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Related Experiment Video

Updated: Aug 9, 2025

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

A Guide to Gene-Centric Analysis Using TreeSAPP.

Connor Morgan-Lang¹, Steven J Hallam^1,2,3,4,5

¹Graduate Program in Bioinformatics, University of British Columbia, Genome Sciences Centre, Vancouver, British Columbia, Canada.

Current Protocols

|February 21, 2023

Summary

This summary is machine-generated.

This study introduces TreeSAPP protocols for accurate microbial gene-centric analysis. The new workflow standardizes marker gene analysis, improving accuracy and utility for metagenomic and metatranscriptomic datasets.

Keywords:

metagenomics methanogenesis microbial ecology phylogenetic placement

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Last Updated: Aug 9, 2025

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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

Area of Science:

Microbial Ecology
Bioinformatics
Genomics

Background:

Gene-centric analysis is crucial for understanding microbial communities but often relies on inaccurate custom marker gene sets.
Existing methods for analyzing phylogenetic and functional marker genes lack standardization and can be limited in scope.
The Tree-based Sensitive and Accurate Phylogenetic Profiler (TreeSAPP) offers a standardized approach using comprehensive reference packages.

Purpose of the Study:

To provide standardized protocols for utilizing the TreeSAPP software package for gene-centric analysis.
To detail a workflow for constructing, refining, and applying reference packages for marker gene identification and abundance calculation.
To enhance the accuracy and utility of microbial community analysis using phylogenetic and functional marker genes.

Main Methods:

Development and presentation of a coherent workflow linking TreeSAPP analysis modules.
Construction and refinement of information-rich reference packages including multiple sequence alignments, HMMs, taxonomic data, and phylogenetic trees.
Application of TreeSAPP to identify marker genes (e.g., McrA) and calculate normalized relative abundances in metagenomic and metatranscriptomic data.

Main Results:

Established best practices for reference package construction, refinement, and manual curation for reproducible gene-centric analysis.
Demonstrated the utility of TreeSAPP with a use case involving the methyl-coenzyme M reductase alpha subunit (McrA) gene.
Provided protocols that fill gaps in existing TreeSAPP documentation, enhancing user experience and analytical performance.

Conclusions:

The presented TreeSAPP protocols standardize and improve the accuracy of gene-centric analysis in microbial ecology.
This workflow supports reproducible analysis of phylogenetic and functional marker genes in diverse environmental datasets.
TreeSAPP, with these protocols, offers a robust solution for taxonomic and functional profiling of microbial communities.