SNP-CRISPR: a web tool for SNP-specific genome editing

Chen, Chiao-Lin; Rodiger, Jonathan; Chung, Verena; Viswanatha, Raghuvir; Mohr, Stephanie E.; Hu, Yanhui; Perrimon, Norbert

doi:10.1101/847277

Cited by 5 publications

(5 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are approximately 10–15 million common human SNVs, which can impact the efficacy of CRISPR/Cas9 editing ( Chen et al ., 2020 ; Eichler et al ., 2007 ). Since CROTON accurately predicts 1 bp insertion probability with the best performance ( Tables 1 and 2 ), we utilized 1 bp insertion probability to analyze the effect of SNVs on CRISPR/Cas9 editing outcomes.…”

Section: Resultsmentioning

confidence: 99%

CROTON: an automated and variant-aware deep learning framework for predicting CRISPR/Cas9 editing outcomes

Troyanskaya

2021

Bioinformatics

View full text Add to dashboard Cite

Motivation CRISPR/Cas9 is a revolutionary gene-editing technology that has been widely utilized in biology, biotechnology and medicine. CRISPR/Cas9 editing outcomes depend on local DNA sequences at the target site and are thus predictable. However, existing prediction methods are dependent on both feature and model engineering, which restricts their performance to existing knowledge about CRISPR/Cas9 editing. Results Herein, deep multi-task convolutional neural networks (CNNs) and neural architecture search (NAS) were used to automate both feature and model engineering and create an end-to-end deep-learning framework, CROTON (CRISPR Outcomes Through cONvolutional neural networks). The CROTON model architecture was tuned automatically with NAS on a synthetic large-scale construct-based dataset and then tested on an independent primary T cell genomic editing dataset. CROTON outperformed existing expert-designed models and non-NAS CNNs in predicting 1 base pair insertion and deletion probability as well as deletion and frameshift frequency. Interpretation of CROTON revealed local sequence determinants for diverse editing outcomes. Finally, CROTON was utilized to assess how single nucleotide variants (SNVs) affect the genome editing outcomes of four clinically relevant target genes: the viral receptors ACE2 and CCR5 and the immune checkpoint inhibitors CTLA4 and PDCD1. Large SNV-induced differences in CROTON predictions in these target genes suggest that SNVs should be taken into consideration when designing widely applicable gRNAs. Availability and implementation https://github.com/vli31/CROTON. Supplementary information Supplementary data are available at Bioinformatics online.

show abstract

Section: Resultsmentioning

confidence: 99%

CROTON: an automated and variant-aware deep learning framework for predicting CRISPR/Cas9 editing outcomes

Troyanskaya

2021

Bioinformatics

View full text Add to dashboard Cite

show abstract

“…2020). Drury et al ., (2017) demonstrated that minor natural polymorphisms in target sites reduce gene drive effectiveness in flour beetles, and tools have been developed to help researchers design gRNAs accounting for population variation (Chen et al . 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Gene drive mechanisms to eliminate D. suzukii have been experimentally tested on multiple lines to ensure the miRNAs are broadly effective (Buchman et al 2018), but a large dataset of wild population sequencing allow researchers to more confidently select target sites that are non-variable and thus nonresistant to Cas9 targeting (Schmidt et al 2020). Drury et al, (2017) demonstrated that minor natural polymorphisms in target sites reduce gene drive effectiveness in flour beetles, and tools have been developed to help researchers design gRNAs accounting for population variation (Chen et al 2020). Similarly, with the recent development of a CRISPR-Cas9 editing and RNAi knockdown protocols for D. suzukii (Murphy et al 2016;Li and Scott 2016;Taning et al 2016;Ahmed et al 2020), prior knowledge of allelic variation will allow researchers to design targeting oligonucleotides more precisely to avoid loci with variability.…”

Section: Despite Being Recently Established Invasive Populations Botmentioning

confidence: 99%

Population structure ofDrosophila suzukiiand signals of multiple invasions into the continental United States

Lewald¹,

Abrieux²,

Wilson³

et al. 2021

Preprint

View full text Add to dashboard Cite

Drosophila suzukii, or spotted-wing drosophila, is now an established pest in many parts of the world, causing significant damage to numerous fruit crop industries. Native to East Asia, D. suzukii infestations started in the United States a decade ago, occupying a wide range of climates. To better understand invasion ecology of this pest, knowledge of past migration events, population structure, and genetic diversity is needed. To improve on previous studies examining genetic structure of D. suzukii, we sequenced whole genomes of 237 individual flies collected across the continental U.S., as well as several representative sites in Europe, Brazil, and Asia, to identify hundreds of thousands of genetic markers for analysis. We analyzed these markers to detect population structure, to reconstruct migration events, and to estimate genetic diversity and differentiation within and among the continents. We observed strong population structure between West and East Coast populations in the U.S., but no evidence of any population structure North to South, suggesting there is no broad-scale adaptations occurring in response to the large differences in regional weather conditions. We also find evidence of repeated migration events from Asia into North America have provided increased levels of genetic diversity, which does not appear to be the case for Brazil or Europe. This large genomic dataset will spur future research into genomic adaptations underlying D. suzukii pest activity and development of novel control methods for this agricultural pest.

show abstract

“…Although one should be careful to draw general conclusions from a single example, this result suggests that SNVs can induce unexpected off-target activity and that individual level genetic variation should be taken into consideration when designing gRNAs for medical purposes. Computational strategies that take into account SNVs in gRNA binding prediction already exist 42,43 , but those rely on databases that does not contain all variants that any individual carries. Our results further demonstrate that gRNAs can bind to genomic DNA despite having three or more single nucleotide mismatches, or even insertion or deletion mismatches.…”

Section: Discussionmentioning

confidence: 99%

Amplification-free long read sequencing reveals unforeseen CRISPR-Cas9 off-target activity

Höijer

Johansson

Gudmundsson

et al. 2020

Preprint

View full text Add to dashboard Cite

A much-debated concern about CRISPR-Cas9 genome editing is that unspecific guide RNA (gRNA) binding may induce off-target mutations. However, accurate prediction of CRISPR-Cas9 off-target sites and activity is challenging. Here we present SMRT-OTS and Nano-OTS, two amplification-free long-read sequencing protocols for detection of gRNA driven digestion of genomic DNA by Cas9. The methods were assessed using the human cell line HEK293, which was first re-sequenced at 18x coverage using highly accurate (HiFi) SMRT reads to get a detailed view of all on-and off-target binding regions. We then applied SMRT-OTS and Nano-OTS to investigate the specificity of three different gRNAs, resulting in a set of 55 highconfidence gRNA binding sites identified by both methods. Twenty-five (45%) of these sites were not reported by off-target prediction software, either because they contained four or more single nucleotide mismatches or insertion/deletion mismatches, as compared with the human reference. We further discovered that a heterozygous SNP can cause allele-specific gRNA binding. Finally, by performing a de novo genome assembly of the HiFi reads, we were able to re-discover 98.7% of the gRNA binding sites without any prior information about the human reference genome. This suggests that CRISPR-Cas9 off-target sites can be efficiently mapped also in organisms where the genome sequence is unknown. In conclusion, the amplificationfree sequencing protocols revealed many gRNA binding sites in vitro that would be difficult to predict based on gRNA sequence alignment to a reference. Nevertheless, it is still unknown whether in vivo off-target editing would occur at these sites.

show abstract

SNP-CRISPR: a web tool for SNP-specific genome editing

Cited by 5 publications

References 39 publications

CROTON: an automated and variant-aware deep learning framework for predicting CRISPR/Cas9 editing outcomes

CROTON: an automated and variant-aware deep learning framework for predicting CRISPR/Cas9 editing outcomes

Population structure ofDrosophila suzukiiand signals of multiple invasions into the continental United States

Amplification-free long read sequencing reveals unforeseen CRISPR-Cas9 off-target activity

Contact Info

Product

Resources

About