Liposome-based transfection enhances RNAi and CRISPR-mediated mutagenesis in non-model nematode systems, bioRxiv, 2018-09-27
AbstractNematodes belong to one of the most diverse animal phyla. However, functional genomic studies in nematodes, other than in a few species, have often been limited in their reliability and success. Here we report that by combining liposome-based technology with microinjection, we were able to establish a wide range of genomic techniques in the newly described nematode genus Auanema. The method also allowed heritable changes in dauer larvae of Auanema, despite the immaturity of the gonad at the time of the microinjection. As proof of concept for potential functional studies in other nematode species, we also induced RNAi in the free-living nematode Pristionchus pacificus and targeted the human parasite Strongyloides stercoralis.
biorxiv developmental-biology 0-100-users 2018Local epigenomic state cannot discriminate interacting and non-interacting enhancer–promoter pairs with high accuracy, bioRxiv, 2018-09-27
AbstractWe report an overfitting issue in recent machine learning formulations of the enhancer-promoter interaction problem arising from the fact that many enhancer-promoter pairs share features. Cross- fold validation schemes which do not correctly separate these feature sharing enhancer-promoter pairs into one test set report high accuracy, which is actually due to overfitting. Cross-fold validation schemes which properly segregate pairs with shared features show markedly reduced ability to predict enhancer-promoter interactions from epigenomic state. Parameter scans with multiple models indicate that local epigenomic features of individual pairs of enhancers and promoters cannot distinguish those pairs that interact from those which do with high accuracy, suggesting that additional information is required to predict enhancer-promoter interactions.
biorxiv genomics 0-100-users 2018PlotsOfData – 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 2018Towards inferring causal gene regulatory networks from single cell expression Measurements, bioRxiv, 2018-09-27
AbstractSingle-cell transcriptome sequencing now routinely samples thousands of cells, potentially providing enough data to reconstruct causal gene regulatory networks from observational data. Here, we present Scribe, a toolkit for detecting and visualizing causal regulatory interactions between genes and explore the potential for single-cell experiments to power network reconstruction. Scribe employs Restricted Directed Information to determine causality by estimating the strength of information transferred from a potential regulator to its downstream target. We apply Scribe and other leading approaches for causal network reconstruction to several types of single-cell measurements and show that there is a dramatic drop in performance for pseudotime” ordered single-cell data compared to true time series data. We demonstrate that performing causal inference requires temporal coupling between measurements. We show that methods such as “RNA velocity” restore some degree of coupling through an analysis of chromaffin cell fate commitment. These analyses therefore highlight an important shortcoming in experimental and computational methods for analyzing gene regulation at single-cell resolution and point the way towards overcoming it.
biorxiv genomics 100-200-users 2018beditor A computational workflow for designing libraries of guide RNAs for CRISPR-mediated base editing, bioRxiv, 2018-09-26
ABSTRACTCRISPR-mediated base editors have opened unique avenues for scar-free genome-wide mutagenesis. Here, we describe a comprehensive computational workflow called beditor that can be broadly adapted for designing guide RNA libraries with a range of CRISPR-mediated base editors, PAM recognition sequences and genomes of many species. Additionally, in order to assist users in selecting the best sets of guide RNAs for their experiments, a priori estimates, called beditor scores are calculated. These beditor scores are intended to select guide RNAs that conform to requirements for optimal base editing the editable base falls within maximum activity window of the CRISPR-mediated base editor and produces non-confounding mutational effects with minimal predicted off-target effects. We demonstrate the utility of the software by designing guide RNAs for base-editing to create or remove thousands of clinically important human disease mutations.
biorxiv synthetic-biology 0-100-users 2018Efficient 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