Linked Life Data

19336255

Source:http://linkedlifedata.com/resource/pubmed/id/19336255

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2009-7-14
pubmed:abstractText
The ability to quantitatively survey the global behavior of transcriptomes has been a key milestone in the field of systems biology, enabled by the advent of DNA microarrays. While this approach has literally transformed our vision and approach to cellular physiology, microarray technology has always been limited by the requirement to decide, a priori, what regions of the genome to examine. While very high density tiling arrays have reduced this limitation for simpler organisms, it remains an obstacle for larger, more complex, eukaryotic genomes. The recent development of "next-generation" massively parallel sequencing (MPS) technologies by companies such as Roche (454 GS FLX), Illumina (Genome Analyzer II), and ABI (AB SOLiD) has completely transformed the way in which quantitative transcriptomics can be done. These new technologies have reduced both the cost-per-reaction and time required by orders of magnitude, making the use of sequencing a cost-effective option for many experimental approaches. One such method that has recently been developed uses MPS technology to directly survey the RNA content of cells, without requiring any of the traditional cloning associated with EST sequencing. This approach, called "RNA-seq", can generate quantitative expression scores that are comparable to microarrays, with the added benefit that the entire transcriptome is surveyed without the requirement of a priori knowledge of transcribed regions. The important advantage of this technique is that not only can quantitative expression measures be made, but transcript structures including alternatively spliced transcript isoforms, can also be identified. This article discusses the experimental approach for both sample preparation and data analysis for the technique of RNA-seq.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1095-9130
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
48
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
249-57
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
RNA-Seq-quantitative measurement of expression through massively parallel RNA-sequencing.
pubmed:affiliation
Laboratory of Molecular Genetics of Stem Cells, C.P. 6128 Succursale Centre-Ville, Montréal, Que. H3C3J7, Canada. Brian.wilhelm@umontreal.ca
pubmed:publicationType
Journal Article