Massively parallel CRISPR off-target detection enables rapid off-target prediction model building.

BACKGROUND: CRISPR (clustered regularly interspaced short palindromic repeats) genome editing holds tremendous potential in clinical translation. However, the off-target effect has always been a major concern. METHODS: Here, we have developed a novel sensitive and specific off-target detection method, AID-seq (adaptor-mediated off-target identification by sequencing), that can comprehensively and faithfully detect the low-frequency off targets generated by different CRISPR nucleases (including Cas9 and Cas12a). FINDINGS: Based on AID-seq, we developed a pooled strategy to simultaneously identify the on/off targets of multiple gRNAs, as well as using mixed human and human papillomavirus (HPV) genomes to screen the most efficient and safe targets from 416 HPV gRNA candidates for antiviral therapy. Moreover, we used the pooled strategy with 2,069 single-guide RNAs (sgRNAs) at a pool size of about 500 to profile the properties of our newly discovered CRISPR, FrCas9. Importantly, we successfully built an off-target detection model using these off-target data via the CRISPR-Net deep learning method (area under the receiver operating characteristic curve [AUROC] = 0.97, area under the precision recall curve [AUPRC] = 0.29). CONCLUSIONS: To our knowledge, AID-seq is the most sensitive and specific in vitro off-target detection method to date. And the pooled AID-seq strategy can be used as a rapid and high-throughput platform to select the best sgRNAs and characterize the properties of new CRISPRs. FUNDING: This work was supported by The National Natural Science Foundation of China (grant nos. 32171465 and 82102392), the General Program of Natural Science Foundation of Guangdong Province of China (grant no. 2021A1515012438), Guangdong Basic and Applied Basic Research Foundation (grant no. 2020A1515110170), and the National Ten Thousand Plan-Young Top Talents of China (grant no. 80000-41180002).

Glacial vicariance and oceanic circulation shape population structure of the coastal legume Derris trifoliata in the Indo-West Pacific.

PREMISE: The phylogeography of coastal plant species is shaped by contemporary and historical biogeographic processes. In this study, we aim to decipher the phylogeography of Derris trifoliata, a woody legume of relatively recent origin and wide distribution, in coastal areas in the Indo-West Pacific (IWP) region. METHODS: Genetic diversity and population structure were assessed by analyzing six nuclear and three chloroplast DNA sequences from 30 populations across the species' range. Phylogeography was inferred by estimating gene flow, divergence time, historical population size changes, and historical habitat suitability using paleoclimatic niche modeling. RESULTS: High genetic diversity was observed at the species level. The populations of three oceanic regions included in this study (i.e., Indian Ocean, South China Sea, and Pacific Ocean) formed distinct clades and likely diverged during the late Pleistocene. Potential barriers to gene flow were identified, including the Sunda and Sahul shelves, geographic distance, and current patterns of oceanic circulation. Analysis of changes in population size supported the bottleneck model, which was strengthened by estimates of habitat suitability across paleoclimatic conditions. CONCLUSIONS: The once widespread distribution of D. trifoliata was fragmented by changes in climatic suitability and biogeographic barriers that arose following sea-level changes during the Pleistocene. In addition, contemporary patterns of oceanic circulation and geographic distance between populations appear to maintain genetic differentiation across its distribution in the IWP.

FrCas9 is a CRISPR/Cas9 system with high editing efficiency and fidelity.

Genome editing technologies hold tremendous potential in biomedical research and drug development. Therefore, it is imperative to discover gene editing tools with superior cutting efficiency, good fidelity, and fewer genomic restrictions. Here, we report a CRISPR/Cas9 from Faecalibaculum rodentium, which is characterized by a simple PAM (5'-NNTA-3') and a guide RNA length of 21-22 bp. We find that FrCas9 could achieve comparable efficiency and specificity to SpCas9. Interestingly, the PAM of FrCas9 presents a palindromic sequence, which greatly expands its targeting scope. Due to the PAM sequence, FrCas9 possesses double editing-windows for base editor and could directly target the TATA-box in eukaryotic promoters for TATA-box related diseases. Together, our results broaden the understanding of CRISPR/Cas-mediated genome engineering and establish FrCas9 as a safe and efficient platform for wide applications in research, biotechnology and therapeutics.

Gene knock-out chain reaction enables high disruption efficiency of HPV18 E6/E7 genes in cervical cancer cells.

A genome editing tool targeting the high-risk human papillomavirus (HPV) oncogene is a promising therapeutic strategy to treat HPV-related cervical cancer. To improve gene knockout efficiency, we developed a gene knockout chain reaction (GKCR) method for continually generating mutagenic disruptions and used this method to disrupt the HPV18 E6 and E7 genes. We verified that the GKCR Cas9/guide RNA (gRNA) cassettes could integrated into the targeted loci via homology-independent targeted insertion (HITI). The qPCR results revealed that the GKCR method enabled a relatively higher Cas9/gRNA cassette insertion rate than a control method (the common CRISPR-Cas9 strategy). Tracking of Indels by DEcomposition (TIDE) assay results showed that the GKCR method produced a significantly higher percentage of insertions or deletions (indels) in the HPV18 E6 and E7 genes. Furthermore, by targeting the HPV18 E6/E7 oncogenes, we found that the GKCR method significantly upregulated the P53/RB proteins and inhibited the proliferation and motility of HeLa cells. The GKCR method significantly improved the gene knockout efficiency of the HPV18 E6/E7 oncogenes, which might provide new insights into treatment of HPV infection and related cervical cancer.

Non-homologous dsODN increases the mutagenic effects of CRISPR-Cas9 to disrupt oncogene E7 in HPV positive cells.

Genome editing tools targeting high-risk human papillomavirus (HPV) oncogene could be a promising therapeutic strategy for the treatment of HPV-related cervical cancer. We aimed to improve the editing efficiency and detect off-target effects concurrently for the clinical translation strategy by using CRISPR-Cas9 system co-transfected with 34nt non-homologous double-stranded oligodeoxynucleotide (dsODN). We firstly tested this strategy on targeting the Green Fluorescent Protein (GFP) gene, of which the expression is easily observed. Our results showed that the GFP+ cells were significantly decreased when using GFP-sgRNAs with dsODN, compared to using GFP-sgRNAs without donors. By PCR and Sanger sequencing, we verified the dsODN integration into the break sites of the GFP gene. And by amplicon sequencing, we observed that the indels% of the targeted site on the GFP gene was increased by using GFP-sgRNAs with dsODN. Next, we went on to target the HPV18 E7 oncogene by using single E7-sgRNA and multiplexed E7-sgRNAs respectively. Whenever using single sgRNA or multiplexed sgRNAs, the mRNA expression of HPV18 E7 oncogene was significantly decreased when adding E7-sgRNAs with dsODN, compared to E7-sgRNAs without donor. And the indels% of the targeted sites on the HPV18 E7 gene was markedly increased by adding dsODN with E7-sgRNAs. Finally, we performed GUIDE-Seq to verify that the integrated dsODN could serve as the marker to detect off-target effects in using single or multiplexed two sgRNAs. And we detected fewer on-target reads and off-target sites in multiplexes compared to the single sgRNAs when targeting the GFP and the HPV18 E7 genes. Together, CRISPR-Cas9 system co-transfected with 34nt dsODN concurrently improved the editing efficiency and monitored off-target effects, which might provide new insights in the treatment of HPV infections and related cervical cancer.

The comparison of ZFNs, TALENs, and SpCas9 by GUIDE-seq in HPV-targeted gene therapy.

Zinc-finger nucleases (ZFNs), transcription activator-like endonucleases (TALENs), and CRISPR-associated Cas9 endonucleases are three major generations of genome editing tools. However, no parallel comparison about the efficiencies and off-target activity of the three nucleases has been reported, which is critical for the final clinical decision. We for the first time developed the genome-wide unbiased identification of double-stranded breaks enabled by sequencing (GUIDE-seq) method in ZFNs and TALENs with novel bioinformatics algorithms to evaluate the off-targets. By targeting human papillomavirus 16 (HPV16), we compared the performance of ZFNs, TALENs, and SpCas9 in vivo. Our data showed that ZFNs with similar targets could generate distinct massive off-targets (287-1,856), and the specificity could be reversely correlated with the counts of middle "G" in zinc finger proteins (ZFPs). We also compared the TALENs with different N-terminal domains (wild-type [WT]/αN/ßN) and G recognition modules (NN/NH) and found the design (αN or NN) to improve the efficiency of TALEN inevitably increased off-targets. Finally, our results showed that SpCas9 was more efficient and specific than ZFNs and TALENs. Specifically, SpCas9 had fewer off-target counts in URR (SpCas9, n = 0; TALEN, n = 1; ZFN, n = 287), E6 (SpCas9, n = 0; TALEN, n = 7), and E7 (SpCas9, n = 4; TALEN, n = 36). Taken together, we suggest that for HPV gene therapies, SpCas9 is a more efficient and safer genome editing tool. Our off-target data could be used to improve the design of ZFNs and TALENs, and the universal in vivo off-target detection pipeline for three generations of artificial nucleases provided useful tools for genome engineering-based gene therapy.

DeepHBV: a deep learning model to predict hepatitis B virus (HBV) integration sites.

BACKGROUND: The hepatitis B virus (HBV) is one of the main causes of viral hepatitis and liver cancer. HBV integration is one of the key steps in the virus-promoted malignant transformation. RESULTS: An attention-based deep learning model, DeepHBV, was developed to predict HBV integration sites. By learning local genomic features automatically, DeepHBV was trained and tested using HBV integration site data from the dsVIS database. Initially, DeepHBV showed an AUROC of 0.6363 and an AUPR of 0.5471 for the dataset. The integration of genomic features of repeat peaks and TCGA Pan-Cancer peaks significantly improved model performance, with AUROCs of 0.8378 and 0.9430 and AUPRs of 0.7535 and 0.9310, respectively. The transcription factor binding sites (TFBS) were significantly enriched near the genomic positions that were considered. The binding sites of the AR-halfsite, Arnt, Atf1, bHLHE40, bHLHE41, BMAL1, CLOCK, c-Myc, COUP-TFII, E2A, EBF1, Erra, and Foxo3 were highlighted by DeepHBV in both the dsVIS and VISDB datasets, revealing a novel integration preference for HBV. CONCLUSIONS: DeepHBV is a useful tool for predicting HBV integration sites, revealing novel insights into HBV integration-related carcinogenesis.

DeepEBV: a deep learning model to predict Epstein-Barr virus (EBV) integration sites.

MOTIVATION: Epstein-Barr virus (EBV) is one of the most prevalent DNA oncogenic viruses. The integration of EBV into the host genome has been reported to play an important role in cancer development. The preference of EBV integration showed strong dependence on the local genomic environment, which enables the prediction of EBV integration sites. RESULTS: An attention-based deep learning model, DeepEBV, was developed to predict EBV integration sites by learning local genomic features automatically. First, DeepEBV was trained and tested using the data from the dsVIS database. The results showed that DeepEBV with EBV integration sequences plus Repeat peaks and 2-fold data augmentation performed the best on the training dataset. Furthermore, the performance of the model was validated in an independent dataset. In addition, the motifs of DNA-binding proteins could influence the selection preference of viral insertional mutagenesis. Furthermore, the results showed that DeepEBV can predict EBV integration hotspot genes accurately. In summary, DeepEBV is a robust, accurate and explainable deep learning model, providing novel insights into EBV integration preferences and mechanisms. AVAILABILITYAND IMPLEMENTATION: DeepEBV is available as open-source software and can be downloaded from https://github.com/JiuxingLiang/DeepEBV.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DeepHPV: a deep learning model to predict human papillomavirus integration sites.

Human papillomavirus (HPV) integrating into human genome is the main cause of cervical carcinogenesis. HPV integration selection preference shows strong dependence on local genomic environment. Due to this theory, it is possible to predict HPV integration sites. However, a published bioinformatic tool is not available to date. Thus, we developed an attention-based deep learning model DeepHPV to predict HPV integration sites by learning environment features automatically. In total, 3608 known HPV integration sites were applied to train the model, and 584 reviewed HPV integration sites were used as the testing dataset. DeepHPV showed an area under the receiver-operating characteristic (AUROC) of 0.6336 and an area under the precision recall (AUPR) of 0.5670. Adding RepeatMasker and TCGA Pan Cancer peaks improved the model performance to 0.8464 and 0.8501 in AUROC and 0.7985 and 0.8106 in AUPR, respectively. Next, we tested these trained models on independent database VISDB and found the model adding TCGA Pan Cancer performed better (AUROC: 0.7175, AUPR: 0.6284) than the model adding RepeatMasker peaks (AUROC: 0.6102, AUPR: 0.5577). Moreover, we introduced attention mechanism in DeepHPV and enriched the transcription factor binding sites including BHLHA15, CHR, COUP-TFII, DMRTA2, E2A, HIC1, INR, NPAS, Nr5a2, RARa, SCL, Snail1, Sox10, Sox3, Sox4, Sox6, STAT6, Tbet, Tbx5, TEAD, Tgif2, ZNF189, ZNF416 near attention intensive sites. Together, DeepHPV is a robust and explainable deep learning model, providing new insights into HPV integration preference and mechanism. Availability: DeepHPV is available as an open-source software and can be downloaded from https://github.com/JiuxingLiang/DeepHPV.git, Contact: huzheng1998@163.com, liangjiuxing@m.scnu.edu.cn, lizheyzy@163.com.

An effective vaginal gel to deliver CRISPR/Cas9 system encapsulated in poly (ß-amino ester) nanoparticles for vaginal gene therapy.

BACKGROUND: Gene therapy has held promises for treating specific genetic diseases. However, the key to clinical application depends on effective gene delivery. METHODS: Using a large animal model, we developed two pharmaceutical formulations for gene delivery in the pigs' vagina, which were made up of poly (ß-amino ester) (PBAE)-plasmid polyplex nanoparticles (NPs) based two gel materials, modified montmorillonite (mMMT) and hectorite (HTT). FINDINGS: By conducting flow cytometry of the cervical cells, we found that PBAE-GFP-NPs-mMMT gel was more efficient than PBAE-GFP-NPs-HTT gel in delivering exogenous DNA intravaginally. Next, we designed specific CRISPR/SpCas9 sgRNAs targeting porcine endogenous retroviruses (PERVs) and evaluated the genome editing efficacy in vivo. We discovered that PERV copy number in vaginal epithelium could be significantly reduced by the local delivery of the PBAE-SpCas9/sgRNA NPs-mMMT gel. Comparable genome editing results were also obtained by high-fidelity version of SpCas9, SpCas9-HF1 and eSpCas9, in the mMMT gel. Further, we confirmed that the expression of topically delivered SpCas9 was limited to the vagina/cervix and did not diffuse to nearby organs, which was relatively safe with low toxicity. INTERPRETATION: Our data suggested that the PBAE-NPs mMMT vaginal gel is an effective preparation for local gene therapy, yielding insights into novel therapeutic approaches to sexually transmitted disease in the genital tract. FUNDING: This work was supported by the National Science and Technology Major Project of the Ministry of science and technology of China (No. 2018ZX10301402); the National Natural Science Foundation of China (81761148025, 81871473 and 81402158); Guangzhou Science and Technology Programme (No. 201704020093); National Ten Thousand Plan-Young Top Talents of China, Fundamental Research Funds for the Central Universities (17ykzd15 and 19ykyjs07); Three Big Constructions-Supercomputing Application Cultivation Projects sponsored by National Supercomputer Center In Guangzhou; the National Research FFoundation (NRF) South Africa under BRICS Multilateral Joint Call for Proposals; grant 17-54-80078 from the Russian Foundation for Basic Research.

Endovascular treatment for ischemic stroke beyond the time window: A meta-analysis.

Currently, endovascular treatment has been proven to be effective when conducted within 6 hours of symptom onset. However, when patients have symptoms for more than 6 hours, have a daytime-unwitnessed stroke (DUS) or wake up with a stroke (wake-up stroke, WUS), the safety and efficacy of endovascular treatment need to be further elucidated. Therefore, we performed a systematic review and meta-analysis to compare the clinical outcomes of endovascular treatment in patients with ischemic stroke beyond the time window with that ≤6 hours. PubMed, EMBASE, and Ovid MEDLINE were searched from inception to November 2018. The following outcomes were evaluated by a random-effects model: efficacy outcomes, that is, functional independence and successful recanalization, and safety outcomes, that is, symptomatic intracranial hemorrhage and mortality. Subgroup analyses were also performed to examine whether patient or study characteristics were associated with the outcomes. Nine observational studies, including 5192 patients (1414 patients with extended time windows [ETWs]; 3778 patients ≤6 hours), were eligible for analysis. The overall analysis demonstrated that the functional independence was worse in patients with ETWs vs those ≤6 hours (OR, 0.78; 95% CI, 0.68-0.90, P = .0006). However, subgroup analysis showed that there was no significant difference in functional independence between the two groups when patients were selected for a perfusion mismatch by imaging (OR, 1.00; 95% CI, 0.70-1.43, P = 1.000). Therefore, compared with a window ≤6 hours, endovascular treatment with ETWs for ischemic stroke may not result in poor outcomes when patients are typically selected by perfusion techniques.

Risk stratification of cervical lesions using capture sequencing and machine learning method based on HPV and human integrated genomic profiles.

From initial human papillomavirus (HPV) infection and precursor stages, the development of cervical cancer takes decades. High-sensitivity HPV DNA testing is currently recommended as primary screening method for cervical cancer, whereas better triage methodologies are encouraged to provide accurate risk management for HPV-positive women. Given that virus-driven genomic variation accumulates during cervical carcinogenesis, we designed a 39 Mb custom capture panel targeting 17 HPV types and 522 mutant genes related to cervical cancer. Using capture-based next-generation sequencing, HPV integration status, somatic mutation and copy number variation were analyzed on 34 paired samples, including 10 cases of HPV infection (HPV+), 10 cases of cervical intraepithelial neoplasia (CIN) grade and 14 cases of CIN2+ (CIN2: n = 1; CIN2-3: n = 3; CIN3: n = 9; squamous cell carcinoma: n = 1). Finally, the machine learning algorithm (Random Forest) was applied to build the risk stratification model for cervical precursor lesions based on CIN2+ enriched biomarkers. Generally, HPV integration events (11 in HPV+, 25 in CIN1 and 56 in CIN2+), non-synonymous mutations (2 in CIN1, 12 in CIN2+) and copy number variations (19.1 in HPV+, 29.4 in CIN1 and 127 in CIN2+) increased from HPV+ to CIN2+. Interestingly, 'common' deletion of mitochondrial chromosome was significantly observed in CIN2+ (P = 0.009). Together, CIN2+ enriched biomarkers, classified as HPV information, mutation, amplification, deletion and mitochondrial change, successfully predicted CIN2+ with average accuracy probability score of 0.814, and amplification and deletion ranked as the most important features. Our custom capture sequencing combined with machine learning method effectively stratified the risk of cervical lesions and provided valuable integrated triage strategies.

Development of microsatellite markers for Eurya acuminatissima (Theaceae).

PREMISE OF THE STUDY: Sixteen microsatellite markers were developed to study the fine-scale spatial genetic structure of Eurya acuminatissima, a dioecious tree species of Theaceae endemic to southern China. METHODS AND RESULTS: A total of 30 primer pairs were initially designed and tested on the basis of the transcriptome data of E. acuminatissima, of which 16 were successfully amplified and showed clear polymorphism. For these microsatellites, one to 17 alleles per locus were identified. The observed and expected heterozygosities ranged from 0 to 1.000 and 0 to 0.903, respectively. CONCLUSIONS: The microsatellite markers described here can be used to study genetic diversity and spatial genetic structure of E. acuminatissima. Furthermore, all loci were successfully cross-amplified in a related species, E. auriformis.

Chloroplast and mitochondrial microsatellites for Millettia pinnata (Fabaceae) and cross-amplification in related species.

PREMISE OF THE STUDY: Chloroplast and mitochondrial microsatellites were identified to study the population genetics of Millettia pinnata (Fabaceae). METHODS AND RESULTS: Based on publicly available plastid genome sequence data of M. pinnata, 42 primer pairs were developed, of which 17 displayed polymorphisms across 89 individuals from four populations. For chloroplast loci, two to six alleles were recovered and the unbiased haploid diversity per locus ranged from 0.391 to 0.857. For mitochondrial loci, two to four alleles were recovered and the unbiased haploid diversity ranged from 0.264 to 0.740. Sixteen of the 17 screened markers could be successfully amplified in the related species M. pulchra. CONCLUSIONS: The 17 microsatellite markers developed here exhibited variation in M. pinnata and 16 presented transferability in the related species M. pulchra, suggesting that these markers will be valuable for genetic studies across M. pinnata and its related species.

Effect of WC/Co coherency phase boundaries on Fracture toughness of the nanocrystalline cemented carbides.

The effect of coherency WC/Co phase boundaries on the fracture toughness of the nanocrystalline WC-Co cemented carbides is studied by MD simulation method. The simulation results show that the nanocrystalline WC-Co cemented carbides with coherency WC/Co phase boundaries has higher fracture toughness than that without coherency WC/Co phase boundaries. Moreover, the mechanism of why coherency WC/Co phase boundaries can improve the fracture toughness of the nanocrystalline cemented carbides is also investigated. It is found the fact that the separation energy of the coherent WC/Co phase boundary is larger than that of the incoherent WC/Co phase boundaries is the main reason for this excellent mechanical property.

Development of EST-SSR markers in Barringtonia racemosa (Lecythidaceae) and cross-amplification in related species.

PREMISE OF THE STUDY: Microsatellite markers were identified and characterized to study the genetic diversity and structure of Barringtonia racemosa (Lecythidaceae). METHODS AND RESULTS: Based on the transcriptome data of B. racemosa, 30 primer pairs were initially designed and tested, of which 15 were successfully amplified and displayed clear polymorphisms across the 43 individuals from three distant populations tested in the study. The results showed that the number of alleles per locus ranged from two to seven and the expected heterozygosity and observed heterozygosity per locus varied from 0 to 0.772 and from 0 to 0.933, respectively. CONCLUSIONS: The expressed sequence tag-simple sequence repeat (EST-SSR) markers described here will be useful for studying genetic diversity and structure of B. racemosa. Furthermore, all loci were successfully cross-amplified in B. asiatica and B. acutangula and will be of great value for genetic studies across this genus.

A Free-Standing Sulfur/Nitrogen-Doped Carbon Nanotube Electrode for High-Performance Lithium/Sulfur Batteries.

A free-standing sulfur/nitrogen-doped carbon nanotube (S/N-CNT) composite prepared via a simple solution method was first studied as a cathode material for lithium/sulfur batteries. By taking advantage of the self-weaving behavior of N-CNT, binders and current collectors are rendered unnecessary in the cathode, thereby simplifying its manufacturing and increasing the sulfur weight ratio in the electrode. Transmission electronic microscopy showed the formation of a highly developed core-shell tubular structure consisting of S/N-CNT composite with uniform sulfur coating on the surface of N-CNT. As a core in the composite, the N-CNT with N functionalization provides a highly conductive and mechanically flexible framework, enhancing the electronic conductivity and consequently the rate capability of the material.

Development of microsatellite markers for Carallia brachiata (Rhizophoraceae).

PREMISE OF THE STUDY: Microsatellite markers were developed for Carallia brachiata to assess the genetic diversity and structure of this terrestrial species of the Rhizophoraceae. METHODS AND RESULTS: Based on transcriptome data for C. brachiata, 40 primer pairs were initially designed and tested, of which 18 were successfully amplified and 11 were polymorphic. For these microsatellites, one to three alleles per locus were identified. The observed and expected heterozygosities ranged from 0 to 0.727 and 0 to 0.520, respectively. In addition, all primers were successfully amplified in two congeners: C. pectinifolia and C. garciniifolia. CONCLUSIONS: The microsatellite markers described here will be useful in population genetic studies of C. brachiata and related species, suggesting that developing microsatellite markers from next-generation sequencing data can be efficient for genetic studies across this genus.

Mechanism for direct graphite-to-diamond phase transition.

Using classical molecular dynamics with a more reliable reactive LCBOPII potential, we have performed a detailed study on the direct graphite-to-diamond phase transition. Our results reveal a new so-called "wave-like buckling and slipping" mechanism, which controls the transformation from hexagonal graphite to cubic diamond. Based on this mechanism, we have explained how polycrystalline cubic diamond is converted from hexagonal graphite, and demonstrated that the initial interlayer distance of compressed hexagonal graphite play a key role to determine the grain size of cubic diamond. These results can broaden our understanding of the high pressure graphite-to-diamond phase transition.