de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Datenschutzhinweis Impressum Kontakt
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Hochschulschrift

Towards rapid and cost-effective genome characterisation using LNA-modified oligonucleotide DNA hybridisation

MPG-Autoren

Jianping,  Liu
Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Jianping, L. (2007). Towards rapid and cost-effective genome characterisation using LNA-modified oligonucleotide DNA hybridisation. PhD Thesis, Freie Universität, Berlin.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0010-8142-F
Zusammenfassung
Oligonucleotide fingerprinting (OFP) is a high-throughput alternative to tag sequencing methods to determine the spectrum and abundance of genes in genomic DNA or cDNA libraries. This method currently relies on the sequential hybridisations of at least 200 short (8-12 mer), radioactively labeled DNA oligonucleotides to arrayed dsDNAs. After image analysis, a sequence fingerprint is generated for each clone based on the hybridisation signals. Then according to the fingerprint similarity, the clones from the same gene can be grouped together using clustering algorithms. The main problems of the classic OFP method include high oligoprobe number and the use of radioactivity. To resolve these problems, here we have exploited the high affinity and good mismatch discrimination of oligoprobes modified with locked nucleic acid (LNA). In our method, short (hexamer or heptamer) LNA-modified oligoprobes are labelled with fluorescent dyes (e.g. Cy5). Hybridisation results are recorded with a CCD-camera developed for this purpose. The sensitivity of the fluorescence detection permits the convenient use of homogenous liquid assay as well as nylon membrane support. Thus hybridisation data quality is improved, and the process accelerated, simplified, and less expensive.