Paper
Session: POPGEN3, Population Genetics/Genomics III
Location: Virtual/Virtual
Date: Friday, July 31st, 2020
Time: 10:30 AM
Number: POPGEN3003
Abstract ID:201
Candidate for Awards:Margaret Menzel Award

Copyright © 2000-2020, Botanical Society of America. All rights reserved