This paper discusses the origin, evolution and functions of single exon genes (SEG), also called intronless genes in higher eukaryotes.

Fusion genes have been reported as a means of enabling the development of novel or enhanced functions. In this report, we analyzed fusion genes in the genomes of two Helicobacter pylori strains (26695 and J99) and identified 32 fusion genes that are present as neighbours in one strain (components) and are fused in the second (composite), and vice-versa. The mechanism for each case of gene fusion is explored. All the genes identified as fusion products in this analysis were reported as essential genes in this bacterium in the previously documented transposon mutagenesis of H. pylori strain G27. This observation suggests the potential of the products of fusion genes as putative microbial drug targets. These results underscore the utility of bacterial genomic sequence comparisons for understanding gene evolution and for in silico drug target identification in the post-genomic era.

Snake neurotoxins are important experimental tool in pharmacological research. Over the years, the number of snake neurotoxin sequences identified is increasing at a very fast pace. However, only a small portion of them are experimentally characterized from more than 200,000 variants estimated to exist in nature. In this paper, we report a systematic functional analysis on snake neurotoxins using a statistical machine learning method - nearest neighbour approach for functional prediction together with a set of rules. Based on this method we built a highly accurate functional prediction tool for putative annotation for snake neurotoxins

BACKGROUND: A number of completely sequenced eukaryotic genome data are available in the public domain. Eukaryotic genes are either 'intron containing' or 'intronless'. Eukaryotic 'intronless' genes are interesting datasets for comparative genomics and evolutionary studies. The SEGE database containing a collection of eukaryotic single exon genes is available. However, SEGE is derived using GenBank. The redundant, incomplete and heterogeneous qualities of GenBank data are a bottleneck for biological investigation in comparative genomics and evolutionary studies. Such studies often require representative gene sets from each genome and this is possible only by deriving specific datasets from completely sequenced genome data. Thus Genome SEGE, a database for 'intronless' genes in completely sequenced eukaryotic genomes, has been constructed. AVAILABILITY: http://sege.ntu.edu.sg/wester/intronless DESCRIPTION: Eukaryotic 'intronless' genes are extracted from nine completely sequenced genomes (four of which are unicellular and five of which are multi-cellular). The complete dataset is available for download. Data subsets are also available for 'intronless' pseudo-genes. The database provides information on the distribution of 'intronless' genes in different genomes together with their length distributions in each genome. Additionally, the search tool provides pre-computed PROSITE motifs for each sequence in the database with appropriate hyperlinks to InterPro. A search facility is also available through the web server. CONCLUSIONS: The unique features that distinguish Genome SEGE from SEGE is the service providing representative 'intronless' datasets for completely sequenced genomes. 'Intronless' gene sets available in this database will be of use for subsequent bio-computational analysis in comparative genomics and evolutionary studies. Such analysis may help to revisit the original genome data for re-examination and re-annotation.

UNLABELLED: Eukaryotes have both 'intron containing' and 'intron less' genes. Several databases are available for 'intron containing' genes in eukaryotes. In this note, we describe a database for 'intron less' genes from eukaryotes. 'Intron less' eukaryotic genes having prokaryotic architecture will help to understand gene evolution in a much simpler way unlike 'intron containing' genes. AVAILABILITY: SEGE is available at http://intron.bic.nus.edu.sg/seg/ CONTACT: [email protected]

MOTIVATION: Intron sliding is the relocation of intron-exon boundaries over short distances and is often also referred to as intron slippage or intron migration or intron drift. We have generated a database containing discordant intron positions in homologous genes (MIDB--Mismatched Intron DataBase). Discordant intron positions are those that are either closely located in homologous genes (within a window of 10 nucleotides) or an intron position that is present in one gene but not in any of its homologs. The MIDB database aims at systematically collecting information about mismatched introns in the genes from GenBank and organizing it into a form useful for understanding the genomics and dynamics of introns thereby helping understand the evolution of genes. RESULTS: Intron displacement or sliding is critically important for explaining the present distribution of introns among orthologous and paralogous genes. MIDB allows examining of intron movements and allows mapping of intron positions from homologous proteins onto a single sequence. The database is of potential use for molecular biologists in general and for researchers who are interested in gene evolution and eukaryotic gene structure. Partial analysis of this database allowed us to identify a few putative cases of intron sliding. AVAILABILITY: http://intron.bic.nus.edu.sg/midb/midb.html

Abstract Summary: Comparative promoter analysis is a promising strategy for elucidation of common regulatory modules conserved in evolutionarily related sequences or in genes showing common expression profiles. To facilitate such analysis, we have developed a software tool that detects conserved transcription factor binding sites, cis-elements, palindromes and k-tuples simultaneously in a set of sequences, and thus helps to identify putative motifs for designing further experiments. Availability: The program TRES can be accessed at URL: http://www.bic.nus.edu.sg:8888/tres Contact: [email protected] *** To whom correspondance should be addressed Vidya S. Gupta, Division of Biochemical Sciences, National Chemical Laboratory, Pune-411 008, INDIA

Abstract Summary: IE-Kb (Intron Exon-Knowledge base) illustrates the intron–exon dynamics in eukaryotic genes. We have developed three different knowledge sets, namely ‘Non-redundant ExInt’, ‘Non-redundant Pfam-ExInt complement’ and ‘Non-redundant GenBank eukaryotic subdivisional sets’ to understand this phenomenon. Statistical analysis is performed on each knowledge set and the results are made available online. The entries in knowledge sets are ranked based on their intron length, exon length and protein length with relational hyper-links to the corresponding intron phase, intron position, intron sequence, gene definition and parent GenBank entry. Availability: http://intron.bic.nus.edu.sg/iekb/iekb.html Contact: [email protected] * To whom correspondence should be addressed.