Editing Transcriptome (section)

{{Short description|Set of all RNA molecules in one cell or a population of cells}}
The '''transcriptome''' is the set of all [[RNA]] transcripts, including coding and [[non-coding RNA|non-coding]], in an individual or a population of [[cell (biology)|cells]]. The term can also sometimes be used to refer to [[RNA#Types of RNA|all RNAs]], or just [[Messenger RNA|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 (biology)|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.<ref name="biblio1" /> 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 [[Phylogenetic inference using transcriptomic data|finds applications]] in establishing [[phylogenetics|phylogenetic relationships]] during the process of evolution and in [[in vitro fertilization|''in vitro'' fertilization]]. The transcriptome is closely related to other [[Omics|-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.<ref>{{Cite journal |last1=Cavicchioli |first1=Maria Vittoria |last2=Santorsola |first2=Mariangela |last3=Balboni |first3=Nicola |last4=Mercatelli |first4=Daniele |last5=Giorgi |first5=Federico Manuel |date=January 2022 |title=Prediction of Metabolic Profiles from Transcriptomics Data in Human Cancer Cell Lines |journal=International Journal of Molecular Sciences |language=en |volume=23 |issue=7 |pages=3867 |doi=10.3390/ijms23073867| pmid=35409231 |pmc=8998886 |issn=1422-0067|doi-access=free }}</ref> There are numerous publicly available transcriptome databases.