What is transcriptomics?
July 7, 2019What is transcriptomics?
Simple defintion
Transcriptomics is the study of all the RNA molecules within a cell, otherwise known as the transcriptome.
Brief defintion
It’s the study of transcriptome of organisms. Transcriptome is the set of all RNA molecules, including mRNA, rRNA, tRNA, and non-coding RNA produced in one or a population of cells. Transcriptomics is also referred to as expression profiling, examines the expression level of RNAs in a given cell population.
What is a transcriptome?
The human genome is made up of DNA (deoxyribonucleic acid), a long, winding molecule that contains the instructions needed to build and maintain cells. These instructions are spelled out in the form of “base pairs” of four different chemicals, organized into 20,000 to 25,000 genes. For the instructions to be carried out, DNA must be “read” and transcribed – in other words, copied – into RNA (ribonucleic acid). These gene readouts are called transcripts, and a transcriptome is a collection of all the gene readouts present in a cell.
There are various kinds of RNA. The major type, called messenger RNA (mRNA), plays a vital role in making proteins. In this process: mRNA is transcribed from genes; then the mRNA transcripts are delivered to ribosomes, the molecular machines located in the cell’s cytoplasm; then the ribosomes read, or “translate,” the sequence of chemical letters in the mRNA and assemble building blocks called amino acids into proteins.
DNA can also be transcribed into other types of RNA that do not code for proteins. Such transcripts may serve to influence cell structure and to regulate genes.
Image courtesy: National Human Genome Research Institute
Difficulty in analysing transcriptome
Unlike the nuclear genome, whose composition and size are essentially static, the transcriptome often changes. The transcriptome is influenced by the phase of the cell cycle, the organ, exposure to drugs or physical agents, aging, diseases and a multitude of other variables, all of which must be considered at the time of its determination. However,this property that makes the transcriptome useful for the discovery of gene function and as a molecular signature
Why we need to study transcriptome?
Understanding the transcriptome is essential for interpreting the functional elements of the genome and revealing the molecular constituents of cells and tissues, and also for understanding development and disease.
Platform level analysis for transcriptomics
Various technologies have been developed to deduce and quantify the transcriptome, including hybridization-or sequence-based approaches. Hybridization-based approaches typically involve incubating fluorescently labelled cDNA with custom-made microarrays or commercial high-density oligo microarrays. Specialized microarrays have also been designed; for example, arrays with probes spanning exon junctions can be used to detect and quantify distinct spliced isoforms.However, these methods have several limitations, which include: reliance upon existing knowledge about genome sequence; high background levels owing to cross-hybridization; and a limited dynamic range of detection owing to both background and saturation of signals.
Recently, the development of novel high-throughput DNA sequencing methods has provided a new method for both mapping and quantifying transcriptomes. This method, termed RNA-Seq (RNA sequencing), has clear advantages over existing approaches and is expected to revolutionize the manner in which eukaryotic transcriptomes are analysed.
A transcriptomics dataset, produced by either next-generation sequencing (NGS) or microarray platforms, usually comprises the quantitative measurement of thousands of genes, a desirable feature for exploration of mechanisms.
The power of such a dataset can only be revealed when an adequate data analysis is in place. Post hoc analysis comprises three major steps in the sequence: platform level processing, contrast level data filtering or extraction, and module level characterization of behavior or synergistic effect of groups of genes.
References
1.Wang, Z., Gerstein, M., & Snyder, M. (2009). RNA-Seq: a revolutionary tool for transcriptomics. Nature reviews genetics, 10(1), 57.
2.Assis, A. F., Oliveira, E. H., Donate, P. B., Giuliatti, S., Nguyen, C., & Passos, G. A. (2014). What is the transcriptome and how it is evaluated?. In Transcriptomics in Health and Disease (pp. 3-48). Springer, Cham.
