Author: Moyosore Shittu
Plants are continuously exposed to environmental stresses such as ultraviolet (UV) radiation, which can disrupt cellular processes and gene regulation. This project investigates the transcriptomic response of Arabidopsis thaliana to UV stress using RNA-seq data.
A reproducible Nextflow pipeline was developed to automate raw data retrieval, quality control, trimming, genome preparation, alignment, and gene-level quantification. The resulting gene count matrix is intended for downstream differential expression and functional enrichment analysis.
The leaf vasculature plays an essential role in coordinating systemic stress responses by integrating transport and signaling functions. Previous studies have shown that UV radiation induces strong transcriptional reprogramming associated with DNA repair, oxidative stress, and metabolic adaptation.
Using publicly available RNA-seq datasets, this project focuses on characterizing gene expression changes associated with UV exposure in Arabidopsis thaliana.
The main objectives of this project were to:
- Build an automated and reproducible RNA-seq processing pipeline using Nextflow
- Perform quality control and preprocessing of raw RNA-seq reads
- Align reads to the Arabidopsis thaliana reference genome
- Generate a gene-level count matrix for downstream differential expression analysis
The analysis workflow consisted of the following major stages:
- Data acquisition from public RNA-seq repositories
- Quality control of raw sequencing reads
- Adapter removal and quality trimming
- Reference genome and annotation retrieval
- Genome indexing
- Splice-aware read alignment
- Post-alignment processing and sorting
- Gene-level read quantification
All steps were integrated into a single automated pipeline to ensure reproducibility and scalability.
RNA-seq FASTQ files → Quality control → Trimming → Genome download → Index building → Read alignment → BAM processing → Gene count generation
- Nextflow (workflow management)
- FastQC & MultiQC (quality assessment)
- fastp (read trimming)
- HISAT2 (splice-aware alignment)
- SAMtools (alignment processing)
- featureCounts (gene quantification)
- Ensembl Plants (reference genome & annotation)
The pipeline produces:
- Quality control reports
- Trimmed FASTQ files
- Sorted and indexed BAM files
- A gene-level count matrix
- A summary file for downstream RNA-seq analysis
These outputs are suitable for differential expression analysis using tools such as DESeq2 or edgeR.
This project demonstrates the development of a complete transcriptomics workflow for plant stress biology. The pipeline can be adapted for other plant species or experimental conditions and serves as a foundation for integrative transcriptomic and functional genomics studies.