Skip to Main Content
Data mining for discovery of endophytic and epiphytic fungal diversity in short-read genomic data from deciduous treesAuthor(s): Nicholas R. LaBonte; James Jacobs; Aziz Ebrahimi; Shaneka Lawson; Keith Woeste
Source: Fungal Ecology. 9 p.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
View PDF (1.0 MB)
DescriptionHigh-throughput sequencing of DNA barcodes, such as the internal transcribed spacer (ITS) of the 16s rRNA sequence, has expanded the ability of researchers to investigate the endophytic fungal communities of living plants. With a large and growing database of complete fungal genomes, it may be possible to utilize portions of fungal symbiont genomes outside conventional marker sequences for community analysis of short-read data. We designed a bioinformatics pipeline to identify putative fungal coding sequences from 100 bp Illumina reads of DNA extracted from several angiosperm species (Castanea, Juglans, and Ulmus). Reads remaining after a two-step filtering process made up a small fraction of total reads (2–100 putative fungal reads per 10,000 plant reads) and were assigned to fungal genera and orders based on similarity to proteins from complete fungal genomes. Some of the taxa identified are known to be ubiquitous class 2 endophytes. We detected some differences in endophyte community composition based on ITS sequence data versus results from the short-read pipeline, particularly among Ulmus. ITS results in Juglans and Castanea, however, closely reflected results from the short-read pipeline, and both methods portrayed similar intergeneric differences in endophyte community composition.
- Check the Northern Research Station web site to request a printed copy of this publication.
- Our on-line publications are scanned and captured using Adobe Acrobat.
- During the capture process some typographical errors may occur.
- Please contact Sharon Hobrla, firstname.lastname@example.org if you notice any errors which make this publication unusable.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationLaBonte, Nicholas R.; Jacobs, James; Ebrahimi, Aziz; Lawson, Shaneka; Woeste, Keith. 2018. Data mining for discovery of endophytic and epiphytic fungal diversity in short-read genomic data from deciduous trees. Fungal Ecology. 9 p. https://doi.org/10.1016/j.funeco.2018.04.004.
KeywordsEndophytes, Epiphytes, Microbiome, Illumina sequencing, Data mining, Metagenomics
- Three American tragedies: chestnut blight, butternut canker, and Dutch elm disease
- Emerging hardwood pest problems and implications for the Central Hardwood region
- Native and exotic insects and diseases in forest ecosystems in the Hoosier-Shawnee ecological assessment area
XML: View XML