Identification of activated cryptic 5′ splice sites using structure profiles and odds measure
Author(s) -
KunNan Tsai,
Daryi Wang
Publication year - 2012
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gks061
Subject(s) - biology , sss* , rna splicing , species complex , genetics , splice , computational biology , identification (biology) , markov chain , artificial intelligence , gene , computer science , machine learning , rna , botany , phylogenetic tree
The activation of cryptic 5' splice sites (5' SSs) is often related to human hereditary diseases. The DNA-based mutation screening strategies are commonly used to recognize the cryptic 5' SSs, because features of the local DNA sequence can influence the choice of cryptic 5' SSs. To improve the identification of the cryptic 5' SSs, we developed a structure-based method, named SPO (structure profiles and odds measure), which combines two parameters, the structural feature derived from hydroxyl radical cleavage pattern and odds measure, to assess the likelihood of a cryptic 5' SS activation in competing with its paired authentic 5' SS. Compared to the current tools for identifying activated cryptic 5' SSs, the SPO algorithm achieves higher prediction accuracy than the other methods, including MaxEnt, MDD, Markov model, weight matrix model, Shapiro and Senapathy matrix, R(i) and ΔG. In addition, the predicted ΔSPO scores from the SPO algorithm exhibited a greater degree of correlation with the strength of cryptic 5' SS activation than that measured from the other seven methods. In conclusion, the SPO algorithm provides an optimal identification of cryptic 5' SSs, can be applied in designing mutagenesis experiments for various splicing events and may be helpful to investigate the relationship between structural variants and human hereditary diseases.
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