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SPoRE: a mathematical model to predict double strand breaks and axis protein sites in meiosis

BACKGROUND: Meiotic recombination between homologous chromosomes provides natural combinations of genetic variations and is a main driving force of evolution. It is initiated via programmed DNA double-strand breaks (DSB) and involves a specific axial chromosomal structure. So far, recombination regi...

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Detalles Bibliográficos
Autores principales: Champeimont, Raphaël, Carbone, Alessandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4268827/
https://www.ncbi.nlm.nih.gov/pubmed/25495332
http://dx.doi.org/10.1186/s12859-014-0391-1
Descripción
Sumario:BACKGROUND: Meiotic recombination between homologous chromosomes provides natural combinations of genetic variations and is a main driving force of evolution. It is initiated via programmed DNA double-strand breaks (DSB) and involves a specific axial chromosomal structure. So far, recombination regions have been mainly determined by experiments, both expensive and time-consuming. RESULTS: SPoRE is a mathematical model that describes the non-uniform localisation of DSB and axis proteins sites, and distinguishes high versus low protein density. It is based on a combination of genomic signals, based on what is known from wet-lab experiments, whose contribution is precisely quantified. It models axis proteins accumulation at gene 5’-ends with a discrete approximation of their diffusion and convection along genes. It models DSB accumulation at approximated gene promoter positions with intergenic region length and GC-content. SPoRE can be used for prediction and it is parameterised in an obvious way that makes it easy to understand from a biological viewpoint. CONCLUSIONS: When compared to Saccharomyces cerevisiae experimental data, SPoRE predicts axis protein and DSB positions with high sensitivity and precision, axis protein density with an average local correlation r=0.63 and DSB density with an average local correlation r=0.62. SPoRE outbreaks previous DSB predictors, which are based on nucleotide patterning, and it reaches 85% of success rate in DSB prediction compared to 54% obtained by available tools on a benchmarked dataset. SPoRE is available at the address http://www.lcqb.upmc.fr/SPoRE/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-014-0391-1) contains supplementary material, which is available to authorized users.