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  • ISSN 1674-8301
  • CN 32-1810/R
Volume 35 Issue 2
Mar.  2021
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Article Contents
Abstract
Introduction
Materials and methods
Results
Discussion
References
Related Articles
Song Jun, Zhang Jifeng, Xu Jie, Garcia-Barrio Minerva, Chen Y. Eugene, Yang Dongshan. Genome engineering technologies in rabbits[J]. The Journal of Biomedical Research, 2021, 35(2): 135-147. DOI: 10.7555/JBR.34.20190133
Citation: Song Jun, Zhang Jifeng, Xu Jie, Garcia-Barrio Minerva, Chen Y. Eugene, Yang Dongshan. Genome engineering technologies in rabbits[J]. The Journal of Biomedical Research, 2021, 35(2): 135-147. DOI: 10.7555/JBR.34.20190133
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Genome engineering technologies in rabbits

  • Center for Advanced Models for Translational Sciences and Therapeutics, University of Michigan Medical Center, Ann Arbor, MI 48109, USA

More Information
  • Corresponding author:

    Y. Eugene Chen and Dongshan Yang, Center for Advanced Models for Translational Sciences and Therapeutics, University of Michigan Medical Center, 2800 Plymouth Road, Ann Arbor, MI 48109, USA. Tel/Fax: +1-734-647-5742/+1-734-763-7097, E-mails: echenum@umich.edu and doyang@umich.edu

  • Received Date: October 21, 2019
  • Accepted Date: April 28, 2020
  • Available Online: June 11, 2020
    Graphical Abstract
    • Abstract
  • The rabbit has been recognized as a valuable model in various biomedical and biological research fields because of its intermediate size and phylogenetic proximity to primates. However, the technology for precise genome manipulations in rabbit has been stalled for decades, severely limiting its applications in biomedical research. Novel genome editing technologies, especially CRISPR/Cas9, have remarkably enhanced precise genome manipulation in rabbits, and shown their superiority and promise for generating rabbit models of human genetic diseases. In this review, we summarize the brief history of transgenic rabbit technology and the development of novel genome editing technologies in rabbits.
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  • Ovarian cancer is the deadliest cancer of the female reproductive system[1], and epithelial ovarian cancer (EOC) is the most common subtype, accounting for 90% of ovarian cancer cases. EOC has a high incidence with a high mortality rate[2]. Although great efforts have been made to treat EOC patients with cytoreductive surgery and chemotherapy as well as targeted therapies, EOC still has high rates of recurrence with a poor prognosis[3]. As the pathogenesis of EOC remains unclear, it is urgent to explore the pathogenesis of this disease to identify additional targets for the treatment of EOC.

    With the development of human genome sequencing technologies, various nonprotein-coding transcripts have been discovered. Those transcripts with more than 200 nucleotides in length are termed long noncoding RNAs (lncRNAs)[4]. It has been widely reported that lncRNAs participate in multiple biological processes, including the regulation of transcriptional and posttranscriptional gene expression. Antisense lncRNAs originating from complementary strands of the protein-coding genes have been reported to participate in the pathogenesis of various diseases, including cancer[5]. For example, lncRNA HIF1A-AS1 induced gemcitabine resistance in patients with pancreatic cancer by upregulating hypoxia-inducible factor-1 alpha (HIF-1α) expression and enhancing glycolysis[6]. LncRNA TRAF3IP2-AS1 suppressed the progression of NONO-TFE3 translocation in renal cell carcinoma by promoting the PARP1 mRNA decay[7]. LncRNA NR2F1-AS1 regulated NR2F1 translation and ΔNp63 transcription to induce lung metastatic dormancy in breast cancer patients[8].

    LncRNA IDH1 antisense RNA 1 (IDH1-AS1) was first discovered to be correlated with the functions of HIF-1α and c-Myc through IDH1 to regulate the Warburg effect, an essential metabolic mechanism for providing energy to maintain the high proliferation of cancer cells[9]. IDH1-AS1 has also been reported to promote cell proliferation and suppress apoptosis of prostate cancer cells via autophagy induced by ATG5[10]. Additionally, IDH1-AS1 has been demonstrated to inhibit cell proliferation and tumorigenesis in glioma by altering IDH1 enzymatic activities[11]. Because the role of IDH1-AS1 in EOC has not been reported to date, we conducted a strategy combining bioinformatics analysis and experiments to investigate whether IDH1-AS1 participates in EOC development, which may assist in identifying new targets for the treatment of EOC.

    Cell culture

    The human EOC cell lines (3AO, A2780, and OVCAR3) were purchased from Shanghai Mingjin Biotech Co., Ltd. (Shanghai, China). SKOV3, CAOV3, and HEK293T cells were obtained from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). The normal ovarian epithelial cell line IOSE-386 was provided by Prof. Jin Zhu (General Hospital of Eastern Theater Command, Nanjing, Jiangsu, China). CAOV3, A2780, HEK293T, and IOSE-386 cells were maintained in Dulbecco's modified Eagle's medium (DMEM; KeyGEN, Jiangsu, China). Specifically, 3AO and OVCAR3 cells were incubated in RPMI-1640 medium (KeyGEN), and SKOV3 cells were cultured in McCoy's 5A medium (KeyGEN). Each culture medium contained 10% fetal bovine serum (FBS; Thermo Fisher Scientific, Waltham, MA, USA), except for the medium used to culture OVCAR3 cells, which contained 20% FBS.

    Transient transfection

    Lipofectamine 3000 transfection reagent (Invitrogen, Carlsbad, CA, USA) was utilized to transfect cells with short interfering RNAs (siRNAs), plasmids, microRNA (miRNA) mimics, or miRNA inhibitors according to the manufacturer's instructions. The siRNAs targeting IDH1-AS1, including si-IDH1-AS1 (1), si-IDH1-AS1 (2), and si-IDH1-AS1 (3), as well as negative control siRNA (si-NC), were purchased from RiboBio Co., Ltd. (Cat. Nos. stB0019366A, stB0019366B, stB0019366C, and siN0000001-1-5, Guangzhou, Guangdong, China). The IDH1-AS1-overexpressing plasmid (pc-IDH1-AS1) and the negative empty vector plasmid (pc-DNA3.1) were constructed by Genecreate Biological Engineering Co., Ltd. (Wuhan, Hubei, China). The miR-518c-5p mimic, miR-518c-5p inhibitor, NC mimic, and NC inhibitor were obtained from RiboBio Co., Ltd. (Cat. Nos. miR10002847, miR20002847, miR1N0000001-1-5, and miR2N000001-1-5).

    Stable transfection

    We obtained the IDH1-AS1-overexpressing (LV-IDH1-AS1) and negative control (LV-NC) recombinant lentiviruses from GenePharma Co., Ltd. (Shanghai, China). SKOV3 cells were seeded into a 24-well plate and incubated overnight, and the cells were transfected, when the cellular confluence reached 30%. The original medium was replaced with 500 μL serum-containing medium with 10% lentivirus fluid, and cells were cultured in the lentiviral solution for 24 h. After the lentivirus-free medium was continuously incubated for 48 h, a concentration of 1 μg/mL puromycin was added to the medium to obtain stably transfected cells.

    RNA extraction and quantitative real-time PCR (qPCR)

    Tissue and cell RNAs were extracted according to the instruction of Thermo Scientific GeneJET RNA Purification Kit (Thermo Fisher Scientific), and RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific) was used to obtain cDNA. The PARIS Kit protein and RNA isolation system (Invitrogen, Carlsbad, CA, USA) was utilized to divide cellular RNA into cytoplasmic and nuclear components. The qPCR assays were performed using SYBR Green dye (Thermo Fisher Scientific) and the following thermocycler program: 5 min at 95 ℃; 15 s at 95 ℃ for 40 cycles; and 1 min at 60 ℃. The relative expression levels of different genes were calculated using the 2−ΔΔCT method. ACTB, GAPDH, and U6 were utilized as internal controls. The primer sequences are listed in Table 1. miRNA-specific stem-loop U6 primers were constructed from RiboBio Co., Ltd. (Cat. #MQPS0000002-1-100).

    Table  1.  Primer sequences for quantitative real-time PCR
    GenesForward (5′-3′)Reverse (5′-3′)
    IDH1-AS1 GTCATGGAGGTGTCTGTGTTAG GTCACTCTGCGGATGTTTCT
    RBM47 TGATGGACTTTGACGGCAAGA GGGCGGATCTCGTAGTTGTT
    ZNF621 CTCCAAACAACTTGGCCTCAG GAATGGAAACGCTACCAGAGAA
    CASTOR2 GCCACCACCCTCATAGATGT AGGAGGTCACTGGGGAACTT
    U6 CTCGCTTCGGCAGCACA AACGCTTCACGAATTTGCGT
    ACTB TCCCTGGAGAAGAGCTACGA AGCACTGTGTTGGCGTACAG
    GAPDH CAATGACCCCTTCATTGACC TTGATTTTGGAGGGATCTCG
     | Show Table
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    Cell counting kit-8 (CCK-8) assay

    After cell transfection for 24 h, approximately 2000 to 3000 cells in 100 μL of medium were added to each well of a 96-well plate. After allowing the cells to adhere for 4 to 6 h, 10 µL of CCK-8 solution (KeyGEN) was added to each well of the plate followed by incubation for 2 h. The absorbance was read at 450 nm using a BioTek Synergy H4 (BioTek, Winooski, Vermont, USA), which was considered the 0-h time point. The same process was performed on additional cells at the same time in the next three days, representing the 24-h, 48-h, and 72-h time points.

    Colony formation assay

    SKOV3 and A2780 cells were seeded and transfected with siRNAs, overexpression plasmid, or miRNA mimics in six-well plates. After the cells were digested and counted, 2000 to 3000 cells were re-cultured in new six-well plates. The cells were allowed to adhere and grow for 7 days to 2 weeks. Cells were then fixed with 1 mL of paraformaldehyde for 30 to 60 min and stained with crystal violet solution for approximately 30 min. The number of colonies was photographed and counted using ImageJ software (National Institutes of Health, Bethesda, MD, USA).

    EdU assay

    SKOV3 cells (1.5 × 104) or A2780 cells (3 × 104) were seeded in each well of a 96-well plate and cultured for 24 h. Cell-Light EdU DNA Apollo In Vitro Kit (RiboBio) was applied to perform the EdU assay. The cells were labeled with 50 mmol/L EdU solution for 2 h, and stained with Apollo and Hoechst 33342 Dye Solution (RiboBio) in sequence after been fixed with 4% paraformaldehyde. Axio Observer D1 fluorescence microscope (Carl Zeiss, Jena, Germany) was used to take photographs of the stained cells.

    Transwell assay

    Medium (600 μL) containing 20% FBS was added to the lower chamber of the Transwell (Corning Inc., Corning, NY, USA), and 200 μL of serum-free medium was added to the upper chamber. SKOV3 cells (3 × 104) or A2780 cells (5 × 104) were seeded into Transwell chambers without or with Matrigel (BD Biosciences, San Jose, CA, USA) (60 μL/well; medium/Matrigel ratio, 7∶1) to conduct migration or invasion assays, respectively. Following 24 to 72 h of cultivation, the chamber was fixed with 4% paraformaldehyde (BioSharp, Hefei, Anhui, China) and then stained with 0.1% crystal violet solution (BioSharp). Cells were wiped away from the upper surface of the chamber using a cotton swab, and images of the lower surface of the chamber were acquired for randomly selected areas using an Axio Observer D1 fluorescence microscope (Carl Zeiss).

    Wound-healing assay

    SKOV3 and A2780 cells were cultured in six-well plates with medium containing 10% FBS. When the cellular confluence reached more than 95%, horizontal lines were made on the backside of the plate, and longitudinal lines were scratched in the cell bed using 200 μL pipette tips. The FBS-containing medium was then replaced with a serum-free medium. Images were acquired at 0, 24, and 48 h after the wound was generated using an EVOS XL Core digital microscope (Thermo Fisher Scientific) and analyzed by ImageJ software.

    Xenografts in nude mice

    Ten female BALB/c nude mice aged 6 weeks were purchased from the Model Animal Research Center of Nanjing University (Nanjing, Jiangsu, China). The nude mice were kept in a specific pathogen-free environment and randomly and equally divided into the LV-IDH1-AS1 group and the LV-NC group (n = 5 for each group). SKOV3 cells (9 × 106) transfected with LV-IDH1-AS1 or LV-NC in 200 μL of PBS solution were subcutaneously injected into the left axilla of the LV-IDH1-AS1 group or the LV-NC group nude mice, respectively. The tumor size was measured every 2 to 3 days using manual calipers, and the tumor volume was calculated according to the following formula: Tumor volume = 0.5 × length × width2. The tumors were resected 25 days after injection of cells. All animal protocols were approved by the Animal Ethical and Welfare Committee of Nanjing Medical University (Approval No. IACUC-1911022).

    Dual-luciferase reporter assay

    Bioinformatics tools were utilized to predict the binding site between IDH1-AS1 and miR-518c-5p. The wild type (WT) and mutant type (MT) plasmids of IDH1-AS1 were inserted into the pmirGLO plasmid. A total of 250 ng of pmirGLO-IDH1-AS1-WT or pmirGLO-IDH1-AS1-MT and 250 ng of miR-518c-5p mimics or NC mimics were cotransfected into HEK293T cells with 2.5 μL of Lipofectamine 3000 and 0.5 μL of P3000 (Invitrogen) for 48 h. Luciferase activities of Firefly and Renilla were measured using the Dual-Luciferase Reporter Gene Assay Kit (Promega, Madison, WI, USA) and detected by the GloMax 96-well fluorescence detector (Promega) according to the manufacturer's instructions. The ratio of firefly to Renilla luciferase activity was calculated as the relative luciferase activity. To verify the targeting relevance between miR-518c-5p and the 3′ UTR of RBM47, the same procedure was used but with different plasmids, respectively.

    Western blotting analysis

    Total protein was isolated by lysing cells with RIPA lysis buffer (Servicebio, Wuhan, Hubei, China), and the protein concentration was measured using a BCA Protein Assay Kit (Beyotime, Shanghai, China). Protein samples were separated by SDS-PAGE and transferred onto PVDF membranes (Millipore, Boston, MA, USA). After blocking the membranes with 5% skim milk, the membranes were incubated with the following primary antibodies at 4 ℃ overnight: anti-β-actin antibody (1∶2000 dilution; Cat. No. GB15003, Servicebio) and anti-RBM47 antibody (1∶5000 dilution; Cat. No. ab167164, Abcam, Cambridge, UK). The membranes were then incubated with the secondary antibody for 2 h at 37 ℃. Protein bands were visualized by using the FluuroChem M imaging system (Protein Simple Inc., San Jose, CA, USA) according to the manufacturer's instructions.

    Immunohistochemistry

    Tissue specimens were paraffin-embedded and sliced into sections that were dewaxed with xylene and dehydrated with gradient alcohol. The slices were heated in citrate buffer, followed by blocking with 3% H2O2, and sealed with goat serum. The sections were incubated with primary antibody overnight at 4 ℃, including anti-RBM47 antibody (1∶100 dilution; Cat. No. ab167164, Abcam), anti-Ki67 antibody (1∶300 dilution; Cat. No. NB500-170, Novus Biologicals, Littleton, CO, USA), and then incubated with HRP-labeled secondary antibody (1∶500 dilution; Cat. No. abs20040ss, Absin Bioscience, Shanghai, China). The slices were treated with 3,39-diaminobenzidine tetrahydrochloride reagent to develop color, and re-stained with hematoxylin. Each section was photographed under the microscope (Carl Zeiss) at 400× magnification. Integrated optical density summation of RRBM47 and Ki67 protein expression was calculated by Image-Pro Plus software (Media Cybernetics, Silver Spring, MD, USA).

    Bioinformatics analysis

    The association between IDH1-AS1 and the prognosis of EOC patients was analyzed using the GEPIA database (http://gepia.cancer-pku.cn). The clinical data of EOC patients were obtained from The Cancer Genome Atlas (TCGA) database (http://cancergenome.nih.gov), and the IDH1-AS1 expression data of EOC patients were acquired from the Atlas of non-coding RNA in Cancer (TANRIC) database (http://ibl.mdanderson.org/tanric/_design/basic/index.html). The downstream miRNA targets of IDH1-AS1 were searched from the RNA22 (https://cm.jefferson.edu/rna22/), miRDB (http://www.mirdb.org/), and LncRNASNP2 (http://bioinfo.life.hust.edu.cn/lncRNASNP/) databases. The downstream gene targets of miR-518c-5p were screened from the miRWalk (http://mirwalk.umm.uni-heidelberg.de/) database. RNAHybrid (v2.2) software (https://bibiserv.cebitec.uni-bielefeld.de/rnahybrid/) was used to predict binding sites between IDH1-AS1 and miR-518c-5p as well as between miR-518c-5p and the 3′ UTR of RBM47.

    Statistical analysis

    The data of cellular experiments were presented as the mean ± standard deviation of three independent experiments, and the data of animal tests were presented as mean ± standard error of the mean. The Chi-square (χ2) test was applied to compare the rates (%) of the two groups. The Cox proportional hazards regression model was used to analyze the association between clinical data and survival of EOC patients. Two-tailed Student's t-test and two-way analysis of variance (ANOVA) followed by Dunnett's tests were applied to compare the data between two or more groups by using GraphPad Prism 7 (GraphPad Software, La Jolla, CA, USA). P < 0.05 was considered statistically significant.

    IDH1-AS1 was decreased in EOC cells and associated with the prognosis of EOC

    To identify the potential effects of IDH1-AS1 on EOC, we first investigated the expression levels of IDH1-AS1 in EOC cell lines. The abundance of IDH1-AS1 was lower in EOC cells (OVCAR3, SKOV3, 3AO, A2780, and CAOV3) than in normal ovarian epithelial cells (IOSE386) (Fig. 1A). Because SKOV3 and A2780 cells were the commonly used EOC cells, we selected them for further investigation. We next detected IDH1-AS1 expression in EOC cells from the patients included in the GEPIA, TCGA, and TANRIC databases. High IDH1-AS1 expression was associated with an increased overall survival (OS) and disease-free survival in EOC patients according to the GEPIA database (Fig. 1B). Furthermore, we downloaded clinical information of EOC patients from TCGA and the expression data of IDH1-AS1 from the TANRIC database. Patients with incomplete primary clinical data or lacking IDH1-AS1 expression data were excluded. A total of 410 EOC patients were included in this analysis. The IDH1-AS1 expression levels were not associated with the Federation International of Gynecology and Obstetrics (FIGO) stage, grade, lymph node invasion or neoplasm status of EOC, but with age and race (Table 2). According to univariate and multivariate Cox regression analyses, IDH1-AS1 expression level may be an independent predictor for OS of EOC patients (Tables 3 and 4). Taken together, these results indicated that the expression levels of IDH1-AS1 were decreased in EOC cells and that low IDH1-AS1 expression was associated with a poor prognosis in EOC patients.

    Figure  1.  IDH1-AS1 was downregulated in EOC cells and was associated with the prognosis of EOC.
    A: Relative expression of IDH1-AS1 in one normal ovarian epithelial cell line and five EOC cell lines was measured by qPCR assay. ACTB was used as an internal reference gene. B: Correlation between the level of IDH1-AS1 and the prognosis of EOC patients according to the GEPIA database. The low expression group and high expression group were defined according to the median of IDH1-AS1 level. Data were obtained from three independent experiments. Values are presented as mean ± standard deviation. Two-tailed Student's t-test was performed to indicate significance. **P < 0.01 and ***P < 0.001. Abbreviations: EOC, epithelial ovarian cancer; qPCR, quantitative real-time PCR; GEPIA, Gene Expression Profiling Interactive Analysis.
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    Table  2.  Correlation between IDH1-AS1 expression and clinicopathological features in patients with epithelial ovarian cancer
    Clinicopathological
    features    		Casesa (n)IDH1-AS1
    expression    		P-valueb
    LowcHighc
    Age (years) 409 0.042*
    　<60 216 98 (45.4) 118 (54.6)
    　≥60 193 107 (55.4) 86 (44.6)
    Race 397 0.022*
    　White 360 188 (52.2) 172 (47.8)
    　Others 37 12 (33.4) 25 (66.6)
    Neoplasm statusd 358 0.395
    　With tumor 266 138 (51.9) 128 (48.1)
    　Tumor free 92 43 (46.7) 49 (53.3)
    Site 384 0.726
    　Bilateral 285 141 (49.5) 144 (50.5)
    　Unilateral 99 51 (51.5) 48 (48.5)
    Stagee 407 0.392
    　Ⅱ 21 11 (52.4) 10 (47.6)
    　Ⅲ 325 156 (48.0) 169 (52.0)
    　Ⅳ 61 35 (57.4) 26 (42.6)
    Grade 410 0.668
    　G1/G2/GXf 57 30 (52.6) 27 (47.4)
    　G3/G4 353 175 (49.6) 178 (50.4)
    Invasion 158 0.314
    　Yes 104 55 (52.9) 49 (47.1)
    　No 54 24 (44.4) 30 (55.6)
    Overall status 410 0.221
    　Deceased 256 134 (52.3) 122 (47.7)
    　Alive 154 71 (46.1) 83 (53.9)
    aThe data for "cases" in the second column represent the actual patient cases for statistics, which might be less than the total patient cases because of the missing data in the database. bP-values were determined by using the Chi-square test. *P < 0.05. cThe low expression group and high expression group were defined according to the median of IDH1-AS1 level.dNeoplasm status indicates the state or condition of an individual's tumor at a specific time, including with tumor and tumor free. ''Tumor free'' means the tumor has been removed while ''With tumor'' refers to the presence of a tumor.eStage was classified according to the Federation International of Gynecology and Obstetrics (FIGO) criterion.fGX indicates the undefined grade. The case number of G1, G2, G3, G4 and GX were 1, 47, 352, 1, and 9, respectively.
     | Show Table
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    Table  3.  Univariate and multivariate Cox regression analyses of overall survival in patients with epithelial ovarian cancer
    VariablesaOverall survival
    Univariate analysisMultivariate analysis
    nHR (95% CI)PnHR (95% CI)P
    Age (years, <60 vs. ≥60) 409 1.021 (1.010–1.033) <0.001* 409 1.017 (1.005–1.030) 0.007*
    Race (white vs. others) 397 1.626 (1.004–2.635) 0.048* 397 1.514 (0.916–2.504) 0.106
    Neoplasm statusb (with tumor vs. tumor free) 358 0.123 (0.070–0.216) <0.001* 358 0.129 (0.073–0.227) <0.001*
    Site (bilateral vs. unilateral) 384 1.337 (0.897–1.993) 0.154
    Stagec (Ⅱ vs. Ⅲ & Ⅳ) 407 1.276 (0.971–1.677) 0.080
    Grade (G1/G2/GX vs. G3/G4) 410 1.109 (0.781–1.574) 0.562
    Invasion (yes vs. no) 158 0.855 (0.528–1.385) 0.525
    IDH1-AS1 expression (low vs. high) 410 0.729 (0.570–0.932) 0.012* 410 0.727 (0.555–0.952) 0.020*
    aThe first variable was the reference variable in each group. bNeoplasm Status indicates the state or condition of an individual's tumor at a specific time, including with tumor and tumor free. ''Tumor free'' means the tumor has been removed while ''With tumor'' refers to the presence of a tumor.cStage was classified according to the Federation International of Gynecology and Obstetrics (FIGO) criterion.P-values were determined by univariate and multivariate Cox regression analyses. When the factors with a P < 0.05 in the univariate analyses, they were subjected to multivariate analysis. *P < 0.05. Abbreviation: HR, hazard ratio; CI, confidence interval; GX, undefined grade.
     | Show Table
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    Table  4.  Univariate and multivariate Cox regression analyses of disease-free survival in patients with epithelial ovarian cancer
    Variables aDisease-free survival
    Univariate analysisMultivariate analysis
    nHR (95% CI)PnHR (95% CI)P
    Age (years, <60 vs. ≥60) 409 1.008 (0.996–1.019) 0.189
    Race (white vs. others) 397 1.291 (0.831–2.006) 0.255
    Neoplasm statusb (with tumor vs. tumor free) 358 0.161 (0.107–0.244) <0.001* 358 0.165 (0.109–0.250) <0.001*
    Site (bilateral vs. unilateral) 384 0.804 (0.597–1.083) 0.151
    Stagec (Ⅱ vs. Ⅲ &. Ⅳ) 407 1.309 (1.001–1.711) 0.049* 407 0.794 (0.617–1.022) 0.073
    Grade (G1/G2/GX vs. G3/G4) 410 1.156 (0.801–1.668) 0.438
    Invasion (yes vs. no) 158 1.019 (0.645–1.610) 0.934
    IDH1-AS1 expression (low vs. high) 410 0.812 (0.635–1.037) 0.095
    aThe first variable was the reference variable in each group. bNeoplasm Status indicates the state or condition of an individual's tumor at a specific time, including with tumor and tumor free. ''Tumor free'' means the tumor has been removed while ''With tumor'' refers to the presence of a tumor.cStage was classified according to the Federation International of Gynecology and Obstetrics (FIGO) criterion. P-values were determined by univariate and multivariate Cox regression analyses. When the factors with a P < 0.05 in the univariate analyses, they were subjected to multivariate analysis. *P < 0.05. Abbreviations: HR, hazard ratio; CI, confidence interval; GX, undefined grade.
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    IDH1-AS1 inhibited the proliferation of EOC cells in vitro

    Given the effect of IDH1-AS1 on the prognosis of EOC, we further investigated the influence of IDH1-AS1 on cellular proliferation, migration, and invasion by knocking down or overexpressing IDH1-AS1 in EOC cells with siRNAs or overexpressing plasmid, respectively (Fig. 2A and 2B). The CCK-8 assay results demonstrated that the downregulation of IDH1-AS1 promoted EOC cell viability, while the overexpression of IDH1-AS1 significantly suppressed EOC cell viability (Fig. 2C and 2D). Moreover, both the colony formation and the EdU assays were utilized to evaluate cell proliferation, and the trends were similar to those in the CCK-8 assays (Fig. 2E and 2F). Transwell assays and wound-healing assays indicated that IDH1-AS1 had no significant effect on the invasion and migration of EOC cells (Supplementary Fig. 1A and 1B, available online). Together, these results indicated that IDH1-AS1 inhibited EOC cell proliferation in vitro.

    Figure  2.  IDH1-AS1 inhibited the proliferation of EOC cells in vitro.
    A and B: Transfection efficiency of IDH1-AS1 siRNAs and overexpressing plasmid in SKOV3 and A2780 cells according to qPCR analysis. ACTB was used as an internal reference gene. C and D: SKOV3 and A2780 cell viability after transfection of IDH1-AS1 siRNAs and overexpressing plasmid according to CCK-8 assay. E and F: SKOV3 and A2780 cell proliferation after transfection of IDH1-AS1 siRNAs and overexpressing plasmid evaluated by colony formation assay and EdU assay. The proliferating cells were labeled with EdU (red), while cell nuclei were stained with Hoechst (blue). Scale bar: 100 μm. Data are presented as mean ± standard deviation from three independent experiments. Two-tailed Student's t-test was performed to indicate significance, except that statistical analysis for C was performed by two-way ANOVA followed by Dunnett's tests, and D was performed by two-way ANOVA. *P < 0.05, **P < 0.01, and ***P < 0.001. Abbreviations: EOC, epithelial ovarian cancer; siRNA, short interfering RNA; CCK-8, cell counting kit-8; EdU, 5-ethynyl-2′-deoxyuridine; ANOVA, analysis of variance.
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    IDH1-AS1 acted by sponging miR-518c-5p in EOC cells

    To investigate the mechanism of IDH1-AS1 in EOC cells, the nuclear and cytoplasmic RNA isolation assay was applied to define its cellular location. IDH1-AS1 was confirmed to be distributed mainly in the cytoplasm of EOC cells (Fig. 3A). The databases of RNA22, miRDB, and LncRNASNP2 were then utilized to screen downstream miRNA targets, which identified miR-518c-5p, miR-1301-5p, and miR-3907 (Fig. 3B). The number of consecutive binding sites between IDH1-AS1 and miR-518c-5p was predicted to be the largest among these miRNAs by RNAhybrid software (Fig. 3C), which indicated their greatest binding possibility. Dual-luciferase reporter analysis and qPCR assays were performed to verify the correlation between IDH1-AS1 and miR-518c-5p. The results showed that miR-518c-5p upregulation suppressed the luciferase activity of IDH1-AS1-WT but did not affect the luciferase activity of IDH1-AS1-MT (Fig. 3D). The expression level of miR-518c-5p was increased after IDH1-AS1 knockdown but decreased after IDH1-AS1 overexpression in EOC cells (Fig. 3E). Subsequently, transfection of miR-518c-5p mimic into SKOV3 and A2780 cells (Fig. 3F) promoted cell viability and colony formation in EOC cells (Fig. 3G and 3H). Rescue experiments of the EdU assay further indicated that the miR-518c-5p mimic reversed the proliferation inhibiting effect induced by overexpression of IDH1-AS1 in EOC cells (Fig. 3I). Thus, these findings suggest that IDH1-AS1 may serve as a suppressor by sponging miR-518c-5p in EOC cells.

    Figure  3.  IDH1-AS1 acted by sponging miR-518c-5p in EOC cells.
    A: Nuclear and cytoplasmic RNA isolation of IDH1-AS1 in SKOV3 and A2780 cells. B: The downstream three miRNAs of IDH1-AS1 were predicted from the RNA22, miRDB, and LncRNASNP2 databases. C: The binding sites between IDH1-AS1 and the three miRNAs were predicted by RNAhybrid (v2.2). D: The interaction between IDH1-AS1 and miR-518c-5p was verified by dual-luciferase reporter assay. E: The expression correlation between IDH1-AS1 and miR-518c-5p was confirmed by qPCR analysis. F: The transfection efficiency of the miR-518c-5p mimic in SKOV3 and A2780 cells was evaluated by qPCR analysis. Stem-loop U6 was used as an internal reference gene (E and F). G and H: Cell viability and proliferation of SKOV3 and A2780 cells after transfection of miR-518c-5p mimics according to CCK-8 assay and colony formation assay. I: Rescue experiment of EdU assay after cotransfection of the NC mimic or miR-518c-5p mimic and empty vector plasmid or IDH1-AS1 overexpressing plasmid in EOC cells. The bar represents 100 μm. Data were obtained from three independent experiments. Values are presented as mean ± standard deviation. Two-tailed Student's t-test was performed to indicate significance, except that statistical analysis for G, which was performed by two-way ANOVA. *P < 0.05, **P < 0.01, and ***P < 0.001. Abbreviations: ns, not significant; EOC, epithelial ovarian cancer; miRNA, microRNA; qPCR, quantitative real-time PCR; CCK-8, cell counting kit-8; EdU, 5-ethynyl-2′-deoxyuridine; ANOVA, analysis of variance.
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    IDH1-AS1 affected EOC cells by targeting the miR-518c-5p/RBM47 axis

    To identify the putative targets of miR-518c-5p, we used the miRWalk website, including the miRDB and miTarBase databases, and identified eight shared genes (Fig. 4A). Because previous studies have reported that RNA binding motif protein 47 (RBM47), zinc finger protein 621 (ZNF621), and cytosolic arginine sensor for mTORC1 subunit 2 (CASTOR2) function as tumor suppressors, we selected these genes for further verification. The qPCR analysis showed that only the mRNA level of RBM47 was significantly decreased after IDH1-AS1 knockdown in EOC cells (Fig. 4B). The mRNA expression of RBM47 was also inhibited after miR-518c-5p overexpression (Fig. 4C). Next, we predicted the binding sites between 3′ UTR of RBM47 and miR-518c-5p by the RNAhybrid software (Fig. 4D). A dual-luciferase reporter assay revealed that the luciferase activity of RBM47-WT was significantly decreased when cotransfected with the miR-518c-5p mimic, but this change did not occur in the luciferase activity of RBM47-MT (Fig. 4E). Furthermore, Western blotting analysis indicated the protein level of RBM47 was decreased after IDH1-AS1 suppression or miR-518c-5p overexpression, but increased after miR-518c-5p suppression in EOC cells (Fig. 4F). Furthermore, RBM47 overexpression (Fig. 4G) inhibited cell viability and colony formation in EOC cells (Fig. 4H and 4I). Rescue experiments of the EdU assay revealed that the RBM47 overexpressing plasmid counteracted the proliferation-promoting effect caused by the IDH1-AS1 knockdown in EOC cells (Fig. 4J). Taken together, these results demonstrate that IDH1-AS1 may inhibit the proliferation of EOC cells via the miR-518c-5p/RBM47 axis.

    Figure  4.  IDH1-AS1 affected EOC cells by targeting the miR-518c-5p/RBM47 axis.
    A: Selection of miR-518c-5p target genes from the miRWalk website by miRDB and miTarBase databases. Tumor suppressor genes were marked in red. B: Relative mRNA expressions of the selected three tumor suppressor genes were assessed by qPCR analysis after IDH1-AS1 siRNA transfection in SKOV3 and A2780 cells. C: Relative mRNA expression of RBM47 was evaluated by qPCR analysis after miR-518c-5p mimic transfection in SKOV3 and A2780 cells. D: The binding sites between RBM47 and miR-518c-5p were predicted by RNAhybrid (v2.2). E: The binding between RBM47 and miR-518c-5p was verified by dual-luciferase reporter assay. F: Western blotting analysis of the relative protein expression of RBM47 after transfection of IDH1-AS1 siRNA, miR-518c-5p mimic or miR-518c-5p inhibitor in SKOV3 and A2780 cells. G: qPCR analysis of the transfection efficiency of the RBM47 overexpressing plasmid in SKOV3 and A2780 cells. ACTB was used as an internal reference gene (B, C, and G). H and I: SKOV3 and A2780 cell viability and proliferation after transfection of RBM47 overexpressing plasmid according to CCK-8 assay and colony formation assay. J: Rescue experiment of EdU assay after cotransfection of empty vector plasmid or RBM47 overexpressing plasmid and NC siRNA or IDH1-AS1 siRNA in EOC cells. Scale bar: 100 μm. Data are presented as mean ± standard deviation from three independent experiments. Two-tailed Student's t-test was performed to indicate significance, except that statistical analysis for H, which was performed by two-way ANOVA. *P < 0.05, **P < 0.01, and ***P < 0.001. Abbreviations: ns, not significant; EOC, epithelial ovarian cancer; siRNA, short interfering RNA; CCK-8, cell counting kit-8; EdU, 5-ethynyl-2′-deoxyuridine; ANOVA, analysis of variance.
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    IDH1-AS1 suppressed tumor growth of EOC cells in vivo

    Considering the suppressive effects of IDH1-AS1 on EOC in vitro, we further investigated its function in vivo. The qPCR confirmed that the expression of IDH1-AS1 was significantly higher in SKOV3 cells transfected with LV-IDH1-AS1, compared with the control cells (Fig. 5A). There was no significant difference in the weight of nude mice after SKOV3 cell injection in the LV-NC group and LV-IDH1-AS1 group (Fig. 5B). The tumor growth curve showed that the tumor volume of nude mice was significantly lower in the LV-IDH1-AS1 group than in the control group (Fig. 5C). Subcutaneous tumors were dissected from nude mice after cells injection for 25 days (Fig. 5D), and the tumor weight was significantly lower in the LV-IDH1-AS1 group than in the control group (Fig. 5E). The qPCR also showed that the expression of miR-518c-5p was obviously lower in subcutaneous tumors of the LV-IDH1-AS1 group (Fig. 5F). Then, immunohistochemistry was performed to detect RBM47 and Ki67 protein expression in tumor tissues, identifying that RBM47 protein was highly expressed, while Ki67 protein was lowly expressed in IDH1-AS1-overexpressing tumor tissues (Fig. 5G). These results suggested that IDH1-AS1 suppressed xenograft tumor growth of EOC cells in vivo.

    Figure  5.  IDH1-AS1 suppressed tumor growth of EOC in vivo.
    A: The expression of IDH1-AS1 after LV-IDH1-AS1 transfection in SKOV3 cells was evaluated by qPCR analysis (n = 3). ACTB was used as an internal reference gene. B: The weight growth curve of nude mice after SKOV3 cell injection in the LV-NC group and LV-IDH1-AS1 group (n = 5 for each group). C: The tumor growth curve of nude mice was based on tumor volume in the nude mice of the two groups (n = 5). D: Photographs of subcutaneous tumors resected from each group of nude mice (n = 5). E: The subcutaneous tumor weight of nude mice was compared between the two groups (n = 5). F: qPCR analysis of the expression of miR-518c-5p in subcutaneous tumor tissues of the two groups (n = 5). Stem-loop U6 was used as an internal reference G: RBM47 and Ki67 protein expression was assessed in the form of integrated optical density summation in tumor tissues of the two groups by immunohistochemistry assay (n = 5). Scale bar: 50 μm. Data are presented as mean ± standard error of the mean, except for values in A presented as the mean ± standard deviation. Two-tailed Student's t-test was performed to indicate significance, except that statistical analyses for B and C were performed by two-way ANOVA. *P < 0.05, **P < 0.01, and ***P < 0.001. Abbreviations: EOC, epithelial ovarian cancer; LV-IDH1-AS1, IDH1-AS1-overexpressing lentivirus; qPCR, quantitative real-time PCR; LV-NC, negative control lentivirus; ANOVA, analysis of variance.
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    Accumulating evidence indicates that lncRNAs participate in the progression of EOC[12]. IDH1-AS1 is an antisense lncRNA derived from the complementary strand of the IDH1 gene. IDH1-AS1 has recently been demonstrated to affect cell proliferation and tumorigenesis of cervical cancer, prostate cancer, and glioblastoma[9–11], but it remains unknown whether IDH1-AS1 plays a role in the pathogenesis of EOC cells.

    In the present study, we identified that low expression of IDH1-AS1 was an independent predictor for a shorter OS in EOC patients based on the analyses using TCGA and TANRIC data. Moreover, an increasing age was associated with an increased risk of EOC progression, which was consistent with the previous reports[13–14]. The present results also indicated that the FIGO stage, grade, and lymph node invasion were not indicators of OS and disease-free survival in EOC. Although the grade was considered a controversial prognostic marker[13–14], the FIGO stage and lymph node invasion have been indicated as significant prognostic factors of EOC[15–18]. These differences may be due to the fact that the clinical information provided by the databases used in the present study was only from serous EOC patients, and the clinical data were incomplete, especially the data on lymph node metastasis. Therefore, it is necessary to perform further analysis to precisely clarify the association between IDH1-AS1 and clinical features.

    Similar to the study conducted by Xiang et al[9] in HeLa cells, we demonstrated that silencing IDH1-AS1 enhanced EOC cell proliferation, while overexpressing IDH1-AS1 attenuated EOC cell growth. Wang J et al[11] also reported that IDH1-AS1 suppressed glioblastoma cell proliferation and tumorigenesis. However, Zhang et al[10] revealed that IDH1-AS1 knockdown promoted cell apoptosis in addition to inhibiting cell proliferation and tumor growth in prostate cancer. These studies indicate that different effects of IDH1-AS1 may result from different mechanisms in various cancers.

    IDH1-AS1 has been demonstrated to participate in the progression of multiple cancers by regulating the IDH1 activity[9,11,19]. In the present study, we found that IDH1-AS1 was mainly distributed in the cytoplasm of EOC cells. It is possible that IDH1-AS1 functions in EOC through some other pathways, and some evidence suggests that different subcellular localizations may present distinct biological functions of lncRNAs[20–21]. The ceRNA hypothesis is the widely accepted mechanism for cytoplasmic lncRNAs that are suggested to compete against protein-coding mRNAs for the miRNA binding[12]. Currently, lncRNA-miRNA-mRNA interactions attract much attention, because they play an extensive role in the pathogenesis of EOC[22–24]. In the present study, we demonstrated that IDH1-AS1 suppressed EOC cell proliferation and tumor growth by sponging miR-518c-5p.

    miR-518c-5p is a member of the miR-515 family that belongs to the largest human miRNA cluster on chromosome 19, known as C19MC, encoding as many as 59 mature miRNAs[25]. miR-518c-5p has been reported to be involved in the progression of bladder cancer in a multivariate Cox regression analysis[26]. A reported miRNA microarray analysis has indicated that miR-518c-5p is also upregulated in retinoblastoma and related to tumorigenesis[27]. In addition, miR-518c-5p has been suggested to participate in the growth and metastasis of oral cancer by targeting the SDF-1/CXCR4 system[28]. In line with these findings, miR-518c-5p may promote EOC cell proliferation in the present study as an oncomiR[25]. However, another study has reported that hsa_circ_0007843 promotes the progression of colon cancer by sponging miR-518c-5p to regulate MMP2 expression[29]. As the above-mentioned functions of miR-518c-5p range from oncomiR to tumor suppressor, our findings have suggested that the effect of miR-518c-5p is determined by the cellular context in which it is activated.

    As an RNA-binding motif protein, RBM47 is a conserved RNA-binding protein in vertebrates and proved to be essential for the viability and growth of vertebrate embryo[30]. RBM47 significantly regulates mRNA transcription, RNA splicing, and RNA transportation[31]. It is widely accepted that RBM47 functions as a tumor suppressor in multiple cancers. Sakurai T et al[32] demonstrated that RBM47 suppressed tumor growth of lung adenocarcinoma by inhibiting Nrf2 function. Guo et al[33] reported that RBM47 acted as a DNA/RNA modulator to inhibit the progression of hepatocellular carcinoma. Qin et al[34] found that RBM47 suppressed cell proliferation and activated autophagy in papillary thyroid carcinoma. Shen et al[35] revealed that RBM47 stabilized AXIN1 mRNA to suppress Wnt/β-catenin signaling and inhibited tumor proliferation and metastasis in non-small cell lung cancer. Consistent with these investigations, the present study showed that RBM47 suppressed EOC cell proliferation, and thus we concluded that IDH1-AS1 inhibited EOC cell proliferation and tumor growth by upregulating RBM47 mediated by miR-518c-5p.

    In conclusion, the present findings reveal that IDH1-AS1 is downregulated in EOC cells and suppresses EOC cell proliferation and tumor growth. IDH1-AS1 regulates RBM47 expression levels by a miR-518c-5p-dependent mechanism (Fig. 6). Thus, these results indicate that IDH1-AS1 suppresses cell proliferation in EOC by regulating the miR-518c-5p/RBM47 axis.

    Figure  6.  A mechanism schematic of the role of IDH1-AS1 in EOC.
    IDH1-AS1 is transported from the nucleus to the cytoplasm after transcription where it competitively binds to miR-518c-5p, which promotes the mRNA and protein expression of RBM47, ultimately inhibiting cell proliferation and tumor growth of EOC. Abbreviation: EOC, epithelial ovarian cancer.
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    However, there were still some deficiencies in the present study. Most EOC patients were in an advanced stage without paracancerous tissues, resulting in a lack of comparison of the IDH1-AS1 expression in EOC tissues and paracancerous control tissues. In addition, most of the EOC patients from the TCGA database were white, and may not represent the expression of IDH1-AS1 in Chinese. We have been collecting samples of EOC patients from Chinese, and when the sample size is sufficient, we will conduct clinical data analysis of IDH1-AS1 in these samples. Taken together, once confirmed by other investigators, the IDH1-AS1/miR-518c-5p/RBM47 regulatory axis may be a new treatment target for EOC in the future.

    • References (134)
  • [1]
    Esteves PJ, Abrantes J, Baldauf HM, et al. The wide utility of rabbits as models of human diseases[J]. Exp Mol Med, 2018, 50: 1–10. doi: 10.1038/s12276-018-0094-1
    [2]
    Fan JL, Watanabe T. Transgenic rabbits as therapeutic protein bioreactors and human disease models[J]. Pharmacol Ther, 2003, 99(3): 261–282. doi: 10.1016/S0163-7258(03)00069-X
    [3]
    Peng XW. Transgenic rabbit models for studying human cardiovascular diseases[J]. Comp Med, 2012, 62(6): 472–429. https://pubmed.ncbi.nlm.nih.gov/23561880/
    [4]
    Peng XW, Knouse JA, Hernon KM. Rabbit models for studying human infectious diseases[J]. Comp Med, 2015, 65(6): 499–507. https://pubmed.ncbi.nlm.nih.gov/26678367/
    [5]
    Fan JL, Kitajima S, Watanabe T, et al. Rabbit models for the study of human atherosclerosis: from pathophysiological mechanisms to translational medicine[J]. Pharmacol Ther, 2015, 146: 104–119. doi: 10.1016/j.pharmthera.2014.09.009
    [6]
    Li WH, Gouy M, Sharp PM, et al. Molecular phylogeny of Rodentia, Lagomorpha, Primates, Artiodactyla, and Carnivora and molecular clocks[J]. Proc Natl Acad Sci U S A, 1990, 87(17): 6703–6707. doi: 10.1073/pnas.87.17.6703
    [7]
    Graur D, Duret L, Gouy M. Phylogenetic position of the order Lagomorpha (rabbits, hares and allies)[J]. Nature, 1996, 379(6563): 333–335. doi: 10.1038/379333a0
    [8]
    Pearce J. Louis Pasteur and rabies: a brief note[J]. J Neurol Neurosurg Psychiatry, 2002, 73(1): 82. doi: 10.1136/jnnp.73.1.82
    [9]
    Cambau E, Drancourt M. Steps towards the discovery of Mycobacterium tuberculosis by Robert Koch, 1882[J]. Clin Microbiol Infect, 2014, 20(3): 196–201. doi: 10.1111/1469-0691.12555
    [10]
    Goldstein JL, Kita T, Brown MS. Defective lipoprotein receptors and atherosclerosis—Lessons from an animal counterpart of familial hypercholesterolemia[J]. N Engl J Med, 1983, 309(5): 288–296. doi: 10.1056/NEJM198308043090507
    [11]
    Endo A. Regulation of cholesterol synthesis, as focused on the regulation of HMG-CoA reductase (author's transl)[J]. Seikagaku (in Japanese), 1980, 52(10): 1033–1049.
    [12]
    Biggers JD. Walter Heape, FRS: a pioneer in reproductive biology. Centenary of his embryo transfer experiments[J]. J Reprod Fert, 1991, 93(1): 173–186. doi: 10.1530/jrf.0.0930173
    [13]
    Chang MC. Fertilization of rabbit ova in vitro[J]. Nature, 1959, 184(4684): 466–467. doi: 10.1038/184466a0
    [14]
    Hammer RE, Pursel VG, Rexroad CE Jr, et al. Production of transgenic rabbits, sheep and pigs by microinjection[J]. Nature, 1985, 315(6021): 680–683. doi: 10.1038/315680a0
    [15]
    Zernii EY, Baksheeva VE, Iomdina EN, et al. Rabbit models of ocular diseases: new relevance for classical approaches[J]. CNS Neurol Disord Drug Targets, 2016, 15(3): 267–291. doi: 10.2174/1871527315666151110124957
    [16]
    Kamaruzaman NA, Kardia E, Kamaldin N, et al. The rabbit as a model for studying lung disease and stem cell therapy[J]. Biomed Res Int, 2013, 2013: 691830.
    [17]
    Burkholder TH, Linton G, Hoyt RF Jr, et al. The rabbit as an experimental model[M]//Suckow MA, Stevens KA, Wilson RP. The Laboratory Rabbit, Guinea Pig, Hamster, and Other Rodents. Boston: Academic Press, 2012: 529–560.
    [18]
    Christensen ND, Peng XW. Rabbit genetics and transgenic models[M]//Suckow MA, Stevens KA, Wilson RP. The Laboratory Rabbit, Guinea Pig, Hamster, and Other Rodents. Boston: Academic Press, 2012: 165–193.
    [19]
    Isola LM, Gordon JW. Transgenic animals: a new era in developmental biology and medicine[J]. Biotechnology, 1991, 16: 3–20. https://pubmed.ncbi.nlm.nih.gov/2007198/
    [20]
    Gordon JW, Scangos GA, Plotkin DJ, et al. Genetic transformation of mouse embryos by microinjection of purified DNA[J]. Proc Natl Acad Sci U S A, 1980, 77(12): 7380–7384. doi: 10.1073/pnas.77.12.7380
    [21]
    Brinster RL, Chen HY, Trumbauer M, et al. Somatic expression of herpes thymidine kinase in mice following injection of a fusion gene into eggs[J]. Cell, 1981, 27(1): 223–231. doi: 10.1016/0092-8674(81)90376-7
    [22]
    Costantini F, Lacy E. Introduction of a rabbit β-globin gene into the mouse germ line[J]. Nature, 1981, 294(5836): 92–94. doi: 10.1038/294092a0
    [23]
    Gordon JW, Ruddle FH. Integration and stable germ line transmission of genes injected into mouse pronuclei[J]. Science, 1981, 214(4526): 1244–1246. doi: 10.1126/science.6272397
    [24]
    Wagner EF, Stewart TA, Mintz B. The human beta-globin gene and a functional viral thymidine kinase gene in developing mice[J]. Proc Natl Acad Sci U S A, 1981, 78(8): 5016–5020. doi: 10.1073/pnas.78.8.5016
    [25]
    Wagner TE, Hoppe PC, Jollick JD, et al. Microinjection of a rabbit beta-globin gene into zygotes and its subsequent expression in adult mice and their offspring[J]. Proc Natl Acad Sci U S A, 1981, 78(10): 6376–6380. doi: 10.1073/pnas.78.10.6376
    [26]
    Campbell KHS, McWhir J, Ritchie WA, et al. Sheep cloned by nuclear transfer from a cultured cell line[J]. Nature, 1996, 380(6569): 64–66. doi: 10.1038/380064a0
    [27]
    Bibikova M, Golic M, Golic KG, et al. Targeted chromosomal cleavage and mutagenesis in Drosophila using zinc-finger nucleases[J]. Genetics, 2002, 161(3): 1169–1175. https://pubmed.ncbi.nlm.nih.gov/12136019/
    [28]
    Chesne P, Adenot PG, Viglietta C, et al. Cloned rabbits produced by nuclear transfer from adult somatic cells[J]. Nat Biotechnol, 2002, 20(4): 366–369. doi: 10.1038/nbt0402-366
    [29]
    Li SG, Guo Y, Shi JJ, et al. Transgene expression of enhanced green fluorescent protein in cloned rabbits generated from in vitro-transfected adult fibroblasts[J]. Transgenic Res, 2009, 18(2): 227–235. doi: 10.1007/s11248-008-9227-y
    [30]
    Geurts AM, Cost GJ, Freyvert Y, et al. Knockout rats via embryo microinjection of zinc-finger nucleases[J]. Science, 2009, 325(5939): 433. doi: 10.1126/science.1172447
    [31]
    Flisikowska T, Thorey IS, Offner S, et al. Efficient immunoglobulin gene disruption and targeted replacement in rabbit using zinc finger nucleases[J]. PLoS One, 2011, 6(6): e21045. doi: 10.1371/journal.pone.0021045
    [32]
    Tesson L, Usal C, Menoret S, et al. Knockout rats generated by embryo microinjection of TALENs[J]. Nat Biotechnol, 2011, 29(8): 695–696. doi: 10.1038/nbt.1940
    [33]
    Gasiunas G, Barrangou R, Horvath P, et al. Cas9-crRNA ribonucleoprotein complex mediates specific DNA cleavage for adaptive immunity in bacteria[J]. Proc Natl Acad Sci U S A, 2012, 109(39): E2579–E2586. doi: 10.1073/pnas.1208507109
    [34]
    Jinek M, Chylinski K, Fonfara I, et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity[J]. Science, 2012, 337(6096): 816–821. doi: 10.1126/science.1225829
    [35]
    Wang H, Yang H, Shivalila CS, et al. One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering[J]. Cell, 2013, 153(4): 910–918. doi: 10.1016/j.cell.2013.04.025
    [36]
    Song J, Zhong J, Guo XG, et al. Generation of RAG 1- and 2-deficient rabbits by embryo microinjection of TALENs[J]. Cell Res, 2013, 23(8): 1059–1062. doi: 10.1038/cr.2013.85
    [37]
    Yang D, Xu J, Zhu T, et al. Effective gene targeting in rabbits using RNA-guided Cas9 nucleases[J]. J Mol Cell Biol, 2014, 6(1): 97–99. doi: 10.1093/jmcb/mjt047
    [38]
    Carneiro M, Rubin CJ, Di Palma F, et al. Rabbit genome analysis reveals a polygenic basis for phenotypic change during domestication[J]. Science, 2014, 345(6200): 1074–1079. doi: 10.1126/science.1253714
    [39]
    Komor AC, Kim YB, Packer MS, et al. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage[J]. Nature, 2016, 533(7603): 420–424. doi: 10.1038/nature17946
    [40]
    Wang Z, Zhang JF, Li H, et al. Hyperlipidemia-associated gene variations and expression patterns revealed by whole-genome and transcriptome sequencing of rabbit models[J]. Sci Rep, 2016, 6: 26942. doi: 10.1038/srep26942
    [41]
    Liu Z, Chen M, Chen S, et al. Highly efficient RNA-guided base editing in rabbit[J]. Nat Commun, 2018, 9(1): 2717. doi: 10.1038/s41467-018-05232-2
    [42]
    Shen W, Li L, Pan QJ, et al. Efficient and simple production of transgenic mice and rabbits using the new DMSO-sperm mediated exogenous DNA transfer method[J]. Mol Reprod Dev, 2006, 73(5): 589–594. doi: 10.1002/mrd.20401
    [43]
    Hiripi L, Negre D, Cosset FL, et al. Transgenic rabbit production with simian immunodeficiency virus-derived lentiviral vector[J]. Transgenic Res, 2010, 19(5): 799–808. doi: 10.1007/s11248-009-9356-y
    [44]
    Smith KR. Sperm-mediated gene transfer: concepts and controversies[M]. Sharjah, UAE: Bentham Science, 2012.
    [45]
    Kuznetsov AV, Kuznetsova IV, Schit IY. DNA interaction with rabbit sperm cells and its transfer into ova in vitro and in vivo[J]. Mol Reprod Dev, 2000, 56(S2): 292–297. doi: 10.1002/(SICI)1098-2795(200006)56:2+<292::AID-MRD18>3.0.CO;2-Z
    [46]
    Houdebine LM. The methods to generate transgenic animals and to control transgene expression[J]. J Biotechnol, 2002, 98(2-3): 145–160. doi: 10.1016/S0168-1656(02)00129-3
    [47]
    Katter K, Geurts AM, Hoffmann O, et al. Transposon-mediated transgenesis, transgenic rescue, and tissue-specific gene expression in rodents and rabbits[J]. FASEB J, 2013, 27(3): 930–941. doi: 10.1096/fj.12-205526
    [48]
    Ivics Z, Hiripi L, Hoffmann OI, et al. Germline transgenesis in rabbits by pronuclear microinjection of Sleeping beauty transposons[J]. Nat Protoc, 2014, 9(4): 794–809. doi: 10.1038/nprot.2014.009
    [49]
    Evans MJ, Kaufman MH. Establishment in culture of pluripotential cells from mouse embryos[J]. Nature, 1981, 292(5819): 154–156. doi: 10.1038/292154a0
    [50]
    Martin GR. Isolation of a pluripotent cell line from early mouse embryos cultured in medium conditioned by teratocarcinoma stem cells[J]. Proc Natl Acad Sci U S A, 1981, 78(12): 7634–7638. doi: 10.1073/pnas.78.12.7634
    [51]
    Gossler A, Doetschman T, Korn R, et al. Transgenesis by means of blastocyst-derived embryonic stem cell lines[J]. Proc Natl Acad Sci U S A, 1986, 83(23): 9065–9069. doi: 10.1073/pnas.83.23.9065
    [52]
    Robertson E, Bradley A, Kuehn M, et al. Germ-line transmission of genes introduced into cultured pluripotential cells by retroviral vector[J]. Nature, 1986, 323(6087): 445–448. doi: 10.1038/323445a0
    [53]
    Kuehn MR, Bradley A, Robertson EJ, et al. A potential animal model for Lesch-Nyhan syndrome through introduction of HPRT mutations into mice[J]. Nature, 1987, 326(6110): 295–298. doi: 10.1038/326295a0
    [54]
    Okita K, Ichisaka T, Yamanaka S. Generation of germline-competent induced pluripotent stem cells[J]. Nature, 2007, 448(7151): 313–317. doi: 10.1038/nature05934
    [55]
    Wernig M, Meissner A, Foreman R, et al. In vitro reprogramming of fibroblasts into a pluripotent ES-cell-like state[J]. Nature, 2007, 448(7151): 318–324. doi: 10.1038/nature05944
    [56]
    Boland MJ, Hazen JL, Nazor KL, et al. Adult mice generated from induced pluripotent stem cells[J]. Nature, 2009, 461(7260): 91–94. doi: 10.1038/nature08310
    [57]
    Kang L, Wang JL, Zhang Y, et al. iPS cells can support full-term development of tetraploid blastocyst-complemented embryos[J]. Cell Stem Cell, 2009, 5(2): 135–138. doi: 10.1016/j.stem.2009.07.001
    [58]
    Zhao XY, Li W, Lv Z, et al. iPS cells produce viable mice through tetraploid complementation[J]. Nature, 2009, 461(7260): 86–90. doi: 10.1038/nature08267
    [59]
    Capecchi MR. Gene targeting in mice: functional analysis of the mammalian genome for the twenty-first century[J]. Nat Rev Genet, 2005, 6(6): 507–512. doi: 10.1038/nrg1619
    [60]
    Fang ZF, Gai H, Huang YZ, et al. Rabbit embryonic stem cell lines derived from fertilized, parthenogenetic or somatic cell nuclear transfer embryos[J]. Exp Cell Res, 2006, 312(18): 3669–3682. doi: 10.1016/j.yexcr.2006.08.013
    [61]
    Wang SF, Tang XH, Niu YY, et al. Generation and characterization of rabbit embryonic stem cells[J]. Stem Cells, 2007, 25(2): 481–489. doi: 10.1634/stemcells.2006-0226
    [62]
    Honda A, Hirose M, Inoue K, et al. Stable embryonic stem cell lines in rabbits: potential small animal models for human research[J]. Reprod Biomed Online, 2008, 17(5): 706–715. doi: 10.1016/S1472-6483(10)60320-3
    [63]
    Osteil P, Tapponnier Y, Markossian S, et al. Induced pluripotent stem cells derived from rabbits exhibit some characteristics of naïve pluripotency[J]. Biol Open, 2013, 2(6): 613–628. doi: 10.1242/bio.20134242
    [64]
    Xue F, Ma YH, Chen YE, et al. Recombinant rabbit leukemia inhibitory factor and rabbit embryonic fibroblasts support the derivation and maintenance of rabbit embryonic stem cells[J]. Cell Reprogram, 2012, 14(4): 364–376. doi: 10.1089/cell.2012.0001
    [65]
    Du FL, Chen CH, Li Y, et al. Derivation of rabbit embryonic stem cells from vitrified-thawed embryos[J]. Cell Reprogram, 2015, 17(6): 453–462. doi: 10.1089/cell.2015.0044
    [66]
    Zakhartchenko V, Flisikowska T, Li S, et al. Cell-mediated transgenesis in rabbits: chimeric and nuclear transfer animals[J]. Biol Reprod, 2011, 84(2): 229–237. doi: 10.1095/biolreprod.110.087098
    [67]
    Tancos Z, Nemes C, Polgar Z, et al. Generation of rabbit pluripotent stem cell lines[J]. Theriogenology, 2012, 78(8): 1774–1786. doi: 10.1016/j.theriogenology.2012.06.017
    [68]
    McCreath KJ, Howcroft J, Campbell KHS, et al. Production of gene-targeted sheep by nuclear transfer from cultured somatic cells[J]. Nature, 2000, 405(6790): 1066–1069. doi: 10.1038/35016604
    [69]
    Lai LX, Kolber-Simonds D, Park KW, et al. Production of α-1,3-galactosyltransferase knockout pigs by nuclear transfer cloning[J]. Science, 2002, 295(5557): 1089–1092. doi: 10.1126/science.1068228
    [70]
    Richt JA, Kasinathan P, Hamir AN, et al. Production of cattle lacking prion protein[J]. Nat Biotechnol, 2007, 25(1): 132–138. doi: 10.1038/nbt1271
    [71]
    Stice SL, Robl JM. Nuclear reprogramming in nuclear transplant rabbit embryos[J]. Biol Reprod, 1988, 39(3): 657–664. doi: 10.1095/biolreprod39.3.657
    [72]
    Du FL, Xu J, Zhang JF, et al. Beneficial effect of young oocytes for rabbit somatic cell nuclear transfer[J]. Cloning Stem Cells, 2009, 11(1): 131–140. doi: 10.1089/clo.2008.0042
    [73]
    Li SG, Chen XJ, Fang ZF, et al. Rabbits generated from fibroblasts through nuclear transfer[J]. Reproduction, 2006, 131(6): 1085–1090. doi: 10.1530/rep.1.01065
    [74]
    Li SG, Flisikowska T, Kessler B, et al. Production of cloned transgenic rabbits from mesenchymal stem cells[J]. Reprod Fertil Dev, 2010, 22(1): 192–192. doi: 10.1071/RDv22n1Ab67
    [75]
    Yin MR, Jiang WH, Fang ZF, et al. Generation of hypoxanthine phosphoribosyltransferase gene knockout rabbits by homologous recombination and gene trapping through somatic cell nuclear transfer[J]. Sci Rep, 2015, 5: 16023. doi: 10.1038/srep16023
    [76]
    Gaj T, Gersbach CA, Barbas III CF. ZFN, TALEN, and CRISPR/Cas-based methods for genome engineering[J]. Trends Biotechnol, 2013, 31(7): 397–405. doi: 10.1016/j.tibtech.2013.04.004
    [77]
    Conklin BR. Sculpting genomes with a hammer and chisel[J]. Nat Methods, 2013, 10(9): 839–840. doi: 10.1038/nmeth.2608
    [78]
    Cui XX, Ji DA, Fisher DA, et al. Targeted integration in rat and mouse embryos with zinc-finger nucleases[J]. Nat Biotechnol, 2011, 29(1): 64–67. doi: 10.1038/nbt.1731
    [79]
    Paques F, Duchateau P. Meganucleases and DNA double-strand break-induced recombination: perspectives for gene therapy[J]. Curr Gene Ther, 2007, 7(1): 49–66. doi: 10.2174/156652307779940216
    [80]
    Kim YG, Cha J, Chandrasegaran S. Hybrid restriction enzymes: zinc finger fusions to Fok I cleavage domain[J]. Proc Natl Acad Sci U S A, 1996, 93(3): 1156–1160. doi: 10.1073/pnas.93.3.1156
    [81]
    Yang DS, Yang HQ, Li W, et al. Generation of PPARγ mono-allelic knockout pigs via zinc-finger nucleases and nuclear transfer cloning[J]. Cell Res, 2011, 21(6): 979–982. doi: 10.1038/cr.2011.70
    [82]
    Yu SL, Luo JJ, Song ZY, et al. Highly efficient modification of beta-lactoglobulin (BLG) gene via zinc-finger nucleases in cattle[J]. Cell Res, 2011, 21(11): 1638–1640. doi: 10.1038/cr.2011.153
    [83]
    Perez EE, Wang JB, Miller JC, et al. Establishment of HIV-1 resistance in CD4+ T cells by genome editing using zinc-finger nucleases[J]. Nat Biotechnol, 2008, 26(7): 808–816. doi: 10.1038/nbt1410
    [84]
    Meng XD, Noyes MB, Zhu LJ, et al. Targeted gene inactivation in zebrafish using engineered zinc-finger nucleases[J]. Nat Biotechnol, 2008, 26(6): 695–701. doi: 10.1038/nbt1398
    [85]
    Yang DS, Zhang JF, Xu J, et al. Production of apolipoprotein C-III knockout rabbits using zinc finger nucleases[J]. J Vis Exp, 2013, (81): e50957. doi: 10.3791/50957
    [86]
    Ji DA, Zhao GJ, Songstad A, et al. Efficient creation of an APOE knockout rabbit[J]. Transgenic Res, 2015, 24(2): 227–235. doi: 10.1007/s11248-014-9834-8
    [87]
    Niimi M, Yang DS, Kitajima S, et al. ApoE knockout rabbits: a novel model for the study of human hyperlipidemia[J]. Atherosclerosis, 2016, 245: 187–193. doi: 10.1016/j.atherosclerosis.2015.12.002
    [88]
    Zhang JF, Niimi M, Yang DS, et al. Deficiency of cholesteryl ester transfer protein protects against atherosclerosis in rabbits[J]. Arterioscler Thromb Vasc Biol, 2017, 37(6): 1068–1075. doi: 10.1161/ATVBAHA.117.309114
    [89]
    Miller JC, Tan SY, Qiao GJ, et al. A TALE nuclease architecture for efficient genome editing[J]. Nat Biotechnol, 2011, 29(2): 143–148. doi: 10.1038/nbt.1755
    [90]
    Christian M, Cermak T, Doyle EL, et al. Targeting DNA double-strand breaks with TAL effector nucleases[J]. Genetics, 2010, 186(2): 757–761. doi: 10.1534/genetics.110.120717
    [91]
    Boch J, Scholze H, Schornack S, et al. Breaking the code of DNA binding specificity of TAL-type III effectors[J]. Science, 2009, 326(5959): 1509–1512. doi: 10.1126/science.1178811
    [92]
    Moscou MJ, Bogdanove AJ. A simple cipher governs DNA recognition by TAL effectors[J]. Science, 2009, 326(5959): 1501. doi: 10.1126/science.1178817
    [93]
    Hsu PD, Lander ES, Zhang F. Development and applications of CRISPR-Cas9 for genome engineering[J]. Cell, 2014, 157(6): 1262–1278. doi: 10.1016/j.cell.2014.05.010
    [94]
    Yang DS, Xu J, Chen YE. Generation of rabbit models by gene editing nucleases[M]//Liu CY, Du YB. Microinjection. New York: Humana Press, 2019: 327–345.
    [95]
    Li L, Zhang QJ, Yang HQ, et al. Fumarylacetoacetate hydrolase knock-out rabbit model for hereditary tyrosinemia type 1[J]. J Biol Chem, 2017, 292(11): 4755–4763. doi: 10.1074/jbc.M116.764787
    [96]
    Chen M, Yao B, Yang QB, et al. Truncated C-terminus of fibrillin-1 induces Marfanoid-progeroid-lipodystrophy (MPL) syndrome in rabbit[J]. Dis Model Mech, 2018, 11(4): dmm031542. doi: 10.1242/dmm.031542
    [97]
    Sui TT, Lau YS, Liu D, et al. A novel rabbit model of Duchenne muscular dystrophy generated by CRISPR/Cas9[J]. Dis Model Mech, 2018, 11(6): dmm032201. doi: 10.1242/dmm.032201
    [98]
    Sui TT, Xu L, Lau YS, et al. Development of muscular dystrophy in a CRISPR-engineered mutant rabbit model with frame-disrupting ANO5 mutations[J]. Cell Death Dis, 2018, 9(6): 609. doi: 10.1038/s41419-018-0674-y
    [99]
    Yuan L, Yao HB, Xu YX, et al. CRISPR/cas9-mediated mutation of αA-crystallin gene induces congenital cataracts in rabbits[J]. Invest Ophthalmol Vis Sci, 2017, 58(6): BIO34–BIO41. doi: 10.1167/iovs.16-21287
    [100]
    Yuan L, Sui TT, Chen M, et al. CRISPR/Cas9-mediated GJA8 knockout in rabbits recapitulates human congenital cataracts[J]. Sci Rep, 2016, 6: 22024. doi: 10.1038/srep22024
    [101]
    Lu R, Yuan T, Wang Y, et al. Spontaneous severe hypercholesterolemia and atherosclerosis lesions in rabbits with deficiency of low-density lipoprotein receptor (LDLR) on exon 7[J]. EBioMedicine, 2018, 36: 29–38. doi: 10.1016/j.ebiom.2018.09.020
    [102]
    Guo R, Wan Y, Xu D, et al. Generation and evaluation of Myostatin knock-out rabbits and goats using CRISPR/Cas9 system[J]. Sci Rep, 2016, 6: 29855. doi: 10.1038/srep29855
    [103]
    Lv Q, Yuan L, Deng J, et al. Efficient Generation of Myostatin Gene Mutated Rabbit by CRISPR/Cas9[J]. Sci Rep, 2016, 6: 25029. doi: 10.1038/srep25029
    [104]
    Song Y, Liu T, Wang Y, et al. Mutation of the Sp1 binding site in the 5' flanking region of SRY causes sex reversal in rabbits[J]. Oncotarget, 2017, 8(24): 38176–38183. doi: 10.18632/oncotarget.16979
    [105]
    Song Y, Xu Y, Liang M, et al. CRISPR/Cas9-mediated mosaic mutation of SRY gene induces hermaphroditism in rabbits[J]. Biosci Rep, 2018, 38(2): BSR20171490. doi: 10.1042/BSR20171490
    [106]
    Sui T, Yuan L, Liu H, et al. CRISPR/Cas9-mediated mutation of PHEX in rabbit recapitulates human X-linked hypophosphatemia (XLH)[J]. Hum Mol Genet, 2016, 25(13): 2661–2671. doi: 10.1093/hmg/ddw125
    [107]
    Sui T, Liu D, Liu T, et al. LMNA-mutated rabbits: a model of premature aging syndrome with muscular dystrophy and dilated cardiomyopathy[J]. Aging Dis, 2019, 10(1): 102–115. doi: 10.14336/AD.2018.0209
    [108]
    Wu H, Liu Q, Shi H, et al. Engineering CRISPR/Cpf1 with tRNA promotes genome editing capability in mammalian systems[J]. Cell Mol Life Sci, 2018, 75(19): 3593–3607. doi: 10.1007/s00018-018-2810-3
    [109]
    Honda A, Hirose M, Sankai T, et al. Single-step generation of rabbits carrying a targeted allele of the tyrosinase gene using CRISPR/Cas9[J]. Exp Anim, 2015, 64(1): 31–37. doi: 10.1538/expanim.14-0034
    [110]
    Song Y, Xu Y, Deng J, et al. CRISPR/Cas9-mediated mutation of tyrosinase (Tyr) 3' UTR induce graying in rabbit[J]. Sci Rep, 2017, 7(1): 1569. doi: 10.1038/s41598-017-01727-y
    [111]
    Jiang WH, Liu LL, Chang QR, et al. Production of Wilson disease model rabbits with homology-directed precision point mutations in the ATP7B gene using the CRISPR/Cas9 system[J]. Sci Rep, 2018, 8: 1332. doi: 10.1038/s41598-018-19774-4
    [112]
    Song YN, Zhang YX, Chen M, et al. Functional validation of the albinism-associated tyrosinase T373K SNP by CRISPR/Cas9-mediated homology-directed repair (HDR) in rabbits[J]. EBioMedicine, 2018, 36: 517–525. doi: 10.1016/j.ebiom.2018.09.041
    [113]
    Song YN, Yuan L, Wang Y, et al. Efficient dual sgRNA-directed large gene deletion in rabbit with CRISPR/Cas9 system[J]. Cell Mol Life Sci, 2016, 73(15): 2959–2968. doi: 10.1007/s00018-016-2143-z
    [114]
    Song J, Wang GS, Hoenerhoff MJ, et al. Bacterial and Pneumocystis infections in the lungs of gene-knockout rabbits with severe combined immunodeficiency[J]. Front Immunol, 2018, 9: 429. doi: 10.3389/fimmu.2018.00429
    [115]
    Song J, Yang DS, Ruan JX, et al. Production of immunodeficient rabbits by multiplex embryo transfer and multiplex gene targeting[J]. Sci Rep, 2017, 7(1): 12202. doi: 10.1038/s41598-017-12201-0
    [116]
    Yan Q, Zhang Q, Yang H, et al. Generation of multi-gene knockout rabbits using the Cas9/gRNA system[J]. Cell Regen (Lond), 2014, 3(1): 12. doi: 10.1186/2045-9769-3-12
    [117]
    Liu H, Sui T, Liu D, et al. Multiple homologous genes knockout (KO) by CRISPR/Cas9 system in rabbit[J]. Gene, 2018, 647: 261–267. doi: 10.1016/j.gene.2018.01.044
    [118]
    Yang DS, Song J, Zhang JF, et al. Identification and characterization of rabbit ROSA26 for gene knock-in and stable reporter gene expression[J]. Sci Rep, 2016, 6: 25161. doi: 10.1038/srep25161
    [119]
    Song J, Yang DS, Xu J, et al. RS-1 enhances CRISPR/Cas9- and TALEN-mediated knock-in efficiency[J]. Nat Commun, 2016, 7: 10548. doi: 10.1038/ncomms10548
    [120]
    Gaudelli NM, Komor AC, Rees HA, et al. Programmable base editing of A·T to G·C in genomic DNA without DNA cleavage[J]. Nature, 2017, 551(7681): 464–471. doi: 10.1038/nature24644
    [121]
    Komor AC, Zhao KT, Packer MS, et al. Improved base excision repair inhibition and bacteriophage Mu Gam protein yields C: G-to-T: a base editors with higher efficiency and product purity[J]. Sci Adv, 2017, 3(8): eaao4774. doi: 10.1126/sciadv.aao4774
    [122]
    Koblan LW, Doman JL, Wilson C, et al. Improving cytidine and adenine base editors by expression optimization and ancestral reconstruction[J]. Nat Biotechnol, 2018, 36(9): 843–846. doi: 10.1038/nbt.4172
    [123]
    Hsu PD, Scott DA, Weinstein JA, et al. DNA targeting specificity of RNA-guided Cas9 nucleases[J]. Nat Biotechnol, 2013, 31(9): 827–832. doi: 10.1038/nbt.2647
    [124]
    Schmid-Burgk JL, Gao LY, Li D, et al. Highly parallel profiling of cas9 variant specificity[J]. Mol Cell, 2020, . doi: 10.1016/j.molcel.2020.02.023
    [125]
    Tycko J, Myer VE, Hsu PD. Methods for optimizing crispr-cas9 genome editing specificity[J]. Mol Cell, 2016, 63(3): 355–370. doi: 10.1016/j.molcel.2016.07.004
    [126]
    Chen SM, Yao YF, Zhang YC, et al. CRISPR system: discovery, development and off-target detection[J]. Cell Signal, 2020, 70: 109577. doi: 10.1016/j.cellsig.2020.109577
    [127]
    Li JJ, Hong SY, Chen WJ, et al. Advances in detecting and reducing off-target effects generated by CRISPR-mediated genome editing[J]. J Genet Genomics, 2019, 46(11): 513–521. doi: 10.1016/j.jgg.2019.11.002
    [128]
    Zischewski J, Fischer R, Bortesi L. Detection of on-target and off-target mutations generated by CRISPR/Cas9 and other sequence-specific nucleases[J]. Biotechnol Adv, 2017, 35(1): 95–104. doi: 10.1016/j.biotechadv.2016.12.003
    [129]
    Kosicki M, Tomberg K, Bradley A. Repair of double-strand breaks induced by CRISPR-Cas9 leads to large deletions and complex rearrangements[J]. Nat Biotechnol, 2018, 36(8): 765–771. doi: 10.1038/nbt.4192
    [130]
    Mou HW, Smith JL, Peng LT, et al. CRISPR/Cas9-mediated genome editing induces exon skipping by alternative splicing or exon deletion[J]. Genome Biol, 2017, 18(1): 108. doi: 10.1186/s13059-017-1237-8
    [131]
    Prykhozhij SV, Steele SL, Razaghi B, et al. A rapid and effective method for screening, sequencing and reporter verification of engineered frameshift mutations in zebrafish[J]. Dis Model Mech, 2017, 10(6): 811–822. doi: 10.1242/dmm.026765
    [132]
    Sharpe JJ, Cooper TA. Unexpected consequences: exon skipping caused by CRISPR-generated mutations[J]. Genome Biol, 2017, 18(1): 109. doi: 10.1186/s13059-017-1240-0
    [133]
    Sui TT, Song YN, Liu ZQ, et al. CRISPR-induced exon skipping is dependent on premature termination codon mutations[J]. Genome Biol, 2018, 19(1): 164. doi: 10.1186/s13059-018-1532-z
    [134]
    Li P, Estrada J, Zhang F, et al. Isolation, characterization, and nuclear reprogramming of cell lines derived from porcine adult liver and fat[J]. Cell Reprogram, 2010, 12(5): 599–607. doi: 10.1089/cell.2010.0006
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