2023
DOI: 10.1101/2023.12.27.573436
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The genetic consequences of population marginality: a case study in maritime pine

Adélaïde Theraroz,
Carlos Guadaño-Peyrot,
Juliette Archambeau
et al.

Abstract: Marginal tree populations, either those located at the edges of the species’ range or in suboptimal environments, are often a valuable genetic resource for biological conservation. However, there is a lack of knowledge about the genetic consequences of population’s marginality, estimated across entire species’ ranges. Using 10,185 SNPs across 82 populations ofPinus pinasterAit., a widespread and economically important conifer characterised by a fragmented range, we modelled the relationship of five genetic ind… Show more

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Cited by 1 publication
(2 citation statements)
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“…Maritime pine has a strong population genetic structure (Alberto et al 2013), with eight gene pools and two isolated one-population genetic clusters described in Theraroz et al (2023). The sampled populations originated from six of the main gene pools previously identified in Jaramillo-Correa et al (2015), each probably originating from an unique glacial refugia (Bucci et al 2007, Santos-del-Blanco et al 2012).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Maritime pine has a strong population genetic structure (Alberto et al 2013), with eight gene pools and two isolated one-population genetic clusters described in Theraroz et al (2023). The sampled populations originated from six of the main gene pools previously identified in Jaramillo-Correa et al (2015), each probably originating from an unique glacial refugia (Bucci et al 2007, Santos-del-Blanco et al 2012).…”
Section: Methodsmentioning
confidence: 99%
“…Neutral evolutionary and demographic processes also impact GO predictions and how to account for them remains unclear. In particular, greater genetic drift in small populations results in greater allele turnover (e.g., in ecologically-marginal populations; Theraroz et al 2023), and thus higher GO predictions without any selection pressure being involved (Láruson et al 2020). Then, to avoid the confounding effects of the population genetic structure, it was initially recommended to predict GO based on a set of genetic markers previously identified as potentially involved in climate adaptation (Fitzpatrick and Keller 2015, Fitzpatrick et al 2018), e.g., using gene-environment association (GEA) analyses correcting for population genetic structure.…”
Section: Introductionmentioning
confidence: 99%