The gene identification procedure in a completely new gene with no good homology with protein sequences can be a very complex task. In order to identify the protein-coding region, a new method, 'SYNCOD', based on the analysis of conservative evolutionary properties of coding regions, has been realized. This program is able to identify and use the coding region homologies of the non-annotated (unknown) protein-coding sequences already present in the nucleotide sequence databases by using the alignment produced by BLASTN. The ratio of number mismatches resulting in synonymous codons to the number of mismatches resulting in non-synonymous codons is estimated for each open reading frame. Monte Carlo simulations are then used to estimate the significance of the ratio deviation from random behavior. The SYNCOD program has been tested on generated random sequences and on different control sets. The high accuracy of predicting protein-coding regions (the correlation coefficient, CC, varies from 0.67 to 0.79) and the high specificity (the portion of wrong exons, WE, varies from 0.06 to 0.07) have proved to be important features of the suggested approach. The SYNCOD program is resident on the ITBA-CNR Web Server and can be used via the Internet (URL: www.itba.mi.cnr.it/webgene). (C) 1999 Elsevier Science B.V. All rights reserved.
Protein-coding regions prediction combining similarity searches and conservative evolutionary properties of protein-coding sequences
Milanesi L
1999
Abstract
The gene identification procedure in a completely new gene with no good homology with protein sequences can be a very complex task. In order to identify the protein-coding region, a new method, 'SYNCOD', based on the analysis of conservative evolutionary properties of coding regions, has been realized. This program is able to identify and use the coding region homologies of the non-annotated (unknown) protein-coding sequences already present in the nucleotide sequence databases by using the alignment produced by BLASTN. The ratio of number mismatches resulting in synonymous codons to the number of mismatches resulting in non-synonymous codons is estimated for each open reading frame. Monte Carlo simulations are then used to estimate the significance of the ratio deviation from random behavior. The SYNCOD program has been tested on generated random sequences and on different control sets. The high accuracy of predicting protein-coding regions (the correlation coefficient, CC, varies from 0.67 to 0.79) and the high specificity (the portion of wrong exons, WE, varies from 0.06 to 0.07) have proved to be important features of the suggested approach. The SYNCOD program is resident on the ITBA-CNR Web Server and can be used via the Internet (URL: www.itba.mi.cnr.it/webgene). (C) 1999 Elsevier Science B.V. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
