RNA-Seq analysis is a powerful alternative when information from genomic analysis is insufficient. With our powerful RNA-Seq workflows, we identify differentially expressed genes, differentially spliced regions, genomic variants, and perturbed molecular pathways, among others.
Total RNA (Whole Transcriptome) Sequencing
The transcriptome reflects cellular activity within a tissue at a given time. Whole transcriptome contains coding and non-coding RNAs. Whole transcriptome sequencing can be used for cancer research, de novo transcriptome assembly studies or investigation of pre- and post-transcriptional changes. In addition, this method can be used to analyze regulatory regions, global expression levels of transcripts, splice patterns, and to determine exons and introns and their boundaries.
mRNA sequencing corresponds to 3-7% of the mammalian transcriptome. This method, in which only coding RNAs are sequenced, is generally preferred to detect genes with altered expression. The list of differentially expressed genes can be analyzed to identify perturbed molecular pathways and cellular processes.
miRNAs (microRNAs) are short, non-coding RNA molecules. They have inhibitory roles against mRNAs. They play roles in gene silencing and post-transcriptional regulation of gene expression.
Long non-coding RNA Sequencing
Long non-coding RNAs (lncRNAs) are defined as transcripts that are more than 200 nucleotides in length and do not encode protein. They interact with mRNAs and miRNAs to modulate regulatory events in the cell.
Single cell RNA Sequencing
Single cell RNA Sequencing (scRNA-Seq) is a popular and powerful method that allows the entire transcriptome of individual cells to be profiled. scRNA-Seq enables detection of cell-specific changes such as cell type identification, heterogeneity of cell responses, stochasticity of gene expression, and inference of gene regulatory networks across the cells.