Dataset Information

Finding schizophrenia genes.

ABSTRACT: Genetic epidemiological studies suggest that individual variation in susceptibility to schizophrenia is largely genetic, reflecting alleles of moderate to small effect in multiple genes. Molecular genetic studies have identified a number of potential regions of linkage and 2 associated chromosomal abnormalities, and accumulating evidence favors several positional candidate genes. These findings are grounds for optimism that insight into genetic factors associated with schizophrenia will help further our understanding of this disease and contribute to the development of new ways to treat it.

SUBMITTER: Kirov G

PROVIDER: S-EPMC1137005 | biostudies-literature | 2005 Jun

REPOSITORIES: biostudies-literature

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Publications

Finding schizophrenia genes.

Kirov George G O'Donovan Michael C MC Owen Michael J MJ

The Journal of clinical investigation 20050601 6

Genetic epidemiological studies suggest that individual variation in susceptibility to schizophrenia is largely genetic, reflecting alleles of moderate to small effect in multiple genes. Molecular genetic studies have identified a number of potential regions of linkage and 2 associated chromosomal abnormalities, and accumulating evidence favors several positional candidate genes. These findings are grounds for optimism that insight into genetic factors associated with schizophrenia will help fur ...[more]

PMID: 15931379

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Project description:BACKGROUND:Analysis of any newly sequenced bacterial genome starts with the identification of protein-coding genes. Despite the accumulation of multiple complete genome sequences, which provide useful comparisons with close relatives among other organisms during the annotation process, accurate gene prediction remains quite difficult. A major reason for this situation is that genes are tightly packed in prokaryotes, resulting in frequent overlap. Thus, detection of translation initiation sites and/or selection of the correct coding regions remain difficult unless appropriate biological knowledge (about the structure of a gene) is imbedded in the approach. RESULTS:We have developed a new program that automatically identifies biologically significant candidate genes in a bacterial genome. Twenty-six complete prokaryotic genomes were analyzed using this tool, and the accuracy of gene finding was assessed by comparison with existing annotations. This analysis revealed that, despite the enormous effort of genome program annotators, a small but not negligible number of genes annotated within the framework of sequencing projects are likely to be partially inaccurate or plainly wrong. Moreover, the analysis of several putative new genes shows that, as expected, many short genes have escaped annotation. In most cases, these new genes revealed frameshifts that could be either artifacts or genuine frameshifts. Some entirely unexpected new genes have also been identified. This allowed us to get a more complete picture of prokaryotic genomes. The results of this procedure are progressively integrated into the SWISS-PROT reference databank. CONCLUSIONS:The results described in the present study show that our procedure is very satisfactory in terms of gene finding accuracy. Except in few cases, discrepancies between our results and annotations provided by individual authors can be accounted for by the nature of each annotation process or by specific characteristics of some genomes. This stresses that close cooperation between scientists, regular update and curation of the findings in databases are clearly required to reduce the level of errors in genome annotation (and hence in reducing the unfortunate spreading of errors through centralized data libraries).

Dataset Information

Finding schizophrenia genes.

Publications

Finding schizophrenia genes.

Similar Datasets

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