journal contributionposted on 11.02.2021, 23:49 by Rohan LoweRohan Lowe, Neil Shirley, Mark BleackleyMark Bleackley, Stephen Dolan, Thomas ShafeeThomas Shafee
© 2017 Lowe et al. Transcriptomics technologies are the techniques used to study an organism’s transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst noncoding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. The first attempts to study the whole transcriptome began in the early 1990s, and technological advances since the late 1990s have made transcriptomics a widespread discipline. Transcriptomics has been defined by repeated technological innovations that transform the field. There are two key contemporary techniques in the field: microarrays, which quantify a set of predetermined sequences, and RNA sequencing (RNA-Seq), which uses high-throughput sequencing to capture all sequences. Measuring the expression of an organism’s genes in different tissues, conditions, or time points gives information on how genes are regulated and reveals details of an organism’s biology. It can also help to infer the functions of previously unannotated genes. Transcriptomic analysis has enabled the study of how gene expression changes in different organisms and has been instrumental in the understanding of human disease. An analysis of gene expression in its entirety allows detection of broad coordinated trends which cannot be discerned by more targeted assays.
This work was supported by the Australian Research Council grant DP160100309. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Australian Research Council | DP160100309
JournalPLoS Computational Biology
Pagination23p. (p. 1-23)
PublisherPublic Library of Science
Rights StatementThe Author reserves all moral rights over the deposited text and must be credited if any re-use occurs. Documents deposited in OPAL are the Open Access versions of outputs published elsewhere. Changes resulting from the publishing process may therefore not be reflected in this document. The final published version may be obtained via the publisher’s DOI. Please note that additional copyright and access restrictions may apply to the published version.
Science & TechnologyLife Sciences & BiomedicineBiochemical Research MethodsMathematical & Computational BiologyBiochemistry & Molecular BiologyDIFFERENTIAL EXPRESSION ANALYSESMICROARRAY EXPERIMENT MIAMESINGLE-STEP METHODCELL RNA-SEQGENE-EXPRESSIONDNA MICROARRAYMINIMUM INFORMATIONNONCODING RNASRIBOSOMAL-RNASEQUENCE TAGSAnimalsHumansMiceRatsRNAOligonucleotide Array Sequence AnalysisCluster AnalysisGene Expression ProfilingSequence Analysis, RNAOrgan SpecificityImage Processing, Computer-AssistedHigh-Throughput Nucleotide SequencingBioinformatics