Biology subjects

Hughes, J. R.

Publications and source records attributed to Hughes, J. R..

6 recordsLinked to original sources

bioRxiv2018

NGseqBasic - a single-command UNIX tool for ATAC-seq, DNaseI-seq, Cut-and-Run, and ChIP-seq data mapping, high-resolution visualisation, and quality control

With decreasing cost of next-generation sequencing (NGS), we are observing a rapid rise in the volume of big data in academic research, healthcare and drug discovery sectors. The present bottleneck for extracting value from these big data sets is data processing and analysis. Considering this, there is still a lack of reliable, automated and easy to use tools that will allow experimentalists to assess the quality of the sequenced libraries and explore the data first hand, without the need of investing a lot of time of computational core analysts in the early stages of analysis.\n\nNGseqBasic is an easy-to-use single-command analysis tool for chromatin accessibility (ATAC, DNaseI) and ChIP sequencing data, providing support to also new techniques such as low cell number sequencing and Cut-and-Run. It takes in fastq, fastq.gz or bam files, conducts all quality control, trimming and mapping steps, along with quality control and data processing statistics, and combines all this to a single-click loadable UCSC data hub, with integral statistics html page providing detailed reports from the analysis tools and quality control metrics. The tool is easy to set up, and no installation is needed. A wide variety of parameters are provided to fine-tune the analysis, with optional setting to generate DNase footprint or high resolution ChIP-seq tracks. A tester script is provided to help in the setup, along with a test data set and downloadable example user cases.\n\nNGseqBasic has been used in the routine analysis of next generation sequencing (NGS) data in high-impact publications 1,2. The code is actively developed, and accompanied with Git version control and Github code repository. Here we demonstrate NGseqBasic analysis and features using DNaseI-seq data from GSM689849, and CTCF-ChIP-seq data from GSM2579421, as well as a Cut-and-Run CTCF data set GSM2433142, and provide the one-click loadable UCSC data hubs generated by the tool, allowing for the ready exploration of the run results and quality control files generated by the tool.\n\nAvailabilityDownload, setup and help instructions are available on the NGseqBasic web site http://userweb.molbiol.ox.ac.uk/public/telenius/NGseqBasicManual/external/\n\nBioconda users can load the tool as library \"ngseqbasic\". The source code with Git version control is available in https://github.com/Hughes-Genome-Group/NGseqBasic/releases.\n\nContactjelena.telenius@imm.ox.ac.uk

bioinformatics↗

bioRxiv2018

DOT1L inhibition reveals a distinct class ofenhancers dependent on H3K79 methylation

Enhancer elements are a key regulatory feature of many important genes. Several general features including the presence of specific histone modifications are used to identify and subcategorize enhancers. Here we identify a distinct subset of enhancers in leukemia cells that are functionally dependent upon H3K79me3. Using the DOT1L inhibitor, EPZ-5676, we show that loss of H3K79me3 at these H3K79me3 enhancer elements (KEEs) leads to reduced chromatin accessibility, histone acetylation and transcription factor binding. We then use Capture-C, a high-resolution chromosome conformation capture technique, to show that H3K79me3 is required for KEE interactions with the promoter as well as transcription of the associated genes. Together these data implicate H3K79me3 in having a functional role at a subset of active enhancers where it helps maintain histone acetylation and chromatin accessibility, potentially by promoting phase-separated condensates.

molecular biology↗

bioRxiv2018

Single-cell chromatin interactions reveal regulatory hubs in dynamic compartmentalized domains

The promoters of mammalian genes are commonly regulated by multiple distal enhancers, which physically interact within discrete chromatin domains. How such domains form and how the regulatory elements within them interact within single cells is not understood. To address this we developed Tri-C, a new Chromosome Conformation Capture (3C) approach to identify concurrent chromatin interactions at individual alleles within single cells. The heterogeneity of interactions observed between such cells shows that CTCF-mediated formation of chromatin domains and interactions within them are dynamic processes. Importantly, our analyses reveal higher-order structures involving simultaneous interactions between multiple enhancers and promoters within individual cells. This provides a structural basis for understanding how multiple cis-elements act together to establish robust regulation of gene expression.

genetics↗

bioRxiv2017

A tissue-specific self-interacting chromatin domain forms independently of enhancer-promoter interactions

A variety of self-interacting domains, defined at different levels of resolution, have been described in mammalian genomes. These include Chromatin Compartments (A and B)1, Topologically Associated Domains (TADs)2,3, contact domains4,5, sub-TADs6, insulated neighbourhoods7 and frequently interacting regions (FIREs)8. Whereas many studies have found the organisation of self-interacting domains to be conserved across cell types389, some do form in a lineage-specific manner6710. However, it is not clear to what degree such tissue-specific structures result from processes related to gene activity such as enhancer-promoter interactions or whether they form earlier during lineage commitment and are therefore likely to be prerequisite for promoting gene expression. To examine these models of genome organisation in detail, we used a combination of high-resolution chromosome conformation capture, a newly-developed form of quantitative fluorescence in-situ hybridisation and super-resolution imaging to study a 70 kb self-interacting domain containing the mouse -globin locus. To understand how this self-interacting domain is established, we studied the region when the genes are inactive and during erythroid differentiation when the genes are progressively switched on. In contrast to many current models of long-range gene regulation, we show that an erythroid-specific, decompacted self-interacting domain, delimited by convergent CTCF/cohesin binding sites, forms prior to the onset of robust gene expression. Using previously established mouse models we show that formation of the self-interacting domain does not rely on interactions between the -globin genes and their enhancers. As there are also no tissue-specific changes in CTCF binding, then formation of the domain may simply depend on the presence of activated lineage-specific cis-elements driving a transcription-independent mechanism for opening chromatin throughout the 70 kb region to create a permissive environment for gene expression. These findings are consistent with a model of loop-extrusion in which all segments of chromatin, within a region delimited by CTCF boundary elements, can contact each other. Our findings suggest that activation of tissue-specific element(s)within such a self-interacting region is sufficient to influence all chromatin within the domain.

cell biology↗

bioRxiv2017

Development of a Self-Report Measure of Reward Sensitivity: A Test in Current and Former Smokers

IntroductionTobacco use or abstinence may increase or decrease reward sensitivity. Most existing measures of reward sensitivity were developed decades ago, and few have undergone extensive psychometric testing.\n\nMethodsWe developed a 58-item survey of the anticipated enjoyment from, wanting for, and frequency of common rewards (the Rewarding Events Inventory - REI). The current analyses focuses on ratings of anticipated enjoyment. The first validation study recruited current and former smokers from internet sites. The second study recruited smokers who wished to quit and monetarily reinforced them to stay abstinent in a laboratory study, and a comparison group of former smokers. In both studies, participants completed the inventory on two occasions, 3-7 days apart. They also completed four anhedonia scales and a behavioral test of reduced reward sensitivity.\n\nResultsHalf of the enjoyment ratings loaded on four factors: socializing, active hobbies, passive hobbies, and sex/drug use. Cronbach alpha coefficients were all [≥] 0.73 for overall mean and factor scores. Test-retest correlations were all [≥] 0.83. Correlations of the overall and factor scores with frequency of rewards, anhedonia scales were 0.19 - 0.53, except for the sex/drugs factor. The scores did not correlate with behavioral tests of reward and did not differ between current and former smokers. Lower overall mean enjoyment score predicted a shorter time to relapse.\n\nDiscussionInternal reliability and test-retest reliability of the enjoyment outcomes of the REI are excellent, and construct and predictive validity are modest but promising. The REI is comprehensive and up-to-date, yet is short enough to use on repeated occasions. Replication tests, especially predictive validity tests, are needed.\n\nImplicationsBoth use of and abstinence from nicotine appears to increase or decrease how rewarding non-drug rewards are; however, self-report scales to test this have limitations. Our inventory of enjoyment from 58 rewards appears to be reliable and valid as well as comprehensive and up-to-date, yet is short enough to use on repeated occasions. Replication tests, especially of the predictive validity of our scale, are needed.

neuroscience↗

bioRxiv2017

Does tobacco abstinence decrease reward sensitivity? A human laboratory test

IntroductionAnimal studies report abstinence from nicotine makes rewards less rewarding; however, the results of human tests of the effects of cessation on reward sensitivity are mixed. The current study tested reward sensitivity in abstinent smokers using more rigorous methods than most prior studies.\n\nMethodsA human laboratory study compared outcomes for 1 week prior to quitting to those during 4 weeks post-quit. The study used smokers trying to quit, objective and subjective measures, multiple measures during smoking and abstinence, and monetary rewards to increase the prevalence of abstinence. Current daily smokers (n = 211) who were trying to quit completed an operant measure of reward sensitivity and a survey of pleasure from various rewards as well as self-reports of anhedonia, delay discounting, positive affect and tobacco withdrawal twice each week. A comparison group of long-term former smokers (n = 67) also completed the tasks weekly for 4 weeks. Primary analyses were based on the 61 current smokers who abstained for all 4 weeks.\n\nResultsStopping smoking decreased self-reported pleasure from rewards but did not decrease reward sensitivity on the operant task. Abstinence also decreased self-reported reward frequency and increased the two anhedonia measures. However, the changes with abstinence were small for all outcomes (6-14%) and most lasted less than a week.\n\nConclusionAbstinence from tobacco decreased most self-report measures of reward sensitivity; however, it did not change the objective measure. The self-report effects were small.\n\nImplicationsO_LIAnimal research suggests that nicotine withdrawal decreases reward sensitivity. Replication tests of this in humans have produced inconsistent results.\nC_LIO_LIWe report what we believe is a more rigorous test\nC_LIO_LIWe found smoking abstinence slightly decreases self-reports of reward sensitivity but does not do so for behavioral measures of reward sensitivity\nC_LI

neuroscience↗