Comparison of sashimi plots generated by ggsashimi and IGV.

Sashimi plots of 12 ENCODE samples belonging to 3 cell type groups (endothelial, epithelial and mesenchymal) for the region chr10:27040584-27048100 obtained by ggsashimi (A) and the sashimi-plot utility within IGV (B). The inclusion level of the exon chr10:27044584-27044670 is clearly higher in mesenchymal cells (blue), followed by epithelial (green) and endothelial cells (red). While this trend is barely observable in the IGV sashimi, which becomes complex and confusing with multiple samples, as it makes one sashimi plot per sample; the --overlay option of ggsashimi allows aggregating samples belonging to the same groups, providing a much better overview of the event. In addition, the presence of long introns flanking the exon of interest substantially enlarges the connective elements and hinders visualization in IGV sashimi. Conversely, ggsashimi avoids this problem thanks to its --shrink option, which updates the original intron lengths, enhancing visualization.</p

Benchmarking and performance.

(A) Genome size and filtered protospacer density for the five species tested. (B) The fraction of protospacers passing filters of off-targeting, efficiency score, and both. The latter are defined as “filtered protospacers”, whose density is shown in (A). Data are displayed as a fraction of the total number of canonical PAM sequences in each genome. (C) The effect on library quality of modifying design variables. Y-axis denotes the percent of target regions, divided by: “successful”, where n = 10 distinct sgRNA pair designs are returned per target; “intermediate” designs, where 0Materials and Methods for details). The first column represents the run performed with default settings, and in each subsequent column one variable is modified (see Table 3 for details).</p

Genome-wide knockout libraries for entire classes of genomic elements in humans and other species.

(A) An example of paired sgRNAs designed against the upstream ultraconserved element (UCE) and promoter of the human IRX3 gene. IRX3 lies on the antisense strand. The exact target regions are shown in black, flanked by the design regions in green. The ten sgRNA pairs for each are denoted by red bars. Integrated chromatin marks from the ENCODE project [26] are displayed below, in addition to PhyloP multispecies conservation scores [33]. Note the region of elevated conservation corresponding to the UCE. (B,C) Summary of paired sgRNA designs targeting entire classes of genomic elements. In each figure, the left scale and grey bars represent the design performance, as in Fig 2. The right scale and black bars indicate the total number of elements in each class. (B) shows a series of genomic element classes for human, while (C) shows designs for the entire set of annotated microRNA genes in five species. Designs were created with default settings; designs using “DECKO” construction method give identical results.</p

Climate Change Communication in the Netherlands

Climate change communication in the Netherlands started in the 1950s, but it was not until the late 1970s that the issue earned a place on the public agenda, as an aspect of the energy problem, and in the shadow of controversy about nuclear energy. Driven largely by scientific reports and political initiatives, the first climate change wave can be observed in the period from 1987 to 1989, as part of a broader environmental consciousness wave. The Netherlands took an active role in international climate change initiatives at the time but struggled to achieve domestic emission reductions throughout the 1990s. The political turmoil in the early 2000s dominated Dutch public debate, until An Inconvenient Truth triggered the second climate change wave in 2006–2007, generating peak media attention and broad societal activity. The combination of COP15 and Climategate in late 2009 marked a turning point in Dutch climate change communication, with online communication and climate-sceptic voices gaining much more prominence. Climate change mitigation was pushed down on the societal and political agenda in the 2010s. Climate change adaptation had received much attention during the second climate change wave and had been firmly institutionalized with respect to flood defense and other water management issues. By 2015 a landmark climate change court case and the Paris Agreement at COP21 were fueling climate change communication once again.<br/><br/>Keywords: climate change, communication, the Netherlands, media, framing, public agenda, science-policy interface, social medi

Pre-generated paired CRISPR libraries.

<p>Pre-generated paired CRISPR libraries.</p

User-defined parameters.

<p>User-defined parameters.</p

Additional file 1 of ChimPipe: accurate detection of fusion genes and transcription-induced chimeras from RNA-seq data

Supplementary Tables, Figures and Methods (PDF 717 kb

Overview of CRISPETa pipeline.

(A) Schematic of CRISPR-mediated genomic deletion. The aim is elimination of the Target region through recruitment of a pair of Cas9 proteins. Red boxes represent protospacers, the 20 bp upstream of a PAM and recognised by the sgRNA. (B) The CRISPETa workflow.</p

Benchmarking results.

<p>Analyses were performed on a set of 7000 regions composed of different human target types (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005341#sec009" target="_blank">Methods</a> for details). % full depth refers to the percent of targets receiving <i>n</i> = 10 sgRNA pair designs. % partial depth refers to targets receiving 0<<i>n</i><10 designs. Designed targets refers to the total number of target features receiving full or partial depth designs.</p

Additional file 2 of ChimPipe: accurate detection of fusion genes and transcription-induced chimeras from RNA-seq data

Simulated data (TAR.GZ 7.4Gb