Dataset Information

A comparative analysis of serpin genes in the silkworm genome.

ABSTRACT: Serine protease inhibitors (serpins) are a superfamily of proteins, most of which control protease-mediated processes by inhibiting their cognate enzymes. Sequencing of the silkworm genome provides an opportunity to investigate serpin structure, function, and evolution at the genome level. There are thirty-four serpin genes in Bombyx mori. Six are highly similar to their Manduca sexta orthologs that regulate innate immunity. Three alternative exons in serpin1 gene and four in serpin28 encode a variable region including the reactive site loop. Splicing of serpin2 pre-mRNA yields variations in serpin2A, 2A' and 2B. Sequence similarity and intron positions reveal the evolutionary pathway of seven serpin genes in group C. RT-PCR indicates an increase in the mRNA levels of serpin1, 3, 5, 6, 9, 12, 13, 25, 27, 32 and 34 in fat body and hemocytes of larvae injected with bacteria. These results suggest that the silkworm serpins play regulatory roles in defense responses.

SUBMITTER: Zou Z

PROVIDER: S-EPMC2772820 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature

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A comparative analysis of serpin genes in the silkworm genome.

Zou Zhen Z Picheng Zhao Z Weng Hua H Mita Kazuei K Jiang Haobo H

Genomics 20090116 4

Serine protease inhibitors (serpins) are a superfamily of proteins, most of which control protease-mediated processes by inhibiting their cognate enzymes. Sequencing of the silkworm genome provides an opportunity to investigate serpin structure, function, and evolution at the genome level. There are thirty-four serpin genes in Bombyx mori. Six are highly similar to their Manduca sexta orthologs that regulate innate immunity. Three alternative exons in serpin1 gene and four in serpin28 encode a v ...[more]

PMID: 19150649

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Project description:The identification of genes essential for survival is of theoretical importance in the understanding of the minimal requirements for cellular life, and of practical importance in the identification of potential drug targets in novel pathogens. With the great time and expense required for experimental studies aimed at constructing a catalog of essential genes in a given organism, a computational approach which could identify essential genes with high accuracy would be of great value.We gathered numerous features which could be generated automatically from genome sequence data and assessed their relationship to essentiality, and subsequently utilized machine learning to construct an integrated classifier of essential genes in both S. cerevisiae and E. coli. When looking at single features, phyletic retention, a measure of the number of organisms an ortholog is present in, was the most predictive of essentiality. Furthermore, during construction of our phyletic retention feature we for the first time explored the evolutionary relationship among the set of organisms in which the presence of a gene is most predictive of essentiality. We found that in both E. coli and S. cerevisiae the optimal sets always contain host-associated organisms with small genomes which are closely related to the reference. Using five optimally selected organisms, we were able to improve predictive accuracy as compared to using all available sequenced organisms. We hypothesize the predictive power of these genomes is a consequence of the process of reductive evolution, by which many parasites and symbionts evolved their gene content. In addition, essentiality is measured in rich media, a condition which resembles the environments of these organisms in their hosts where many nutrients are provided. Finally, we demonstrate that integration of our most highly predictive features using a probabilistic classifier resulted in accuracies surpassing any individual feature.Using features obtainable directly from sequence data, we were able to construct a classifier which can predict essential genes with high accuracy. Furthermore, our analysis of the set of genomes in which the presence of a gene is most predictive of essentiality may suggest ways in which targeted sequencing can be used in the identification of essential genes. In summary, the methods presented here can aid in the reduction of time and money invested in essential gene identification by targeting those genes for experimentation which are predicted as being essential with a high probability.

Dataset Information

A comparative analysis of serpin genes in the silkworm genome.

Publications

A comparative analysis of serpin genes in the silkworm genome.

Similar Datasets

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