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🦠 SCTLD Microbiome Meta-Analysis

This repository contains the data and code for the meta-analysis conducted in:

“A meta‑analysis of the stony coral tissue loss disease microbiome finds key bacteria in unaffected and lesion tissue in diseased colonies”
S. M. Rosales et al. (2025), ISME Communications :contentReference[https://doi.org/10.1038/s43705-023-00220-0]


📚 Study Highlights

  • 🔎 Largest meta-analysis to date on the microbiome of Stony Coral Tissue Loss Disease (SCTLD)
  • Examined 17 studies (16 SCTLD + 1 Rapid Tissue Loss)
  • Compared microbiomes in:
    • Apparently Healthy (AH) corals across different disease zones (vulnerable, endemic, epidemic)
    • Diseased coral tissue – Diseased Unaffected (DU) vs. Disease Lesion (DL)
  • 🧬 Key findings:
    • AH corals in endemic/epidemic zones had bacterial changes that might indicate compromised health or resistance
    • DU samples: dominated by Flavobacteriales and Synechococcales
    • DL samples: enriched in Rhodobacterales and Peptostreptococcales–Tissierellales, with the latter potentially involved in tissue loss via phospholipase C/α-toxin pathways.

📁 Repository Structure

  • Data/

    • Compiled ASV tables, taxonomy assignments, and metadata across all included studies.
  • Notebooks/

    • Jupyter notebooks (R/Python) for data cleaning, processing, and meta-analysis workflows.
  • DADA2_output

    • Notebooks of Qiime2 analysis of each study and then merged.

  • **`## 🛠️ Reproducing the Analysis
  1. Clone the repo
    git clone https://github.com/srosales712/SCTLD_microbiome_meta_analysis.git
    cd SCTLD_microbiome_meta_analysis

About

The goal of this study is to conduct a meta-analysis of publicly available and unpublished SCLTD microbiome datasets. In doing this we aim to: (1) Characterize the microbiome of SCTLD across region, species, year, and studies. (2) Identify drivers leading to variation among datasets.

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