A computational analysis of sequence features involved in recognition of short introns

Splicing of short introns by the nuclear pre-mRNA splicing machinery is thought to proceed via an "intron definition" mechanism, in which the 5' and 3' splice sites (5'ss, 3'ss, respectively) are initially recognized and paired across the intron. Here, we describe a computational analysis of sequence features involved in recognition of short introns by using available transcript data from five eukaryotes with complete or nearly complete genomic sequences. The information content of five different transcript features was measured by using methods from information theory, and Monte Carlo simulations were used to determine the amount of information required for accurate recognition of short introns in each organism. We conclude: (i) that short introns in Drosophila melanogaster and Caenorhabditis elegans contain essentially all of the information for their recognition by the splicing machinery, and computer programs that simulate splicing specificity can predict the exact boundaries of approximately 95% of short introns in both organisms; (ii) that in yeast, the 5'ss, branch signal, and 3'ss can accurately identify intron locations but do not precisely determine the location of 3' cleavage in every intron; and (iii) that the 5'ss, branch signal, and 3'ss are not sufficient to accurately identify short introns in plant and human transcripts, but that specific subsets of candidate intronic enhancer motifs can be identified in both human and Arabidopsis that contribute dramatically to the accuracy of splicing simulators.

Assessment of the total number of human transcription units

Variation in the estimates of the number of genes encoded by the human genome (28,000-120,000) attests to the difficulty of systematically identifying human genes. Sequencing of human chromosome 22 (Chr22) provided the first comprehensive, unbiased view of an entire human chromosome, and intensive analysis of this sequence identified 545 genes and 134 pseudogenes that had similarity or identity to known proteins and/or ESTs and which were listed in the gene annotation (http://www.sanger.ac.uk/HGP/Chr22). This analysis yielded an estimate of approximately 36,000 functional expressed genes in the human genome (and 9000 pseudogenes). However, a key uncertainty in this estimate was that hundreds of additional genes beyond those annotated in the Chr22 sequence are predicted by the gene prediction program Genscan, an unknown number of which might represent additional expressed genes. To determine what fraction of these "predicted novel genes" (PNGs) represents expressed human genes, we used a sensitive RT-PCR assay to detect predicted transcripts in 17 tissues and one cell line. Our results indicate that at least 5000-9000 additional human genes which lack similarity to known genes or proteins exist in the human genome, increasing baseline gene estimates to approximately 41,000-45,000.

Computational inference of homologous gene structures in the human genome

With the human genome sequence approaching completion, a major challenge is to identify the locations and encoded protein sequences of all human genes. To address this problem we have developed a new gene identification algorithm, GenomeScan, which combines exon-intron and splice signal models with similarity to known protein sequences in an integrated model. Extensive testing shows that GenomeScan can accurately identify the exon-intron structures of genes in finished or draft human genome sequence with a low rate of false-positives. Application of GenomeScan to 2.7 billion bases of human genomic DNA identified at least 20,000-25,000 human genes out of an estimated 30,000-40,000 present in the genome. The results show an accurate and efficient automated approach for identifying genes in higher eukaryotic genomes and provide a first-level annotation of the draft human genome.

Initial sequencing and analysis of the human genome

The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

Computational and experimental analysis identifies many novel human genes

Because of advances in automation, human genomic sequences are being deposited in public databases at a dramatic rate. However, the process of detecting genes in these sequences is still something of an art. Here we describe the implementation and testing of a relatively straightforward computational approach, the Virtual Transcribed Sequence project, which analyzes their gene content using the gene prediction program GENSCAN (GENSCAN 1.0 1,2) in combination with similarity-based methods. This approach identifies many novel human genes not found even in EST databases.

Development of an expert system for the interpretation of serial peak expiratory flow measurements in the diagnosis of occupational asthma. Midlands Thoracic Society Research Group

If asthma is due to work exposures there must be a relation between these exposures and the asthma. Asthma causes airway hyperresponsiveness and obstruction; the obstruction can be measured with portable meters, which usually measure peak expiratory flow, or sometimes forced expiratory volume in 1 second (FEV1). These can be measured serially (for instance 2 hourly) over several weeks at and away from work. Once occupational asthma develops, the asthma will be induced by many non-specific triggers common to non-occupational asthma. The challenge is to identify changes in peak expiratory flow due to work among other non-occupational causes. Standard statistical tests have been found to be insensitive or non-specific, principally because of the variable period for deterioration to occur after exposure, and the sometimes prolonged time for recovery to occur, such that days away from work may initially have lower measurements than days at work. A computer assisted diagnostic aid (Oasys) has been developed to separate occupational from non-occupational causes of airflow obstruction. Oasys-2 is based on a discriminant analysis, and achieved a sensitivity of 75% and a specificity of at least 94%; therefore peak expiratory flow monitoring combined with Oasys-2 analysis is better to confirm than to exclude occupational asthma. A neural network version in development has improved on this. Both have been based on expert interpretation of peak flow measurements plotted as daily maximum, mean, and minimum, with the first reading at work taken as the first reading of the day. Oasys has been evaluated with independent criteria against measurements made in a wide range of occupational situations. Oasys is sufficiently developed to be the initial method for the confirmation, although less so for exclusion of occupational asthma.

Evolutionary fates and origins of U12-type introns

U2-type and U12-type introns are spliced by distinct spliceosomes in eukaryotic nuclei. A classification method was devised to distinguish these two types of introns based on splice site sequence properties and was used to identify 56 different genes containing U12-type introns in available genomic sequences. U12-type introns occur with consistently low frequency in diverse eukaryotic taxa but have almost certainly been lost from C. elegans. Comparisons with available homologous sequences demonstrate subtype switching of U12 introns between termini of AT-AC and GT-AG as well as conversion of introns from U12-type to U2-type and provide evidence for a fission/fusion model in which the two splicing systems evolved in separate lineages that were fused in a eukaryotic progenitor.

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.