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Platt, D. E.

Publications and source records attributed to Platt, D. E..

3 recordsLinked to original sources

Multiple Loci Selection with Multi-way Epistasis in Coalescence with Recombination

As studies move into deeper characterization of the impact of selection through non-neutral mutations in whole genome population genetics, modeling for selection becomes crucial. Moreover, epistasis has long been recognized as a significant component in understanding evolution of complex genetic systems. We present a backward coalescent model EpiSimRA, that builds multiple loci selection, with multi-way (k-way) epistasis for any arbitrary k. Starting from arbitrary extant populations with epistatic sites, we trace the Ancestral Recombination Graph (ARG), sampling relevant recombination and coalescent events. Our framework allows for studying different complex evolutionary scenarios in the presence of selective sweeps, positive and negative selection with multiway epistasis. We also present a forward counterpart of the coalescent model based on a Wright-Fisher (WF) process which we use as a validation framework, comparing the hallmarks of the ARG between the two. We provide the first framework that allows a nose-to-nose comparison of multiway epistasis in a coalescent simulator with its forward counterpart with respect to the hallmarks of the ARG. We demonstrate through extensive experiments, that EpiSimRA is consistently superior in term of performance (seconds vs. hours) in comparison to the forward model without compromising on its accuracy. EpiSimRA (both backward and forward) source, executable, user manuals are available at: https://github.com/ComputationalGenomics/SimRA.

genomics↗

Insight into the genomic history of the Near East from whole-genome sequences and genotypes of Yemenis

We report high-coverage whole-genome sequencing data from 46 Yemeni individuals as well as genome-wide genotyping data from 169 Yemenis from diverse locations. We use this dataset to define the genetic diversity in Yemen and how it relates to people elsewhere in the Near East. Yemen is a vast region with substantial cultural and geographic diversity, but we found little genetic structure correlating with geography among the Yemenis - probably reflecting continuous movement of people between the regions. African ancestry from admixture in the past 800 years is widespread in Yemen and is the main contributor to the countrys limited genetic structure, with some individuals in Hudayda and Hadramout having up to 20% of their genetic ancestry from Africa. In contrast, individuals from Maarib appear to have been genetically isolated from the African gene flow and thus have genomes likely to reflect Yemens ancestry before the admixture. This ancestry was comparable to the ancestry present during the Bronze Age in the distant Northern regions of the Near East. After the Bronze Age, the South and North of the Near East therefore followed different genetic trajectories: in the North the Levantines admixed with a Eurasian population carrying steppe ancestry whose impact never reached as far south as the Yemen, where people instead admixed with Africans leading to the genetic structure observed in the Near East today.

genomics↗

Dissecting Population Substructure in India via Correlation Optimization of Genetics and Geodemographics

India represents an intricate tapestry of population substructure shaped by geography, language, culture and social stratification. While geography closely correlates with genetic structure in other parts of the world, the strict endogamy imposed by the Indian caste system and the large number of spoken languages add further levels of complexity to understand Indian population structure. To date, no study has attempted to model and evaluate how these factors have interacted to shape the patterns of genetic diversity within India. We merged all publicly available data from the Indian subcontinent into a data set of 891 individuals from 90 well-defined groups. Bringing together geography, genetics and demographic factors, we developed COGG (Correlation Optimization of Genetics and Geodemographics) to build a model that explains the observed population genetic substructure. We show that shared language along with social structure have been the most powerful forces in creating paths of gene flow in the subcontinent. Furthermore, we discover the ethnic groups that best capture the diverse genetic substructure highlighted by COGG. Integrating data from India with a data set of additional 1,323 individuals from 50 populations we find that Europeans show shared genetic drift with the Indo-European and Dravidian speakers of India, whereas the East Asians have the maximum shared genetic drift with Tibeto-Burman speaking tribal groups.

genomics↗