A Bioinformatic Analysis of Foliar Fungal Endophytes in Litter Decomposition

Overview

Litter decomposition is a key ecological process that plays a vital role in the global carbon cycle. In the present study, the relationship between endophyte abundance and litter mass loss was examined in the Torrey pine. Total DNA and RNA was extracted, followed by next-generation sequencing and bioinformatic analysis to identify core endophyte species across geographic regions. Endophyte abundance was discovered to be positively correlated with mass loss, and endophytes OTU4 and OTU211 were most prevalent throughout all samples. A Naïve Bayes algorithm was developed to more effectively classify mycological genuses based on their ITS1 sequences. Optimizing for hyperparameters led to a model accuracy of 94.0% with an AUC value of 97.1% as well as identification of the OTUs as the species Salinomyces thailandica and Aulographina pinorum, respectively. With the high accuracy of the model and novel CTAB protocol, this work is the first of its kind in this field.

Competition history

• AJAS 2024 Category not listed

Related projects

Closest projects by meaning, across every fair and year in the corpus.

Browse more like this

• AJAS None projects
• Every AJAS 2024 project