Molecular tools to support metabolic and immune function research in the Guinea Fowl (Numida meleagris)

Background Guinea fowl (Numidia meleagris) production as an alternative source of meat and poultry has shown potential for economic viability. However, there has been little progress in characterizing the transcriptome of the guinea fowl. In this study RNA-sequencing and de novo transcriptome assembly of several Guinea fowl tissues (pancreas, hypothalamus, liver, bone marrow and bursa) which play key roles in regulating feed intake, satiety, and immune function was performed using Illumina’s Hi-Seq 2000. Results 74 million sequences were generated and assembled into 96,492 contigs using the Trinity software suite. Over 39,000 of these transcripts were found to have in silico translated protein sequences that are homologous to chicken protein sequences. Gene ontology analysis uncovered 416 transcripts with metabolic functions and 703 with immune function. Conclusion The transcriptome information presented here will support the development of molecular approaches to improve production efficiency of the guinea fowl and other avian species

Sleep EEG in young people with 22q11.2 deletion syndrome:a cross-sectional study of slow-waves, spindles and correlations with memory and neurodevelopmental symptoms

Background:: Young people living with 22q11.2 Deletion Syndrome (22q11.2DS) are at increased risk of schizophrenia, intellectual disability, attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). In common with these conditions, 22q11.2DS is also associated with sleep problems. We investigated whether abnormal sleep or sleep-dependent network activity in 22q11.2DS reflects convergent, early signatures of neural circuit disruption also evident in associated neurodevelopmental conditions. Methods:: In a cross-sectional design, we recorded high-density sleep EEG in young people (6–20 years) with 22q11.2DS (n=28) and their unaffected siblings (n=17), quantifying associations between sleep architecture, EEG oscillations (spindles and slow waves) and psychiatric symptoms. We also measured performance on a memory task before and after sleep. Results:: 22q11.2DS was associated with significant alterations in sleep architecture, including a greater proportion of N3 sleep and lower proportions of N1 and REM sleep than in siblings. During sleep, deletion carriers showed broadband increases in EEG power with increased slow-wave and spindle amplitudes, increased spindle frequency and density, and stronger coupling between spindles and slow-waves. Spindle and slow-wave amplitudes correlated positively with overnight memory in controls, but negatively in 22q11.2DS. Mediation analyses indicated that genotype effects on anxiety, ADHD and ASD were partially mediated by sleep EEG measures. Conclusions:: This study provides a detailed description of sleep neurophysiology in 22q11.2DS, highlighting alterations in EEG signatures of sleep which have been previously linked to neurodevelopment, some of which were associated with psychiatric symptoms. Sleep EEG features may therefore reflect delayed or compromised neurodevelopmental processes in 22q11.2DS, which could inform our understanding of the neurobiology of this condition and be biomarkers for neuropsychiatric disorders. Funding:: This research was funded by a Lilly Innovation Fellowship Award (UB), the National Institute of Mental Health (NIMH 5UO1MH101724; MvdB), a Wellcome Trust Institutional Strategic Support Fund (ISSF) award (MvdB), the Waterloo Foundation (918-1234; MvdB), the Baily Thomas Charitable Fund (2315/1; MvdB), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment (IMAGINE) (MR/L011166/1; JH, MvdB and MO), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment 2 (IMAGINE-2) (MR/T033045/1; MvdB, JH and MO); Wellcome Trust Strategic Award ‘Defining Endophenotypes From Integrated Neurosciences’ Wellcome Trust (100202/Z/12/Z MO, JH). NAD was supported by a National Institute for Health Research Academic Clinical Fellowship in Mental Health and MWJ by a Wellcome Trust Senior Research Fellowship in Basic Biomedical Science (202810/Z/16/Z). CE and HAM were supported by Medical Research Council Doctoral Training Grants (C.B.E. 1644194, H.A.M MR/K501347/1). HMM and UB were employed by Eli Lilly & Co during the study; HMM is currently an employee of Boehringer Ingelheim Pharma GmbH & Co KG. The views and opinions expressed are those of the author(s), and not necessarily those of the NHS, the NIHR or the Department of Health funders

Distribution of Genes and Repetitive Elements in the Diabrotica virgifera virgifera Genome Estimated Using BAC Sequencing

Feeding damage caused by the western corn rootworm, Diabrotica virgifera virgifera, is destructive to corn plants in North America and Europe where control remains challenging due to evolution of resistance to chemical and transgenic toxins. A BAC library, DvvBAC1, containing 109,486 clones with 1 0 4 ± 3 4 . 5 kb inserts was created, which has an ~4.56X genome coverage based upon a 2.58 Gb (2.80 pg) flow cytometry-estimated haploid genome size. Paired end sequencing of 1037 BAC inserts produced 1.17 Mb of data (~0.05% genome coverage) and indicated ~9.4 and 16.0% of reads encode, respectively, endogenous genes and transposable elements (TEs). Sequencing genes within BAC full inserts demonstrated that TE densities are high within intergenic and intron regions and contribute to the increased gene size. Comparison of homologous genome regions cloned within different BAC clones indicated that TE movement may cause haplotype variation within the inbred strain. The data presented here indicate that the D. virgifera virgifera genome is large in size and contains a high proportion of repetitive sequence. These BAC sequencing methods that are applicable for characterization of genomes prior to sequencing may likely be valuable resources for genome annotation as well as scaffolding

Automated White Matter Hyperintensity Segmentation Using Bayesian Model Selection: Assessment and Correlations with Cognitive Change.

Accurate, automated white matter hyperintensity (WMH) segmentations are needed for large-scale studies to understand contributions of WMH to neurological diseases. We evaluated Bayesian Model Selection (BaMoS), a hierarchical fully-unsupervised model selection framework for WMH segmentation. We compared BaMoS segmentations to semi-automated segmentations, and assessed whether they predicted longitudinal cognitive change in control, early Mild Cognitive Impairment (EMCI), late Mild Cognitive Impairment (LMCI), subjective/significant memory concern (SMC) and Alzheimer's (AD) participants. Data were downloaded from the Alzheimer's disease Neuroimaging Initiative (ADNI). Magnetic resonance images from 30 control and 30 AD participants were selected to incorporate multiple scanners, and were semi-automatically segmented by 4 raters and BaMoS. Segmentations were assessed using volume correlation, Dice score, and other spatial metrics. Linear mixed-effect models were fitted to 180 control, 107 SMC, 320 EMCI, 171 LMCI and 151 AD participants separately in each group, with the outcomes being cognitive change (e.g. mini-mental state examination; MMSE), and BaMoS WMH, age, sex, race and education used as predictors. There was a high level of agreement between BaMoS' WMH segmentation volumes and a consensus of rater segmentations, with a median Dice score of 0.74 and correlation coefficient of 0.96. BaMoS WMH predicted cognitive change in: control, EMCI, and SMC groups using MMSE; LMCI using clinical dementia rating scale; and EMCI using Alzheimer's disease assessment scale-cognitive subscale (p < 0.05, all tests). BaMoS compares well to semi-automated segmentation, is robust to different WMH loads and scanners, and can generate volumes which predict decline. BaMoS can be applicable to further large-scale studies

Long-term ecological research in a human-dominated world

Author Posting. © American Institute of Biological Sciences, 2012. This article is posted here by permission of American Institute of Biological Sciences for personal use, not for redistribution. The definitive version was published in BioScience 62 (2012): 342-253, doi:10.1525/bio.2012.62.4.6.The US Long Term Ecological Research (LTER) Network enters its fourth decade with a distinguished record of achievement in ecological science. The value of long-term observations and experiments has never been more important for testing ecological theory and for addressing today's most difficult environmental challenges. The network's potential for tackling emergent continent-scale questions such as cryosphere loss and landscape change is becoming increasingly apparent on the basis of a capacity to combine long-term observations and experimental results with new observatory-based measurements, to study socioecological systems, to advance the use of environmental cyberinfrastructure, to promote environmental science literacy, and to engage with decisionmakers in framing major directions for research. The long-term context of network science, from understanding the past to forecasting the future, provides a valuable perspective for helping to solve many of the crucial environmental problems facing society today.2012-10-0

Rapid population decline in migratory shorebirds relying on Yellow Sea tidal mudflats as stopover sites

Migratory animals are threatened by human-induced global change. However, little is known about how stopover habitat, essential for refuelling during migration, affects the population dynamics of migratory species. Using 20 years of continent-wide citizen science data, we assess population trends of ten shorebird taxa that refuel on Yellow Sea tidal mudflats, a threatened ecosystem that has shrunk by >65% in recent decades. Seven of the taxa declined at rates of up to 8% per year. Taxa with the greatest reliance on the Yellow Sea as a stopover site showed the greatest declines, whereas those that stop primarily in other regions had slowly declining or stable populations. Decline rate was unaffected by shared evolutionary history among taxa and was not predicted by migration distance, breeding range size, non-breeding location, generation time or body size. These results suggest that changes in stopover habitat can severely limit migratory populations

The correlation between reading and mathematics ability at age twelve has a substantial genetic component

Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve

Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke

Genetic factors have been implicated in stroke risk but few replicated associations have been reported. We conducted a genome-wide association study (GWAS) in ischemic stroke and its subtypes in 3,548 cases and 5,972 controls, all of European ancestry. Replication of potential signals was performed in 5,859 cases and 6,281 controls. We replicated reported associations between variants close to PITX2 and ZFHX3 with cardioembolic stroke, and a 9p21 locus with large vessel stroke. We identified a novel association for a SNP within the histone deacetylase 9(HDAC9) gene on chromosome 7p21.1 which was associated with large vessel stroke including additional replication in a further 735 cases and 28583 controls (rs11984041, combined P = 1.87×10−11, OR=1.42 (95% CI) 1.28-1.57). All four loci exhibit evidence for heterogeneity of effect across the stroke subtypes, with some, and possibly all, affecting risk for only one subtype. This suggests differing genetic architectures for different stroke subtypes