The transcriptome is the set of all RNA transcripts, including coding and non-coding, in an individual or a population of cells. The term can also sometimes be used to refer to all RNAs, or just mRNA, depending on the particular experiment. The term transcriptome is a portmanteau of the words transcript and genome; it is associated with the process of transcript production during the biological process of transcription.
The early stages of transcriptome annotations began with cDNA libraries published in the 1980s. Subsequently, the advent of high-throughput technology led to faster and more efficient ways of obtaining data about the transcriptome. Two biological techniques are used to study the transcriptome, namely DNA microarray, a hybridization-based technique and RNA-seq, a sequence-based approach.[1] RNA-seq is the preferred method and has been the dominant transcriptomics technique since the 2010s. Single-cell transcriptomics allows tracking of transcript changes over time within individual cells.
Data obtained from the transcriptome is used in research to gain insight into processes such as cellular differentiation, carcinogenesis, transcription regulation and biomarker discovery among others. Transcriptome-obtained data also finds applications in establishing phylogenetic relationships during the process of evolution and in in vitro fertilization. The transcriptome is closely related to other -ome based biological fields of study; it is complementary to the proteome and the metabolome and encompasses the translatome, exome, meiome and thanatotranscriptome which can be seen as ome fields studying specific types of RNA transcripts. There are quantifiable and conserved relationships between the Transcriptome and other -omes, and Transcriptomics data can be used effectively to predict other molecular species, such as metabolites.[2] There are numerous publicly available transcriptome databases.
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