Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/119811
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Type: | Journal article |
Title: | Transcriptomics technologies |
Author: | Lowe, R. Shirley, N. Bleackley, M. Dolan, S. Shafee, T. |
Citation: | PLoS Computational Biology, 2017; 13(5):e1005457-1-e1005457-23 |
Publisher: | Public Library of Science (PLoS) |
Issue Date: | 2017 |
ISSN: | 1553-7358 1553-734X |
Statement of Responsibility: | Rohan Lowe, Neil Shirley, Mark Bleackley, Stephen Dolan, Thomas Shafee |
Abstract: | 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. |
Keywords: | Animals Humans Mice Rats RNA Oligonucleotide Array Sequence Analysis Cluster Analysis Gene Expression Profiling Sequence Analysis, RNA Organ Specificity Image Processing, Computer-Assisted High-Throughput Nucleotide Sequencing |
Rights: | Copyright: © 2017 Lowe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
DOI: | 10.1371/journal.pcbi.1005457 |
Grant ID: | http://purl.org/au-research/grants/arc/DP160100309 |
Published version: | http://dx.doi.org/10.1371/journal.pcbi.1005457 |
Appears in Collections: | Agriculture, Food and Wine publications Aurora harvest 8 |
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hdl_119811.pdf | Published Version | 1.29 MB | Adobe PDF | View/Open |
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