Jumpponen is interested on the controlling mechanisms of microbial communities. He is currently investigating on the primary mechanisms that dictate the compositional differences between urban and rural fungal communities inhabiting tree roots and foliage. Jones is a research scientist at the University of Georgia’s Georgia Genomics Facility, where he leads the next generation sequencing group. His current interests are in the application of next generation sequencing to population and community genetics. Mattox is the City Forester for the City of Manhattan. He is interested in the maintenance of a diverse arboreal portfolio in urban environments. Yaege is interested in genetics of fungi used in industrial and food fermentation. She has investigated genetics and transformation of red rice mold Monascus purpureus for pigment production and its potential as a fungal model for production of fungal metabolites.
Massively parallel 454-sequencing of fungal communities in Quercus spp. ectomycorrhizas indicates seasonal dynamics in urban and rural sites
Article first published online: 10 FEB 2010
© 2010 Blackwell Publishing Ltd
Special Issue: Next Generation Molecular Ecology
Volume 19, Issue Supplement s1, pages 41–53, March 2010
How to Cite
JUMPPONEN, A., JONES, K. L., DAVID MATTOX, J. and YAEGE, C. (2010), Massively parallel 454-sequencing of fungal communities in Quercus spp. ectomycorrhizas indicates seasonal dynamics in urban and rural sites. Molecular Ecology, 19: 41–53. doi: 10.1111/j.1365-294X.2009.04483.x
- Issue published online: 10 FEB 2010
- Article first published online: 10 FEB 2010
- Received 20 May 2009; revision received 27 September 2009; accepted 29 September 2009
Table S1. List of the Internal Transcribed Spacer (ITS) primers that combine fungus specific (ITS1F; Gardes & Bruns 1993) and universal (ITS2; White 1990) primers and the 454sequencing endemic (Margulies et al. 2005) A- and B-primers plus a 5 bp DNA-tag for post-sequencing sample identification.
Table S2. OTU assignments and summaries at 95% sequence identity. Included are sample read length as well as Blast-derived coverage and sequence identity. For each best match GenBank accession and taxon information (Genus and Specific epithet, family, order and phylum as well as nutritional mode) are listed. OTUs with significant differences in the repeated measures ANOVAs are highlighted with listing of the significant terms.
Table S3. OTU richness estimators, number of singletons, proportion of singletons, number of doubletons, and two extrapolative estimators (Chao 1 and first order jackknife). Standard deviations and 95% confidence intervals displayed where appropriate. Singletons comprise on average ~50% of the observed richness indicating that the sampling on a level of a tree did not reach saturation. Extrapolative estimators corroborate and exceed the observed estimators two-fold. ACE and ICE estimators provided richness estimates far exceeding those presented here and were omitted.
Fig. S1. Total richness (S) of Operational Taxonomic Units (OTUs) for the three sampling occasions (May, July, and September) across sixteen CAP3 (Huang & Madan 1999) sequence similarity (identity) thresholds. Note that 95% sequence identity was selected for the OTU and taxon level analyses as the OTU richness assumes an exponential growth above this level.
Fig. S2. Soil chemical parameters in urban (closed symbols) and rural (open symbols) sites (mean ± 1SD) sampled repeatedly in May, July and September. (a) soil pH, (b) soil organic matter, (c) soil ammonium, (d) soil nitrate, (e) soil phosphorus, (f) soil potassium, (g) soil lead, and (h) soil cadmium. The asterisks indicate results of one-way ANOVAs comparing land use (urban vs. rural) at each sampling. * 0.01 < P ≤ 0.05; ** 0.001 < P ≤ 0.01; *** P ≤ 0.001
Fig. S3. Rank abundances (mean ± 1 SD) of the 50 most abundant OTUs among those that were determined to occur at frequencies > 0 based on Student’s t-test at α < 0.05. Asterisks indicate OTUs that differ significantly among the land uses. The best Blast matches for the shown OTUs are 237 Nectria mauriticola; 431 Tuber whetstonense; 454 Tuber whetstonense; 506* Tuber lyonii; 236 Boletus cf. rubelus; 401 Uncultured Lophiostomataceae; 341* Tuber lyonii; 4 Tuber talyanense; 23 Tomentella stuposa; 520 Tomentella cf. coerulea; 69* Russula pulverulenta; 389 Tomentella ellisii; 74 Hebeloma velutipes; 8 Hymenogaster subalpinus; 36 Scleroderma cepa; 82 Inocybe aff. oblectabilis; 30* Inocybe fibrosa; 189* Tomentella cf. coerulea; 13 Leohumicola minima; 491 Tuber talyanense; 12 Russula puellula; 2* Uncultured Fungus; 57* Thelephoraceae; 56 Thelephoraceae; 141 Tomentella sp.; 101 Russula pectinatoides; 180 Tomentella fuscocinerea; 73 Tomentella stuposa; 196* Tomentella cf. coerulea; 109 Thelephoraceae; 182 Peziza depressa; 15 Tomentella sp.; 232 Tomentella sp.; 89 Nectriaceae; 34 Uncultured Fungus; 334 Hebeloma velutipes; 44 Uncultured Fungus; 65 Xylaria sp.; 159* Thelephoraceae; 7 Uncultured Fungus; 111 Sebacina aff. incrustans; 265 Phialocephala fortinii; 107* Uncultured Fungus; 100 Fusarium oxysporum; 217 Saccharomyces cerevisiae; 103 Tuber talyanense; 202* Thelephoraceae; 228 Heterochaete shearii; 329 Tuber lyonii; 78 Uncultured Fungus.
Fig. S4. Non-metric Multidimensional Scaling (NMS) of the fungal communities of the sampled hosts (mean ± 1 SD) suggesting partial host control of the fungal community. The superscripted letters following taxon names indicate results of Tukey’s HSD at α = 0.05 for the two displayed NMS axes. Hosts followed by different letters differ on either or both of the NMS axes.
Fig. S5. Phylogenetically inferred taxon affinities of the most commonly occurring families: (a) Tuberaceae; (b) Thelephoraceae; (c) Nectriaceae and related Hypocreales; and (d) Cortinariaceae. Neighbor-joining (NJ) topologies with bootstrap support (>50%) for NJ and maximum parsimony (MP) analyses are shown. The nodes that provide well-supported placement of the short environmental sequences are highlighted for emphasis.
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