Luis A. Barrera

UniPROBE, update 2015: new tools and content for the online database of protein-binding microarray data on protein–DNA interactions

The Universal PBM Resource for Oligonucleotide Binding Evaluation (UniPROBE) serves as a convenient source of information on published data generated using universal protein-binding microarray (PBM) technology, which provides in vitro data about the relative DNA-binding preferences of transcription factors for all possible sequence variants of a length k (‘k-mers’). The database displays important information about the proteins and displays their DNA-binding specificity data in terms of k-mers, position weight matrices and graphical sequence logos. This update to the database documents the growth of UniPROBE since the last update 4 years ago, and introduces a variety of new features and tools, including a new streamlined pipeline that facilitates data deposition by universal PBM data generators in the research community, a tool that generates putative nonbinding (i.e. negative control) DNA sequences for one or more proteins and novel motifs obtained by analyzing the PBM data using the BEEML-PBM algorithm for motif inference. The UniPROBE database is available at http://uniprobe.org.

The NF-κB Genomic Landscape in Lymphoblastoid B Cells

The nuclear factor κB (NF-κΒ) subunits RelA, RelB, cRel, p50, and p52 are each critical for B cell development and function. To systematically characterize their responses to canonical and noncanonical NF-κB pathway activity, we performed chromatin immunoprecipitation followed by high-throughput DNA sequencing (ChIP-seq) analysis in lymphoblastoid B cell lines (LCLs). We found a complex NF-κB-binding landscape, which did not readily reflect the two NF-κB pathway paradigms. Instead, 10 subunit-binding patterns were observed at promoters and 11 at enhancers. Nearly one-third of NF-κB-binding sites lacked κB motifs and were instead enriched for alternative motifs. The oncogenic forkhead box protein FOXM1 co-occupied nearly half of NF-κB-binding sites and was identified in protein complexes with NF-κB on DNA. FOXM1 knockdown decreased NF-κB target gene expression and ultimately induced apoptosis, highlighting FOXM1 as a synthetic lethal target in B cell malignancy. These studies provide a resource for understanding mechanisms that underlie NF-κB nuclear activity and highlight opportunities for selective NF-κB blockade.

EpiFire: An Open Source C++ Library and Application for Contact Network Epidemiology

BackgroundContact network models have become increasingly common in epidemiology, but we lack a flexible programming framework for the generation and analysis of epidemiological contact networks and for the simulation of disease transmission through such networks.ResultsHere we present EpiFire, an applications programming interface and graphical user interface implemented in C++, which includes a fast and efficient library for generating, analyzing and manipulating networks. Network-based percolation and chain-binomial simulations of susceptible-infected-recovered disease transmission, as well as traditional non-network mass-action simulations, can be performed using EpiFire.ConclusionsEpiFire provides an open-source programming interface for the rapid development of network models with a focus in contact network epidemiology. EpiFire also provides a point-and-click interface for generating networks, conducting epidemic simulations, and creating figures. This interface is particularly useful as a pedagogical tool.

Context influences on TALE–DNA binding revealed by quantitative profiling

Transcription activator-like effector (TALE) proteins recognize DNA using a seemingly simple DNA-binding code, which makes them attractive for use in genome engineering technologies that require precise targeting. Although this code is used successfully to design TALEs to target specific sequences, off-target binding has been observed and is difficult to predict. Here we explore TALE–DNA interactions comprehensively by quantitatively assaying the DNA-binding specificities of 21 representative TALEs to ∼5,000–20,000 unique DNA sequences per protein using custom-designed protein-binding microarrays (PBMs). We find that protein context features exert significant influences on binding. Thus, the canonical recognition code does not fully capture the complexity of TALE–DNA binding. We used the PBM data to develop a computational model, Specificity Inference For TAL-Effector Design (SIFTED), to predict the DNA-binding specificity of any TALE. We provide SIFTED as a publicly available web tool that predicts potential genomic off-target sites for improved TALE design.

The experimental design and data interpretation in ‘Unexpected mutations after CRISPR Cas9 editing in vivo’ by Schaefer et al. are insufficient to support the conclusions drawn by the authors

The recent correspondence to the Editor of Nature Methods by Schaefer et. al. has garnered significant attention since its publication as a result of its strong conclusions contradicting numerous publications in the field using similar analytical approaches and methods. The authors suggest that the CRISPR-Cas9 system is highly mutagenic in genomic regions not expected to be targeted by the gRNA. Based on experimental design and a re-analysis of the primary data, we believe that the conclusions drawn from this study are unsubstantiated by the disclosed experiments as they were designed and carried out. Further, it is impossible to ascribe the observed differences in the subject mice to the effects of CRISPR per se. The genetic differences seen in this comparative analysis were likely present prior to editing with CRISPR.

CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types.

We present a sensitive approach to predict genes expressed selectively in specific cell types, by searching publicly available expression data for genes with a similar expression profile to known cell-specific markers. Our method, CellMapper, strongly outperforms previous computational algorithms to predict cell type-specific expression, especially for rare and difficult-to-isolate cell types. Furthermore, CellMapper makes accurate predictions for human brain cell types that have never been isolated, and can be rapidly applied to diverse cell types from many tissues. We demonstrate a clinically relevant application to prioritize candidate genes in disease susceptibility loci identified by GWAS.

Pairwise library screen systematically interrogates Staphylococcus aureus Cas9 specificity in human cells

Therapeutic genome editing with Staphylococcus aureus Cas9 (SaCas9) requires a rigorous understanding of its potential off-target activity in the human genome. Here we report a high-throughput screening approach to measure SaCas9 genome editing variation in human cells across a large repertoire of 88,692 single guide RNAs (sgRNAs) paired with matched or mismatched target sites in a synthetic cassette. We incorporate randomized barcodes that enable whitelisting of correctly synthesized molecules for further downstream analysis, in order to circumvent the limitation of oligonucleotide synthesis errors. We find SaCas9 sgRNAs with 21-mer or 22-mer spacer sequences are generally more active, although high efficiency 20-mer spacers are markedly less tolerant of mismatches. Using this dataset, we developed an SaCas9 specificity model that performs robustly in ranking off-target sites. The barcoded pairwise library screen enabled high-fidelity recovery of guide-target relationships, providing a scalable framework for the investigation of CRISPR enzyme properties and general nucleic acid interactions.A rigorous understanding of off-target effects is necessary for SaCas9 to be used in therapeutic genome editing. Here the authors measure SaCas9 mismatch tolerance across a pairwise library screen of 88,000 guides and targets in human cells and develop a model which ranks off-target sites.