Phylogenetically Structured Differences in rRNA Gene Sequence Variation among Species of Arbuscular Mycorrhizal Fungi and Their Implications for Sequence Clustering

Abstract

Arbuscular mycorrhizal (AM) fungi form mutualisms with plant roots that increase plant growth and shape plant communities. Each AM fungal cell contains a large amount of genetic diversity, but it is unclear if this diversity varies across evolutionary lineages. We found that sequence variation in the nuclear large-subunit (LSU) rRNA gene from 29 isolates representing 21 AM fungal species generally assorted into genus-and species-level clades, with the exception of species of the genera Claroideoglomus and Entrophospora. However, there were significant differences in the levels of sequence variation across the phylogeny and between genera, indicating that it is an evolutionarily constrained trait in AM fungi. These consistent patterns of sequence variation across both phylogenetic and taxonomic groups pose challenges to interpreting operational taxonomic units (OTUs) as approximations of species-level groups of AM fungi. We demonstrate that the OTUs produced by five sequence clustering methods using 97% or equivalent sequence similarity thresholds failed to match the expected species of AM fungi, although OTUs from AbundantOTU, CD-HIT-OTU, and CROP corresponded better to species than did OTUs from mothur or UPARSE. This lack of OTU-to-species correspondence resulted both from sequences of one species being split into multiple OTUs and from sequences of multiple species being lumped into the same OTU. The OTU richness therefore will not reliably correspond to the AM fungal species richness in environmental samples. Conservatively, this error can overestimate species richness by 4-fold or underestimate richness by one-half, and the direction of this error will depend on the genera represented in the sample. IMPORTANCEArbuscular mycorrhizal (AM) fungi form important mutualisms with the roots of most plant species. Individual AM fungi are genetically diverse, but it is unclear whether the level of this diversity differs among evolutionary lineages. We found that the amount of sequence variation in an rRNA gene that is commonly used to identify AM fungal species varied significantly between evolutionary groups that correspond to different genera, with the exception of two genera that are genetically indistinguishable from each other. When we clustered groups of similar sequences into operational taxonomic units (OTUs) using five different clustering methods, these patterns of sequence variation caused the number of OTUs to either over-or underestimate the actual number of AM fungal species, depending on the genus. Our results indicate that OTU-based inferences about AM fungal species composition from environmental sequences can be improved if they take these taxonomically structured patterns of sequence variation into account. Sequences of rRNA genes have revolutionized our understanding of microbial diversity (1, 2) and the factors structuring microbial communities (3). When used in combination with high-throughput sequencing, rRNA gene sequences have provided critical insights into the composition and dynami...

Disturbance reduces the differentiation of mycorrhizal fungal communities in grasslands along a precipitation gradient

“…However there were strong correlations between OTUs, as expected because single AM fungal cells may contain multiple OTUs (House et al. ). This prevents us from confidently isolating the effects of single OTUs using LDA as is possible using a random forest classifier because of its randomizations.…”

“…Concatenated read pairs were clustered into OTUs with AbundantOTU (Ye ) using a 97% sequence similarity threshold; this method performs well for AM fungi although no clustering method can generate OTUs that consistently match morphologically defined AM fungal species (House et al. ). The consensus sequence representing each OTU was added to a reference alignment of AM fungal sequences (House et al.…”

“…The consensus sequence representing each OTU was added to a reference alignment of AM fungal sequences (House et al. ) using MAFFT (Katoh and Standley ), and the gap in the aligned consensus sequences that represented the non‐overlapping forward and reverse reads was manually deleted. Consensus sequences that aligned poorly with the reference sequences were removed before creating a rooted phylogeny containing both the consensus and reference sequences using RAxML (Stamatakis ) with the GTR‐GAMMA model and using Mortierella elongata as an outgroup.…”

“…Concatenated read pairs were clustered into OTUs with AbundantOTU (Ye 2010) using a 97% sequence similarity threshold; this method performs well for AM fungi although no clustering method can generate OTUs that consistently match morphologically defined AM fungal species (House et al 2016). The consensus sequence representing each OTU was added to a reference alignment of AM fungal sequences (House et al 2016) using MAFFT (Katoh and Standley 2013), and the gap in the aligned consensus sequences that represented the non-overlapping forward and reverse reads was manually deleted. Consensus sequences that aligned poorly with the reference sequences were removed before creating a rooted phylogeny containing both the consensus and reference sequences using RAxML (Stamatakis 2014) with the GTR-GAMMA model and using Mortierella elongata as an outgroup.…”

ITS fungal barcoding primers versus 18S AMF‐specific primers reveal similar AMF‐based diversity patterns in roots and soils of three mountain vineyards

“…The ITS region, which is the standard barcode for fungi (Schoch et al, 2012), is hyper-variable within AMF (Thiery et al, 2016) and is not able to resolve at the species level for some AMF taxonomic groups (Stockinger et al, 2010). Generally, nucleotide variation is highest in ITS and lowest in 18S rDNA (House et al, 2016;Thiery et al, 2016).…”