Stability, affinity and chromatic variants of the glutamate sensor iGluSnFR, bioRxiv, 2017-12-16
AbstractSingle-wavelength fluorescent reporters allow visualization of specific neurotransmitters with high spatial and temporal resolution. We report variants of the glutamate sensor iGluSnFR that are functionally brighter; can detect sub-micromolar to millimolar concentrations of glutamate; and have blue, green or yellow emission profiles. These variants allow in vivo imaging where original-iGluSnFR was too dim, reveal glutamate transients at individual spine heads, and permit kilohertz imaging with inexpensive, powerful fiber lasers.
biorxiv neuroscience 0-100-users 2017Transcription organizes euchromatin similar to an active microemulsion, bioRxiv, 2017-12-16
Chromatin is organized into heterochromatin, which is transcriptionally inactive, and euchromatin, which can switch between transcriptionally active and inactive states. This switch in euchromatin activity is accompanied by changes in its spatial distribution. How euchromatin rearrangements are established is unknown. Here we use super-resolution and live-cell microscopy to show that transcriptionally inactive euchromatin moves away from transcriptionally active euchromatin. This movement is driven by the formation of RNA-enriched microenvironments that exclude inactive euchromatin. Using theory, we show that the segregation into RNA-enriched microenvironments and euchromatin domains can be considered an active microemulsion. The tethering of transcripts to chromatin via RNA polymerase II forms effective amphiphiles that intersperse the two segregated phases. Taken together with previous experiments, our data suggest that chromatin is organized in the following way heterochromatin segregates from euchromatin by phase separation, while transcription organizes euchromatin similar to an active microemulsion.
biorxiv cell-biology 100-200-users 2017Examining the genetic influences of educational attainment and the validity of value-added measures of progress, bioRxiv, 2017-12-15
AbstractIn this study, we estimate (i) the SNP heritability of educational attainment at three time points throughout the compulsory educational lifecourse; (ii) the SNP heritability of value-added measures of educational progress built from test data; and (iii) the extent to which value-added measures built from teacher rated ability may be biased due to measurement error. We utilise a genome wide approach using generalized restricted maximum likelihood (GCTA-GREML) to determine the total phenotypic variance in educational attainment and value-added measures that is attributable to common genetic variation across the genome within a sample of unrelated individuals from a UK birth cohort, the Avon Longitudinal Study of Parents and Children. Our findings suggest that the heritability of educational attainment measured using point score test data increases with age from 47% at age 11 to 61% at age 16. We also find that genetic variation does not contribute towards value-added measures created only from educational attainment point score data, but it does contribute a small amount to measures that additionally control for background characteristics (up to 20.09% [95%CI 6.06 to 35.71] from age 11 to 14). Finally, our results show that value-added measures built from teacher rated ability have higher heritability than those built from exam scores. Our findings suggest that the heritability of educational attainment increases through childhood and adolescence. Value-added measures based upon fine grain point scores may be less prone to between-individual genomic differences than measures that control for students’ backgrounds, or those built from more subjective measures such as teacher rated ability.
biorxiv genetics 0-100-users 2017Intrinsic neuronal dynamics predict distinct functional roles during working memory, bioRxiv, 2017-12-15
AbstractWorking memory (WM) is characterized by the ability to maintain stable representations over time; however, neural activity associated with WM maintenance can be highly dynamic. We explore whether complex population coding dynamics during WM relate to the intrinsic temporal properties of single neurons in lateral prefrontal cortex (lPFC), the frontal eye fields (FEF) and lateral intraparietal cortex (LIP) of two monkeys (Macaca mulatta). We found that cells with short timescales carried memory information relatively early during memory encoding in lPFC; whereas long timescale cells played a greater role later during processing, dominating coding in the delay period. We also observed a link between functional connectivity at rest and intrinsic timescale in FEF and LIP. Our results indicate that individual differences in the temporal processing capacity predicts complex neuronal dynamics during WM; ranging from rapid dynamic encoding of stimuli to slower, but stable, maintenance of mnemonic information.
biorxiv neuroscience 0-100-users 2017Isolation of nucleic acids from low biomass samples detection and removal of sRNA contaminants, bioRxiv, 2017-12-15
ABSTRACTBackgroundSequencing-based analyses of low-biomass samples are known to be prone to misinterpretation due to the potential presence of contaminating molecules derived from laboratory reagents and environments. Due to its inherent instability, contamination with RNA is usually considered to be unlikely.ResultsHere we report the presence of small RNA (sRNA) contaminants in widely used microRNA extraction kits and means for their depletion. Sequencing of sRNAs extracted from human plasma samples was performed and significant levels of non-human (exogenous) sequences were detected. The source of the most abundant of these sequences could be traced to the microRNA extraction columns by qPCR-based analysis of laboratory reagents. The presence of artefactual sequences originating from the confirmed contaminants were furthermore replicated in a range of published datasets. To avoid artefacts in future experiments, several protocols for the removal of the contaminants were elaborated, minimal amounts of starting material for artefact-free analyses were defined, and the reduction of contaminant levels for identification of bona fide sequences using ‘ultraclean’ extraction kits was confirmed.ConclusionThis is the first report of the presence of RNA molecules as contaminants in laboratory reagents. The described protocols should be applied in the future to avoid confounding sRNA studies.
biorxiv molecular-biology 100-200-users 2017Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks, bioRxiv, 2017-12-15
AbstractSkeletal bone age assessment is a common clinical practice to diagnose endocrine and metabolic disorders in child development. In this paper, we describe a fully automated deep learning approach to the problem of bone age assessment using data from the 2017 Pediatric Bone Age Challenge organized by the Radiological Society of North America. The dataset for this competition consists of 12,600 radiological images. Each radiograph in this dataset is an image of a left hand labeled with bone age and sex of a patient. Our approach utilizes several deep neural network architectures trained end-to-end. We use images of whole hands as well as specific parts of a hand for both training and prediction. This approach allows us to measure the importance of specific hand bones for automated bone age analysis. We further evaluate the performance of the suggested method in the context of skeletal development stages. Our approach outperforms other common methods for bone age assessment.
biorxiv pathology 200-500-users 2017