Does the seed fall far from the tree? Weak fine-scale genetic structure in a continuous Scots pine population
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Abstract
Knowledge of fine-scale spatial genetic structure, i.e. , the distribution of genetic diversity at short distances, is important in evolutionary research and in practical applications such as conservation and breeding programs. In trees, related individuals often grow close to each other due to limited seed and/or pollen dispersal. The extent of seed dispersal also limits the speed at which a tree species can spread to new areas. We studied the fine-scale spatial genetic structure of Scots pine ( Pinus sylvestris ) in two naturally regenerated sites located 20 km from each other in continuous south-eastern Finnish forest. We genotyped almost 500 adult trees for 150k SNPs using a custom made Affymetrix array. We detected some pairwise relatedness at short distances, but the average relatedness was low and decreased with increasing distance, as expected. Despite the clustering of related individuals, the sampling sites were not differentiated ( F ST = 0.0005). According to our results, Scots pine has a large neighborhood size ( Nb = 1680–3210), but a relatively short gene dispersal distance ( σ g = 36.5–71.3 m). Knowledge of Scots pine fine-scale spatial genetic structure can be used to define suitable sampling distances for evolutionary studies and practical applications. Detailed empirical estimates of dispersal are necessary both in studying post-glacial recolonization and predicting the response of forest trees to climate change.
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Spatial genetic structure, i.e. the non-random spatial distribution of genotypes, arises in populations because of different processes including spatially limited dispersal and selection. Knowledge on the spatial genetic structure of plant populations is important to assess biological parameters such as gene dispersal distances and the potential for local adaptations, as well as for applications in conservation management and breeding. In their work, Niskanen and colleagues demonstrate a multifaceted approach to characterise the spatial genetic structure in two replicate sites of a continuously distributed Scots pine population in South-Eastern Finland. They mapped and assessed the ages of 469 naturally regenerated adults and genotyped them using a SNP array which resulted in 157 325 filtered polymorphic SNPs. Their dataset is …
Spatial genetic structure, i.e. the non-random spatial distribution of genotypes, arises in populations because of different processes including spatially limited dispersal and selection. Knowledge on the spatial genetic structure of plant populations is important to assess biological parameters such as gene dispersal distances and the potential for local adaptations, as well as for applications in conservation management and breeding. In their work, Niskanen and colleagues demonstrate a multifaceted approach to characterise the spatial genetic structure in two replicate sites of a continuously distributed Scots pine population in South-Eastern Finland. They mapped and assessed the ages of 469 naturally regenerated adults and genotyped them using a SNP array which resulted in 157 325 filtered polymorphic SNPs. Their dataset is remarkably powerful because of the large numbers of both individuals and SNPs genotyped. This made it possible to characterise precisely the decay of genetic relatedness between individuals with spatial distance despite the extensive dispersal capacity of Scots pine through pollen, and ensuing expectations of an almost panmictic population.
The authors’ data analysis was particularly thorough. They demonstrated that two metrics of pairwise relatedness, the genomic relationship matrix (GRM, Yang et al. 2011) and the kinship coefficient (Loiselle et al. 1995) were strongly correlated and produced very similar inference of family relationships: >99% of pairs of individuals were unrelated, and the remainder exhibited 2nd (e.g., half-siblings) to 4th degree relatedness. Pairwise relatedness decayed with spatial distance which resulted in extremely weak but statistically significant spatial genetic structure in both sites, quantified as Sp=0.0005 and Sp=0.0008. These estimates are at least an order of magnitude lower than estimates in the literature obtained in more fragmented populations of the same species or in other conifers. Estimates of the neighbourhood size, the effective number of potentially mating individuals belonging to a within-population neighbourhood (Wright 1946), were relatively large with Nb=1680-3210 despite relatively short gene dispersal distances, σg = 36.5–71.3m, which illustrates the high effective density of the population.
The authors showed the implications of their findings for selection. The capacity for local adaptation depends on dispersal distances and the strength of the selection coefficient. In the study population, the authors inferred that local adaptation can only occur if environmental heterogeneity occurs over a distance larger than approximately one kilometre (or larger, if considering long-distance dispersal). Interestingly, in Scots pine, no local adaptation has been described on similar geographic scales, in contrast to some other European or Mediterranean conifers (Scotti et al. 2023).
The authors’ results are relevant for the management of conservation and breeding. They showed that related individuals occurred within sites only and that they shared a higher number of rare alleles than unrelated ones. Since rare alleles are enriched in new and recessive deleterious variants, selecting related individuals could have negative consequences in breeding programmes. The authors also showed, in their response to reviewers, that their powerful dataset was not suitable to obtain a robust estimate of effective population size, Ne, based on the linkage disequilibrium method (Do et al. 2014). This illustrated that the estimation of Ne used for genetic indicators supported in international conservation policy (Hoban et al. 2020, CBD 2022) remains challenging in large and continuous populations (see also Santo-del-Blanco et al. 2023, Gargiulo et al. 2024).
References
CBD (2022) Kunming-Montreal Global Biodiversity Framework. https://www.cbd.int/doc/decisions/cop-15/cop-15-dec-04-en.pdf
Do C, Waples RS, Peel D, Macbeth GM, Tillett BJ, Ovenden JR (2014). NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne ) from genetic data. Molecular Ecology Resources 14: 209–214. https://doi.org/10.1111/1755-0998.12157
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