Search Results

  • Prediction of on-target and off-target activity of CRISPR-Cas13d guide RNAs using deep learning.

    Hans-Hermann Wessels, Andrew Stirn, Alejandro Méndez-Mancilla, Eric J. Kim, Sydney K. Hart, David A. Knowles & Neville E. Sanjana

  • AI and CRISPR Precisely Control Gene Expression

    Deep learning model predicts activity of RNA-targeting CRISPRs Artificial intelligence can predict on- and off-target activity of CRISPR tools that target RNA instead of DNA, according to new research published in Nature Biotechnology. The study by researchers at New York University, Columbia University, and the New York Genome Center, combines a deep learning model with CRISPR screens to control the expression of human genes in different ways—such as flicking a light switch to shut them off completely or by using a dimmer knob to partially turn down their activity. These precise gene controls could be used to develop new CRISPR-based therapies. CRISPR is a gene editing technology with many uses in biomedicine and beyond, from treating sickle cell anemia to engineering tastier mustard greens. It often works by targeting DNA using an enzyme called Cas9. In recent years, scientists discovered another type of CRISPR that instead targets RNA using an enzyme called Cas13. RNA-targeting CRISPRs can be used in a wide range of applications, including RNA editing, knocking down RNA to block expression of a particular gene, and high-throughput screening to determine promising drug candidates. Researchers at NYU and the New York Genome Center created a platform for RNA-targeting CRISPR screens using Cas13 to better understand RNA…

  • Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq.

    Hans-Hermann Wessels, Alejandro Méndez-Mancilla, Yuhan Hao, Efthymia Papalexi, William M. Mauck III, Lu Lu, John A. Morris, Eleni P. Mimitou, Peter Smibert, Neville E. Sanjana & Rahul Satija

  • Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq.

    Hans-Hermann Wessels, Alejandro Mendez-Mancilla, Efthymia Papalexi, William M Mauck, Lu Lu, John A Morris, Eleni P Mimitou, Peter Smibert, Neville E Sanjana, Rahul Satija

  • Transcriptome-wide Cas13 guide RNA design for model organisms and viral RNA pathogens.

    Xinyi Guo, Hans-Hermann Wessels, Alejandro Méndez-Mancilla, Daniel Haro, Neville E. Sanjana

  • Sanjana Lab of NYGC/NYU Extends RNA-Targeting CRISPR-Cas13 Genomics Tools to Model Organisms and Viruses Including SARS-CoV-2

    Last year, researchers in the lab of Neville Sanjana, PhD, at the New York Genome Center (NYGC) and New York University (NYU) unveiled a suite of CRISPR-based tools to probe RNA in human cells in a high-throughput fashion using a RNA-targeting CRISPR enzyme (Cas13). Now, as detailed in a report published today in Cell Genomics, the lab has expanded this resource to enable researchers to optimize Cas13 guide RNA selection for six frequently used model organisms – human, mouse, zebrafish, fly, worm, and a flowering plant – as well as four viral RNA pathogens – influenza H1N1, HIV, the coronavirus MERS, and SARS-CoV-2, the virus responsible for the COVID-19 pandemic. The authors have made the CRISPR-Cas13 guide RNAs designs available online via a dedicated website: cas13design.nygenome.org. “A key feature of our study was to understand whether we can efficiently target viruses despite their constant mutations. We analyzed thousands of variants of coronaviruses and retroviruses to find optimal regions for targeting their RNA genomes,” said Xinyi (Cathy) Guo, a graduate student in NYU’s Department of Biology and the Sanjana Lab member who is the study’s first author. The team focused on three areas: designing and scoring Cas13 RNA guides targeting protein-coding…

  • Chemically modified guide RNAs enhance CRISPR-Cas13 knockdown in human cells.

    Alejandro Méndez-Mancilla, Hans-Hermann Wessels, Mateusz Legut, Anastasia Kadina, Megumi Mabuchi, John Walker, G. Brett Robb, Kevin Holden, Neville E Sanjana

  • Sanjana Lab of NYGC/NYU Boosts Gene Knockdown in Human Cells With CRISPR-Cas13 Using Chemically-Modified Guide RNAs

    Modified RNA guides improve gene targeting for next-generation CRISPR tools and therapies In the latest of ongoing efforts to expand technologies for modifying genes and their expression, researchers in the lab of Neville Sanjana, PhD, at the New York Genome Center (NYGC) and New York University (NYU) have developed chemically modified guide RNAs for a CRISPR system that targets RNA instead of DNA. These chemically-modified guide RNAs significantly enhance the ability to target — trace, edit, and/or knockdown — RNA in human cells. In a study published today in Cell Chemical Biology, the team explores a range of different RNA modifications and details how the modified guides increase efficiencies of CRISPR activity from 2- to 5-fold over unmodified guides. They also show that the optimized chemical modifications extend CRISPR targeting activity from 48 hours to four days. The researchers worked in collaboration with scientists at Synthego Corporation and New England BioLabs, bringing together a diverse team with expertise in enzyme purification and RNA chemistry. To apply these optimized chemical modifications, the research team targeted cell surface receptors in human T cells from healthy donors and a “universal” segment of the genetic sequence shared by all known variants of the RNA…

  • Profiling the genetic determinants of chromatin accessibility with scalable single-cell CRISPR screens.

    Noa Liscovitch-Brauer, Antonino Montalbano, Jiale Deng, Alejandro Méndez-Mancilla, Hans-Hermann Wessels, Nicholas G. Moss, Chia-Yu Kung, Akash Sookdeo, Xinyi Guo, Evan Geller, Suma Jaini, Peter Smibert & Neville E. Sanjana

  • NYGC News — Summer 2020

    MAY 2020 – AUGUST 2020 RESEARCH HIGHLIGHTS Updates from Faculty Labs Hemali Phatnani (l) and CZI Neurodegeneration Challenge Network grant partner Liam Holt, PhD Hemali Phatnani Awarded CZI Neurodegeneration Challenge Network Grant for Collaborative Research Project with NYU’s Liam Holt for In-depth Study of Live Neuron Cells in Real Time The cellular framework of neurons is an incredibly crowded, complex, bustling environment, so full of molecules and organelles that the system is close to jamming. Is overcrowding a key factor that causes cellular components to stick together, leading to protein aggregate formation and disease onset? Is Alzheimer’s disease the result of crowding becoming even more dense as we age, causing neurons to shut down? Those are the biological questions that Hemali Phatnani, PhD, Director, Center for Genomics of Neurodegenerative Disease, NYGC and Liam Holt, PhD, Assistant Professor, Institute for Systems Genetics, NYU School of Medicine will explore in a collaborative project that was awarded a pilot grant through the Chan Zuckerberg Initiative’s Neurodegeneration Challenge Network program in August. Their award-winning project, “The Physical Biology of Neurodegeneration,” will utilize a mix of emerging new technologies, including cutting-edge microscopy techniques, genetically encoded nanoparticles, and spatial transcriptomics, to track what’s happening inside neurons…

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