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The Computational Population Genetics Group, or CpG group, is located in the International Laboratory for Human Genome Research at the Campus Juriquilla of the National Autonomous University of Mexico. We develop and apply new computational and statistical methods to infer the impact of past evolutionary processes on patterns of genetic and phenotypic variation. We are particularly interested on understanding how natural selection acts across the genome and on inferring past population history using large-scale population genomic data. Some of our ongoing and past topics of research can be found below.

Understanding the joint impact of demographic history and natural selection in patterns of genetic and haplotypic variation

The efficiency of natural selection to remove deleterious mutations and to increase the frequency of beneficial mutations is dependent on the past population history.  In the past, we have studied how population size decreases in canids has changed the amount of deleterious genetic variation across the genome (Marsden CD*, Ortega-Del Vecchyo D*, et al. 2016 PNAS; Robinson et al. 2016 Genome Research). These analysis included the development of a new software program, PReFerSim (Ortega-Del Vecchyo D et al. 2016 Bioinformatics), that can perform simulations of independent genetic variants under natural selection in different demographic scenarios. Currently we are interested in studying how selection is acting across the genome by developing methods that leverage haplotypic information to infer the distribution of fitness effects for new mutations (Ortega-Del Vecchyo et al. 2019 BioRxiv).

 

Inferring past demographic history and the impact of selection using present-day and ancient samples

We are currently working on developing methods to infer past population history by jointly analyzing ancient and present-day samples. In the past, we have developed analytical theory to study how the use of ancient samples changes the values of measures of population differentiation under different demographic scenarios (Ortega-Del Vecchyo and Slatkin 2019 Heredity). Currently we are developing methods that take into account the contamination and sequencing errors found in ancient samples to infer past population history. We are also interested in using ancient DNA to infer the strength of natural selection acting on alleles, and on analyzing the evolution of trait-associated alleles.