Anatomy of mouse recombination hot spots

Genome-wide analyses have suggested thousands of meiotic recombination hot spots across mammalian genomes. However, very few hot spots have been directly analyzed at a sub-kb scale for crossover (CO) activity. Using recombinant inbred strains as a CO library, here we report the identification and detailed characterization of seven new meiotic hot spots on mouse chromosome 19, more than doubling the number of currently available mouse hot spots. Although a shared feature is the narrow 1.5–2.5-kb width of these recombinogenic sites, these analyses revealed that hot spots have diverse sequence attributes and distinct symmetric and asymmetric CO profiles. Interestingly, CO molecules with discontinuous conversion tracts are commonly observed, contrasting with those found in human. Furthermore, unlike human hot spots, those present in the mouse do not necessarily have a quasi-normal CO distribution but harbor CO repulsion zones within recombinogenic cores. We propose a model where local chromatin landscape directs these repulsion zones

Missed treatment opportunities and barriers to comprehensive treatment for sexual violence survivors in Kenya: a mixed methods study

Background In Kenya, most sexual violence survivors either do not access healthcare, access healthcare late or do not complete treatment. To design interventions that ensure optimal healthcare for survivors, it is important to understand the characteristics of those who do and do not access healthcare. In this paper, we aim to: compare the characteristics of survivors who present for healthcare to those of survivors reporting violence on national surveys; understand the healthcare services provided to survivors; and, identify barriers to treatment. Methods A mixed methods approach was used. Hospital records for survivors from two referral hospitals were compared with national-level data from the Kenya Demographic and Health Survey 2014, and the Violence Against Children Survey 2010. Descriptive summaries were calculated and differences in characteristics of the survivors assessed using chi-square tests. Qualitative data from six in-depth interviews with healthcare providers were analysed thematically. Results Among the 543 hospital respondents, 93.2% were female; 69.5% single; 71.9% knew the perpetrator; and 69.2% were children below 18 years. Compared to respondents disclosing sexual violence in nationally representative datasets, those who presented at hospital were less likely to be partnered, male, or assaulted by an intimate partner. Data suggest missed opportunities for treatment among those who did present to hospital: HIV PEP and other STI prophylaxis was not given to 30 and 16% of survivors respectively; 43% of eligible women did not receive emergency contraceptive; and, laboratory results were missing in more than 40% of the records. Those aged 18 years or below and those assaulted by known perpetrators were more likely to miss being put on HIV PEP. Qualitative data highlighted challenges in accessing and providing healthcare that included stigma, lack of staff training, missing equipment and poor coordination of services. Conclusions Nationally, survivors at higher risk of not accessing healthcare include older survivors; partnered or ever partnered survivors; survivors experiencing sexual violence from intimate partners; children experiencing violence in schools; and men. Interventions at the community level should target survivors who are unlikely to access healthcare and address barriers to early access to care. Staff training and specific clinical guidelines/protocols for treating children are urgently needed

Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map

Hotspots of meiotic recombination can change rapidly over time. This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers. To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees. We then compared the positions of crossovers with the hotspots computed from HapMap data and performed extensive computer simulations to compare the observed distributions of crossovers with the distributions expected from the calculated recombination rate maps. Here we show that a population-averaged hotspot map computed from linkage disequilibrium data predicts well present-day genetic crossovers. We find that computed hotspot maps accurately estimate both the strength and the position of meiotic hotspots. An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations. In summary, we find that by combining several computed population-specific maps we can capture the variation in individual hotspots to generate a hotspot map that can predict almost all present-day genetic crossovers

The Drosophila Zinc Finger Protein Trade Embargo Is Required for Double Strand Break Formation in Meiosis

Homologous recombination in meiosis is initiated by the programmed induction of double strand breaks (DSBs). Although the Drosophila Spo11 ortholog Mei-W68 is required for the induction of DSBs during meiotic prophase, only one other protein (Mei-P22) has been shown to be required for Mei-W68 to exert this function. We show here that the chromatin-associated protein Trade Embargo (Trem), a C2H2 zinc finger protein, is required to localize Mei-P22 to discrete foci on meiotic chromosomes, and thus to promote the formation of DSBs, making Trem the earliest known function in the process of DSB formation in Drosophila oocytes. We speculate that Trem may act by either directing the binding of Mei-P22 to preferred sites of DSB formation or by altering chromatin structure in a manner that allows Mei-P22 to form foci

The Case of the Fickle Fingers: How the PRDM9 Zinc Finger Protein Specifies Meiotic Recombination Hotspots in Humans

Recent discoveries have revealed the central role of PRDM9 in mammalian recombination. The precise function of this protein, however, remains poorly understood, as do the causes for its rapid evolution and its role in reproductive isolation

Genetic instability in lung cancer: concurrent analysis of chromosomal, mini- and microsatellite instability and loss of heterozygosity

To investigate what kind of genetic instability plays important roles in lung carcinogenesis, we analyzed micro- and minisatellite instability, loss of heterozygosity (LOH) and chromosome instability in 55 cases of lung cancer, including, 10 squamous cell, 5 large cell, and 3 small cell carcinomas, and 37 adenocarcinomas. Analysis of minisatellite instability, the mechanism of which is different from microsatellite instability, has not been reported previously. Minisatellite instability was detected in only one case (1/55, 1.8%), and the frequency of microsatellite instability was low, being found only in three cases (3/55, 5.5%). In contrast, LOH, for at least in one locus, was observed in 27 cases (49.1%). In adenocarcinomas, the frequency of LOH was higher in poorly differentiated compared to more differentiated carcinomas. For chromosome instability, a similar correlation between differentiation grade and instability was observed in adenocarcinomas. And instability was more common in large cell and small cell carcinomas than in adenocarcinomas. Our analysis showed that chromosome instability and LOH, rather than mini- and microsatellite instability, play significant roles in the development of lung cancer

Origin and Evolution of GALA-LRR, a New Member of the CC-LRR Subfamily: From Plants to Bacteria?

The phytopathogenic bacterium Ralstonia solanacearum encodes type III effectors, called GALA proteins, which contain F-box and LRR domains. The GALA LRRs do not perfectly fit any of the previously described LRR subfamilies. By applying protein sequence analysis and structural prediction, we clarify this ambiguous case of LRR classification and assign GALA-LRRs to CC-LRR subfamily. We demonstrate that side-by-side packing of LRRs in the 3D structures may control the limits of repeat variability within the LRR subfamilies during evolution. The LRR packing can be used as a criterion, complementing the repeat sequences, to classify newly identified LRR domains. Our phylogenetic analysis of F-box domains proposes the lateral gene transfer of bacterial GALA proteins from host plants. We also present an evolutionary scenario which can explain the transformation of the original plant LRRs into slightly different bacterial LRRs. The examination of the selective evolutionary pressure acting on GALA proteins suggests that the convex side of their horse-shoe shaped LRR domains is more prone to positive selection than the concave side, and we therefore hypothesize that the convex surface might be the site of protein binding relevant to the adaptor function of the F-box GALA proteins. This conclusion provides a strong background for further functional studies aimed at determining the role of these type III effectors in the virulence of R. solanacearum

Improving a Natural CaMKII Inhibitor by Random and Rational Design

CaM-KIIN has evolved to inhibit stimulated and autonomous activity of the Ca(2+)/calmodulin (CaM)-dependent protein kinase II (CaMKII) efficiently, selectively, and potently (IC50 ∼100 nM). The CN class of peptides, derived from the inhibitory region of CaM-KIIN, provides powerful new tools to study CaMKII functions. The goal of this study was to identify the residues required for CaMKII inhibition, and to assess if artificial mutations could further improve the potency achieved during evolution.First, the minimal region with full inhibitory potency was identified (CN19) by determining the effect of truncated peptides on CaMKII activity in biochemical assays. Then, individual residues of CN19 were mutated. Most individual Ala substitutions decreased potency of CaMKII inhibition, however, P3A, K13A, and R14A increased potency. Importantly, this initial Ala scan suggested a specific interaction of the region around R11 with the CaMKII substrate binding site, which was exploited for further rational mutagenesis to generate an optimized pseudo-substrate sequence. Indeed, the potency of the optimized peptide CN19o was >250fold improved (IC50 <0.4 nM), and CN19o has characteristics of a tight-binding inhibitor. The selectivity for CaMKII versus CaMKI was similarly improved (to almost 100,000fold for CN19o). A phospho-mimetic S12D mutation decreased potency, indicating potential for regulation by cellular signaling. Consistent with importance of this residue in inhibition, most other S12 mutations also significantly decreased potency, however, mutation to V or Q did not.These results provide improved research tools for studying CaMKII function, and indicate that evolution fine-tuned CaM-KIIN not for maximal potency of CaMKII inhibition, but for lower potency that may be optimal for dynamic regulation of signal transduction

The TGF-β/Smad Repressor TG-Interacting Factor 1 (TGIF1) Plays a Role in Radiation-Induced Intestinal Injury Independently of a Smad Signaling Pathway

Despite advances in radiation delivery protocols, exposure of normal tissues during the course of radiation therapy remains a limiting factor of cancer treatment. If the canonical TGF-β/Smad pathway has been extensively studied and implicated in the development of radiation damage in various organs, the precise modalities of its activation following radiation exposure remain elusive. In the present study, we hypothesized that TGF-β1 signaling and target genes expression may depend on radiation-induced modifications in Smad transcriptional co-repressors/inhibitors expressions (TGIF1, SnoN, Ski and Smad7). In endothelial cells (HUVECs) and in a model of experimental radiation enteropathy in mice, radiation exposure increases expression of TGF-β/Smad pathway and of its target gene PAI-1, together with the overexpression of Smad co-repressor TGIF1. In mice, TGIF1 deficiency is not associated with changes in the expression of radiation-induced TGF-β pathway-related transcripts following localized small intestinal irradiation. In HUVECs, TGIF1 overexpression or silencing has no influence either on the radiation-induced Smad activation or the Smad3-dependent PAI-1 overexpression. However, TGIF1 genetic deficiency sensitizes mice to radiation-induced intestinal damage after total body or localized small intestinal radiation exposure, demonstrating that TGIF1 plays a role in radiation-induced intestinal injury. In conclusion, the TGF-β/Smad co-repressor TGIF1 plays a role in radiation-induced normal tissue damage by a Smad-independent mechanism

A Model-Based Bayesian Estimation of the Rate of Evolution of VNTR Loci in Mycobacterium tuberculosis

Variable numbers of tandem repeats (VNTR) typing is widely used for studying the bacterial cause of tuberculosis. Knowledge of the rate of mutation of VNTR loci facilitates the study of the evolution and epidemiology of Mycobacterium tuberculosis. Previous studies have applied population genetic models to estimate the mutation rate, leading to estimates varying widely from around to per locus per year. Resolving this issue using more detailed models and statistical methods would lead to improved inference in the molecular epidemiology of tuberculosis. Here, we use a model-based approach that incorporates two alternative forms of a stepwise mutation process for VNTR evolution within an epidemiological model of disease transmission. Using this model in a Bayesian framework we estimate the mutation rate of VNTR in M. tuberculosis from four published data sets of VNTR profiles from Albania, Iran, Morocco and Venezuela. In the first variant, the mutation rate increases linearly with respect to repeat numbers (linear model); in the second, the mutation rate is constant across repeat numbers (constant model). We find that under the constant model, the mean mutation rate per locus is (95% CI: ,)and under the linear model, the mean mutation rate per locus per repeat unit is (95% CI: ,). These new estimates represent a high rate of mutation at VNTR loci compared to previous estimates. To compare the two models we use posterior predictive checks to ascertain which of the two models is better able to reproduce the observed data. From this procedure we find that the linear model performs better than the constant model. The general framework we use allows the possibility of extending the analysis to more complex models in the future