RESUMO
A crucial part in the gene structure prediction is to identify the accurate splice sites, not only constitutive but also alternative ones. Here, we use the maximum information principle (MIP) to analyze the conservative segments around splice sites. According to the MIP, a reaction free energy (RFE) expression is deduced, which can be employed to estimate the free energy change during splicing reaction involving a donor or acceptor site. The expression contains not only the background probability factors, but also all kinds of dependencies among both adjacent and non-adjacent bases. We apply the RFE expression to recognize splice sites and their flanking competitors in human genes, the results show high sensitivity and specificity, so the RFE expression accords well with the splicing reaction process. Moreover, the RFE expression is better than previous methods for predicting competitors of splice sites, and it outperforms the reaction free energy subtraction (RFES), that implies RFE competition between a given splice site and its flanking competitor may not be an only primary factor for alternative splice site selection. The work is helpful to not only the understanding of splicing reaction from its relation to MIP, but also the research on computational recognition of splicing sites and alternative splice events.
Assuntos
Splicing de RNA , Processamento Alternativo , Éxons , Íntrons , Cinética , Valor Preditivo dos Testes , Proteínas/genética , Precursores de RNA/genética , RNA Mensageiro/genética , Sensibilidade e Especificidade , TermodinâmicaRESUMO
Based on the statistical analysis of 119 human and 92 E. coli proteins it was found that for both human and E. coli, the mRNA sequences consisting of tri-codon and tetra-codon with high translation speed preferably code for alpha helices more than for coils. For beta strand, the preference/avoidance oscillates with the translation speed. Moreover, the non-homogeneous usages of tri-codon and tetra-codon with different translation speeds in a given secondary structure have also been found. These results cannot be simply explained by the effect of stochastic fluctuation.
