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"Root, David E"
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Nonlinear circuit simulation and modeling : fundamentals for microwave design
\"Discover the nonlinear methods and tools needed to design real-world microwave circuits with this tutorial guide. Balancing theoretical background with practical tools and applications, it covers everything from the basic properties of nonlinear systems such as gain compression, intermodulation and harmonic distortion, to nonlinear circuit analysis and simulation algorithms, and state-of-the-art equivalent circuit and behavioral modeling techniques\"-- Provided by publisher.
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Optimized libraries for CRISPR-Cas9 genetic screens with multiple modalities
The creation of genome-wide libraries for CRISPR knockout (CRISPRko), interference (CRISPRi), and activation (CRISPRa) has enabled the systematic interrogation of gene function. Here, we show that our recently-described CRISPRko library (Brunello) is more effective than previously published libraries at distinguishing essential and non-essential genes, providing approximately the same perturbation-level performance improvement over GeCKO libraries as GeCKO provided over RNAi. Additionally, we present genome-wide libraries for CRISPRi (Dolcetto) and CRISPRa (Calabrese), and show in negative selection screens that Dolcetto, with fewer sgRNAs per gene, outperforms existing CRISPRi libraries and achieves comparable performance to CRISPRko in detecting essential genes. We also perform positive selection CRISPRa screens and demonstrate that Calabrese outperforms the SAM approach at identifying vemurafenib resistance genes. We further compare CRISPRa to genome-scale libraries of open reading frames (ORFs). Together, these libraries represent a suite of genome-wide tools to efficiently interrogate gene function with multiple modalities.
Genome-wide libraries for CRISPR knockout, interference, and activation have allowed the systemic interrogation of gene function. Here, the authors evaluate the Brunello CRISPRko library and introduce Dolcetto and Calabrese for CRISPRi and CRISPRa, respectively.
Journal Article
Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects
CRISPR loss of function screens are powerful tools to interrogate biology but exhibit a number of biases and artifacts that can confound the results. Here, we introduce Chronos, an algorithm for inferring gene knockout fitness effects based on an explicit model of cell proliferation dynamics after CRISPR gene knockout. We test Chronos on two pan-cancer CRISPR datasets and one longitudinal CRISPR screen. Chronos generally outperforms competitors in separation of controls and strength of biomarker associations, particularly when longitudinal data is available. Additionally, Chronos exhibits the lowest copy number and screen quality bias of evaluated methods. Chronos is available at
https://github.com/broadinstitute/chronos
.
Journal Article
Evaluation of RNAi and CRISPR technologies by large-scale gene expression profiling in the Connectivity Map
The application of RNA interference (RNAi) to mammalian cells has provided the means to perform phenotypic screens to determine the functions of genes. Although RNAi has revolutionized loss-of-function genetic experiments, it has been difficult to systematically assess the prevalence and consequences of off-target effects. The Connectivity Map (CMAP) represents an unprecedented resource to study the gene expression consequences of expressing short hairpin RNAs (shRNAs). Analysis of signatures for over 13,000 shRNAs applied in 9 cell lines revealed that microRNA (miRNA)-like off-target effects of RNAi are far stronger and more pervasive than generally appreciated. We show that mitigating off-target effects is feasible in these datasets via computational methodologies to produce a consensus gene signature (CGS). In addition, we compared RNAi technology to clustered regularly interspaced short palindromic repeat (CRISPR)-based knockout by analysis of 373 single guide RNAs (sgRNAs) in 6 cells lines and show that the on-target efficacies are comparable, but CRISPR technology is far less susceptible to systematic off-target effects. These results will help guide the proper use and analysis of loss-of-function reagents for the determination of gene function.
Journal Article
Genome-Scale CRISPR-Cas9 Knockout Screening in Human Cells
The simplicity of programming the CRISPR (clustered regularly interspaced short palindromic repeats)–associated nuclease Cas9 to modify specific genomic loci suggests a new way to interrogate gene function on a genome-wide scale. We show that lentiviral delivery of a genome-scale CRISPR-Cas9 knockout (GeCKO) library targeting 18,080 genes with 64,751 unique guide sequences enables both negative and positive selection screening in human cells. First, we used the GeCKO library to identify genes essential for cell viability in cancer and pluripotent stem cells. Next, in a melanoma model, we screened for genes whose loss is involved in resistance to vemurafenib, a therapeutic RAF inhibitor. Our highest-ranking candidates include previously validated genes NF1 and MED12, as well as novel hits NF2, CUL3, TADA2B, and TADA1. We observe a high level of consistency between independent guide RNAs targeting the same gene and a high rate of hit confirmation, demonstrating the promise of genome-scale screening with Cas9.
Journal Article
Rational design of highly active sgRNAs for CRISPR-Cas9–mediated gene inactivation
Analysis of the genome editing activity of more than 1800 sgRNAs in mouse and human cells yields rules to facilitate design of highly active RNA guides for Cas-9 genome editing.
Components of the prokaryotic clustered, regularly interspaced, short palindromic repeats (CRISPR) loci have recently been repurposed for use in mammalian cells
1
,
2
,
3
,
4
,
5
,
6
. The CRISPR-associated (Cas)9 can be programmed with a single guide RNA (sgRNA) to generate site-specific DNA breaks, but there are few known rules governing on-target efficacy of this system
7
,
8
. We created a pool of sgRNAs, tiling across all possible target sites of a panel of six endogenous mouse and three endogenous human genes and quantitatively assessed their ability to produce null alleles of their target gene by antibody staining and flow cytometry. We discovered sequence features that improved activity, including a further optimization of the protospacer-adjacent motif (PAM) of
Streptococcus pyogenes
Cas9. The results from 1,841 sgRNAs were used to construct a predictive model of sgRNA activity to improve sgRNA design for gene editing and genetic screens. We provide an online tool for the design of highly active sgRNAs for any gene of interest.
Journal Article
Mutational processes shape the landscape of TP53 mutations in human cancer
Unlike most tumor suppressor genes, the most common genetic alterations in tumor protein p53 (TP53) are missense mutations
1
,
2
. Mutant p53 protein is often abundantly expressed in cancers and specific allelic variants exhibit dominant-negative or gain-of-function activities in experimental models
3
–
8
. To gain a systematic view of p53 function, we interrogated loss-of-function screens conducted in hundreds of human cancer cell lines and performed TP53 saturation mutagenesis screens in an isogenic pair of TP53 wild-type and null cell lines. We found that loss or dominant-negative inhibition of wild-type p53 function reliably enhanced cellular fitness. By integrating these data with the Catalog of Somatic Mutations in Cancer (COSMIC) mutational signatures database
9
,
10
, we developed a statistical model that describes the TP53 mutational spectrum as a function of the baseline probability of acquiring each mutation and the fitness advantage conferred by attenuation of p53 activity. Collectively, these observations show that widely-acting and tissue-specific mutational processes combine with phenotypic selection to dictate the frequencies of recurrent TP53 mutations.
Large-scale loss-of-function screens and TP53 saturation mutagenesis screens in human cancer cell lines suggest that mutational processes combine with phenotypic selection to shape the landscape of somatic mutations at the TP53 locus.
Journal Article
Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration
The availability of multiple datasets comprising genome-scale RNAi viability screens in hundreds of diverse cancer cell lines presents new opportunities for understanding cancer vulnerabilities. Integrated analyses of these data to assess differential dependency across genes and cell lines are challenging due to confounding factors such as batch effects and variable screen quality, as well as difficulty assessing gene dependency on an absolute scale. To address these issues, we incorporated cell line screen-quality parameters and hierarchical Bayesian inference into DEMETER2, an analytical framework for analyzing RNAi screens (
https://depmap.org/R2-D2
). This model substantially improves estimates of gene dependency across a range of performance measures, including identification of gold-standard essential genes and agreement with CRISPR/Cas9-based viability screens. It also allows us to integrate information across three large RNAi screening datasets, providing a unified resource representing the most extensive compilation of cancer cell line genetic dependencies to date.
Integrated analyses of multiple large-scale screenings can be complicated by batch effects and technical artefacts. McFarland et al. introduce DEMETER2, a hierarchical model coupled with model-based normalization, which allows the assessment of differential dependencies across genes and cell lines.
Journal Article
(R)-2-Hydroxyglutarate Is Sufficient to Promote Leukemogenesis and Its Effects Are Reversible
Mutations in IDH1 and IDH2, the genes coding for isocitrate dehydrogenases 1 and 2, are common in several human cancers, including leukemias, and result in overproduction of the (R)-enantiomer of 2-hydroxyglutarate [(R)-2HG]. Elucidation of the role of IDH mutations and (R)-2HG in leukemogenesis has been hampered by a lack of appropriate cell-based models. Here, we show that a canonical IDH1 mutant, IDH1 R132H, promotes cytokine independence and blocks differentiation in hematopoietic cells. These effects can be recapitulated by (R)-2HG, but not (S)-2HG, despite the fact that (S)-2HG more potently inhibits enzymes, such as the 5'-methylcytosine hydroxylase TET2, that have previously been linked to the pathogenesis of IDH mutant tumors. We provide evidence that this paradox relates to the ability of (S)-2HG, but not (R)-2HG, to inhibit the EglN prolyl hydroxylases. Additionally, we show that transformation by (R)-2HG is reversible.
Journal Article
DYNLL1 binds to MRE11 to limit DNA end resection in BRCA1-deficient cells
Limited DNA end resection is the key to impaired homologous recombination in
BRCA1
-mutant cancer cells. Here, using a loss-of-function CRISPR screen, we identify DYNLL1 as an inhibitor of DNA end resection. The loss of DYNLL1 enables DNA end resection and restores homologous recombination in
BRCA1
-mutant cells, thereby inducing resistance to platinum drugs and inhibitors of poly(ADP-ribose) polymerase. Low BRCA1 expression correlates with increased chromosomal aberrations in primary ovarian carcinomas, and the junction sequences of somatic structural variants indicate diminished homologous recombination. Concurrent decreases in DYNLL1 expression in carcinomas with low BRCA1 expression reduced genomic alterations and increased homology at lesions. In cells, DYNLL1 limits nucleolytic degradation of DNA ends by associating with the DNA end-resection machinery (MRN complex, BLM helicase and DNA2 endonuclease). In vitro, DYNLL1 binds directly to MRE11 to limit its end-resection activity. Therefore, we infer that DYNLL1 is an important anti-resection factor that influences genomic stability and responses to DNA-damaging chemotherapy.
DYNLL1 antagonizes end resection of DNA double-strand breaks, thereby inhibiting homologous repair, and the loss of DYNLL1 correlates with poor progression-free survival of patients with
BRCA1
-mutant ovarian cancer.
Journal Article