Transcriptome

The transcriptome is the set of all RNA molecules, including coding and non-coding, in a bilogical cells or a population of cells, such as tissue, organ or organism. 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 transcriptome is dynamic — it changes with cell type, developmental stage, environment, disease state, and stimuli — and therefore represents the active gene expression state rather than the static DNA sequence (genome).

Key points Same genome, different transcriptomes: Every nucleated cell normally contains the same DNA sequence, but different cells/tissues have distinct transcriptomes because they express different subsets and levels of genes. Components: mRNAs (including alternatively spliced isoforms), noncoding RNAs (miRNA, lncRNA, snoRNA, etc.), and precursor RNAs (pre‑mRNA) with various processing states. Dynamics: Transcript abundance varies quantitatively (levels) and qualitatively (which isoforms are present); it responds rapidly to signals and stress and reflects both transcriptional and post‑transcriptional regulation. Relationship to proteome: The transcriptome is upstream of the proteome; RNA levels often correlate with protein abundance but not perfectly because of translational control and protein stability. Biological insight: Studying the transcriptome reveals which genes are active, regulatory programs, cell‑type identities, pathways engaged in responses, and biomarkers for disease. How it’s measured (common methods)

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. 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. There are numerous publicly available transcriptome databases.

The word transcriptome is a portmanteau of the words transcript and genome. It appeared along with other neologisms formed using the suffixes -ome and -omics to denote all studies conducted on a genome-wide scale in the fields of life sciences and technology. As such, transcriptome and transcriptomics were one of the first words to emerge along with genome and proteome. The first study to present a case of a collection of a cDNA library for silk moth mRNA was published in 1979. The first seminal study to mention and investigate the transcriptome of an organism was published in 1997 and it described 60,633 transcripts expressed in S. cerevisiae using serial analysis of gene expression (SAGE). With the rise of high-throughput technologies and bioinformatics and the subsequent increased computational power, it became increasingly efficient and easy to characterize and analyze enormous amount of data. Attempts to characterize the transcriptome became more prominent with the advent of automated DNA sequencing during the 1980s. During the 1990s, expressed sequence tag sequencing was used to identify genes and their fragments. This was followed by techniques such as serial analysis of gene expression (SAGE), cap analysis of gene expression (CAGE), and massively parallel signature sequencing (MPSS).

The transcriptome encompasses all the ribonucleic acid (RNA) transcripts present in a given organism or experimental sample. RNA is the main carrier of genetic information that is responsible for the process of converting DNA into an organism's phenotype. A gene can give rise to a single-stranded messenger RNA (mRNA) through a molecular process known as transcription; this mRNA is complementary to the strand of DNA it originated from. The enzyme RNA polymerase II attaches to the template DNA strand and catalyzes the addition of ribonucleotides to the 3' end of the growing sequence of the mRNA transcript.

In order to initiate its function, RNA polymerase II needs to recognize a promoter sequence, located upstream (5') of the gene. In eukaryotes, this process is mediated by transcription factors, most notably Transcription factor II D (TFIID) which recognizes the TATA box and aids in the positioning of RNA polymerase at the appropriate start site. To finish the production of the RNA transcript, termination takes place usually several hundred nuclecotides away from the termination sequence and cleavage takes place. This process occurs in the nucleus of a cell along with RNA processing by which mRNA molecules are capped, spliced and polyadenylated to increase their stability before being subsequently taken to the cytoplasm. The mRNA gives rise to proteins through the process of translation that takes place in ribosomes.

Almost all functional transcripts are derived from known genes. The only exceptions are a small number of transcripts that might play a direct role in regulating gene expression near the prompters of known genes. (See Enhancer RNA.)