Postglacial recolonization history of the European crabapple (Malus sylvestris Mill.), a wild contributor to the domesticated apple
Understanding the way in which the climatic oscillations of the Quaternary Period have shaped the distribution and genetic structure of extant tree species provides insight into the processes driving species diversification, distribution and survival. Deciphering the genetic consequences of past cli...
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Published in: | Molecular ecology Vol. 22; no. 8; pp. 2249 - 2263 |
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Main Authors: | , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Oxford
Blackwell Publishing Ltd
01-04-2013
Blackwell Wiley |
Subjects: | |
Online Access: | Get full text |
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Summary: | Understanding the way in which the climatic oscillations of the Quaternary Period have shaped the distribution and genetic structure of extant tree species provides insight into the processes driving species diversification, distribution and survival. Deciphering the genetic consequences of past climatic change is also critical for the conservation and sustainable management of forest and tree genetic resources, a timely endeavour as the Earth heads into a period of fast climate change. We used a combination of genetic data and ecological niche models to investigate the historical patterns of biogeographic range expansion of a wild fruit tree, the European crabapple (Malus sylvestris), a wild contributor to the domesticated apple. Both climatic predictions for the last glacial maximum and analyses of microsatellite variation indicated that M. sylvestris experienced range contraction and fragmentation. Bayesian clustering analyses revealed a clear pattern of genetic structure, with one genetic cluster spanning a large area in Western Europe and two other genetic clusters with a more limited distribution range in Eastern Europe, one around the Carpathian Mountains and the other restricted to the Balkan Peninsula. Approximate Bayesian computation appeared to be a powerful technique for inferring the history of these clusters, supporting a scenario of simultaneous differentiation of three separate glacial refugia. Admixture between these three populations was found in their suture zones. A weak isolation by distance pattern was detected within each population, indicating a high extent of historical gene flow for the European crabapple. |
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Bibliography: | ArticleID:MEC12231 istex:E887CAB171751F4AA46EB104DEC5A06A7A8A7C9B ark:/67375/WNG-H7HN4ZNN-S Dataset S1 X/Y coordinates of presences of Malus sylvestris in Europe used for ENM. Text S1 ENM methodology used to project paleodistribution of Malus sylvestris. Fig. S1 Sampling of the different Malus sylvestris sites through Europe. Fig. S2 Bayesian clustering results of Malus sylvestris in Europe (N = 381) using the program structure from K = 2 to K = 6. Fig. S3 Maps of mean membership probabilities per site from the structure analysis for Malus sylvestris assuming 2 to 5 clusters. Fig. S4 Estimated number of populations in Malus sylvestris from TESS analyses using the DIC. Fig. S5 Estimated number of populations in Malus sylvestris from structure analyses using the ∆K. Fig. S6 PCA on 3,000 simulations for Malus sylvestris. Fig. S7 Marginal posterior distributions of demographic and historical parameters estimated by Simcoal2. Fig. S8 Ensemble forecast using Malus sylvestris presence records and pseudo-absences projected onto the map of Europe and Western Russia using 19 bioclimatic variables. Table S1 Description of the Malus sylvestris accessions analysed with their geographical origins and providers, and acknowledgement. Table S2 Prior distributions used in approximate Bayesian computations. Table S3 Summary statistics for each Malus sylvestris sampling site with at least four individuals. Table S4 Summary statistics for the 26 microsatellite loci in Malus sylvestris. Table S5 Pairwise genetic differentiation (FST) among the 25 sites. Table S6 AUC Index for ENM ran with eight and 19 bioclimatic variables for each of the six models and each repetition. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
ISSN: | 0962-1083 1365-294X |
DOI: | 10.1111/mec.12231 |