Biology subjects

Tunc, I.

Publications and source records attributed to Tunc, I..

3 recordsLinked to original sources

bioRxiv2020

Validation and Long-Term Follow Up of CD33 Off-Targets Predicted In Vitro and In Silico Using Error-Corrected Sequencing in Rhesus Macaques

ABSTRACTThe programmable nuclease technology CRISPR/Cas9 has revolutionized gene editing in the last decade. Due to the risk of off-target editing, accurate and sensitive methods for off-target characterization are crucial prior to applying CRISPR/Cas9 therapeutically. Here, we utilized a rhesus macaque model to ask whether CIRCLE-Seq (CS), an in vitro off-target prediction method, more accurately identifies off-targets compared to in silico prediction (ISP) based solely on genomic sequence comparisons. We use AmpliSeq HD error-corrected sequencing to validate off-target sites predicted by CIRCLE-Seq and ISP for guide RNAs designed against TET2 and CD33 genes. A gRNA targeting TET2 designed using modern algorithms and predicted to have low off-target risk by both ISP and CIRCLE-Seq created no detectable mutations at off-target sites in hematopoietic cells following transplantation, even when applying highly sensitive error-corrected sequencing. In contrast, a CD33 gRNA designed using less robust algorithms with over 10-fold more off-targets sites predicted by both ISP and CIRCLE-Seq, however there was poor correlation between the sites predicted by the two methods. When almost 500 sites identified by each method were searched for in hematopoietic cells following transplantation, 19 detectable mutations in off-target sites were detected via error-corrected sequencing. Of these 19 sites, 8 sites were predicted in the top 500 sites by both methods, 8 by CIRCLE-Seq only, and 3 by ISP only. Cells with off-target editing exhibited no expansion or abnormal behavior in vivo in animals followed for up to 2 years. In conclusion, neither methodology predicted all sites, and a combination of careful gRNA design, followed by screening for predicted off-target sites in target cells by multiple methods may be required for optimizing safety of clinical development.Competing Interest StatementThe authors have declared no competing interest.View Full Text

molecular biology↗

bioRxiv2020

Network Analysis and Transcriptome Profiling Identify Autophagic and Mitochondrial Dysfunctions in SARS-CoV-2 Infection

Analyzing host transcriptional changes in response to SARS-CoV-2 infection will help delineate biological processes underlying viral pathogenesis. Comparison of expression profiles of lung cell lines A549 (infected with either SARS-CoV-2 (with ACE2 expression)) or Influenza A virus (IAV)) and Calu3 (infected with SARS-CoV-2 or MERS-CoV) revealed upregulation of the antiviral interferon signaling in all three viral infections. However, perturbations in inflammatory, mitochondrial, and autophagy processes were specifically observed in SARS-CoV-2 infected cells. Validation of findings from cell line data revealed perturbations in autophagy and mitochondrial processes in the infected human nasopharyngeal samples. Specifically, downregulation of mTOR expression, mitochondrial ribosomal, mitochondrial complex I, and lysosome acidification genes were concurrently observed in both infected cell lines and human datasets. Furthermore, SARS-CoV-2 infection impedes autophagic flux by upregulating GSK3B in lung cell lines, or by downregulating autophagy genes, SNAP29 and lysosome acidification genes in human samples, contributing to increased viral replication. Therefore, drugs targeting lysosome acidification or autophagic flux could be tested as intervention strategies. Additionally, downregulation of MTFP1 (in cell lines) or SOCS6 (in human samples) results in hyperfused mitochondria and impede proper interferon response. Coexpression networks analysis identifies correlated clusters of genes annotated to inflammation and mitochondrial processes that are misregulated in SARS-CoV-2 infected cells. Finally, comparison of age stratified human gene expression data revealed impaired upregulation of chemokines, interferon stimulated and tripartite motif genes that are critical for antiviral signaling. Together, this analysis has revealed specific aspects of autophagic and mitochondrial function that are uniquely perturbed in SARS-CoV-2 infection.

bioinformatics↗

bioRxiv2019

lncRNAKB: A comprehensive knowledgebase of long non-coding RNAs

We have assembled a comprehensive long non-coding RNA knowledgebase (lncRNAKB) of 77,199 annotated human lncRNAs (224,286 transcripts) by methodically integrating widely used lncRNAs resources. To facilitate functional characterization of lncRNAs, we employed Genotype-Tissue Expression (GTEx) project to provide tissue-specific gene expression profiles of lncRNAs in 31 solid organ tissues. Additional information includes network analysis to identify co-expressed gene modules to potentially delineate lncRNA function. Tissue-specificity, phylogenetic conservation scores and coding potential for lncRNAs are included. Finally, using whole genome sequencing data from GTEx, expression quantitative trait loci (cis-eQTL) regulated lncRNAs were calculated in all tissues. lncRNAKB is available at http://www.lncrnakb.org.

bioinformatics↗