Table of Contents

Transcriptomics

Transcriptomics is the quantitative study of the RNA content in a cell, including coding and non-coding transcripts. With RNA-Sequencing approaches, it is possible to analyse a variety of biological processes such as differential gene expression, co- and post-transcriptional processing events (e.g. alternative splicing, alternative polyadenylation, RNA editing etc.) or identification of binding regions of RNA-binding proteins. The following list comprises RNA-Seq based applications we analyse regularly. We also offer analysis of RNA-Seq datasets from long-read sequencing approaches (PacBio and Oxford Nanopore) derived from cDNA or RNA libraries (ONP dRNA-Seq).

Gene Expression Analysis

Gene expression is the fundamental biological process by which genetic information is transmitted into a functional gene product, either as a protein or a non-coding RNA.

We routinely analyse differential gene expression from bulk RNA-Seq data. Data quality requirements are met through comprehensive quality control and testing. Gene expression analysis is then performed for all pairwise comparisons of experimental conditions using a robust toolchain. Wide functional characterization of differentially expressed genes is performed to provide biologically relevant information. This includes enrichments of biological pathways and gene ontology terms, as well as protein-protein interaction networks.

Data input

Standard compressed single or paired-end FASTQ files from RNA-Seq experiment
Organism name
Experimental conditions linked to samples

Analysis Workflow

1. Quality control raw data
2. Read alignment
3. Gene expression analysis
4. Functional enrichment analysis
5. Protein-protein interaction analysis

Tabular results

Data quality metrics
Read alignment metrics
Gene expression data as TpM per gene
Differential gene expression as fold changes per gene, including statistics
Functional enrichment results
Protein-protein interaction data

Graphical results

Principal component analysis
Sample-to-sample distance tree and matrix
Clustered heatmap
Volcano plot
Protein-protein interaction networks

Alternative Splicing Analysis

Alternative pre-mRNA splicing (AS) is a process resulting in the generation of multiple mRNA isoforms from one precursor. Translation of these isoforms increases the structural and functional space of the proteome. Besides the expansion of protein diversity, AS creates an additional layer of gene expression regulation, as it influences several steps of the mRNA maturation process.

We offer the analysis of alternative splicing from bulk RNA-Seq data. Our pipeline ensures that data quality requirements are met through comprehensive quality control and testing. Alternative splicing analysis is then performed for all pairwise comparisons of experimental conditions using a robust toolchain. Wide functional characterisation of alternative splicing events is performed to provide biologically relevant information. This includes enrichments of biological pathways and gene ontology terms, as well as protein-protein interactions.

Data input

Standard compressed single or paired-end FASTQ files from RNA-Seq experiment
Organism name
Experimental conditions linked to samples

Analysis Workflow

1. Quality control raw data
2. Read alignment
3. Alternative splicing analysis
4. Functional enrichment analysis
5. Protein-protein interaction analysis

Tabular results

Data quality metrics
Read alignment metrics
Alternative splicing ratios as percent spliced in per event
Differential alternative splicing as inclusion changes per event, including statistics
Functional enrichment results
Protein-protein interaction data

Graphical results

Principal component analysis
Sample-to-sample distance tree and matrix
Clustered heatmap
Protein-protein interaction networks

Alternative Polyadenylation Analysis

Alternative polyadenylation (APA) analysis is the process of detecting differential usage of alternative polyadenylation sites from RNA-Seq data. Studying APA is important for better understanding how mRNA processing impacts fundamental biological processes such as the stability, localization and translation of mRNA.

We provide analysis of RNA-Seq data for genome-wide identification of differentially used polyadenylation sites. This is achieved using a state-of-the-art toolchain with integrated quality control steps, which ensures that data quality requirements are met. We also perform downstream analyses such as functional characterization of polyadenylation sites and correlation with gene expression if such data is available.

Intron Retention Analysis

Intron retention is a subtype of alternative splicing, whereby introns are retained in a mature mRNA. This type of RNA processing event has been shown to play an important role in the regulation of gene expression. Exploring the functional impact of intron retention events thus is beneficial for understanding how alternative splicing influences gene expression and might contribute to the emergence of complex diseases.

We offer analysis of RNA-Seq data for genome-wide identification of intron retention events. This is achieved using a robust toolchain with integrated quality control steps, ensuring that results can be trusted. We also perform downstream analyses such as functional characterisation of intron retention events and correlation with gene expression if such data is available.

CLIP-Seq Analysis

Cross-linking immunoprecipitation sequencing combines UV cross-linking with immunoprecipitation and RNA-Seq to identify RNA binding proteins (RBPs) and their binding sites. Investigating the dynamic interactions between RBPs and the transcriptome is crucial for better understanding the life cycle of RNA molecules, and how RNA biology affects a range of physiological processes.

We provide analysis of CLIP-Seq data generated by most common CLIP-Seq protocol variants (HITS-CLIP, iCLIP, eCLIP, PAR-CLIP) for transcriptome-wide identification and characterisation of RBP binding sites. This is achieved using an up-to-date toolchain, capable of both robust quality assurance and peak calling according to current best-practices. We also perform downstream analyses of obtained peaks, including functional enrichment analysis and RNA map construction.

RNA-Editing Analysis

RNA-editing is a type of post-transcriptional modification that leads to the exchange of specific nucleotides in the sequences of RNA transcripts, most notably A-to-I and C-to-U. Studying RNA-editing is fundamental for gaining a better understanding of how RNA modifications might impact and regulate downstream biological processes such as translation efficiency, RNA stability and alternative splicing.

We offer analysis of RNA-Seq data for transcriptome-wide identification of both A-to-I and C-to-U RNA-editing events. This is achieved using a state-of-the-art toolchain with stringent quality assurance and filtration steps, followed by de novo RNA-editing calling. We can also help with integrating the RNA-editing analysis results with other data sources such as gene expression and alternative splicing results for comparison and correlation.

Want to discuss a transcriptomics project?

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