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Efficient in vivo deletion of a large imprinted lncRNA by CRISPR/Cas9
Open accessAbstract
Recent genome-wide studies have revealed that the majority of the mouse genome is transcribed as non-coding RNAs (ncRNAs) and growing evidence supports the importance of ncRNAs in regulating gene expression and epigenetic processes. However, the low efficiency of conventional gene targeting strategies has hindered the functional study of ncRNAs in vivo, particularly in generating large fragment deletions of long non-coding RNAs (lncRNAs) with multiple expression variants. The bacterial clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) system has recently been applied as an efficient tool for engineering site-specific mutations of protein-coding genes in the genome. In this study, we explored the potential of using the CRISPR/Cas9 system to generate large genomic deletions of lncRNAs in mice. We developed an efficient one-step strategy to target the maternally expressed lncRNA, Rian, on chromosome 12 in mice. We showed that paired sgRNAs can precisely generate large deletions up to 23kb and the deletion efficiency can be further improved up to 33% by combining multiple sgRNAs. The deletion successfully abolished the expression of Rian from the maternally inherited allele, validating the biological relevance of the mutations in studying an imprinted locus. Mutation of Rian has differential effects on expression of nearby genes in different somatic tissues. Taken together, we have established a robust one-step method to engineer large deletions to knockout lncRNA genes with the CRISPR/Cas9 system. Our work will facilitate future functional studies of other lncRNAs in vivo.
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Wang, H., Yang, H., Shivalila, C. S., Dawlaty, M. M., Cheng, A. W., Zhang, F., & Jaenisch, R. (2013) · Cell · doi:10.1016/j.cell.2013.04.025 · Cited by 3,495
Long Noncoding RNAs: Cellular Address Codes in Development and Disease
Batista, P. J., & Chang, H. Y. (2013) · Cell · doi:10.1016/j.cell.2013.02.012 · Cited by 2,531
RNA-guided genetic silencing systems in bacteria and archaea
Wiedenheft, B., Sternberg, S. H., & Doudna, J. A. (2012) · Nature · doi:10.1038/nature10886 · Cited by 1,851
Yang, H., Wang, H., Shivalila, C. S., Cheng, A. W., Shi, L., & Jaenisch, R. (2013) · Cell · doi:10.1016/j.cell.2013.08.022 · Cited by 1,596
Pattanayak, V., Lin, S., Guilinger, J. P., Ma, E., Doudna, J. A., & Liu, D. R. (2013) · Nature Biotechnology · doi:10.1038/nbt.2673 · Cited by 1,487
Cited by
The emerging role of lncRNAs in cancer
Huarte, M. (2015) · Nature Medicine · doi:10.1038/nm.3981 · Cited by 2,702
Potential of long non‐coding RNAs in cancer patients: From biomarkers to therapeutic targets
Chandra Gupta, S., & Nandan Tripathi, Y. (2017) · International Journal of Cancer · doi:10.1002/ijc.30546 · Cited by 527
Applications of the CRISPR-Cas9 system in cancer biology
Sánchez-Rivera, F. J., & Jacks, T. (2015) · Nature Reviews Cancer · doi:10.1038/nrc3950 · Cited by 405
CRISPR-based functional genomics for neurological disease
Kampmann, M. (2020) · Nature Reviews Neurology · doi:10.1038/s41582-020-0373-z · Cited by 163
Recent Progress in CRISPR/Cas9 Technology
Mei, Y., Wang, Y., Chen, H., Sun, Z. S., & Ju, X.-D. (2016) · Journal of Genetics and Genomics · doi:10.1016/j.jgg.2016.01.001 · Cited by 148
Metadata
- Authors
- Han, J., Zhang, J., Chen, L., Shen, B., Zhou, J., Hu, B., Du, Y., Tate, P. H., Huang, X., & Zhang, W.
- Venue
- RNA Biology
- Publisher
- Informa UK Limited
- Published
- 2014-07
- Volume
- 11
- Issue
- 7
- Pages
- 829-835
- ISSN
- 1547-6286 (ISSN-L)
- 1555-8584
- OpenAlex
- W1980156946
- Cited by
- 168
- References
- 5
- FWCI
- 6.45
- Type
- journal article
- Language
- en
- Open access
- bronze
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