Comparison of fine-scale genetic structure using nuclear microsatellites within two British oakwoods differing in population history

Cottrell, Joan; Munro, R.C.; Tabbener, Helen; Milner, Allison; Forrest, G. I.; Lowe, Andrew J.

doi:10.1016/s0378-1127(02)00289-x

Cited by 59 publications

(56 citation statements)

References 38 publications

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“…The high genetic diversity observed might have resulted from the out crossing behavior of oil palm as earlier reported on Quercus petraea (Cottrell et al, 2003). In genetic diversity analysis He and Ho results are in close agreement with the findings reported among oil palm genotypes using SSR markers by Okoyo et al, (2016a Arias et al, (2012) reported maximum PIC value with 0.822 in commercial oil palm material.…”

Section: Resultssupporting

confidence: 89%

Identification and Utilization of Polymorphic SSR Markers for Genetic Diversity Studies in Oil Palm

Bhagya¹,

Babu²,

Naika³

et al. 2018

Int.J.Curr.Microbiol.App.Sci

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Section: Resultssupporting

confidence: 89%

Identification and Utilization of Polymorphic SSR Markers for Genetic Diversity Studies in Oil Palm

Bhagya¹,

Babu²,

Naika³

et al. 2018

Int.J.Curr.Microbiol.App.Sci

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“…In a study comparing SGS in 47 plant species, genetic structuration was typically stronger in insect pollinated species, where seed is dispersed by gravity and frugivores than in species pollinated and dispersed by wind . Gaining awareness of within-population SGS in forest tree species, where little is known regarding seed and pollen dispersal patterns, is vital to further the understanding of the ecology of the species and also to inform conservation and breeding strategies (Streiff et al, 1998;Cottrell et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Distribution and fine-scale spatial-genetic structure in British wild cherry (Prunus avium L.)

et al. 2007

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Insights into the within-population spatial-genetic structure (SGS) of forest tree species, where little is known regarding seed and pollen dispersal patterns, enhance understanding of their ecology and provide information of value in conservation and breeding. This study utilised 13 polymorphic simple sequence repeat loci to investigate the impact of asexual recruitment, management regime and tree size on the development of SGS in wild cherry (Prunus avium L). Only 246 genotypes were identified in the 551 trees sampled, reflecting significant levels of clonal reproduction in both managed and unmanaged populations. Naturally regenerated wild cherry was spatially aggregated under both management regimes. However, in the managed population, sexually derived trees accounted for a greater proportion of the smaller size classes, whereas vegetatively produced trees dominated the smaller size classes in the unmanaged population. High overall SGS values (Sp 0.030-Sp 0.045) were observed when considering only sexually derived genets and kinship coefficients were significant up to the 120 m distance class for both populations. The inclusion of clonal ramets in the analysis significantly increased the overall SGS (Sp 0.089-Sp 0.119) as well as kinship coefficients in the 40-80 m distance classes, illustrating the dramatic impact of vegetative propagation on SGS in this species. Increased spatial aggregation and regeneration appeared to be concomitant with increased SGS in the 40 m distance class in the unmanaged population. Neighbourhood size estimates were relatively small for both populations and kinship coefficients were found to decline with distance under both management regimes, suggesting that common mechanisms may restrict gene dispersal in wild cherry.

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“…It should be a key aim for management plans to tailor extraction such that this disturbance is minimised and that remnant genetic structure is sufficient to promote regeneration and maintenance of genetic diversity . To advance these efforts, several recent studies have taken advantage of new, highly variable genetic markers to conduct detailed analysis of tree populations and explore the link between limitations to seed and pollen dispersal and patterns of spatial genetic variation observed on the ground (Doligez and Joly, 1997;Geburek et al, 1998;Strieff et al, 1998;Degen et al, 2001a;Cottrell et al, 2003;Latouche-Halle et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Optimal sampling strategy for estimation of spatial genetic structure in tree populations

Деген²,

et al. 2005

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Fine-scale spatial genetic structure (SGS) in natural tree populations is largely a result of restricted pollen and seed dispersal. Understanding the link between limitations to dispersal in gene vectors and SGS is of key interest to biologists and the availability of highly variable molecular markers has facilitated fine-scale analysis of populations. However, estimation of SGS may depend strongly on the type of genetic marker and sampling strategy (of both loci and individuals). To explore sampling limits, we created a model population with simulated distributions of dominant and codominant alleles, resulting from natural regeneration with restricted gene flow. SGS estimates from subsamples (simulating collection and analysis with amplified fragment length polymorphism (AFLP) and microsatellite markers) were correlated with the 'real' estimate (from the full model population). For both marker types, sampling ranges were evident, with lower limits below which estimation was poorly correlated and upper limits above which sampling became inefficient. Lower limits (correlation of 0.9) were 100 individuals, 10 loci for microsatellites and 150 individuals, 100 loci for AFLPs. Upper limits were 200 individuals, five loci for microsatellites and 200 individuals, 100 loci for AFLPs. The limits indicated by simulation were compared with data sets from real species. Instances where sampling effort had been either insufficient or inefficient were identified. The model results should form practical boundaries for studies aiming to detect SGS. However, greater sample sizes will be required in cases where SGS is weaker than for our simulated population, for example, in species with effective pollen/seed dispersal mechanisms. Heredity (2005) 95, 281-289.

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Comparison of fine-scale genetic structure using nuclear microsatellites within two British oakwoods differing in population history

Cited by 59 publications

References 38 publications

Identification and Utilization of Polymorphic SSR Markers for Genetic Diversity Studies in Oil Palm

Identification and Utilization of Polymorphic SSR Markers for Genetic Diversity Studies in Oil Palm

Distribution and fine-scale spatial-genetic structure in British wild cherry (Prunus avium L.)

Optimal sampling strategy for estimation of spatial genetic structure in tree populations

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