Estimating admixture pedigrees of recent hybrids without a contiguous reference genome

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The genome of recently admixed individuals or hybrids has characteristic genetic patterns that can be used to learn about their recent admixture history. One of these are patterns of interancestry heterozygosity, which can be inferred from SNP data from either called genotypes or genotype likelihoods, without the need for information on genomic location. This makes them applicable to a wide range of data that are often used in evolutionary and conservation genomic studies, such as low-depth sequencing mapped to scaffolds and reduced representation sequencing. Here we implement maximum likelihood estimation of interancestry heterozygosity patterns using two complementary models. We furthermore develop apoh (Admixture Pedigrees of Hybrids), a software that uses estimates of paired ancestry proportions to detect recently admixed individuals or hybrids, and to suggest possible admixture pedigrees. It furthermore calculates several hybrid indices that make it easier to identify and rank possible admixture pedigrees that could give rise to the estimated patterns. We implemented apoh both as a command line tool and as a Graphical User Interface that allows the user to automatically and interactively explore, rank and visualize compatible recent admixture pedigrees, and calculate the different summary indices. We validate the performance of the method using admixed family trios from the 1000 Genomes Project. In addition, we show its applicability on identifying recent hybrids from RAD-seq data of Grant's gazelle (Nanger granti and Nanger petersii) and whole genome low-depth data of waterbuck (Kobus ellipsiprymnus) which shows complex admixture of up to four populations.

OriginalsprogEngelsk
TidsskriftMolecular Ecology Resources
Vol/bind23
Udgave nummer7
Sider (fra-til)1604-1619
Antal sider16
ISSN1755-098X
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
We thank Hans Redlef Siegismund, Laura Bertola, Malthe Sebro Rasmussen, Ida Moltke and all the members of the Population and Statistical Genetics group at the University of Copenhagen for their input in previous versions of the manuscript. We also thank Xi Wang and Mikkel Schubert for their contribution in processing the waterbuck data set. GGE and RH are supported by a Danmarks Frie Forskningsfond Sapere Aude research grant (DFF8049‐00098B), RH is further supported by an European Research Council Starting Grant (No. 853442), and CW and AA are supported by the Independent Research Fund Denmark (grant number: 8021‐00360B) and the University of Copenhagen through the Data+ initiative.

Publisher Copyright:
© 2023 John Wiley & Sons Ltd.

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