Int J Biol Sci 2009; 5(1):13-19. doi:10.7150/ijbs.5.13 This issue Cite
1. The Kazakh National University named after al-Farabi, av. al-Farabi, build. 71, 050038 Almaty, Kazakhstan
2. INRIA (Institut National de Recherche en Informatique et en Automatique), BP 105, Le Chesnay, France
The splice-site sequences of U2-type introns are highly degenerate, so many different sequences can function as U2-type splice sites. Using our new profiles based on hydrophobicity properties we pointed out specific properties for regions surrounding splice sites. We built a set T of flanking regions of genes with 1-3 introns from 21st and 22nd chromosomes extracted from GenBank to define positions having conserved properties, namely hydrophobicity, that are potentially essential for recognition by spliceosome.
GT–AG introns exist in U2 and U12-types. Therefore, intron type cannot be simply determined by the dinucleotide termini. We attempted to distinguish U2 and U12-types introns with help of hydrophobicity profiles on sets of spice sites for U2 or U12-type introns extracted from SpliceRack database. The positions given by our method, which may be important for recognition by spliceosome, were compared to the nucleotide consensus provided by a classical method, Pictogram. We showed that there is a similarity of hydrophobicity profiles inside intron types. On one hand, GT–AG and GC–AG introns belonging to U2-type have resembling hydrophobicity profiles as well as AT–AC and GT–AG introns belonging to U12-type. On the other hand, hydrophobicity profiles of U2 and U12-types GT–AG introns are completely different. We suggest that hydrophobicity profiles facilitate definition of intron type, distinguishing U2 and U12 intron types and can be used to build programs to search splice site and to evaluate their strength.
Therefore, our study proves that hydrophobicity profiles are informative method providing insights into mechanisms of splice sites recognition.
Keywords: hydrophobicity, splice sites, U2-type introns, U12-type introns, Pictograms, P-value, consensus sequences, splice sites recognition.