, Volume 26, Issue 8, pp 895–907 | Cite as

Fine-scale genetic structure of natural Tuber aestivum sites in southern Germany

  • Virginie MolinierEmail author
  • Claude Murat
  • Andri Baltensweiler
  • Ulf Büntgen
  • Francis Martin
  • Barbara Meier
  • Barbara Moser
  • Ludger Sproll
  • Ulrich Stobbe
  • Willy Tegel
  • Simon Egli
  • Martina Peter
Original Article


Although the Burgundy truffle (Tuber aestivum) is an ectomycorrhizal fungus of important economic value, its subterranean life cycle and population biology are still poorly understood. Here, we determine mating type and simple sequence repeat (SSR) maternal genotypes of mapped fruiting bodies to assess their genetic structure within two naturally colonized forest sites in southern Germany. Forty-one genotypes were identified from 112 fruiting bodies. According to their mating types, the maternal genotypes were aggregated only in one population. Genotypic diversity of individuals that mostly were small and occurred in 1 out of 2 years of sampling was high. Although these results suggested a ruderal colonization strategy, some genets spread several hundred meters. This result indicates that, besides sexual spore dispersal, vegetative growth or spreading by mycelial propagules contributes to dissemination. In one site, fewer individuals with a tendency to expand genets belonging to only one genetic group were observed. In the second site, numerous small individuals were found and were grouped into two clearly differentiated genetic groups that were spatially intermingled. Forest characteristics and disturbances are possible reasons for the observed genetic patterns. Our findings contribute to a better understanding of the biology of one of the most widespread and commercially important truffle species. This knowledge is critical for establishing and maintaining sustainable long-term truffle cultivations.


Burgundy truffle Genets Mating-type genes Population genetics Propagation strategy SSR markers 



This project was supported by the COST action Project FP1203, the Swiss State Secretariat for Education Research and Innovation (SERI), the WSL-internal “DITREC” project, as well as the “Ernst Göhner Stiftung”(Grant 2012-1961/3). Virginie Molinier was paid by SERI. The UMR1136 is supported by a grant overseen by the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE). The authors thank Genoscope for financing the Tuber aestivum genome sequencing in the TUBEREVOL project. Daniel Nievergelt and Christian Ginzler supported fieldwork, and Francesco Paolocci contributed to discussion. The authors thank Melissa Dawes for providing English language suggestions. The authors thank the three anonymous reviewers for their helpful comments.

Supplementary material

572_2016_719_MOESM1_ESM.docx (500 kb)
ESM 1 Figure S1 Locations of the two sampling sites Ueberlingen (UL) and Bohlingen (BB). Figure S2 Centered location points for genets >15 m. Sizes of genets are represented by colored ovals and location points by colored dots. Figure S3 Maps of the three different sampling scenarios used for checking potential sampling bias. In case 1, the sampling areas of UB and BB are the same. In case 2, the sampling areas of UB 2013 and UB 2011 are identical. In case 3, three different sampling perimeters with the same area are defined within the BB site. Figure S4 Texture and physico-chemical properties of sampling site soils S4a : Soil texture triangle of the two sites and S4b : Physico-chemical properties of the two sampling site soils Figure S5 Plots of the mean number of genotypes and genotypic diversity versus the number of loci. Figure S6 Spatial autocorrelogram of the kinship coefficient (Fij) as a function of the log of the spatial distance. Panels (a), (b), (c) and (d) represent the autocorrelograms for which all genets were used for BB and UL, UL in 2011 and UL in 2013, respectively. The dashed lines correspond to the 95 % confidence interval for the null hypothesis of complete spatial randomness of genotypes, constructed by 10,000 permutations of genotypes across individual positions. The slope of the regression of kinship with log (dist) is indicated as b for each correlogram. The statistic (Sp), defined as the ratio -b/(1 - F1) where b is the regression slope of the autocorrelogram and F1 is the mean Fij between the individuals belonging to the first distance class that includes all pairs of neighbours (Vekemans & Hardy, 2004), is indicated for each autocorrelogram. An asterisk indicates a b-log with a p value < 0.05. (DOCX 500 kb)
572_2016_719_MOESM2_ESM.docx (107 kb)
ESM 2 Table S1 Vegetation cover and species composition at the study sites BB and UL, based on two 200 m2 circle plot surveys. All species present in the tree layer (individuals >5 m), the shrub layer (individuals 0.5 m – 5 m), and the herb layer (<0.5 m) are listed. The sum of cover of all species may exceed 100 % as species can overlap. An asterisk after the species names indicates potential host trees of T. aestivum. Table S2 Weight, maturity, multi-loci genotype (MLG) and genetic group membership for each fruiting body. Table S3 Allele frequencies over all samples (3a) and per site (3b) for each locus (the majority allele for each SSR marker for each locus is shown in bold). Table S4 Probability of multilocus genotypes (PGen) and probability that these arise from distinct sexual events (P sex) for samples harvested in BB and UL truffle sites. ns = not significant. Table S5 Clonal diversity parameters of the two populations according to the different cases and in comparison with the original data and areas. (DOCX 107 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Virginie Molinier
    • 1
    Email author
  • Claude Murat
    • 2
  • Andri Baltensweiler
    • 1
  • Ulf Büntgen
    • 1
    • 3
    • 4
  • Francis Martin
    • 2
  • Barbara Meier
    • 1
  • Barbara Moser
    • 1
  • Ludger Sproll
    • 5
  • Ulrich Stobbe
    • 5
  • Willy Tegel
    • 6
  • Simon Egli
    • 1
  • Martina Peter
    • 1
  1. 1.Swiss Federal Institute for Forest Snow and Landscape Research (WSL)BirmensdorfSwitzerland
  2. 2.INRAUniversité de Lorraine, UMR1136 Interactions Arbres-Microorganismes, Laboratoire d’Excellence ARBREChampenouxFrance
  3. 3.Oeschger Centre for Climate Change ResearchBernSwitzerland
  4. 4.Global Change Research Centre AS CRBrnoCzech Republic
  5. 5.Deutsche TrüffelbäumeRadolfzellGermany
  6. 6.Institute of Forest Sciences IWWFreiburg UniversityFreiburgGermany

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