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

BMC Bioinformatics

Raphaël Champeimont²  Alessandra Carbone¹ 

[1] Institut Universitaire de France, Paris 75005, France

[2] CNRS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative, Paris F-75006, France

关键词: Saccharomyces cerevisiae;    Intergenic region;    Modeling;    Gene;    Genome;    3D chromosomal structure;    Recombination;   

Others  :  1084442
DOI  :  10.1186/s12859-014-0391-1

 received in 2014-08-27, accepted in 2014-11-19,  发布年份 2014

【 摘 要 】

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/ webcite.

【 授权许可】

   
2014 Champeimont and Carbone; licensee BioMed Central Ltd.

【 图 表 】

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