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Trem2*R47H Differential Splicing Analysis Workflow

License: MIT DOI BMC Genomics

This repository contains the complete bioinformatics workflow used in:

Pandey RS, Kotredes KP, Sasner M, Howell GR, Carter GW. Differential splicing of neuronal genes in a Trem2*R47H mouse model mimics alterations associated with Alzheimer's disease. BMC Genomics. 2023;24:172. https://doi.org/10.1186/s12864-023-09280-x


Overview

We performed differential gene expression and differential splicing analyses on whole-brain transcriptomes from aging mouse models carrying humanized APOE4 and/or the Trem2*R47H variant on a C57BL/6J background. This workflow documents every computational step from raw FASTQ processing through functional annotation, enabling full reproduction of published results.

Key findings:

  • Differentially expressed genes in Trem2*R47H mice were enriched in immune and metabolic pathways
  • Differentially spliced genes were enriched in neuronal functions (GABAergic and glutamatergic synapse)
  • Significant overlap was observed between spliced genes in Trem2*R47H mice and human AD subjects
  • These effects were absent in APOE4 mice and suppressed in APOE4·Trem2*R47H double mutant mice

Workflow Summary

The full step-by-step workflow is documented in WORKFLOW.md.

Part 1 — Upstream RNA-seq Processing (Unix)

Step Tool Version Purpose
1 FastQC v0.11.3 Read quality assessment
2 Trimmomatic v0.33 Adapter and quality trimming
3 STAR v2.5.3 Alignment to reference genome
4 HTSeq v0.8.0 Gene-level read counting
5 RSEM v1.3.3 Isoform-level quantification

Part 2 — Downstream Analysis (R)

Step Tool Version Purpose
6 DESeq2 v1.16.1 Differential gene expression
7 DEXSeq v1.40.0 Differential exon usage
8 IsoformSwitchAnalyzeR v1.20.0 Isoform switch analysis
9 clusterProfiler KEGG and GO enrichment
10 Cell type enrichment (Fisher's exact test)
11 RBPmap RNA-binding protein site prediction
12 Overlap with human AD splicing studies

Data Availability

Raw sequencing data and processed count matrices are available via the AD Knowledge Portal:

https://adknowledgeportal.synapse.org/Explore/Studies/DetailsPage/StudyDetails?Study=syn66318364


Repository Structure

Trem2-RNAseq-splicing-workflow/
│
├── README.md          # This file
├── WORKFLOW.md        # Complete 12-step documented workflow
├── LICENSE            # MIT license
│
└── scripts/
    ├── DEG_function.R              # DESeq2 wrapper function
    ├── ENRICHGO_function.R         # GO enrichment function
    └── cell_type_enrichment.R      # Fisher's exact test for cell types

Requirements

Unix Environment (Part 1)

Tool Version Installation
FastQC v0.11.3 bioinformatics.babraham.ac.uk
Trimmomatic v0.33 usadellab.org
STAR v2.5.3 github.com/alexdobin/STAR
Picard v1.95 broadinstitute.github.io/picard
SAMtools v1.10 samtools.sourceforge.net
HTSeq v0.8.0 htseq.readthedocs.io
RSEM v1.3.3 github.com/deweylab/RSEM

R Environment (Part 2)

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install(c(
  "DESeq2",
  "DEXSeq",
  "IsoformSwitchAnalyzeR",
  "clusterProfiler",
  "org.Mm.eg.db",
  "AnnotationDbi",
  "BiocParallel",
  "BSgenome.Mmusculus.UCSC.mm10"
))

install.packages(c("tidyverse", "xlsx"))

Reference Genome

All analyses used the mouse reference genome GRCm38/mm10 with Ensembl annotation (release 97).


Citation

If you use this workflow, please cite:

Pandey RS, Kotredes KP, Sasner M, Howell GR, Carter GW. Differential splicing of neuronal genes in a Trem2*R47H mouse model mimics alterations associated with Alzheimer's disease. BMC Genomics. 2023;24:172. https://doi.org/10.1186/s12864-023-09280-x


License

MIT — see LICENSE for details.


Contact

Ravi S. Pandey GitHub: @pandeyravi15

About

Bioinformatics workflow for differential splicing analysis in Alzheimer's disease mouse models (Pandey et al. 2023, BMC Genomics)

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