Cohort Profile East London Genes & Health (ELGH), a community based population genomics and health study of British-Bangladeshi and British-Pakistani people., bioRxiv, 2018-09-27

Cohort profile in a nutshell East London Genes & Health (ELGH) is a large scale, community genomics and health study (to date >34,000 volunteers; target 100,000 volunteers). ELGH was set up in 2015 to gain deeper understanding of health and disease, and underlying genetic influences, in British-Bangladeshi and British-Pakistani people living in east London. ELGH prioritises studies in areas important to, and identified by, the community it represents. Current priorities include cardiometabolic diseases and mental illness, these being of notably high prevalence and severity. However studies in any scientific area are possible, subject to community advisory group and ethical approval. ELGH combines health data science (using linked UK National Health Service (NHS) electronic health record data) with exome sequencing and SNP array genotyping to elucidate the genetic influence on health and disease, including the contribution from high rates of parental relatedness on rare genetic variation and homozygosity (autozygosity), in two understudied ethnic groups. Linkage to longitudinal health record data enables both retrospective and prospective analyses. Through Stage 2 studies, ELGH offers researchers the opportunity to undertake recall-by-genotype andor recall-by-phenotype studies on volunteers. Sub-cohort, trial-within-cohort, and other study designs are possible. ELGH is a fully collaborative, open access resource, open to academic and life sciences industry scientific research partners.

biorxiv genomics 0-100-users 2018

PlotsOfData – a web app for visualizing data together with its summaries, bioRxiv, 2018-09-27

AbstractReporting of the actual data in graphs and plots increases transparency and enables independent evaluation. On the other hand, data summaries are often used in graphs since they aid interpretation. State-of-the art data visualizations can be made with the ggplot2 package, which uses the ideas of a ‘grammar of graphics’ to generate a graphic from multiple layers of data. However, ggplot2 requires coding skills and an understanding of the tidy data structure. To democratize state-of-the-art data visualization of raw data with a selection of statistical summaries, a web app was written using Rshiny that uses the ggplot2 package for generating plots. A multilayered approach together with adjustable transparency offers a unique flexibility, enabling users can to choose how to display the data and which of the data summaries to add. Four data summaries are provided, mean, median, boxplot, violinplot, to accommodate several types of data distributions. In addition, 95% confidence intervals can be added for visual inferences. By adjusting the transparency of the layers, the visualization of the raw data together with the summary can be tuned for optimal presentation and interpretation. The app is dubbed PlotsOfData and is available at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpshuygens.science.uva.nlPlotsOfData>httpshuygens.science.uva.nlPlotsOfData<jatsext-link><jatsfig id=ufig1 position=float orientation=portrait fig-type=figure><jatsgraphic xmlnsxlink=httpwww.w3.org1999xlink xlinkhref=426767v3_ufig1 position=float orientation=portrait >

biorxiv scientific-communication-and-education 0-100-users 2018

Efficient generation of endogenous fluorescent reporters by Nested CRISPR in Caenorhabditis elegans, bioRxiv, 2018-09-26

AbstractCRISPR-based genome editing methods in model organisms are evolving at an extraordinary speed. Whereas the generation of deletion or missense mutants is quite straightforward, the production of endogenous fluorescent reporters is still inefficient. The use of plasmids with selection markers is an effective methodology, but often requires laborious and complicated cloning steps. We have established a cloning-free ribonucleoprotein-driven Nested CRISPR method that robustly produces endogenous fluorescent reporters. This methodology is based on the division of the GFP and mCherry sequences in three fragments. In the first step we use ssDNA donors (≤200 bp) to insert 5’ and 3’ fragments in the place of interest. In the second step, we use these sequences as homology regions for Homology Directed Repair (HDR) with a dsDNA donor (PCR product, ≈700 bp) including the middle fragment, thus completing the fluorescent protein sequence. This method is advantageous because the first step with ssDNA donors is known to be very efficient, and the second step, uses universal reagents, including validated PCR products and crRNAs, to create fluorescent reporters reaching reliable editing efficiencies as high as 40%. We have also used Nested CRISPR in a non-essential gene to produce a deletion mutant in the first step and a transcriptional reporter in the second step.In the search of modifications to optimize the method, we tested synthetic sgRNAs, but we did not observe a significant increase in the efficacy compared to independently adding tracrRNA and crRNA to the injection mix. Conveniently, we also found that both steps of Nested CRISPR could be performed in a single injection. Finally, we discuss the utility of Nested CRISPR for targeted insertion of long DNA fragments in other systems and prospects of this method in the future.

biorxiv genetics 0-100-users 2018

 

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