Serotonin and corticosterone rhythms in mice exposed to cigarette smoke and in patients with COPD:implication for COPD-associated neuropathogenesis

The circadian timing system controls daily rhythms of physiology and behavior, and disruption of clock function can trigger stressful life events. Daily exposure to cigarette smoke (CS) can lead to alteration in diverse biological and physiological processes. Smoking is associated with mood disorders, including depression and anxiety. Patients with chronic obstructive pulmonary disease (COPD) have abnormal circadian rhythms, reflected by daily changes in respiratory symptoms and lung function. Corticosterone (CORT) is an adrenal steroid that plays a considerable role in stress and anti-inflammatory responses. Serotonin (5-hydroxytryptamine; 5HT) is a neurohormone, which plays a role in sleep/wake regulation and affective disorders. Secretion of stress hormones (CORT and 5HT) is under the control of the circadian clock in the suprachiasmatic nucleus. Since smoking is a contributing factor in the development of COPD, we hypothesize that CS can affect circadian rhythms of CORT and 5HT secretion leading to sleep and mood disorders in smokers and patients with COPD. We measured the daily rhythms of plasma CORT and 5HT in mice following acute (3 d), sub-chronic (10 d) or chronic (6 mo) CS exposure and in plasma from non-smokers, smokers and patients with COPD. Acute and chronic CS exposure affected both the timing (peak phase) and amplitude of the daily rhythm of plasma CORT and 5HT in mice. Acute CS appeared to have subtle time-dependent effects on CORT levels but more pronounced effects on 5HT. As compared with CORT, plasma 5HT was slightly elevated in smokers but was reduced in patients with COPD. Thus, the effects of CS on plasma 5HT were consistent between mice and patients with COPD. Together, these data reveal a significant impact of CS exposure on rhythms of stress hormone secretion and subsequent detrimental effects on cognitive function, depression-like behavior, mood/anxiety and sleep quality in smokers and patients with COPD

Next Generation Sequencing in Newborn Screening in the United Kingdom National Health Service

Next generation DNA sequencing (NGS) has the potential to improve the diagnostic and prognostic utility of newborn screening programmes. This study assesses the feasibility of automating NGS on dried blood spot (DBS) DNA in a United Kingdom National Health Service (UK NHS) laboratory. An NGS panel targeting the entire coding sequence of five genes relevant to disorders currently screened for in newborns in the UK was validated on DBS DNA. An automated process for DNA extraction, NGS and bioinformatics analysis was developed. The process was tested on DBS to determine feasibility, turnaround time and cost. The analytical sensitivity of the assay was 100% and analytical specificity was 99.96%, with a mean 99.5% concordance of variant calls between DBS and venous blood samples in regions with ≥30× coverage (96.8% across all regions; all variant calls were single nucleotide variants (SNVs), with indel performance not assessed). The pipeline enabled processing of up to 1000 samples a week with a turnaround time of four days from receipt of sample to reporting. This study concluded that it is feasible to automate targeted NGS on routine DBS samples in a UK NHS laboratory setting, but it may not currently be cost effective as a first line test

Genome-wide epigenetic variation among ash trees differing in susceptibility to a fungal disease

Abstract Background European ash trees (Fraxinus excelsior) are currently threatened by ash dieback (ADB) caused by the fungus Hymenoscyphus fraxineus but a small percentage of the population possesses natural low susceptibility. The genome of a European ash tree has recently been sequenced. Here, we present whole genome DNA methylation data for two F. excelsior genotypes with high susceptibility to ADB, and two genotypes with low susceptibility, each clonally replicated. We also include two genotypes of Manchurian ash (F. mandshurica), an ash species which has co-evolved with H. fraxineus and also has low susceptibility to ADB. Results In F. excelsior, we find an average methylation level of 76.2% in the CG context, 52.0% in the CHG context, and 13.9% in the CHH context; similar levels to those of tomato. We find higher methylation in transposable elements as opposed to non-mobile elements, and high densities of Non-Differentially Methylation Positions (N-DMPs) in genes with housekeeping functions. Of genes putatively duplicated in whole genome duplication (WGD) events, an average of 25.9% are differentially methylated in at least one cytosine context, potentially indicative of unequal silencing. Variability in methylation patterns exists among clonal replicates, and this is only slightly less than the variability found between different genotypes. Of twenty genes previously found to have expression levels associated with ADB susceptibility, we find only two of these have differential methylation between high and low susceptibility F. excelsior trees. In addition, we identify 1683 significant Differentially Methylated Regions (DMRs) (q-value< 0.001) between the high and low susceptibility genotypes of F. excelsior trees, of which 665 remain significant when F. mandshurica samples are added to the low susceptibility group. Conclusions We find a higher frequency of differentially methylated WGD-derived gene duplicates in ash than other plant species previously studied. We also identify a set of genes with differential methylation between genotypes and species with high versus low susceptibility to ADB. This provides valuable foundational data for future work on the role that epigenetics may play in gene dosage compensation and susceptibility to ADB in ash

Genomic basis of European ash tree resistance to ash dieback fungus

Populations of European ash trees (Fraxinus excelsior) are being devastated by the invasive alien fungus Hymenoscyphus fraxineus, which causes ash dieback. We sequenced whole genomic DNA from 1,250 ash trees in 31 DNA pools, each pool containing trees with the same ash dieback damage status in a screening trial and from the same seed-source zone. A genome-wide association study identified 3,149 single nucleotide polymorphisms (SNPs) associated with low versus high ash dieback damage. Sixty-one of the 192 most significant SNPs were in, or close to, genes with putative homologues already known to be involved in pathogen responses in other plant species. We also used the pooled sequence data to train a genomic prediction model, cross-validated using individual whole genome sequence data generated for 75 healthy and 75 damaged trees from a single seed source. The model’s genomic estimated breeding values (GEBVs) allocated these 150 trees to their observed health statuses with 67% accuracy using 10,000 SNPs. Using the top 20% of GEBVs from just 200 SNPs, we could predict observed tree health with over 90% accuracy. We infer that ash dieback resistance in F. excelsior is a polygenic trait that should respond well to both natural selection and breeding, which could be accelerated using genomic prediction

Genome sequence and genetic diversity of European ash trees

Eurofins MWG provided a discounted service for Illumina and 454 sequencing of the reference genome, funded by Natural Environment Research Council (NERC) Urgency Grant NE/K01112X/1 to R.J.A.B. The associative transcriptomic and metabolomic work was part of the ‘Nornex’ project led by J.A.D. funded jointly by the UK Biotechnology and Biological Sciences Research Council (BBSRC) (BBS/E/J/000CA5323) and the Department for Environment, Food & Rural Affairs. The Earlham Institute, Norwich, UK, sequenced ‘Tree 35’ funded by ‘Nornex’ and the European Diversity Panel funded by the Earlham Institute National Capability in Genomics (BB/J010375/1) grant. W. Crowther assisted with DNA extractions for the KASP assay; The John Innes Centre contributed KASP analyses. J. F. Miranda assisted with RNA extractions and quantitative PCR with reverse transcription (qRT–PCR) at the University of York. H. V. Florance, N. Smirnoff and the Exeter Metabolomics Facility developed metabolomic methods and ran samples, and T. P. Howard helped with statistics. L.J.K. and R.J.A.B. were partly funded by Living with Environmental Change (LWEC) Tree Health and Plant Biosecurity Initiative - Phase 2 grant BB/L012162/1 to R.J.A.B., S.L. and P. Jepson funded jointly by a grant from the BBSRC, Defra, Economic and Social Research Council, the Forestry Commission, NERC and the Scottish Government, under the Tree Health and Plant Biosecurity Initiative. G.W. was funded by Teagasc Walsh Fellowship 2014001 to R.J.A.B. and G.C.D. E.D.C. was funded by a Marie Skłodowska-Curie Individual Fellowship ‘FraxiFam’ (grant agreement 660003) to E.D.C. and R.J.A.B. E.S.A.S. and J.Z. were funded by the Marie Skłodowska-Curie Initial Training Network INTERCROSSING. J.A.D. received a John Innes Foundation fellowship. We thank A. Joecker for supervising E.S.A.S. at Qiagen and for helpful discussions. R.H.R.G. is supported by a Norwich Research Park PhD Studentship and Earlham Institute Funding and Maintenance Grant. This research used Queen Mary’s MidPlus computational facilities, supported by QMUL Research-IT and funded by Engineering and Physical Sciences Research Council grant EP/K000128/1 and NERC EOS Cloud. D.J.S. acknowledges the support of BBSRC grant BB/N021452/1, which partly supported M.G., C.M.S. and D.J.S. during this work