scholarly journals Engineered PAM-flexible FnCas9 variants for robust and specific genome editing and diagnostics

Author(s):  
Sundaram Acharya ◽  
Asgar Ansari ◽  
Seiichi Hirano ◽  
Deepanjan Paul ◽  
Riya Rauthan ◽  
...  

Abstract The clinical success of CRISPR therapies is dependent on the safety and efficacy ofCas proteins. The Cas9 from Francisella novicida (FnCas9) has negligible affinity formismatched substrates enabling it to discriminate off-targets in DNA with very highprecision even at the level of binding. However, its cellular targeting efficiency is low,limiting its use in therapeutic applications. Here, we rationally engineer the protein todevelop engineered(enFnCas9) variants with enhanced activity and expand its cellularediting activity to genomic loci previously inaccessible. Notably, some of the variantsrelease the protospacer adjacent motif (PAM) constraint from NGG to NGR/NRGmaking them rank just below SpCas9-RY and SpCas9-NG in their accessibility acrosshuman genomic sites. The enFnCas9 proteins, similar to Cas12a and Cas12f, harborhigh intrinsic specificity and can diagnose single nucleotide variants accurately.Importantly, they provide superior outcomes in terms of editing efficiency, knock-inrates, and off-target specificity over other engineered high-fidelity versions of SpCas9(SpCas9-HF1 and eSpCas9). Broad targeting range coupled with remarkablespecificity of DNA interrogation underscores the utility of these variants for safe andefficient therapeutic gene correction across multiple cell lines and target loci.

Science ◽  
2019 ◽  
pp. eaaw7166 ◽  
Author(s):  
Shuai Jin ◽  
Yuan Zong ◽  
Qiang Gao ◽  
Zixu Zhu ◽  
Yanpeng Wang ◽  
...  

Cytosine and adenine base editors (CBEs and ABEs) are promising new tools for achieving the precise genetic changes required for disease treatment and trait improvement. However, genome-wide and unbiased analyses of their off-target effects in vivo are still lacking. Our whole genome sequencing (WGS) analysis of rice plants treated with BE3, high-fidelity BE3 (HF1-BE3), or ABE revealed that BE3 and HF1-BE3, but not ABE, induce substantial genome-wide off-target mutations, which are mostly the C→T type of single nucleotide variants (SNVs) and appear to be enriched in genic regions. Notably, treatment of rice with BE3 or HF1-BE3 in the absence of single-guide RNA also results in the rise of genome-wide SNVs. Thus, the base editing unit of BE3 or HF1-BE3 needs to be optimized in order to attain high fidelity.


Author(s):  
Renata Parissi Buainain ◽  
Matheus Negri Boschiero ◽  
Bruno Camporeze ◽  
Paulo Henrique Pires de Aguiar ◽  
Fernando Augusto Lima Marson ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
pp. 33
Author(s):  
Nayoung Han ◽  
Jung Mi Oh ◽  
In-Wha Kim

For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.


Author(s):  
Pauline Arnaud ◽  
Hélène Morel ◽  
Olivier Milleron ◽  
Laurent Gouya ◽  
Christine Francannet ◽  
...  

Abstract Purpose Individuals with mosaic pathogenic variants in the FBN1 gene are mainly described in the course of familial screening. In the literature, almost all these mosaic individuals are asymptomatic. In this study, we report the experience of our team on more than 5,000 Marfan syndrome (MFS) probands. Methods Next-generation sequencing (NGS) capture technology allowed us to identify five cases of MFS probands who harbored a mosaic pathogenic variant in the FBN1 gene. Results These five sporadic mosaic probands displayed classical features usually seen in Marfan syndrome. Combined with the results of the literature, these rare findings concerned both single-nucleotide variants and copy-number variations. Conclusion This underestimated finding should not be overlooked in the molecular diagnosis of MFS patients and warrants an adaptation of the parameters used in bioinformatics analyses. The five present cases of symptomatic MFS probands harboring a mosaic FBN1 pathogenic variant reinforce the fact that apparently asymptomatic mosaic parents should have a complete clinical examination and a regular cardiovascular follow-up. We advise that individuals with a typical MFS for whom no single-nucleotide pathogenic variant or exon deletion/duplication was identified should be tested by NGS capture panel with an adapted variant calling analysis.


2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Fatao Liu ◽  
Yongsheng Li ◽  
Dongjian Ying ◽  
Shimei Qiu ◽  
Yong He ◽  
...  

AbstractNeuroendocrine carcinoma (NEC) of the gallbladder (GB-NEC) is a rare but extremely malignant subtype of gallbladder cancer (GBC). The genetic and molecular signatures of GB-NEC are poorly understood; thus, molecular targeting is currently unavailable. In the present study, we applied whole-exome sequencing (WES) technology to detect gene mutations and predicted somatic single-nucleotide variants (SNVs) in 15 cases of GB-NEC and 22 cases of general GBC. In 15 GB-NECs, the C > T mutation was predominant among the 6 types of SNVs. TP53 showed the highest mutation frequency (73%, 11/15). Compared with neuroendocrine carcinomas of other organs, significantly mutated genes (SMGs) in GB-NECs were more similar to those in pulmonary large-cell neuroendocrine carcinomas (LCNECs), with driver roles for TP53 and RB1. In the COSMIC database of cancer-related genes, 211 genes were mutated. Strikingly, RB1 (4/15, 27%) and NAB2 (3/15, 20%) mutations were found specifically in GB-NECs; in contrast, mutations in 29 genes, including ERBB2 and ERBB3, were identified exclusively in GBC. Mutations in RB1 and NAB2 were significantly related to downregulation of the RB1 and NAB2 proteins, respectively, according to immunohistochemical (IHC) data (p values = 0.0453 and 0.0303). Clinically actionable genes indicated 23 mutated genes, including ALK, BRCA1, and BRCA2. In addition, potential somatic SNVs predicted by ISOWN and SomVarIUS constituted 6 primary COSMIC mutation signatures (1, 3, 30, 6, 7, and 13) in GB-NEC. Genes carrying somatic SNVs were enriched mainly in oncogenic signaling pathways involving the Notch, WNT, Hippo, and RTK-RAS pathways. In summary, we have systematically identified the mutation landscape of GB-NEC, and these findings may provide mechanistic insights into the specific pathogenesis of this deadly disease.


Transfusion ◽  
2021 ◽  
Author(s):  
Loann Raud ◽  
Marlène Le Tertre ◽  
Léonie Vigneron ◽  
Chandran Ka ◽  
Gaëlle Richard ◽  
...  

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Gavin W. Wilson ◽  
Mathieu Derouet ◽  
Gail E. Darling ◽  
Jonathan C. Yeung

AbstractIdentifying single nucleotide variants has become common practice for droplet-based single-cell RNA-seq experiments; however, presently, a pipeline does not exist to maximize variant calling accuracy. Furthermore, molecular duplicates generated in these experiments have not been utilized to optimally detect variant co-expression. Herein, we introduce scSNV designed from the ground up to “collapse” molecular duplicates and accurately identify variants and their co-expression. We demonstrate that scSNV is fast, with a reduced false-positive variant call rate, and enables the co-detection of genetic variants and A>G RNA edits across twenty-two samples.


2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Ianthe A. E. M. van Belzen ◽  
Alexander Schönhuth ◽  
Patrick Kemmeren ◽  
Jayne Y. Hehir-Kwa

AbstractCancer is generally characterized by acquired genomic aberrations in a broad spectrum of types and sizes, ranging from single nucleotide variants to structural variants (SVs). At least 30% of cancers have a known pathogenic SV used in diagnosis or treatment stratification. However, research into the role of SVs in cancer has been limited due to difficulties in detection. Biological and computational challenges confound SV detection in cancer samples, including intratumor heterogeneity, polyploidy, and distinguishing tumor-specific SVs from germline and somatic variants present in healthy cells. Classification of tumor-specific SVs is challenging due to inconsistencies in detected breakpoints, derived variant types and biological complexity of some rearrangements. Full-spectrum SV detection with high recall and precision requires integration of multiple algorithms and sequencing technologies to rescue variants that are difficult to resolve through individual methods. Here, we explore current strategies for integrating SV callsets and to enable the use of tumor-specific SVs in precision oncology.


2021 ◽  
Author(s):  
Juliana D Siqueira ◽  
Livia R Goes ◽  
Brunna M Alves ◽  
Pedro S de Carvalho ◽  
Claudia Cicala ◽  
...  

Abstract Numerous factors have been identified to influence susceptibility to SARS-CoV-2 infection and disease severity. Cancer patients are more prone to clinically evolve to more severe COVID-19 conditions, but the determinants of such a more severe outcome remain largely unknown. We have determined the full-length SARS-CoV-2 genomic sequences of cancer patients and healthcare workers (non-cancer controls) by deep sequencing and investigated the within-host viral population of each infection, quantifying intrahost genetic diversity. Naso- and oropharyngeal SARS-CoV-2+ swabs from 57 cancer patients and 14 healthcare workers from the Brazilian National Cancer Institute were collected in April–May 2020. Complete genome amplification using ARTIC network V3 multiplex primers was performed followed by next-generation sequencing. Assemblies were conducted in Geneious R11, where consensus sequences were extracted and intrahost single nucleotide variants were identified. Maximum likelihood phylogenetic analysis was performed using PhyMLv.3.0 and lineages were classified using Pangolin and CoV-GLUE. Phylogenetic analysis showed that all but one strain belonged to clade B1.1. Four genetically linked mutations known as the globally dominant SARS-CoV-2 haplotype (C241T, C3037T, C14408T and A23403G) were found in the majority of consensus sequences. SNV signatures of previously characterized Brazilian genomes were also observed in most samples. Another 85 SNVs were found at a lower frequency (1.4-19.7%) among the consensus sequences. Cancer patients displayed a significantly higher intrahost viral genetic diversity compared to healthcare workers. This difference was independent of SARS-CoV-2 Ct values obtained at the diagnostic tests, which did not differ between the two groups. The most common nucleotide changes of intrahost SNVs in both groups were consistent with APOBEC and ADAR activities. Intrahost genetic diversity in cancer patients was not associated with disease severity, use of corticosteroids, or use of antivirals, characteristics that could influence viral diversity. Moreover, the presence of metastasis, either in general or specifically in the lung, was not associated with intrahost diversity among cancer patients. Cancer patients carried significantly higher numbers of minor variants compared to non-cancer counterparts. Further studies on SARS-CoV-2 diversity in especially vulnerable patients will shed light onto the understanding of the basis of COVID-19 different outcomes in humans.


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