Improved inference of population histories by integrating genomic and epigenomic data.
A. thaliana
coalescent theory
epigenomics
evolutionary biology
evolutionary modelling
statistical inference
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
12 Sep 2024
12 Sep 2024
Historique:
medline:
12
9
2024
pubmed:
12
9
2024
entrez:
12
9
2024
Statut:
epublish
Résumé
With the availability of high-quality full genome polymorphism (SNPs) data, it becomes feasible to study the past demographic and selective history of populations in exquisite detail. However, such inferences still suffer from a lack of statistical resolution for recent, for example bottlenecks, events, and/or for populations with small nucleotide diversity. Additional heritable (epi)genetic markers, such as indels, transposable elements, microsatellites, or cytosine methylation, may provide further, yet untapped, information on the recent past population history. We extend the Sequential Markovian Coalescent (SMC) framework to jointly use SNPs and other hyper-mutable markers. We are able to (1) improve the accuracy of demographic inference in recent times, (2) uncover past demographic events hidden to SNP-based inference methods, and (3) infer the hyper-mutable marker mutation rates under a finite site model. As a proof of principle, we focus on demographic inference in
Identifiants
pubmed: 39264367
doi: 10.7554/eLife.89470
pii: 89470
doi:
pii:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Deutsche Forschungsgemeinschaft
ID : 317616126 (TE809/7-1)
Organisme : Austrian Science Fund
ID : project no. TAI 151-B
Informations de copyright
© 2023, Sellinger et al.
Déclaration de conflit d'intérêts
TS, FJ, AT No competing interests declared