Maximum-Likelihood Inference of Population Size Contractions from Microsatellite Data
Raphaël Leblois
(1, 2, 3)
,
Pierre Pudlo
(1, 2, 4)
,
Néron Joseph
(3)
,
François Bertaux
(3, 5)
,
Champak Reddy Beeravolu
(1)
,
Renaud Vitalis
(1, 2)
,
François Rousset
(6, 2)
1
UMR CBGP -
Centre de Biologie pour la Gestion des Populations
2 IBC - Institut de Biologie Computationnelle
3 OSEB - Origine, structure et évolution de la biodiversité
4 I3M - Institut de Mathématiques et de Modélisation de Montpellier
5 Lifeware - Computational systems biology and optimization
6 UMR ISEM - Institut des Sciences de l'Evolution de Montpellier
2 IBC - Institut de Biologie Computationnelle
3 OSEB - Origine, structure et évolution de la biodiversité
4 I3M - Institut de Mathématiques et de Modélisation de Montpellier
5 Lifeware - Computational systems biology and optimization
6 UMR ISEM - Institut des Sciences de l'Evolution de Montpellier
Raphaël Leblois
- Fonction : Auteur
- PersonId : 736469
- IdHAL : raphael-leblois
- ORCID : 0000-0002-3051-4497
- IdRef : 114914508
Pierre Pudlo
- Fonction : Auteur
- PersonId : 752224
- IdHAL : pierre-pudlo
- ORCID : 0000-0003-0995-716X
François Bertaux
- Fonction : Auteur
- PersonId : 746800
- IdHAL : francois-bertaux
- ORCID : 0000-0002-0942-6142
- IdRef : 195638840
Renaud Vitalis
- Fonction : Auteur
- PersonId : 737526
- IdHAL : renaud-vitalis
- ORCID : 0000-0001-7096-3089
- IdRef : 068963408
François Rousset
- Fonction : Auteur
- PersonId : 19671
- IdHAL : francois-rousset
- ORCID : 0000-0003-4670-0371
- IdRef : 073298182
Résumé
Understanding the demographic history of populations and species is a central issue in evolutionary biology and molecular ecology. In this work, we develop a maximum-likelihood method for the inference of past changes in population size from microsatellite allelic data. Our method is based on importance sampling of gene genealogies, extended for new mutation models, notably the generalized stepwise mutation model (GSM). Using simulations, we test its performance to detect and characterize past reductions in population size. First, we test the estimation precision and confidence intervals coverage properties under ideal conditions, then we compare the accuracy of the estimation with another available method (MSVAR) and we finally test its robustness to misspecification of the mutational model and population structure. We show that our method is very competitive compared with alternative ones. Moreover, our implementation of a GSM allows more accurate analysis of microsatellite data, as we show that the violations of a single step mutation assumption induce very high bias toward false contraction detection rates. However, our simulation tests also showed some limits, which most importantly are large computation times for strong disequilibrium scenarios and a strong influence of some form of unaccounted population structure. This inference method is available in the latest implementation of the MIGRAINE software package.
Format du dépôt | Fichier |
---|---|
Type de dépôt | Article dans une revue |
Résumé |
en
Understanding the demographic history of populations and species is a central issue in evolutionary biology and molecular ecology. In this work, we develop a maximum-likelihood method for the inference of past changes in population size from microsatellite allelic data. Our method is based on importance sampling of gene genealogies, extended for new mutation models, notably the generalized stepwise mutation model (GSM). Using simulations, we test its performance to detect and characterize past reductions in population size. First, we test the estimation precision and confidence intervals coverage properties under ideal conditions, then we compare the accuracy of the estimation with another available method (MSVAR) and we finally test its robustness to misspecification of the mutational model and population structure. We show that our method is very competitive compared with alternative ones. Moreover, our implementation of a GSM allows more accurate analysis of microsatellite data, as we show that the violations of a single step mutation assumption induce very high bias toward false contraction detection rates. However, our simulation tests also showed some limits, which most importantly are large computation times for strong disequilibrium scenarios and a strong influence of some form of unaccounted population structure. This inference method is available in the latest implementation of the MIGRAINE software package.
|
Titre |
en
Maximum-Likelihood Inference of Population Size Contractions from Microsatellite Data
|
Auteur(s) |
Raphaël Leblois
1, 2, 3
, Pierre Pudlo
1, 2, 4
, Néron Joseph
3
, François Bertaux
3, 5
, Champak Reddy Beeravolu
1
, Renaud Vitalis
1, 2
, François Rousset
6, 2
1
UMR CBGP -
Centre de Biologie pour la Gestion des Populations
( 12765 )
- 755 avenue du Campus Agropolis, 34988 Montferrier sur Lez
- France
2
IBC -
Institut de Biologie Computationnelle
( 213159 )
- 95 rue de la Galéra, 34095 Montpellier
- France
3
OSEB -
Origine, structure et évolution de la biodiversité
( 97942 )
- 45 Rue Buffon - 75005 PARIS
- France
4
I3M -
Institut de Mathématiques et de Modélisation de Montpellier
( 631 )
- Case Courrier 051 Place Eugène Bataillon 34095 MONTPELLIER CEDEX 5
- France
5
Lifeware -
Computational systems biology and optimization
( 241875 )
- France
6
UMR ISEM -
Institut des Sciences de l'Evolution de Montpellier
( 29770 )
- Place E. Bataillon CC 064 34095 Montpellier Cedex 05
- France
|
Licence |
Paternité
|
Date de publication électronique |
2014-07-11
|
Numéro |
10
|
URL éditeur |
https://academic.oup.com/mbe/article/31/10/2805/1012649
|
Langue du document |
Anglais
|
Nom de la revue |
|
Vulgarisation |
Non
|
Comité de lecture |
Oui
|
Audience |
Internationale
|
Date de publication |
2014-10
|
Volume |
31
|
Page/Identifiant |
2805–2823
|
Public visé |
Scientifique
|
Voir aussi |
|
Domaine(s) |
|
Mots-clés (Mesh) |
|
Projet(s) ANR |
|
Financement |
|
Mots-clés |
en
bottleneck, Coalescent, Demographic inference, Importance sampling, Maximum likelihood, Microsatellites, Mutation processes, Population contraction, Population structure
|
DOI | 10.1093/molbev/msu212 |
Pubmed Id | 25016583 |
UT key WOS | 000343402200022 |
Origine :
Fichiers éditeurs autorisés sur une archive ouverte
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