Recombination events are not uniformly distributed and often cluster in narrow regions known as recombination hotspots. Several studies using different approaches have dramatically advanced our understanding of recombination hotspot regulation. Population genetic data have been used to map and quantify hotspots in the human genome. Genetic variation in recombination rates and hotspots usage have been explored in human pedigrees, mouse intercrosses, and by sperm typing. These studies pointed to the central role of the PRDM9 gene in hotspot modulation. In this study, we used single nucleotide polymorphisms (SNPs) from wholegenome resequencing and genotyping studies of mouse inbred strains to estimate recombination rates across the mouse genome and identified 47,068 historical hotspots-an average of over 2477 per chromosome. We show by simulation that inbred mouse strains can be used to identify positions of historical hotspots. Recombination hotspots were found to be enriched for the predicted binding sequences for different alleles of the PRDM9 protein. Recombination rates were on average lower near transcription start sites (TSS). Comparing the inferred historical recombination hotspots with the recent genome-wide mapping of double-strand breaks (DSBs) in mouse sperm revealed a significant overlap, especially toward the telomeres. Our results suggest that inbred strains can be used to characterize and study the dynamics of historical recombination hotspots. They also strengthen previous findings on mouse recombination hotspots, and specifically the impact of sequence variants in Prdm9. R ECOMBINATION events are not uniformly distributed across the genome; rather they tend to occur at hotspot regions typically 1-2 kb in size (Jeffreys et al. 2001;Kelmenson et al. 2005;Myers et al. 2005;Mancera et al. 2008). The dense map of single nucleotide polymorphisms (SNPs) created by the HapMap Project enabled the highresolution mapping of recombination rates in the human genome and led to the identification of 33,000 recombination hotspots with a coalescent method . The very large number of hotspots and the very high resolution of this mapping made it possible to pinpoint sequence motifs in these hotspots, one of which was instrumental in finding a gene, PRDM9, thought to be a critical component of the recombination mechanism (Baudat and de Massy 2007;Grey et al. 2009;Parvanov et al. 2009).Until recently, the primary strategy for analysis of recombination hotspots in mice has been to use pedigree analysis in strain crosses (Paigen et al. 2008;. The problem with this approach is the high cost of typing SNPs for sufficient numbers of cases in order to define recombination hotspots with power and precision. A different approach that relies on the binding of RAD51 and DMC1 proteins was recently used to map meiotic DNA double-strand breaks (DSBs) that initiate recombination (Smagulova et al. 2011). Recombination initiation sites were found to be associated with testis-specific trimethylation of lysine 4 on histone H3. ...

The approach of Bayesian mixed effects modeling is an appropriate method for estimating both population-specific as well as subject-specific times to steady state. In addition to pure estimation, the approach allows to determine the time until a certain fraction of individuals of a population has reached steady state with a pre-specified certainty. In this paper a mixed effects model for the parameters of a nonlinear pharmacokinetic model is used within a Bayesian framework. Model fitting by means of Markov Chain Monte Carlo methods as implemented in the Gibbs sampler as well as the extraction of estimates and probability statements of interest are described. Finally, the proposed approach is illustrated by application to trough data from a multiple dose clinical trial.