Phosphonoacetate Modifications Enhance the Stability and Editing Yields of Guide RNAs for Cas9 Editors.

CRISPR gene editing and control systems continue to emerge and inspire novel research and clinical applications. Advances in CRISPR performance such as optimizing the duration of activity in cells, tissues, and organisms, as well as limiting off-target activities, have been extremely important for expanding the utility of CRISPR-based systems. By investigating the effects of various chemical modifications in guide RNAs (gRNAs) at defined positions and combinations, we find that 2'-O-methyl-3'-phosphonoacetate (MP) modifications can be substantially more effective than 2'-O-methyl-3'-phosphorothioate (MS) modifications at the 3' ends of single-guide RNAs (sgRNAs) to promote high editing yields, in some instances showing an order of magnitude higher editing yield in human cells. MP-modified 3' ends are especially effective at promoting the activity of guide RNAs cotransfected with Cas messenger RNA (mRNA), as the gRNA must persist in cells until the Cas protein is expressed. We demonstrate such an MP enhancement for sgRNAs cotransfected with a BE4 mRNA for cytidine base editing and also demonstrate that MP at the 3' ends of prime editing guide RNAs (pegRNAs) cotransfected with PE2 mRNA can promote maximal prime editing yields. In the presence of serum, sgRNAs with MP-modified 3' ends showed marked improvements in editing efficiency over sgRNAs with MS-modified 3' ends codelivered with Cas9 mRNA and showed more modest improvements at enhancing the activity of transfected ribonucleoprotein (RNP) complexes. Our results suggest that MP should be considered as a performance-enhancing modification for the 3' ends of synthetic gRNAs, especially in situations where the guide RNAs may be susceptible to exonuclease-mediated degradation.

Improving CRISPR-Cas specificity with chemical modifications in single-guide RNAs.

CRISPR systems have emerged as transformative tools for altering genomes in living cells with unprecedented ease, inspiring keen interest in increasing their specificity for perfectly matched targets. We have developed a novel approach for improving specificity by incorporating chemical modifications in guide RNAs (gRNAs) at specific sites in their DNA recognition sequence ('guide sequence') and systematically evaluating their on-target and off-target activities in biochemical DNA cleavage assays and cell-based assays. Our results show that a chemical modification (2'-O-methyl-3'-phosphonoacetate, or 'MP') incorporated at select sites in the ribose-phosphate backbone of gRNAs can dramatically reduce off-target cleavage activities while maintaining high on-target performance, as demonstrated in clinically relevant genes. These findings reveal a unique method for enhancing specificity by chemically modifying the guide sequence in gRNAs. Our approach introduces a versatile tool for augmenting the performance of CRISPR systems for research, industrial and therapeutic applications.

Global Transcriptional Response to CRISPR/Cas9-AAV6-Based Genome Editing in CD34+ Hematopoietic Stem and Progenitor Cells.

Genome-editing technologies are currently being translated to the clinic. However, cellular effects of the editing machinery have yet to be fully elucidated. Here, we performed global microarray-based gene expression measurements on human CD34+ hematopoietic stem and progenitor cells that underwent editing. We probed effects of the entire editing process as well as each component individually, including electroporation, Cas9 (mRNA or protein) with chemically modified sgRNA, and AAV6 transduction. We identified differentially expressed genes relative to control treatments, which displayed enrichment for particular biological processes. All editing machinery components elicited immune, stress, and apoptotic responses. Cas9 mRNA invoked the greatest amount of transcriptional change, eliciting a distinct viral response and global transcriptional downregulation, particularly of metabolic and cell cycle processes. Electroporation also induced significant transcriptional change, with notable downregulation of metabolic processes. Surprisingly, AAV6 evoked no detectable viral response. We also found Cas9/sgRNA ribonucleoprotein treatment to be well tolerated, in spite of eliciting a DNA damage signature. Overall, this data establishes a benchmark for cellular tolerance of CRISPR/Cas9-AAV6-based genome editing, ensuring that the clinical protocol is as safe and efficient as possible.

ENViz: a Cytoscape App for integrated statistical analysis and visualization of sample-matched data with multiple data types.

ENViz (Enrichment Analysis and Visualization) is a Cytoscape app that performs joint enrichment analysis of two types of sample matched datasets in the context of systematic annotations. Such datasets may be gene expression or any other high-throughput data collected in the same set of samples. The enrichment analysis is done in the context of pathway information, gene ontology or any custom annotation of the data. The results of the analysis consist of significant associations between profiled elements of one of the datasets to the annotation terms (e.g. miR-19 was associated to the cell-cycle process in breast cancer samples). The results of the enrichment analysis are visualized as an interactive Cytoscape network.

A genome-wide analysis in Saccharomyces cerevisiae demonstrates the influence of chromatin modifiers on transcription.

Chromatin structure is important in transcription regulation. Many factors influencing chromatin structure have been identified, but the transcriptional programs in which they participate are still poorly understood. Chromatin modifiers participate in transcriptional control together with DNA-bound transcription factors. High-throughput experimental methods allow the genome-wide identification of binding sites for transcription factors as well as quantification of gene expression under various environmental and genetic conditions. We have developed a new methodology that uses the vast amount of available data to dissect the contribution of chromatin structure to transcription. We measure and characterize the dependence of transcription factor function on specific chromatin modifiers. We apply our methodology to S. cerevisiae, using a compendium of 170 gene expression profiles of strains defective for chromatin modifiers, taken from 26 different studies. Our method succeeds in identifying known intricate genetic interactions between chromatin modifiers and transcription factors and uncovers many previously unknown genetic interactions, giving the first genome-wide picture of the contribution of chromatin structure to transcription in a eukaryote.

miRNA target enrichment analysis reveals directly active miRNAs in health and disease.

microRNAs (miRNAs) are short non-coding regulatory RNA molecules. The activity of a miRNA in a biological process can often be reflected in the expression program that characterizes the outcome of the activity. We introduce a computational approach that infers such activity from high-throughput data using a novel statistical methodology, called minimum-mHG (mmHG), that examines mutual enrichment in two ranked lists. Based on this methodology, we provide a user-friendly web application that supports the statistical assessment of miRNA target enrichment analysis (miTEA) in the top of a ranked list of genes or proteins. Using miTEA, we analyze several target prediction tools by examining performance on public miRNA constitutive expression data. We also apply miTEA to analyze several integrative biology data sets, including a novel matched miRNA/mRNA data set covering nine human tissue types. Our novel findings include proposed direct activity of miR-519 in placenta, a direct activity of the oncogenic miR-15 in different healthy tissue types and a direct activity of the poorly characterized miR-768 in both healthy tissue types and cancer cell lines. The miTEA web application is available at http://cbl-gorilla.cs.technion.ac.il/miTEA/.

Association of N-glycosylation with breast carcinoma and systemic features using high-resolution quantitative UPLC.

An improved separation of the human serum N-glycome using hydrophilic interaction chromatography technology with UPLC is described, where more than 140 N-glycans were assigned. Using this technique, serum samples from 107 healthy controls and 62 newly diagnosed breast cancer patients were profiled. The most statistically significant alterations were observed in cancer patients compared with healthy controls: an increase in sialylation, branching, and outer-arm fucosylation and a decrease in high-mannosylated and biantennary core-fucosylated glycans. In the controls and cases combined systemic features were analyzed; serum estradiol was associated with increase in digalactosylated glycans, and higher mammographic density was associated with increase in biantennary digalactosylated glycans and with decrease in trisialylated and in outer-arm fucosylated glycans. Furthermore, particular glycans were altered in some features of the breast carcinomas; bisected biantennary nonfucosylated glycans were decreased in patients with progesterone receptor positive tumors, and core-fucosylated biantennary bisected monogalactosylated glycans were decreased in patients with the TP53 mutation. Systemic features show more significant associations with the serum N-glycome than do the features of the breast carcinomas. In conclusion, the UPLC-based glycan analysis technique described here reveals highly significant differences between healthy women and breast cancer patients. Significant associations with breast carcinoma and systemic features are described.

Deregulation of cancer-related miRNAs is a common event in both benign and malignant human breast tumors.

MicroRNAs (miRNAs) are endogenous non-coding RNAs, which play an essential role in the regulation of gene expression during carcinogenesis. The role of miRNAs in breast cancer has been thoroughly investigated, and although many miRNAs are identified as cancer related, little is known about their involvement in benign tumors. In this study, we investigated miRNA expression profiles in the two most common types of human benign tumors (fibroadenoma/fibroadenomatosis) and in malignant breast tumors and explored their role as oncomirs and tumor suppressor miRNAs. Here, we identified 33 miRNAs with similar deregulated expression in both benign and malignant tumors compared with the expression levels of those in normal tissue, including breast cancer-related miRNAs such as let-7, miR-21 and miR-155. Additionally, messenger RNA (mRNA) expression profiles were obtained for some of the same samples. Using integrated mRNA/miRNA expression analysis, we observed that overexpression of certain miRNAs co-occurred with a significant downregulation of their candidate target mRNAs in both benign and malignant tumors. In support of these findings, in vitro functional screening of the downregulated miRNAs in non-malignant and breast cancer cell lines identified several possible tumor suppressor miRNAs, including miR-193b, miR-193a-3p, miR-126, miR-134, miR-132, miR-486-5p, miR-886-3p, miR-195 and miR-497, showing reduced growth when re-expressed in cancer cells. The finding of deregulated expression of oncomirs and tumor suppressor miRNAs in benign breast tumors is intriguing, indicating that they may play a role in proliferation. A role of cancer-related miRNAs in the early phases of carcinogenesis and malignant transformation can, therefore, not be ruled out.

The fine-scale and complex architecture of human copy-number variation.

Despite considerable excitement over the potential functional significance of copy-number variants (CNVs), we still lack knowledge of the fine-scale architecture of the large majority of CNV regions in the human genome. In this study, we used a high-resolution array-based comparative genomic hybridization (aCGH) platform that targeted known CNV regions of the human genome at approximately 1 kb resolution to interrogate the genomic DNAs of 30 individuals from four HapMap populations. Our results revealed that 1020 of 1153 CNV loci (88%) were actually smaller in size than what is recorded in the Database of Genomic Variants based on previously published studies. A reduction in size of more than 50% was observed for 876 CNV regions (76%). We conclude that the total genomic content of currently known common human CNVs is likely smaller than previously thought. In addition, approximately 8% of the CNV regions observed in multiple individuals exhibited genomic architectural complexity in the form of smaller CNVs within larger ones and CNVs with interindividual variation in breakpoints. Future association studies that aim to capture the potential influences of CNVs on disease phenotypes will need to consider how to best ascertain this previously uncharacterized complexity.

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists.

BACKGROUND: Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results. RESULTS: GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (e.g. by level of expression or of differential expression). GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list. Building on a complete theoretical characterization of the underlying distribution, called mHG, GOrilla computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations. This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds. The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms. CONCLUSION: GOrilla is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools. GOrilla's unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation. GOrilla is publicly available at: http://cbl-gorilla.cs.technion.ac.il

Clinically driven semi-supervised class discovery in gene expression data.

MOTIVATION: Unsupervised class discovery in gene expression data relies on the statistical signals in the data to exclusively drive the results. It is often the case, however, that one is interested in constraining the search space to respect certain biological prior knowledge while still allowing a flexible search within these boundaries. RESULTS: We develop an approach to semi-supervised class discovery. One component of our approach uses clinical sample information to constrain the search space and guide the class discovery process to yield biologically relevant partitions. A second component consists of using known biological annotation of genes to drive the search, seeking partitions that manifest strong differential expression in specific sets of genes. We develop efficient algorithmics for these tasks, implementing both approaches and combinations thereof. We show that our method is robust enough to detect known clinical parameters in accordance with expected clinical values. We also use our method to elucidate cardiovascular disease (CVD) putative risk factors. AVAILABILITY: MonoClaD (Monotone Class Discovery). See http:// bioinfo.cs.technion.ac.il/people/zohar/MonoClad/. SUPPLEMENTARY INFORMATION: Supplementary data is available at http://bioinfo.cs.technion.ac.il/people/zohar/MonoClad/software. html

Integrative analysis of genome-wide experiments in the context of a large high-throughput data compendium.

Biological systems are orchestrated by heterogeneous regulatory programs that control complex processes and adapt to a dynamic environment. Recent advances in high-throughput experimental methods provide genome-wide perspectives on such regulatory programs. A considerable amount of data on the behavior of model systems in a variety of conditions is rapidly accumulating. Still, the dominant paradigm is to analyze new genome-wide experiments separately from any other extant data, for example, by clustering the new data alone. Here we introduce a new methodology for analyzing the results of a new functional genomic study vis-à-vis a large compendium of previously published results from heterogeneous experimental techniques. We demonstrate our methodology on Saccharomyces cerevisiae, using a compendium of some 2000 experiments from 60 different publications. Most importantly, we show how the integrated analysis reveals unexpected connections among biological processes, and differentiates between novel and known effects in the analyzed experiments. Such characterization is impossible when new data sets are studied in isolation. Our results exemplify the power of the integrative approach in the analysis of genomic scale data sets and call for a paradigm shift in their study.

Serum N-glycan analysis in breast cancer patients--Relation to tumour biology and clinical outcome.

Glycosylation and related processes play important roles in cancer development and progression, including metastasis. Several studies have shown that N-glycans have potential diagnostic value as cancer serum biomarkers. We have explored the significance of the abundance of particular serum N-glycan structures as important features of breast tumour biology by studying the serum glycome and tumour transcriptome (mRNA and miRNA) of 104 breast cancer patients. Integration of these types of molecular data allows us to study the relationship between serum glycans and transcripts representing functional pathways, such as metabolic pathways or DNA damage response. We identified tri antennary trigalactosylated trisialylated glycans in serum as being associated with lower levels of tumour transcripts involved in focal adhesion and integrin-mediated cell adhesion. These glycan structures were also linked to poor prognosis in patients with ER negative tumours. High abundance of simple monoantennary glycan structures were associated with increased survival, particularly in the basal-like subgroup. The presence of circulating tumour cells was found to be significantly associated with several serum glycome structures like bi and triantennary, di- and trigalactosylated, di- and trisialylated. The link between tumour miRNA expression levels and N-glycan production is also examined.

EXPANDER--an integrative program suite for microarray data analysis.

BACKGROUND: Gene expression microarrays are a prominent experimental tool in functional genomics which has opened the opportunity for gaining global, systems-level understanding of transcriptional networks. Experiments that apply this technology typically generate overwhelming volumes of data, unprecedented in biological research. Therefore the task of mining meaningful biological knowledge out of the raw data is a major challenge in bioinformatics. Of special need are integrative packages that provide biologist users with advanced but yet easy to use, set of algorithms, together covering the whole range of steps in microarray data analysis. RESULTS: Here we present the EXPANDER 2.0 (EXPression ANalyzer and DisplayER) software package. EXPANDER 2.0 is an integrative package for the analysis of gene expression data, designed as a 'one-stop shop' tool that implements various data analysis algorithms ranging from the initial steps of normalization and filtering, through clustering and biclustering, to high-level functional enrichment analysis that points to biological processes that are active in the examined conditions, and to promoter cis-regulatory elements analysis that elucidates transcription factors that control the observed transcriptional response. EXPANDER is available with pre-compiled functional Gene Ontology (GO) and promoter sequence-derived data files for yeast, worm, fly, rat, mouse and human, supporting high-level analysis applied to data obtained from these six organisms. CONCLUSION: EXPANDER integrated capabilities and its built-in support of multiple organisms make it a very powerful tool for analysis of microarray data. The package is freely available for academic users at http://www.cs.tau.ac.il/~rshamir/expander.

Chemically modified guide RNAs enhance CRISPR-Cas genome editing in human primary cells.

CRISPR-Cas-mediated genome editing relies on guide RNAs that direct site-specific DNA cleavage facilitated by the Cas endonuclease. Here we report that chemical alterations to synthesized single guide RNAs (sgRNAs) enhance genome editing efficiency in human primary T cells and CD34(+) hematopoietic stem and progenitor cells. Co-delivering chemically modified sgRNAs with Cas9 mRNA or protein is an efficient RNA- or ribonucleoprotein (RNP)-based delivery method for the CRISPR-Cas system, without the toxicity associated with DNA delivery. This approach is a simple and effective way to streamline the development of genome editing with the potential to accelerate a wide array of biotechnological and therapeutic applications of the CRISPR-Cas technology.

Molecular rules governing de novo methylation in cancer.

De novo methylation of CpG islands is seen in many cancers, but the general rules governing this process are not known. By analyzing DNA from tumors, as well as normal tissues, and by utilizing a range of published data, we have identified a universal set of tumor targets, each with its own "coefficient" of methylation that is largely correlated with its inherent relative ability to recruit polycomb. This pattern is initially formed by a slow process of de novo methylation that occurs during aging and then undergoes expansion early in tumorigenesis, where we hypothesize that it may act as an inhibitor of development-associated gene activation.

Specific genomic and transcriptomic aberrations in tumors induced by partial hepatectomy of a chronically inflamed murine liver.

Resection of hepatocellular carcinoma (HCC) tumors by partial hepatectomy (PHx) is associated with promoting hepatocarcinogenesis. We have previously reported that PHx promotes hepatocarcinogenesis in the Mdr2-knockout (Mdr2-KO) mouse, a model for inflammation-mediated HCC. Now, to explore the molecular mechanisms underlying the tumor-promoting effect of PHx, we compared genomic and transcriptomic profiles of HCC tumors developing in the Mdr2-KO mice either spontaneously or following PHx. PHx accelerated HCC development in these mice by four months. PHx-induced tumors had major chromosomal aberrations: all were amplifications affecting multiple chromosomes. Most of these amplifications were located near the acrocentric centromeres of murine chromosomes. Four different chromosomal regions were amplified each in at least three tumors. The human orthologs of these common amplified regions are known to be amplified in HCC. All tumors of untreated mice had chromosomal aberrations, including both deletions and amplifications. Amplifications in spontaneous tumors affected fewer chromosomes and were not located preferentially at the chromosomal edges. Comparison of gene expression profiles revealed a significantly enriched expression of oncogenes, chromosomal instability markers and E2F1 targets in the post-PHx compared to spontaneous tumors. Both tumor groups shared the same frequent amplification at chromosome 18. Here, we revealed that one of the regulatory genes encoded by this amplified region, Crem, was over-expressed in the nuclei of murine and human HCC cells in vivo, and that it stimulated proliferation of human HCC cells in vitro. Our results demonstrate that PHx of a chronically inflamed liver directed tumor development to a discrete pathway characterized by amplification of specific chromosomal regions and expression of specific tumor-promoting genes. Crem is a new candidate HCC oncogene frequently amplified in this model and frequently over-expressed in human HCC.

Identifying in-trans process associated genes in breast cancer by integrated analysis of copy number and expression data.

Genomic copy number alterations are common in cancer. Finding the genes causally implicated in oncogenesis is challenging because the gain or loss of a chromosomal region may affect a few key driver genes and many passengers. Integrative analyses have opened new vistas for addressing this issue. One approach is to identify genes with frequent copy number alterations and corresponding changes in expression. Several methods also analyse effects of transcriptional changes on known pathways. Here, we propose a method that analyses in-cis correlated genes for evidence of in-trans association to biological processes, with no bias towards processes of a particular type or function. The method aims to identify cis-regulated genes for which the expression correlation to other genes provides further evidence of a network-perturbing role in cancer. The proposed unsupervised approach involves a sequence of statistical tests to systematically narrow down the list of relevant genes, based on integrative analysis of copy number and gene expression data. A novel adjustment method handles confounding effects of co-occurring copy number aberrations, potentially a large source of false positives in such studies. Applying the method to whole-genome copy number and expression data from 100 primary breast carcinomas, 6373 genes were identified as commonly aberrant, 578 were highly in-cis correlated, and 56 were in addition associated in-trans to biological processes. Among these in-trans process associated and cis-correlated (iPAC) genes, 28% have previously been reported as breast cancer associated, and 64% as cancer associated. By combining statistical evidence from three separate subanalyses that focus respectively on copy number, gene expression and the combination of the two, the proposed method identifies several known and novel cancer driver candidates. Validation in an independent data set supports the conclusion that the method identifies genes implicated in cancer.

Global methylation patterns in idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic Pulmonary Fibrosis (IPF) is characterized by profound changes in the lung phenotype including excessive extracellular matrix deposition, myofibroblast foci, alveolar epithelial cell hyperplasia and extensive remodeling. The role of epigenetic changes in determining the lung phenotype in IPF is unknown. In this study we determine whether IPF lungs exhibit an altered global methylation profile. METHODOLOGY/PRINCIPAL FINDINGS: Immunoprecipitated methylated DNA from 12 IPF lungs, 10 lung adenocarcinomas and 10 normal histology lungs was hybridized to Agilent human CpG Islands Microarrays and data analysis was performed using BRB-Array Tools and DAVID Bioinformatics Resources software packages. Array results were validated using the EpiTYPER MassARRAY platform for 3 CpG islands. 625 CpG islands were differentially methylated between IPF and control lungs with an estimated False Discovery Rate less than 5%. The genes associated with the differentially methylated CpG islands are involved in regulation of apoptosis, morphogenesis and cellular biosynthetic processes. The expression of three genes (STK17B, STK3 and HIST1H2AH) with hypomethylated promoters was increased in IPF lungs. Comparison of IPF methylation patterns to lung cancer or control samples, revealed that IPF lungs display an intermediate methylation profile, partly similar to lung cancer and partly similar to control with 402 differentially methylated CpG islands overlapping between IPF and cancer. Despite their similarity to cancer, IPF lungs did not exhibit hypomethylation of long interspersed nuclear element 1 (LINE-1) retrotransposon while lung cancer samples did, suggesting that the global hypomethylation observed in cancer was not typical of IPF. CONCLUSIONS/SIGNIFICANCE: Our results provide evidence that epigenetic changes in IPF are widespread and potentially important. The partial similarity to cancer may signify similar pathogenetic mechanisms while the differences constitute IPF or cancer specific changes. Elucidating the role of these specific changes will potentially allow better understanding of the pathogenesis of IPF.

miRNA-mRNA integrated analysis reveals roles for miRNAs in primary breast tumors.

INTRODUCTION: Few studies have performed expression profiling of both miRNA and mRNA from the same primary breast carcinomas. In this study we present and analyze data derived from expression profiling of 799 miRNAs in 101 primary human breast tumors, along with genome-wide mRNA profiles and extensive clinical information. METHODS: We investigate the relationship between these molecular components, in terms of their correlation with each other and with clinical characteristics. We use a systems biology approach to examine the correlative relationship between miRNA and mRNAs using statistical enrichment methods. RESULTS: We identify statistical significant differential expression of miRNAs between molecular intrinsic subtypes, and between samples with different levels of proliferation. Specifically, we point to miRNAs significantly associated with TP53 and ER status. We also show that several cellular processes, such as proliferation, cell adhesion and immune response, are strongly associated with certain miRNAs. We validate the role of miRNAs in regulating proliferation using high-throughput lysate-microarrays on cell lines and point to potential drivers of this process. CONCLUSION: This study provides a comprehensive dataset as well as methods and system-level results that jointly form a basis for further work on understanding the role of miRNA in primary breast cancer.