Automated gene identification in large-scale genomic sequences

Species independence of mutual information in coding and noncoding DNA

We explore if there exist universal statistical patterns that are different in coding and noncoding DNA and can be found in all living organisms, regardless of their phylogenetic origin. We find that (i) the mutual information function [symbol: see text] has a significantly different functional form in coding and noncoding DNA. We further find that (ii) the probability distributions of the average mutual information [symbol: see text] are significantly different in coding and noncoding DNA, while (iii) they are almost the same for organisms of all taxonomic classes. Surprisingly, we find that [symbol: see text] is capable of predicting coding regions as accurately as organism-specific coding measures.

Using bioinformatics in gene and drug discovery

Bioinformatics has, out of necessity, become a key aspect of drug discovery in the genomic revolution, contributing to both target discovery and target validation. The author describes the role that bioinformatics has played and will continue to play in response to the waves of genome-wide data sources that have become available to the industry, including expressed sequence tags, microbial genome sequences, model organism sequences, polymorphisms, gene expression data and proteomics. However, these knowledge sources must be intelligently integrated.

Frequent alternative splicing of human genes

Alternative splicing can produce variant proteins and expression patterns as different as the products of different genes, yet the prevalence of alternative splicing has not been quantified. Here the spliced alignment algorithm was used to make a first inventory of exon-intron structures of known human genes using EST contigs from the TIGR Human Gene Index. The results on any one gene may be incomplete and will require verification, yet the overall trends are significant. Evidence of alternative splicing was shown in 35% of genes and the majority of splicing events occurred in 5' untranslated regions, suggesting wide occurrence of alternative regulation. Most of the alternative splices of coding regions generated additional protein domains rather than alternating domains.

Genome duplications and other features in 12 Mb of DNA sequence from human chromosome 16p and 16q

Several publicly funded large-scale sequencing efforts have been initiated with the goal of completing the first reference human genome sequence by the year 2005. Here we present the results of analysis of 11.8 Mb of genomic sequence from chromosome 16. The apparent gene density varies throughout the region, but the number of genes predicted (84) suggests that this is a gene-poor region. This result may also suggest that the total number of human genes is likely to be at the lower end of published estimates. One of the most interesting aspects of this region of the genome is the presence of highly homologous, recently duplicated tracts of sequence distributed throughout the p-arm. Such duplications have implications for mapping and gene analysis as well as the predisposition to recurrent chromosomal structural rearrangements associated with genetic disease.

A decision tree system for finding genes in DNA

MORGAN is an integrated system for finding genes in vertebrate DNA sequences. MORGAN uses a variety of techniques to accomplish this task, the most distinctive of which is a decision tree classifier. The decision tree system is combined with new methods for identifying start codons, donor sites, and acceptor sites, and these are brought together in a frame-sensitive dynamic programming algorithm that finds the optimal segmentation of a DNA sequence into coding and noncoding regions (exons and introns). The optimal segmentation is dependent on a separate scoring function that takes a subsequence and assigns to it a score reflecting the probability that the sequence is an exon. The scoring functions in MORGAN are sets of decision trees that are combined to give a probability estimate. Experimental results on a database of 570 vertebrate DNA sequences show that MORGAN has excellent performance by many different measures. On a separate test set, it achieves an overall accuracy of 95 %, with a correlation coefficient of 0.78, and a sensitivity and specificity for coding bases of 83 % and 79%. In addition, MORGAN identifies 58% of coding exons exactly; i.e., both the beginning and end of the coding regions are predicted correctly. This paper describes the MORGAN system, including its decision tree routines and the algorithms for site recognition, and its performance on a benchmark database of vertebrate DNA.

A computer program for aligning a cDNA sequence with a genomic DNA sequence

We address the problem of efficiently aligning a transcribed and spliced DNA sequence with a genomic sequence containing that gene, allowing for introns in the genomic sequence and a relatively small number of sequencing errors. A freely available computer program, described herein, solves the problem for a 100-kb genomic sequence in a few seconds on a workstation.

Finding the genes in genomic DNA

Genome sequencing efforts will soon generate hundreds of millions of bases of human genomic DNA containing thousands of novel genes. In the past year, the accuracy of computational gene-finding methods has improved significantly, to the point where a reasonable approximation of the gene structures within an extended genomic region can often be predicted in advance of more detailed experimental studies.