Transcriptome is the total RNA content of an organism or tissue type. It represented all varieties of RNA and their copies in an organism or tissue. Transcriptome is responsible for active changes seen during the life cycle of an organism. The total content of RNAs varies depending on cell function or environmental conditions. At any given time, there could be thousands of RNA transcripts in an organism that represent the gene expression. The study of RNAs content and sum total of RNA transcripts is called “transcriptomics”. mRNA represents the protein content or level of gene expression while non-coding RNA (ncRNA) do not code of any proteins but perform diverse functions.
Advantages of Transcriptomics
- Transcriptomics is easy with fairly straightforward library preparation and reproducible results.
- Transcriptome analysis enables to assay thousands of genes in parallel.
- Transcriptome analysis a snapshot of transcripts or gene expression at a time point for a tissues or samples.
- Transcriptomics study provides a quick review of gene ontology or pathways involved in a tissues / sample in a given environment.
Transcriptome Analysis Overview
Transcriptome analysis or in short transcriptomics has propelled our ability to profile and characterise individual transcript of the whole transcriptome or a transcriptome segment like non-coding RNAs. Transcriptome analysis can be divided into 2 areas:
– In absence of a known set of mRNA transcript draft, a transcript assembly is performed to characterise all mRNAs and isoforms in a transcriptome. De novo transcriptome assembly is a complex process due to the alternative splicing events across various tissues. We have optimized the process of transcriptome de novo assembly. Our robust transcriptome analysis pipeline generate accurate transcriptome assemblies ready for functional annotation.
– To understand gene regulation in an organism or specific tissue under given environment condition.
To read about our gene expression services click in this link: Gene Expression Analysis.
We have standardized our transcriptome analysis pipeline that can handle diverse datasets and generate best results be is transcript assembly, gene expression study or functional annotation of transcripts. We are equally efficient to handle short reads – Illumina sequencing or long reads – PacBio or Nanopore sequencing data.