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AnABlast: a newin silicostrategy for the genome-wide search of novel genes and fossil regions
- Source :
- DNA Research: An International Journal for Rapid Publication of Reports on Genes and Genomes
- Publication Year :
- 2015
- Publisher :
- Oxford University Press (OUP), 2015.
-
Abstract
- Genome annotation, assisted by computer programs, is one of the great advances in modern biology. Nevertheless, the in silico identification of small and complex coding sequences is still challenging. We observed that amino acid sequences inferred from coding—but rarely from non-coding—DNA sequences accumulated alignments in low-stringency BLAST searches, suggesting that this alignments accumulation could be used to highlight coding regions in sequenced DNA. To investigate this possibility, we developed a computer program (AnABlast) that generates profiles of accumulated alignments in query amino acid sequences using a low-stringency BLAST strategy. To validate this approach, all six-frame translations of DNA sequences between every two annotated exons of the fission yeast genome were analysed with AnABlast. AnABlast-generated profiles identified three new copies of known genes, and four new genes supported by experimental evidence. New pseudogenes, ancestral carboxyl- and amino-terminal subtractions, complex gene rearrangements, and ancient fragments of mitDNA and of bacterial origin, were also inferred. Thus, this novel in silico approach provides a powerful tool to uncover new genes, as well as fossil-coding sequences, thus providing insight into the evolutionary history of annotated genomes.
- Subjects :
- Genome evolution
In silico
Pseudogene
Sequence alignment
Computational biology
genome evolution
Biology
Genome
DNA sequencing
Evolution, Molecular
Schizosaccharomyces
Genetics
Computer Simulation
Molecular Biology
Gene
Genetic Association Studies
fossil DNA sequences
General Medicine
Genome project
Full Papers
Introns
Schizosaccharomyces pombe
in silico annotation tool
new genes
Genome, Fungal
Sequence Alignment
Pseudogenes
Subjects
Details
- ISSN :
- 17561663 and 13402838
- Volume :
- 22
- Database :
- OpenAIRE
- Journal :
- DNA Research
- Accession number :
- edsair.doi.dedup.....80b08c0819e74da68139b81afed38284