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Sequences and tree used in: Growth form is strongest predictor of algal photobiont community diversity in lichens: Dissertation chapter

Cite this dataset

Keepers, Kyle (2021). Sequences and tree used in: Growth form is strongest predictor of algal photobiont community diversity in lichens: Dissertation chapter [Dataset]. Dryad.


Lichens are a symbiotic assemblage containing primarily a fungal species in association with at least one photosynthetic partner. Lichens exist in a variety of growth forms and may reproduce sexually or asexually. We investigated how these variables contribute to the community diversity within the thalli of 405 lichens across a broad taxonomic range. We found that reproductive mode is not a predictor for community diversity of lichens using only algal photobionts, but that growth form is a strong predictor. Crustose lichens contain the highest photobiont diversity, foliose lichens contain an intermediate level of diversity, and fruticose lichens have the least diverse photobiont communities. We also found that lichens using cyanobacteria as photobionts decrease in diversity at higher elevations.


DNA Extraction and Whole Genome Shotgun Sequencing – Genomic libraries were prepared according to Pogoda et al. 2018. In short, roughly 1cm x 1cm of tissue from 494 lichen vouchers were pulverized using tungsten carbide beads and DNA was extracted using the Qiagen DNeasy Plant extraction kit. The elution was then prepared for sequencing with the Nextera® XT DNA library prep kit. Libraries that passed QC were processed for paired-end 151 base pair reads on an Illumina NextSeq® sequencer at the University of Colorado’s BioFrontiers Institute (Boulder, Colorado).

De novo Genomic AssemblyLibraries were filtered with Trimmomatic-0.36 to trim adapters from reads, and with parameters “LEADING:3 TRAILING:3 MINLEN:100” (Bolger et al., 2014). Filtered reads were then assembled using SPAdes 3.9.0 with parameters “--careful -k 21,33,65,81” (Bankevich et al., 2012). We then bioinformatically isolated the complete or partial ribosomal DNA complexes of 60 algal photobionts within the dataset. These rDNA sequences were then queried with web BLAST to confirm their identities as either green coccoid (Trebouxioid) or green trentepohlia (Trentepohlioid) algae. We also obtained the rDNA complexes from 43 assemblies containing cyanobionts. We verified the identities of these sequences as Nostocaceae (the group of cyanobacteria used as photobionts by cyanolichens) using web BLAST.

Photobiont Diversity Calculation Pipeline – Our process for identifying the diversity of photobiont communities within our genomic libraries involved two steps. The first step was to map the libraries to algal and cyanobacterial (when applicable, respectively) databases of rDNA to isolate only reads that plausibly sourced from a photobiont of the lichen. The process for ensuring that only photobiont reads were obtained from this step is described in its own section below (see Masking Non-diagnostic Regions of the rDNA Databases). The collection of photobiont rDNA reads were then aligned to one of two algal references (the Trebouxioid photobiont of Usnea ceratina [NCBI Accession KY033354] and the Trentepohlioid photobiont of Opegrapha moroziana [unpublished data]. In the case of lichens with cyanobionts, we mapped cyanobiont reads to a reference from Nostoc sphaeroides [NCBI Accesssion CP031941]. Pileup files were generated from the alignments, which were then passed to PoPoolation v. 1.2.2 (Kofler et al., 2011) with the parameters "--measure theta –input <input.mpileup> --fastq-type sanger --min-qual 20 --max-coverage 200 --pool-size 500 --window-size 25 --step-size 25 --output <output.theta>" to measure θWatterson in a sliding window of 25 bp across the length of the pileup against each reference. A similar command with "--measure pi" was used to calculate θπ. The average of the sliding window values was calculated for each output file, and averages were discarded if the number of windows in an output file containing a calculated value was less than 10.


National Science Foundation, Award: 1432629

National Science Foundation, Award: 1542639