Dataset Information

Computer identification of snoRNA genes using a Mammalian Orthologous Intron Database.

ABSTRACT: Based on comparative genomics, we created a bioinformatic package for computer prediction of small nucleolar RNA (snoRNA) genes in mammalian introns. The core of our approach was the use of the Mammalian Orthologous Intron Database (MOID), which contains all known introns within the human, mouse and rat genomes. Introns from orthologous genes from these three species, that have the same position relative to the reading frame, are grouped in a special orthologous intron table. Our program SNO.pl searches for conserved snoRNA motifs within MOID and reports all cases when characteristic snoRNA-like structures are present in all three orthologous introns of human, mouse and rat sequences. Here we report an example of the SNO.pl usage for searching a particular pattern of conserved C/D-box snoRNA motifs (canonical C- and D-boxes and the 6 nt long terminal stem). In this computer analysis, we detected 57 triplets of snoRNA-like structures in three mammals. Among them were 15 triplets that represented known C/D-box snoRNA genes. Six triplets represented snoRNA genes that had only been partially characterized in the mouse genome. One case represented a novel snoRNA gene, and another three cases, putative snoRNAs. Our programs are publicly available and can be easily adapted and/or modified for searching any conserved motifs within mammalian introns.

SUBMITTER: Fedorov A

PROVIDER: S-EPMC1184218 | biostudies-literature | 2005

REPOSITORIES: biostudies-literature

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Computer identification of snoRNA genes using a Mammalian Orthologous Intron Database.

Fedorov Alexei A Stombaugh Jesse J Harr Michael W MW Yu Saihua S Nasalean Lorena L Shepelev Valery V

Nucleic acids research 20050810 14

Based on comparative genomics, we created a bioinformatic package for computer prediction of small nucleolar RNA (snoRNA) genes in mammalian introns. The core of our approach was the use of the Mammalian Orthologous Intron Database (MOID), which contains all known introns within the human, mouse and rat genomes. Introns from orthologous genes from these three species, that have the same position relative to the reading frame, are grouped in a special orthologous intron table. Our program SNO.pl ...[more]

PMID: 16093549

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Project description:BACKGROUND: In standard BLAST searches, no information other than the sequences of the query and the database entries is considered. However, in situations where two genes from different species have only borderline similarity in a BLAST search, the discovery that the genes are located within a region of conserved gene order (synteny) can provide additional evidence that they are orthologs. Thus, for interpreting borderline search results, it would be useful to know whether the syntenic context of a database hit is similar to that of the query. This principle has often been used in investigations of particular genes or genomic regions, but to our knowledge it has never been implemented systematically. RESULTS: We made use of the synteny information contained in the Yeast Gene Order Browser database for 11 yeast species to carry out a systematic search for protein-coding genes that were overlooked in the original annotations of one or more yeast genomes but which are syntenic with their orthologs. Such genes tend to have been overlooked because they are short, highly divergent, or contain introns. The key features of our software - called SearchDOGS - are that the database entries are classified into sets of genomic segments that are already known to be orthologous, and that very weak BLAST hits are retained for further analysis if their genomic location is similar to that of the query. Using SearchDOGS we identified 595 additional protein-coding genes among the 11 yeast species, including two new genes in Saccharomyces cerevisiae. We found additional genes for the mating pheromone a-factor in six species including Kluyveromyces lactis. CONCLUSIONS: SearchDOGS has proven highly successful for identifying overlooked genes in the yeast genomes. We anticipate that our approach can be adapted for study of further groups of species, such as bacterial genomes. More generally, the concept of doing sequence similarity searches against databases to which external information has been added may prove useful in other settings.

Project description:BACKGROUND: Recent discoveries have highlighted the fact that alternative splicing and alternative transcripts are the rule, rather than the exception, in metazoan genes. Since multiple transcript and protein variants expressed by the same gene are, by definition, structurally distinct and need not to be functionally equivalent, the concept of gene orthology should be extended to the transcript level in order to describe evolutionary relationships between structurally similar transcript variants. In other words, the identification of true orthology relationships between gene products now should progress beyond primary sequence and "splicing orthology", consisting in ancestrally shared exon-intron structures, is required to define orthologous isoforms at transcript level. RESULTS: As a starting step in this direction, in this work we performed a large scale human- mouse gene comparison with a twofold goal: first, to assess if and to which extent traditional gene annotations such as RefSeq capture genuine splicing orthology; second, to provide a more detailed annotation and quantification of true human-mouse orthologous transcripts defined as transcripts of orthologous genes exhibiting the same splicing patterns. CONCLUSIONS: We observed an identical exon/intron structure for 32% of human and mouse orthologous genes. This figure increases to 87% using less stringent criteria for gene structure similarity, thus implying that for about 13% of the human RefSeq annotated genes (and about 25% of the corresponding transcripts) we could not identify any mouse transcript showing sufficient similarity to be confidently assigned as a splicing ortholog. Our data suggest that current gene and transcript data may still be rather incomplete - with several splicing variants still unknown. The observation that alternative splicing produces large numbers of alternative transcripts and proteins, some of them conserved across species and others truly species-specific, suggests that, still maintaining the conventional definition of gene orthology, a new concept of "splicing orthology" can be defined at transcript level.

Dataset Information

Computer identification of snoRNA genes using a Mammalian Orthologous Intron Database.

Publications

Computer identification of snoRNA genes using a Mammalian Orthologous Intron Database.

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