A computational investigation of kinetoplastid trans-splicing.
Trans-splicing is an unusual process in which two separate RNA strands are spliced together to yield a mature mRNA. We present a novel computational approach which has an overall accuracy of 82% and can predict 92% of known trans-splicing sites. We have applied our method to chromosomes 1 and 3 of Leishmania major, with high-confidence predictions for 85% and 88% of annotated genes respectively. We suggest some extensions of our method to other systems.
Gopal
Shuba
S
Laboratory of Computational Genomics, Rockefeller University, 1230 York Avenue, New York, NY 10021, USA. sxgsbi@rit.edu
Awadalla
Saria
S
Gaasterland
Terry
T
Cross
George A M
GA
D000818:Animals; D001482:Base Composition; D002875:Chromosomes / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D018503:Genome, Protozoan; D018320:Leishmania major / Q000235:genetics* / Q000378:metabolism; D022821:RNA Splice Sites / Q000235:genetics; D016053:RNA, Protozoan / Q000378:metabolism*; D017423:Sequence Analysis, RNA / Q000379:methods*; D020040:Trans-Splicing / Q000235:genetics*
D022821:RNA Splice Sites; D016053:RNA, Protozoan