ArticleScientific reports2019
Divergent selection and genetic structure of Sideritis scardica populations from southern Balkan Peninsula as revealed by AFLP fingerprinting.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Genetic diversity analysis and conservation strategy recommendations for ex situ conservation of Cupressus chengiana.BMC plant biology · 2025Article
- DNA Barcoding and Fertilization Strategies inInternational journal of molecular sciences · 2024Article
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- Phenotypic, chemical component and molecular assessment of genetic diversity and population structure of Morinda officinalis germplasm.BMC genomics · 2022Article
- Population structure and adaptive variation of Helichrysum italicum (Roth) G. Don along eastern Adriatic temperature and precipitation gradient.Scientific reports · 2021Article
- Intense browsing by sika deer (Cervus nippon) drives the genetic differentiation of hairy nettle (Urtica thunbergiana) populations.Oecologia · 2021Article
- Population Genetics ofPlants (Basel, Switzerland) · 2020Article
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Abstract
Sideritis scardica Giseb. is a subalpine/alpine plant species endemic to the central part of the Balkan Peninsula. In this study, we combined Amplified Fragment Length Polymorphism (AFLP) and environmental data to examine the adaptive genetic variations in S. scardica natural populations sampled in contrasting environments. A total of 226 AFLP loci were genotyped in 166 individuals from nine populations. The results demonstrated low gene diversity, ranging from 0.095 to 0.133 and significant genetic differentiation ranging from 0.115 to 0.408. Seven genetic clusters were revealed by Bayesian clustering methods as well as by Discriminant Analysis of Principal Components and each population formed its respective cluster. The exception were populations P02 Mt. Shara and P07 Mt. Vermio, that were admixed between two clusters. Both landscape genetic methods Mcheza and BayeScan identified a total of seven (3.10%) markers exhibiting higher levels of genetic differentiation among populations. The spatial analysis method Samβada detected 50 individual markers (22.12%) associated with bioclimatic variables, among them seven were identified by both Mcheza and BayeScan as being under directional selection. Four bioclimatic variables associated with five out of seven outliers were related to precipitation, suggesting that this variable is the key factor affecting the adaptive variation of S. scardica.
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