Detection of domestication signals through the analysis of the full distribution of fitness effects
Castellano Esteve, David (University of Arizona)
Vourlaki, Ioanna Theoni (Centre de Recerca en Agrigenòmica)
Gutenkunst, Ryan N. (University of Arizona)
Ramos Onsins, Sebastián Ernesto (Centre de Recerca en Agrigenòmica)

Fecha:	2025
Resumen:	Domestication is a process marked by complex interactions between demographic changes and selective pressures, which together shape genetic diversity. While the phenotypic outcomes of domestication are well documented, its genetic basis-particularly the dynamics of selection-remain less well understood. To investigate these dynamics, we performed simulations designed to approximate the demographic history of large domestic mammals. These simulations used selection coefficients as a modeling tool to represent changes in selection pressures, recognizing that such coefficients are abstractions rather than direct representations of biological reality. Specifically, we analyzed site frequency spectra (SFS) under varying distributions of fitness effects (DFE) and proportions of mutations with divergent selective pressures. Our results show that the discretized deleterious DFE can be reliably inferred from the SFS of a single population, but reconstructing the beneficial DFE and demographic history remains challenging, even when using the joint SFS of both populations. We further developed a novel joint DFE inference model to estimate the proportion of mutations with divergent selection coefficients (pc), although we found that signals of classic hard sweeps can mimic increases in pc, complicating interpretation. These findings underscore both the utility and limitations of DFE inference and highlight the need for caution when interpreting demographic histories in domesticated populations based on such modeling assumptions.
Ayudas:	Agencia Estatal de Investigación AGL2016-78709-R Agencia Estatal de Investigación PID2020-119255GB-I00 Ministerio de Economía y Competitividad SEV-2015-0533 Agencia Estatal de Investigación CEX2019-000902-S Agencia Estatal de Investigación BES-2017-081139
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Publicado en:	Peer Community Journal, Vol. 5 (March 2025) , art. e35, ISSN 2804-3871

DOI: 10.24072/pcjournal.540

24 p, 6.6 MB

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