Michelle Ng

Bio: Michelle Ng is an academic researcher from Martin Luther University of Halle-Wittenberg. The author has contributed to research in topics: Myeloid leukemia & Haematopoiesis. The author has an hindex of 5, co-authored 9 publications receiving 263 citations. Previous affiliations of Michelle Ng include Hannover Medical School.

Refined sgRNA efficacy prediction improves large- and small-scale CRISPR-Cas9 applications.

Abstract: Genome editing with the CRISPR-Cas9 system has enabled unprecedented efficacy for reverse genetics and gene correction approaches. While off-target effects have been successfully tackled, the effort to eliminate variability in sgRNA efficacies-which affect experimental sensitivity-is in its infancy. To address this issue, studies have analyzed the molecular features of highly active sgRNAs, but independent cross-validation is lacking. Utilizing fluorescent reporter knock-out assays with verification at selected endogenous loci, we experimentally quantified the target efficacies of 430 sgRNAs. Based on this dataset we tested the predictive value of five recently-established prediction algorithms. Our analysis revealed a moderate correlation (r = 0.04 to r = 0.20) between the predicted and measured activity of the sgRNAs, and modest concordance between the different algorithms. We uncovered a strong PAM-distal GC-content-dependent activity, which enabled the exclusion of inactive sgRNAs. By deriving nine additional predictive features we generated a linear model-based discrete system for the efficient selection (r = 0.4) of effective sgRNAs (CRISPRater). We proved our algorithms' efficacy on small and large external datasets, and provide a versatile combined on- and off-target sgRNA scanning platform. Altogether, our study highlights current issues and efforts in sgRNA efficacy prediction, and provides an easily-applicable discrete system for selecting efficient sgRNAs.

The non-coding RNA landscape of human hematopoiesis and leukemia

Abstract: Non-coding RNAs have emerged as crucial regulators of gene expression and cell fate decisions. However, their expression patterns and regulatory functions during normal and malignant human hematopoiesis are incompletely understood. Here we present a comprehensive resource defining the non-coding RNA landscape of the human hematopoietic system. Based on highly specific non-coding RNA expression portraits per blood cell population, we identify unique fingerprint non-coding RNAs—such as LINC00173 in granulocytes—and assign these to critical regulatory circuits involved in blood homeostasis. Following the incorporation of acute myeloid leukemia samples into the landscape, we further uncover prognostically relevant non-coding RNA stem cell signatures shared between acute myeloid leukemia blasts and healthy hematopoietic stem cells. Our findings highlight the importance of the non-coding transcriptome in the formation and maintenance of the human blood hierarchy. While micro-RNAs are known regulators of haematopoiesis and leukemogenesis, the role of long non-coding RNAs is less clear. Here the authors provide a non-coding RNA expression landscape of the human hematopoietic system, highlighting their role in the formation and maintenance of the human blood hierarchy.

Endogenous Tumor Suppressor microRNA-193b: Therapeutic and Prognostic Value in Acute Myeloid Leukemia

Abstract: PurposeDysregulated microRNAs are implicated in the pathogenesis and aggressiveness of acute myeloid leukemia (AML). We describe the effect of the hematopoietic stem-cell self-renewal regulating miR-193b on progression and prognosis of AML.MethodsWe profiled miR-193b-5p/3p expression in cytogenetically and clinically characterized de novo pediatric AML (n = 161) via quantitative real-time polymerase chain reaction and validated our findings in an independent cohort of 187 adult patients. We investigated the tumor suppressive function of miR-193b in human AML blasts, patient-derived xenografts, and miR-193b knockout mice in vitro and in vivo.ResultsmiR-193b exerted important, endogenous, tumor-suppressive functions on the hematopoietic system. miR-193b-3p was downregulated in several cytogenetically defined subgroups of pediatric and adult AML, and low expression served as an independent indicator for poor prognosis in pediatric AML (risk ratio ± standard error, −0.56 ± 0.23; P = .016). miR-193b-3p express...

The Regulatory Roles of Long Noncoding RNAs in Acute Myeloid Leukemia.

Abstract: In this post-genomic era, long noncoding RNAs (lncRNAs) are rapidly gaining recognition for their crucial roles across diverse biological processes and contexts. The human blood system is no exception, where dozens of lncRNAs have been established as regulators of normal and/or malignant hematopoiesis, and where ongoing works continue to uncover novel lncRNA functions. Our review focuses on lncRNAs that are involved in the pathogenesis of acute myeloid leukemia (AML) and the mechanisms through which they control gene expression in this disease context. We also comment on genome-wide sequencing or profiling studies that have implicated large sets of lncRNAs in AML pathophysiology.

Integrative Genomics Viewer

Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Activation of proto-oncogenes by disruption of chromosome neighborhoods

Abstract: The spread of bad neighborhoods Our genomes have complex three-dimensional (3D) arrangements that partition and regulate gene expression. Cancer cells frequently have their genomes grossly rearranged, disturbing this intricate 3D organization. Hnisz et al. show that the disruption of these 3D neighborhoods can bring oncogenes under the control of regulatory elements normally kept separate from them (see the Perspective by Wala and Beroukim). These novel juxtapositions can result in the inappropriate activation of oncogenes. Science, this issue p. 1454; see also p. 1398 Disrupting the boundaries between three-dimensional neighborhoods in the genome can activate cancer-promoting genes. [Also see Perspective by Wala and Beroukim] Oncogenes are activated through well-known chromosomal alterations such as gene fusion, translocation, and focal amplification. In light of recent evidence that the control of key genes depends on chromosome structures called insulated neighborhoods, we investigated whether proto-oncogenes occur within these structures and whether oncogene activation can occur via disruption of insulated neighborhood boundaries in cancer cells. We mapped insulated neighborhoods in T cell acute lymphoblastic leukemia (T-ALL) and found that tumor cell genomes contain recurrent microdeletions that eliminate the boundary sites of insulated neighborhoods containing prominent T-ALL proto-oncogenes. Perturbation of such boundaries in nonmalignant cells was sufficient to activate proto-oncogenes. Mutations affecting chromosome neighborhood boundaries were found in many types of cancer. Thus, oncogene activation can occur via genetic alterations that disrupt insulated neighborhoods in malignant cells.

Optimized libraries for CRISPR-Cas9 genetic screens with multiple modalities

Abstract: 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.

DeepCRISPR: optimized CRISPR guide RNA design by deep learning

Abstract: A major challenge for effective application of CRISPR systems is to accurately predict the single guide RNA (sgRNA) on-target knockout efficacy and off-target profile, which would facilitate the optimized design of sgRNAs with high sensitivity and specificity. Here we present DeepCRISPR, a comprehensive computational platform to unify sgRNA on-target and off-target site prediction into one framework with deep learning, surpassing available state-of-the-art in silico tools. In addition, DeepCRISPR fully automates the identification of sequence and epigenetic features that may affect sgRNA knockout efficacy in a data-driven manner. DeepCRISPR is available at http://www.deepcrispr.net/ .