Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times

Background: Homoplasy affects demographic inference estimates. This effect has been recognized and corrective methods have been developed. However, no studies so far have defined what homoplasy metrics best describe the effects on demographic inference, or have attempted to estimate such metrics in real data. Here we study how homoplasy in chloroplast microsatellites (cpSSR) affects inference of population expansion time. cpSSRs are popular markers for inferring historical demography in plants due to their high mutation rate and limited recombination. Results: In cpSSRs, homoplasy is usually quantified as the probability that two markers or haplotypes that are identical by state are not identical by descent (Homoplasy index, P). Here we propose a new measure of multi-locus homoplasy in linked SSR called Distance Homoplasy (DH), which measures the proportion of pairwise differences not observed due to homoplasy, and we compare it to P and its per cpSSR locus average, which we call Mean Size Homoplasy (MSH). We use simulations and analytical derivations to show that, out of the three homoplasy metrics analyzed, MSH and DH are more correlated to changes in the population expansion time and to the underestimation of that demographic parameter using cpSSR. We perform simulations to show that Approximate Bayesian Computation (ABC) can be used to obtain reasonable estimates of MSH and DH. Finally, we use ABC to estimate the expansion time, MSH and DH from a chloroplast SSR dataset in Pinus caribaea. To our knowledge, this is the first time that homoplasy has been estimated in population genetic data. Conclusions: We show that MSH and DH should be used to quantify how homoplasy affects estimates of population expansion time. We also demonstrate how ABC provides a methodology to estimate homoplasy in population genetic data.

Saved in:
Bibliographic Details
Main Authors: Ortega-Del Vecchyo, Diego, Piñero, Daniel, Jardón-Barbolla, Lev, van Heerwaarden, Joost
Format: Article/Letter to editor biblioteca
Language:English
Subjects:Demography, Haplotypes, Homoplasy, SSRs,
Online Access:https://research.wur.nl/en/publications/appropriate-homoplasy-metrics-in-linked-ssrs-to-predict-an-undere
Tags: Add Tag
No Tags, Be the first to tag this record!
id dig-wur-nl-wurpubs-527368
record_format koha
spelling dig-wur-nl-wurpubs-5273682024-09-20 Ortega-Del Vecchyo, Diego Piñero, Daniel Jardón-Barbolla, Lev van Heerwaarden, Joost Article/Letter to editor BMC Evolutionary Biology 17 (2017) 1 ISSN: 1471-2148 Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times 2017 Background: Homoplasy affects demographic inference estimates. This effect has been recognized and corrective methods have been developed. However, no studies so far have defined what homoplasy metrics best describe the effects on demographic inference, or have attempted to estimate such metrics in real data. Here we study how homoplasy in chloroplast microsatellites (cpSSR) affects inference of population expansion time. cpSSRs are popular markers for inferring historical demography in plants due to their high mutation rate and limited recombination. Results: In cpSSRs, homoplasy is usually quantified as the probability that two markers or haplotypes that are identical by state are not identical by descent (Homoplasy index, P). Here we propose a new measure of multi-locus homoplasy in linked SSR called Distance Homoplasy (DH), which measures the proportion of pairwise differences not observed due to homoplasy, and we compare it to P and its per cpSSR locus average, which we call Mean Size Homoplasy (MSH). We use simulations and analytical derivations to show that, out of the three homoplasy metrics analyzed, MSH and DH are more correlated to changes in the population expansion time and to the underestimation of that demographic parameter using cpSSR. We perform simulations to show that Approximate Bayesian Computation (ABC) can be used to obtain reasonable estimates of MSH and DH. Finally, we use ABC to estimate the expansion time, MSH and DH from a chloroplast SSR dataset in Pinus caribaea. To our knowledge, this is the first time that homoplasy has been estimated in population genetic data. Conclusions: We show that MSH and DH should be used to quantify how homoplasy affects estimates of population expansion time. We also demonstrate how ABC provides a methodology to estimate homoplasy in population genetic data. en application/pdf https://research.wur.nl/en/publications/appropriate-homoplasy-metrics-in-linked-ssrs-to-predict-an-undere 10.1186/s12862-017-1046-4 https://edepot.wur.nl/423948 Demography Haplotypes Homoplasy SSRs https://creativecommons.org/licenses/by/4.0/ Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
language English
topic Demography
Haplotypes
Homoplasy
SSRs
Demography
Haplotypes
Homoplasy
SSRs
spellingShingle Demography
Haplotypes
Homoplasy
SSRs
Demography
Haplotypes
Homoplasy
SSRs
Ortega-Del Vecchyo, Diego
Piñero, Daniel
Jardón-Barbolla, Lev
van Heerwaarden, Joost
Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times
description Background: Homoplasy affects demographic inference estimates. This effect has been recognized and corrective methods have been developed. However, no studies so far have defined what homoplasy metrics best describe the effects on demographic inference, or have attempted to estimate such metrics in real data. Here we study how homoplasy in chloroplast microsatellites (cpSSR) affects inference of population expansion time. cpSSRs are popular markers for inferring historical demography in plants due to their high mutation rate and limited recombination. Results: In cpSSRs, homoplasy is usually quantified as the probability that two markers or haplotypes that are identical by state are not identical by descent (Homoplasy index, P). Here we propose a new measure of multi-locus homoplasy in linked SSR called Distance Homoplasy (DH), which measures the proportion of pairwise differences not observed due to homoplasy, and we compare it to P and its per cpSSR locus average, which we call Mean Size Homoplasy (MSH). We use simulations and analytical derivations to show that, out of the three homoplasy metrics analyzed, MSH and DH are more correlated to changes in the population expansion time and to the underestimation of that demographic parameter using cpSSR. We perform simulations to show that Approximate Bayesian Computation (ABC) can be used to obtain reasonable estimates of MSH and DH. Finally, we use ABC to estimate the expansion time, MSH and DH from a chloroplast SSR dataset in Pinus caribaea. To our knowledge, this is the first time that homoplasy has been estimated in population genetic data. Conclusions: We show that MSH and DH should be used to quantify how homoplasy affects estimates of population expansion time. We also demonstrate how ABC provides a methodology to estimate homoplasy in population genetic data.
format Article/Letter to editor
topic_facet Demography
Haplotypes
Homoplasy
SSRs
author Ortega-Del Vecchyo, Diego
Piñero, Daniel
Jardón-Barbolla, Lev
van Heerwaarden, Joost
author_facet Ortega-Del Vecchyo, Diego
Piñero, Daniel
Jardón-Barbolla, Lev
van Heerwaarden, Joost
author_sort Ortega-Del Vecchyo, Diego
title Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times
title_short Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times
title_full Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times
title_fullStr Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times
title_full_unstemmed Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times
title_sort appropriate homoplasy metrics in linked ssrs to predict an underestimation of demographic expansion times
url https://research.wur.nl/en/publications/appropriate-homoplasy-metrics-in-linked-ssrs-to-predict-an-undere
work_keys_str_mv AT ortegadelvecchyodiego appropriatehomoplasymetricsinlinkedssrstopredictanunderestimationofdemographicexpansiontimes
AT pinerodaniel appropriatehomoplasymetricsinlinkedssrstopredictanunderestimationofdemographicexpansiontimes
AT jardonbarbollalev appropriatehomoplasymetricsinlinkedssrstopredictanunderestimationofdemographicexpansiontimes
AT vanheerwaardenjoost appropriatehomoplasymetricsinlinkedssrstopredictanunderestimationofdemographicexpansiontimes
_version_ 1816157841434607616