Evolutionary criteria outperform operational approaches in producing ecologically relevant fungal species inventories

Mol Ecol. 2011 Feb;20(3):655-66. doi: 10.1111/j.1365-294X.2010.04964.x. Epub 2010 Dec 24.

Abstract

Analyses of the structure and function of microbial communities are highly constrained by the diversity of organisms present within most environmental samples. A common approach is to rely almost entirely on DNA sequence data for estimates of microbial diversity, but to date there is no objective method of clustering sequences into groups that is grounded in evolutionary theory of what constitutes a biological lineage. The general mixed Yule-coalescent (GMYC) model uses a likelihood-based approach to distinguish population-level processes within lineages from processes associated with speciation and extinction, thus identifying a distinct point where extant lineages became independent. Using two independent surveys of DNA sequences associated with a group of ubiquitous plant-symbiotic fungi, we compared estimates of species richness derived using the GMYC model to those based on operational taxonomic units (OTUs) defined by fixed levels of sequence similarity. The model predicted lower species richness in these surveys than did traditional methods of sequence similarity. Here, we show for the first time that groups delineated by the GMYC model better explained variation in the distribution of fungi in relation to putative niche-based variables associated with host species identity, edaphic factors, and aspects of how the sampled ecosystems were managed. Our results suggest the coalescent-based GMYC model successfully groups environmental sequences of fungi into clusters that are ecologically more meaningful than more arbitrary approaches for estimating species richness.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biodiversity*
  • Biological Evolution
  • Cluster Analysis
  • Computational Biology / methods*
  • DNA, Fungal / chemistry
  • DNA, Fungal / genetics
  • DNA, Ribosomal / chemistry
  • DNA, Ribosomal / genetics
  • Ecuador
  • Estonia
  • Fungi / classification*
  • Fungi / genetics*
  • Genetic Speciation
  • Genetic Variation
  • Likelihood Functions
  • Models, Genetic
  • Phylogeny
  • RNA, Fungal / genetics
  • RNA, Ribosomal, 18S / genetics*
  • Sequence Analysis, DNA
  • Species Specificity
  • Time Factors

Substances

  • DNA, Fungal
  • DNA, Ribosomal
  • RNA, Fungal
  • RNA, Ribosomal, 18S