Title |
Modeling Rett Syndrome Using TALEN-Edited MECP2 Mutant Cynomolgus Monkeys
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Published in |
Cell, May 2017
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DOI | 10.1016/j.cell.2017.04.035 |
Pubmed ID | |
Authors |
Yongchang Chen, Juehua Yu, Yuyu Niu, Dongdong Qin, Hailiang Liu, Gang Li, Yingzhou Hu, Jiaojian Wang, Yi Lu, Yu Kang, Yong Jiang, Kunhua Wu, Siguang Li, Jingkuan Wei, Jing He, Junbang Wang, Xiaojing Liu, Yuping Luo, Chenyang Si, Raoxian Bai, Kunshan Zhang, Jie Liu, Shaoyong Huang, Zhenzhen Chen, Shuang Wang, Xiaoying Chen, Xinhua Bao, Qingping Zhang, Fuxing Li, Rui Geng, Aibin Liang, Dinggang Shen, Tianzi Jiang, Xintian Hu, Yuanye Ma, Weizhi Ji, Yi Eve Sun |
Abstract |
Gene-editing technologies have made it feasible to create nonhuman primate models for human genetic disorders. Here, we report detailed genotypes and phenotypes of TALEN-edited MECP2 mutant cynomolgus monkeys serving as a model for a neurodevelopmental disorder, Rett syndrome (RTT), which is caused by loss-of-function mutations in the human MECP2 gene. Male mutant monkeys were embryonic lethal, reiterating that RTT is a disease of females. Through a battery of behavioral analyses, including primate-unique eye-tracking tests, in combination with brain imaging via MRI, we found a series of physiological, behavioral, and structural abnormalities resembling clinical manifestations of RTT. Moreover, blood transcriptome profiling revealed that mutant monkeys resembled RTT patients in immune gene dysregulation. Taken together, the stark similarity in phenotype and/or endophenotype between monkeys and patients suggested that gene-edited RTT founder monkeys would be of value for disease mechanistic studies as well as development of potential therapeutic interventions for RTT. |
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United States | 5 | 17% |
Russia | 2 | 7% |
Ireland | 2 | 7% |
France | 2 | 7% |
Japan | 1 | 3% |
United Kingdom | 1 | 3% |
Unknown | 16 | 55% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 21 | 72% |
Scientists | 5 | 17% |
Science communicators (journalists, bloggers, editors) | 2 | 7% |
Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 210 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 36 | 17% |
Researcher | 32 | 15% |
Student > Bachelor | 27 | 13% |
Student > Master | 24 | 11% |
Student > Doctoral Student | 11 | 5% |
Other | 36 | 17% |
Unknown | 44 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Neuroscience | 36 | 17% |
Biochemistry, Genetics and Molecular Biology | 34 | 16% |
Agricultural and Biological Sciences | 31 | 15% |
Medicine and Dentistry | 22 | 10% |
Psychology | 8 | 4% |
Other | 30 | 14% |
Unknown | 49 | 23% |