Literature DB >> 33085825

Biased assessment of ongoing admixture using STRUCTURE in the absence of reference samples.

Sara Ravagni1, Ines Sanchez-Donoso1, Carles Vilà1.   

Abstract

Detection of hybridization and introgression is important in ecological research as in conservation and evolutionary biology. STRUCTURE is one of the most popular software to study introgression and allows estimating what proportion of the genome of each individual belongs to each ancestral population, even in cases where no reference sample from the ancestral nonadmixed populations is previously identified. In spite of its frequent use, some studies have indicated that ancestry estimates may not always be reliable. We simulated population data under different conditions with regard to the genetic differentiation between ancestral populations, number of loci considered, number of alleles per marker and hybridization rate, and analysed data with STRUCTURE. When reference samples were not included, the comparison of the known degree of admixture for each simulated individual and the value estimated with STRUCTURE revealed a strong underestimation of the level of introgression, classifying many admixed individuals as nonadmixed. This derives from an inaccurate estimation of the ancestral allele frequencies. When samples from the nonadmixed ancestral population were included as reference in the analyses, the bias in the estimations was reduced. The most accurate estimates were obtained when potentially admixed samples were few in relation to reference samples. Thus, whenever possible, a very large proportion of nonadmixed reference samples should be included in admixture assessments and different approaches should be combined. The misestimate of the amount of introgression can impair our understanding of the evolutionary history of species and misguide conservation efforts.
© 2020 John Wiley & Sons Ltd.

Keywords:  Bayesian clustering; hybrid zone; hybridization; introgression; population admixture; simulation

Year:  2020        PMID: 33085825     DOI: 10.1111/1755-0998.13286

Source DB:  PubMed          Journal:  Mol Ecol Resour        ISSN: 1755-098X            Impact factor:   7.090


  1 in total

1.  Population genomic monitoring provides insight into conservation status but no correlation with demographic estimates of extinction risk in a threatened trout.

Authors:  William Hemstrom; Daniel Dauwalter; Mary M Peacock; Douglas Leasure; Seth Wenger; Michael R Miller; Helen Neville
Journal:  Evol Appl       Date:  2022-09-04       Impact factor: 4.929

  1 in total

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