700,000 ORESTES
A Brazilian project has added thousands of open reading frame expressed sequence tags (ORESTES) to efforts to define the complete human transcriptome.

Email: Jonathan B Weitzman - jonathanweitzman@hotmail.com
News from The Scientist 2001, 2(1):20011011-01

Published 11 October 2001

Now that we have the whole human genome sequence, the challenge remains to identify all the genes and transcripts hidden within it. In the October 9 Proceedings of the National Academy of Sciences, Anamaria Camargo and colleagues, from the Ludwig Institute for Cancer Research in Sao Paolo, Brazil, report the results from a Brazilian project aimed at defining the human transcriptome (Proc Natl Acad Sci USA 2001, 98:12103-12108).

The approach being used exploits open reading frame expressed sequence tags ORESTES. This differs from the conventional expressed sequence tag (EST) strategy in that it provides sequence information along the whole length of each transcript, rather than just the ends. The method involves low-stringency PCR to produce cDNA libraries, samples of which are then sequenced.

Camargo et al. generated almost 700,000 ORESTES from 24 types of normal or malignant tissue using 3,540 mini-libraries. They predict that their ORESTES dataset may represent as many as 60% of all human genes (including abundant and rare transcripts). The ORESTES approach generates a larger coverage and a greater number of contigs per gene than to standard EST methods, offering the possibility to complete the closure of most sequences using RT-PCR.



References

1.  [http://www.pnas.org/cgi/content/abstract/98/21/12103]
  Camargoa AA, Samaiaa HPB, Dias-Neto E, et al.: The contribution of 700,000 ORF sequence tags to the definition of the human transcriptome. Proc Natl Acad Sci USA 2001, 98:12103-12108.
Return to citation in text: [1]
 
2.  [http://www.ludwig.org.br]
  Ludwig Institute for Cancer Research
Return to citation in text: [1]
 
3. Shotgun sequencing of the human transcriptome with ORF expressed sequence tags.

  Return to citation in text: [1]
 


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