Structural variation in the chicken genome identified by paired-end next-generation DNA sequencing of reduced representation libraries

<p>Abstract</p> <p>Background</p> <p>Variation within individual genomes ranges from single nucleotide polymorphisms (SNPs) to kilobase, and even megabase, sized structural variants (SVs), such as deletions, insertions, inversions, and more complex rearrangements. Although much is known about the extent of SVs in humans and mice, species in which they exert significant effects on phenotypes, very little is known about the extent of SVs in the 2.5-times smaller and less repetitive genome of the chicken.</p> <p>Results</p> <p>We identified hundreds of shared and divergent SVs in four commercial chicken lines relative to the reference chicken genome. The majority of SVs were found in intronic and intergenic regions, and we also found SVs in the coding regions. To identify the SVs, we combined high-throughput short read paired-end sequencing of genomic reduced representation libraries (RRLs) of pooled samples from 25 individuals and computational mapping of DNA sequences from a reference genome.</p> <p>Conclusion</p> <p>We provide a first glimpse of the high abundance of small structural genomic variations in the chicken. Extrapolating our results, we estimate that there are thousands of rearrangements in the chicken genome, the majority of which are located in non-coding regions. We observed that structural variation contributes to genetic differentiation among current domesticated chicken breeds and the Red Jungle Fowl. We expect that, because of their high abundance, SVs might explain phenotypic differences and play a role in the evolution of the chicken genome. Finally, our study exemplifies an efficient and cost-effective approach for identifying structural variation in sequenced genomes.</p

GABA Receptors and the Pharmacology of Sleep

Current GABAergic sleep-promoting medications were developed pragmatically, without making use of the immense diversity of GABAA receptors. Pharmacogenetic experiments are leading to an understanding of the circuit mechanisms in the hypothalamus by which zolpidem and similar compounds induce sleep at α2βγ2-type GABAA receptors. Drugs acting at more selective receptor types, for example, at receptors containing the α2 and/or α3 subunits expressed in hypothalamic and brain stem areas, could in principle be useful as hypnotics/anxiolytics. A highly promising sleep-promoting drug, gaboxadol, which activates αβδ-type receptors failed in clinical trials. Thus, for the time being, drugs such as zolpidem, which work as positive allosteric modulators at GABAA receptors, continue to be some of the most effective compounds to treat primary insomnia

Population based models of cortical drug response: insights from anaesthesia

A great explanatory gap lies between the molecular pharmacology of psychoactive agents and the neurophysiological changes they induce, as recorded by neuroimaging modalities. Causally relating the cellular actions of psychoactive compounds to their influence on population activity is experimentally challenging. Recent developments in the dynamical modelling of neural tissue have attempted to span this explanatory gap between microscopic targets and their macroscopic neurophysiological effects via a range of biologically plausible dynamical models of cortical tissue. Such theoretical models allow exploration of neural dynamics, in particular their modification by drug action. The ability to theoretically bridge scales is due to a biologically plausible averaging of cortical tissue properties. In the resulting macroscopic neural field, individual neurons need not be explicitly represented (as in neural networks). The following paper aims to provide a non-technical introduction to the mean field population modelling of drug action and its recent successes in modelling anaesthesia

Application of geographic information systems and simulation modelling to dental public health: Where next?

Public health research in dentistry has used geographic information systems since the 1960s. Since then, the methods used in the field have matured, moving beyond simple spatial associations to the use of complex spatial statistics and, on occasions, simulation modelling. Many analyses are often descriptive in nature; however, and the use of more advanced spatial simulation methods within dental public health remains rare, despite the potential they offer the field. This review introduces a new approach to geographical analysis of oral health outcomes in neighbourhoods and small area geographies through two novel simulation methods-spatial microsimulation and agent-based modelling. Spatial microsimulation is a population synthesis technique, used to combine survey data with Census population totals to create representative individual-level population datasets, allowing for the use of individual-level data previously unavailable at small spatial scales. Agent-based models are computer simulations capable of capturing interactions and feedback mechanisms, both of which are key to understanding health outcomes. Due to these dynamic and interactive processes, the method has an advantage over traditional statistical techniques such as regression analysis, which often isolate elements from each other when testing for statistical significance. This article discusses the current state of spatial analysis within the dental public health field, before reviewing each of the methods, their applications, as well as their advantages and limitations. Directions and topics for future research are also discussed, before addressing the potential to combine the two methods in order to further utilize their advantages. Overall, this review highlights the promise these methods offer, not just for making methodological advances, but also for adding to our ability to test and better understand theoretical concepts and pathways

Microevolution of Neisseria lactamica during nasopharyngeal colonisation induced by controlled human infection.

Neisseria lactamica is a harmless coloniser of the infant respiratory tract, and has a mutually-excluding relationship with the pathogen Neisseria meningitidis. Here we report controlled human infection with genomically-defined N. lactamica and subsequent bacterial microevolution during 26 weeks of colonisation. We find that most mutations that occur during nasopharyngeal carriage are transient indels within repetitive tracts of putative phase-variable loci associated with host-microbe interactions (pgl and lgt) and iron acquisition (fetA promotor and hpuA). Recurrent polymorphisms occurred in genes associated with energy metabolism (nuoN, rssA) and the CRISPR-associated cas1. A gene encoding a large hypothetical protein was often mutated in 27% of the subjects. In volunteers who were naturally co-colonised with meningococci, recombination altered allelic identity in N. lactamica to resemble meningococcal alleles, including loci associated with metabolism, outer membrane proteins and immune response activators. Our results suggest that phase variable genes are often mutated during carriage-associated microevolution

Plasma MIC-1 correlates with systemic inflammation but is not an independent determinant of nutritional status or survival in oesophago-gastric cancer

BACKGROUND: Macrophage inhibitory cytokine-1(MIC-1) is a potential modulator of systemic inflammation and nutritional depletion, both of which are adverse prognostic factors in oesophago-gastric cancer (OGC). METHODS: Plasma MIC-1, systemic inflammation (defined as plasma C-reactive protein (CRP) of ⩾10 mg l(–1) or modified Glasgow prognostic score (mGPS) of ⩾1), and nutritional status were assessed in newly diagnosed OGC patients (n=293). Healthy volunteers (n=35) served as controls. RESULTS: MIC-1 was elevated in patients (median=1371 pg ml(–1); range 141–39 053) when compared with controls (median=377 pg ml(–1); range 141–3786; P<0.001). Patients with gastric tumours (median=1592 pg ml(–1); range 141–12 643) showed higher MIC-1 concentrations than patients with junctional (median=1337 pg ml(–1); range 383–39 053) and oesophageal tumours (median=1180 pg ml(–1); range 258–31 184; P=0.015). Patients showed a median weight loss of 6.4% (range 0.0–33.4%), and 42% of patients had an mGPS of ⩾1 or plasma CRP of ⩾10 mg l(–1) (median=9 mg l(–1); range 1–200). MIC-1 correlated positively with disease stage (r(2)=0.217; P<0.001), age (r(2)=0.332; P<0.001), CRP (r(2)=0.314; P<0.001), and mGPS (r(2)=0.336; P<0.001), and negatively with Karnofsky Performance Score (r(2)=−0.269; P<0.001). However, although MIC-1 correlated weakly with dietary intake (r(2)=0.157; P=0.031), it did not correlate with weight loss, BMI, or anthropometry. Patients with MIC-1 levels in the upper quartile showed reduced survival (median=204 days; 95% CI 157–251) when compared with patients with MIC-1 levels in the lower three quartiles (median=316 days; 95% CI 259–373; P=0.036), but MIC-1 was not an independent prognostic indicator. CONCLUSIONS: There is no independent link between plasma MIC-1 levels and depleted nutritional status or survival in OGC

Microbiome to Brain:Unravelling the Multidirectional Axes of Communication

The gut microbiome plays a crucial role in host physiology. Disruption of its community structure and function can have wide-ranging effects making it critical to understand exactly how the interactive dialogue between the host and its microbiota is regulated to maintain homeostasis. An array of multidirectional signalling molecules is clearly involved in the host-microbiome communication. This interactive signalling not only impacts the gastrointestinal tract, where the majority of microbiota resides, but also extends to affect other host systems including the brain and liver as well as the microbiome itself. Understanding the mechanistic principles of this inter-kingdom signalling is fundamental to unravelling how our supraorganism function to maintain wellbeing, subsequently opening up new avenues for microbiome manipulation to favour desirable mental health outcome

CREB regulates excitability and the allocation of memory to subsets of neurons in the amygdala

The mechanisms that determine how information is allocated to specific regions and cells in the brain are fundamentally important for memory capacity, storage and retrieval, but are poorly understood. Here, we manipulated CREB in a subset of lateral amygdala (LA) neurons with a modified Herpes Simplex Virus (HSV), and reversibly inactivated transfected neurons with the Drosophila allatostatin G-protein-coupled receptor (AlstR)/ligand system. We found that inactivation of the HSV-CREB subpopulation of neurons with allatostatin (AL) during training disrupted memory for tone conditioning, while inactivation of a similar proportion of HSV-LacZ control neurons did not. Whole-cell recordings of fluorescently tagged HSV-CREB neurons revealed that neurons with higher CREB levels are more excitable than neighboring neurons, and show larger synaptic efficacy changes following conditioning. Our findings demonstrate that CREB modulates the allocation of fear memory to specific cells in lateral amygdala, and suggest that neuronal excitability plays a key role in this process