Host–parasite genotypic interactions in the honey bee: the dynamics of diversity

Parasites are thought to be a major driving force shaping genetic variation in their host, and are suggested to be a significant reason for the maintenance of sexual reproduction. A leading hypothesis for the occurrence of multiple mating (polyandry) in social insects is that the genetic diversity generated within‐colonies through this behavior promotes disease resistance. This benefit is likely to be particularly significant when colonies are exposed to multiple species and strains of parasites, but host–parasite genotypic interactions in social insects are little known. We investigated this using honey bees, which are naturally polyandrous and consequently produce genetically diverse colonies containing multiple genotypes (patrilines), and which are also known to host multiple strains of various parasite species. We found that host genotypes differed significantly in their resistance to different strains of the obligate fungal parasite that causes chalkbrood disease, while genotypic variation in resistance to the facultative fungal parasite that causes stonebrood disease was less pronounced. Our results show that genetic variation in disease resistance depends in part on the parasite genotype, as well as species, with the latter most likely relating to differences in parasite life history and host–parasite coevolution. Our results suggest that the selection pressure from genetically diverse parasites might be an important driving force in the evolution of polyandry, a mechanism that generates significant genetic diversity in social insects.     

Polysomnographic Characteristics of Sleep in Stroke: A Systematic Review and Meta-Analysis

BackgroundResearch on sleep after stroke has focused mainly on sleep disordered breathing. However, the extend to which sleep physiology is altered in stroke survivors, how these alterations compare to healthy volunteers, and how sleep changes might affect recovery as well as physical and mental health has yet to be fully researched. Motivated by the view that a deeper understanding of sleep in stroke is needed to account for its role in health and well-being as well as its relevance for recovery and rehabilitation, we conducted a systematic review and meta-analysis of polysomnographic studies comparing stroke to control populations.MethodMedline and PsycInfo databases were searched using "stroke" and words capturing polysomnographic parameters as search terms. This yielded 1692 abstracts for screening, with 15 meeting the criteria for systematic review and 9 for meta-analysis. Prisma best practice guidelines were followed for the systematic review; the Comprehensive Meta-Analysis software was used for random effects modelling.ResultsThe meta-analysis revealed that patients with stroke have poorer sleep than controls. Patients had lower sleep efficiency (mean 75% vs 84%), shorter total-sleep-time (309.4 vs 340.3 min) and more wake-after-sleep-onset (97.2 vs 53.8 min). Patients also spend more time in stage 1 (13% vs 10%) and less time in stage 2 sleep (36% vs 45%) and slow-wave-sleep (10% vs 12%). No group differences were identified for REM sleep. The systematic review revealed a strong bias towards studies in the early recovery phase of stroke, with no study reporting specifically on patients in the chronic state. Moreover, participants in the control groups included community samples as well as other patients groups.ConclusionsThese results indicate poorer sleep in patients with stroke than controls. While strongly suggestive in nature, the evidence base is limited and methodologically diverse, and hands a clear mandate for further research. A particular need regards polysomnographic studies in chronic community-dwelling patients compared to age-matched individuals.     

A Meta-Analysis of Retinoblastoma Copy Numbers Refines the List of Possible Driver Genes Involved in Tumor Progression

BackgroundWhile RB1 loss initiates retinoblastoma development, additional somatic copy number alterations (SCNAs) can drive tumor progression. Although SCNAs have been identified with good concordance between studies at a cytoband resolution, accurate identification of single genes for all recurrent SCNAs is still challenging. This study presents a comprehensive meta-analysis of genome-wide SCNAs integrated with gene expression profiling data, narrowing down the list of plausible retinoblastoma driver genes.MethodsWe performed SCNA profiling of 45 primary retinoblastoma samples and eight retinoblastoma cell lines by high-resolution microarrays. We combined our data with genomic, clinical and histopathological data of ten published genome-wide SCNA studies, which strongly enhanced the power of our analyses (N = 310).ResultsComprehensive recurrence analysis of SCNAs in all studies integrated with gene expression data allowed us to reduce candidate gene lists for 1q, 2p, 6p, 7q and 13q to a limited gene set. Besides the well-established driver genes RB1 (13q-loss) and MYCN (2p-gain) we identified CRB1 and NEK7 (1q-gain), SOX4 (6p-gain) and NUP205 (7q-gain) as novel retinoblastoma driver candidates. Depending on the sample subset and algorithms used, alternative candidates were identified including MIR181 (1q-gain) and DEK (6p gain). Remarkably, our study showed that copy number gains rarely exceeded change of one copy, even in pure tumor samples with 100% homozygosity at the RB1 locus (N = 34), which is indicative for intra-tumor heterogeneity. In addition, profound between-tumor variability was observed that was associated with age at diagnosis and differentiation grades.InterpretationSince focal alterations at commonly altered chromosome regions were rare except for 2p24.3 (MYCN), further functional validation of the oncogenic potential of the described candidate genes is now required. For further investigations, our study provides a refined and revised set of candidate retinoblastoma driver genes.     

Analysis of Genes Involved in Body Weight Regulation by Targeted Re-Sequencing

Introduction

Genes involved in body weight regulation that were previously investigated in genome-wide association studies (GWAS) and in animal models were target-enriched followed by massive parallel next generation sequencing.

Methods

We enriched and re-sequenced continuous genomic regions comprising FTO, MC4R, TMEM18, SDCCAG8, TKNS, MSRA and TBC1D1 in a screening sample of 196 extremely obese children and adolescents with age and sex specific body mass index (BMI) ≥ 99^th percentile and 176 lean adults (BMI ≤ 15^th percentile). 22 variants were confirmed by Sanger sequencing. Genotyping was performed in up to 705 independent obesity trios (extremely obese child and both parents), 243 extremely obese cases and 261 lean adults.

Results and Conclusion

We detected 20 different non-synonymous variants, one frame shift and one nonsense mutation in the 7 continuous genomic regions in study groups of different weight extremes. For SNP Arg695Cys (rs58983546) in TBC1D1 we detected nominal association with obesity (p_TDT = 0.03 in 705 trios). Eleven of the variants were rare, thus were only detected heterozygously in up to ten individual(s) of the complete screening sample of 372 individuals. Two of them (in FTO and MSRA) were found in lean individuals, nine in extremely obese. In silico analyses of the 11 variants did not reveal functional implications for the mutations. Concordant with our hypothesis we detected a rare variant that potentially leads to loss of FTO function in a lean individual. For TBC1D1, in contrary to our hypothesis, the loss of function variant (Arg443Stop) was found in an obese individual. Functional in vitro studies are warranted.