Dataset Information

Automatic generation of gene finders for eukaryotic species.

ABSTRACT:

Background

The number of sequenced eukaryotic genomes is rapidly increasing. This means that over time it will be hard to keep supplying customised gene finders for each genome. This calls for procedures to automatically generate species-specific gene finders and to re-train them as the quantity and quality of reliable gene annotation grows.

Results

We present a procedure, Agene, that automatically generates a species-specific gene predictor from a set of reliable mRNA sequences and a genome. We apply a Hidden Markov model (HMM) that implements explicit length distribution modelling for all gene structure blocks using acyclic discrete phase type distributions. The state structure of the each HMM is generated dynamically from an array of sub-models to include only gene features represented in the training set.

Conclusion

Acyclic discrete phase type distributions are well suited to model sequence length distributions. The performance of each individual gene predictor on each individual genome is comparable to the best of the manually optimised species-specific gene finders. It is shown that species-specific gene finders are superior to gene finders trained on other species.

SUBMITTER: Munch K

PROVIDER: S-EPMC1522026 | biostudies-literature | 2006 May

REPOSITORIES: biostudies-literature

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Publications

Automatic generation of gene finders for eukaryotic species.

Munch Kasper K Krogh Anders A

BMC bioinformatics 20060521

<h4>Background</h4>The number of sequenced eukaryotic genomes is rapidly increasing. This means that over time it will be hard to keep supplying customised gene finders for each genome. This calls for procedures to automatically generate species-specific gene finders and to re-train them as the quantity and quality of reliable gene annotation grows.<h4>Results</h4>We present a procedure, Agene, that automatically generates a species-specific gene predictor from a set of reliable mRNA sequences a ...[more]

PMID: 16712739

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Project description:BackgroundAmplified fragment length polymorphism (AFLP) markers are frequently used for a wide range of studies, such as genome-wide mapping, population genetic diversity estimation, hybridization and introgression studies, phylogenetic analyses, and detection of signatures of selection. An important issue to be addressed for some of these fields is the distribution of the markers across the genome, particularly in relation to gene sequences.ResultsUsing in-silico restriction fragment analysis of the genomes of nine eukaryotic species we characterise the distribution of AFLP fragments across the genome and, particularly, in relation to gene locations. First, we identify the physical position of markers across the chromosomes of all species. An observed accumulation of fragments around (peri) centromeric regions in some species is produced by repeated sequences, and this accumulation disappears when AFLP bands rather than fragments are considered. Second, we calculate the percentage of AFLP markers positioned within gene sequences. For the typical EcoRI/MseI enzyme pair, this ranges between 28 and 87% and is usually larger than that expected by chance because of the higher GC content of gene sequences relative to intergenic ones. In agreement with this, the use of enzyme pairs with GC-rich restriction sites substantially increases the above percentages. For example, using the enzyme system SacI/HpaII, 86% of AFLP markers are located within gene sequences in A. thaliana, and 100% of markers in Plasmodium falciparun. We further find that for a typical trait controlled by 50 genes of average size, if 1000 AFLPs are used in a study, the number of those within 1 kb distance from any of the genes would be only about 1-2, and only about 50% of the genes would have markers within that distance.ConclusionsThe high coverage of AFLP markers across the genomes and the high proportion of markers within or close to gene sequences make them suitable for genome scans and detecting large islands of differentiation in the genome. However, for specific traits, the percentage of AFLP markers close to genes can be rather small. Therefore, genome scans directed towards the search of markers closely linked to selected loci can be a difficult task in many instances.

Dataset Information

Automatic generation of gene finders for eukaryotic species.

Background

Results

Conclusion

Publications

Automatic generation of gene finders for eukaryotic species.

Similar Datasets

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