No abstract

Population diversity data have recently provided profound, albeit inferential, insights into meiotic recombination across the human genome, revealing a landscape dominated by thousands of cross-over hotspots. However, very few of these putative hotspots have been directly analyzed for cross-over activity. We now describe a search for very active hotspots, by using extreme breakdown of marker association as a guide for high-resolution sperm cross-over analysis. This strategy has led to the isolation of the most active cross-over hotspots yet described. Their morphology, sequence attributes, and cross-over processes are very similar to those seen at less active hotspots, but their activity in sperm is poorly predicted from population diversity information. Several of these hotspots showed evidence for biased gene conversion accompanying cross-over, in some cases associated with variation between men in cross-over activity and with two hotspots showing complete presence/absence polymorphism in different men. Hotspot polymorphism is very common at less active hotspots but curiously was not seen at any of the most active hotspots. This contrasts with the prediction that extreme hotspots should be the most vulnerable to attenuation by meiotic drive in favor of mutations that suppress recombination and should therefore show rapid rate evolution and thus variation in activity between men. Finally, these very intense hotspots provide a valuable resource for dissecting meiotic recombination processes and pathways in humans.conversion ͉ hotspot ͉ meiosis ͉ polymorphism ͉ recombination T he recombinational exchange of DNA between homologous chromosomes at meiosis is vital to ensure correct chromosome segregation and also plays a major role in increasing haplotype diversity within populations. In humans, the combination of low average cross-over frequency [Ϸ1% recombination frequency (RF) per Mb of DNA] and small numbers of informative meioses in pedigree studies has limited the resolution of current linkage maps to the megabase level (1, 2). Much higher resolution profiles of recombination can instead be obtained indirectly through examining patterns of marker association [linkage disequilibrium (LD)], established through population dynamic processes and eroded by recombination, or directly through labor-intensive screening of millions of sperm for recombinant DNA molecules within short DNA intervals (typically Ͻ10 kb).Population LD (3, 4) and sperm DNA (5-14) analyses have firmly established that most cross-over events in humans cluster into narrow hotspots spaced, on average, 50 kb apart. Recently, the International HapMap Project (15, 16) has mapped the LD landscape genome-wide at the kilobase level. These data allowed inference of the global recombination landscape at high resolution (4) by using coalescent analyses whereby observed haplotypes are explained through in silico reconstruction with variable historical recombination rates. These analyses have identified Ϸ33,000 putative cross-over hotspots (LD hotspots) thro...

BackgroundSputum and blood eosinophil counts predict corticosteroid effects in COPD patients. Bacterial infection causes increased airway neutrophilic inflammation. The relationship of eosinophil counts with airway bacterial load in COPD patients is uncertain. We tested the hypothesis that bacterial load and eosinophil counts are inversely related.MethodsCOPD patients were seen at stable state and exacerbation onset. Sputum was processed for quantitative polymerase chain reaction detection of the potentially pathogenic microorganisms (PPM) H. influenzae, M. catarrhalis and S. pneumoniae. PPM positive was defined as total load ≥1 × 104copies/ml. Sputum and whole blood were analysed for differential cell counts.ResultsAt baseline, bacterial counts were not related to blood eosinophils, but sputum eosinophil % was significantly lower in patients with PPM positive compared to PPM negative samples (medians: 0.5% vs. 1.25% respectively, p = 0.01). Patients with PPM positive samples during an exacerbation had significantly lower blood eosinophil counts at exacerbation compared to baseline (medians: 0.17 × 109/L vs. 0.23 × 109/L respectively, p = 0.008), while no blood eosinophil change was observed with PPM negative samples.ConclusionsThese findings indicate an inverse relationship between bacterial infection and eosinophil counts. Bacterial infection may influence corticosteroid responsiveness by altering the profile of neutrophilic and eosinophilic inflammation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12931-017-0570-5) contains supplementary material, which is available to authorized users.

Meiotic recombination plays a key role in the maintenance of sequence diversity in the human genome. However, little is known about the fine-scale distribution and processes of recombination in human chromosomes, or how these impact on patterns of human diversity. We have therefore developed sperm typing systems that allow human recombination to be analysed at very high resolution. The emerging picture is that human crossovers are far from randomly distributed but instead are targeted into very narrow hot spots that can profoundly influence patterns of haplotype diversity in the human genome. These hot spots provide fundamental information on processes of human crossover and gene conversion, as well as evidence that they can violate basic rules of Mendelian inheritance.

Background: Airway bacterial dysbiosis is a feature of chronic obstructive pulmonary disease (COPD). However, there is limited comparative data of the lung microbiome between healthy smokers, non-smokers and COPD. Methods: We compared the 16S rRNA gene-based sputum microbiome generated from pair-ended Illumina sequencing of 124 healthy subjects (28 smokers and 96 non-smokers with normal lung function), with single stable samples from 218 COPD subjects collected from three UK clinical centres as part of the COPDMAP consortium. Results: In healthy subjects Firmicutes, Bacteroidetes and Actinobacteria were the major phyla constituting 88% of the total reads, and Streptococcus, Veillonella, Prevotella, Actinomyces and Rothia were the dominant genera. Haemophilus formed only 3% of the healthy microbiome. In contrast, Proteobacteria was the most dominant phylum accounting for 50% of the microbiome in COPD subjects, with Haemophilus and Moraxella at genus level contributing 25 and 3% respectively. There were no differences in the microbiome profile within healthy and COPD subgroups when stratified based on smoking history. Principal coordinate analysis on operational taxonomic units showed two distinct clusters, representative of healthy and COPD subjects (PERMANOVA, p = 0•001). Conclusion: The healthy and COPD sputum microbiomes are distinct and independent of smoking history. Our results underline the important role for Gammaproteobacteria in COPD.

No abstract

Genetic variation databases have become indispensable in many areas of health care. In addition, more and more experts are depositing published and unpublished disease-causing variants of particular genes into locus-specific databases (LSDBs). Some of these databases contain such extensive information that they have become known as knowledge bases. Here, we analyzed 1,188 LSDBs and their content for the presence or absence of 44 content criteria related to database features (general presentation, locus-specific information, database structure) and data content (data collection, summary table of variants, database querying). Our analyses revealed that several elements have helped to advance the field and reduce data heterogeneity, such as the development of specialized database management systems and the creation of data querying tools. We also identified a number of deficiencies, namely, the lack of detailed disease and phenotypic descriptions for each genetic variant and links to relevant patient organizations, which, if addressed, would allow LSDBs to better serve the clinical genetics community. We propose a structure, based on LSDBs and closely related repositories (namely, clinical genetics databases), which would contribute to a federated genetic variation browser and also allow the maintenance of variation data.

An open-label study was performed to evaluate the safety and efficacy of combination therapy with weekly oral methotrexate (20 mg) and interferon beta-1a (IFN beta-1a) in 15 patients with MS who had experienced exacerbations while receiving IFN beta monotherapy. Nausea was the only major side effect. A 44% reduction in the number of gadolinium-enhanced lesions seen on MRI scan was observed during combination therapy (p = 0.02). There was a trend toward fewer exacerbations. This combination therapy appears to be safe and well tolerated, and should be studied in a controlled trial.