Chen Tian

Dr. Chen Tian

orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 2013 in Molecular Cell
Verified
Journal Article
Closed access
YZYang Zhang
Yang Zhang
Xiao-Ou ZhangXiao-Ou Zhang
Xiao-Ou Zhang
Chen TianChen Tian
Chen Tian
JXJian-Feng Xiang
Jian-Feng Xiang
QYQing-Fei Yin
Qing-Fei Yin
LCLing-Ling Chen
Ling-Ling Chen

24 February 2015 in Cell Research
Verified
Journal Article
Open access
PDF file
Chen TianChen Tian
Chen Tian
JXJian-Feng Xiang
Jian-Feng Xiang
SZShanshan Zhu
Shanshan Zhu
SCSiye Chen
Siye Chen
QYQing-Fei Yin
Qing-Fei Yin
LCLing-Ling Chen
Ling-Ling Chen
Adenosine deaminases acting on RNA (ADARs) are involved in adenosine-to-inosine RNA editing and are implicated in development and diseases. Here we observed that ADAR1 deficiency in human embryonic stem cells (hESCs) significantly affected hESC differentiation and neural induction with widespread changes in mRNA and miRNA expression, including upregulation of self-renewal-related miRNAs, such as miR302s. Global editing analyses revealed that ADAR1 editing activity contributes little to the altered miRNA/mRNA expression in ADAR1-deficient hESCs upon neural induction. Genome-wide iCLIP studies identified that ADAR1 binds directly to pri-miRNAs to interfere with miRNA processing by acting as an RNA-binding protein. Importantly, aberrant expression of miRNAs and phenotypes observed in ADAR1-depleted hESCs upon neural differentiation could be reversed by an enzymatically inactive ADAR1 mutant, but not by the RNA-binding-null ADAR1 mutant. These findings reveal that ADAR1, but not its editing activity, is critical for hESC differentiation and neural induction by regulating miRNA biogenesis via direct RNA interaction.

27 March 2013 in BMC Genomics
Verified
Journal Article
Open access
PDF file
SZShanshan Zhu
Shanshan Zhu
JXJian-Feng Xiang
Jian-Feng Xiang
Chen TianChen Tian
Chen Tian
LCLing-Ling Chen
Ling-Ling Chen
LYLi Yang
Li Yang
Background: Adenosine-to-inosine (A-to-I) RNA editing is recognized as a cellular mechanism for generating both RNA and protein diversity. Inosine base pairs with cytidine during reverse transcription and therefore appears as guanosine during sequencing of cDNA. Current approaches of RNA editing identification largely depend on the comparison between transcriptomes and genomic DNA (gDNA) sequencing datasets from the same individuals, and it has been challenging to identify editing candidates from transcriptomes in the absence of gDNA information. Results: We have developed a new strategy to accurately predict constitutive RNA editing sites from publicly available human RNA-seq datasets in the absence of relevant genomic sequences. Our approach establishes new parameters to increase the ability to map mismatches and to minimize sequencing/mapping errors and unreported genome variations. We identified 695 novel constitutive A-to-I editing sites that appear in clusters (named “editing boxes”) in multiple samples and which exhibit spatial and dynamic regulation across human tissues. Some of these editing boxes are enriched in non-repetitive regions lacking inverted repeat structures and contain an extremely high conversion frequency of As to Is. We validated a number of editing boxes in multiple human cell lines and confirmed that ADAR1 is responsible for the observed promiscuous editing events in non-repetitive regions, further expanding our knowledge of the catalytic substrate of A-to-I RNA editing by ADAR enzymes. Conclusions: The approach we present here provides a novel way of identifying A-to-I RNA editing events by analyzing only RNA-seq datasets. This method has allowed us to gain new insights into RNA editing and should also aid in the identification of more constitutive A-to-I editing sites from additional transcriptomes.

24 January 2022 in Scientific Reports
Verified
Journal Article
Open access
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LZLihong Zhou
Lihong Zhou
JCJian Chen
Jian Chen
Chen TianChen Tian
Chen Tian
HCHuailong Chang
Huailong Chang
WCWenguang Cui
Wenguang Cui
JSJin Su
Jin Su
The present study aimed to reveal the amount per application of facial sheet masks and its influencing factors in Chinese population to form the base for an accurate exposure assessment. A total of 175 healthy subjects aged 18 years or older were recruited and divided into two subgroups: one group of 35 subjects were asked to apply same mask for 5, 10, 15, 20, 25, and 30 min respectively, and the other 140 subjects were instructed to apply one of four types of facial sheet masks presented in the market for 15 min. Furthermore, phenoxyethanol and methylparaben were measured to reflect actual exposure to chemicals. The sharp increase in the relative exposure to phenoxyethanol (CAS NO.122-99-6) and methylparaben at 25 min and longer suggests applying facial sheet masks for longer than 20 min may drive the exposure to hazardous chemicals to increase significantly. The 90th percentile of amount per application for plant-cellulose, bamboo charcoal fiber, bio-cellulose, and binchotan charcoal fiber-based masks was 5.753, 5.371, 5.017, and 4.821 g respectively. In addition, men and subjects with sebaceous skin demonstrated lower amount per application compared to women and subjects with dry skin, respectively. Finally, our data showed that the larger the contacting area between face and mask, the more amount per application. We concluded that the appropriate time of application should be less than 20 min. And mask fabrics, gender, sebum content, and contacting area could significantly impact the risk assessment of facial sheet masks. Our data for the first time provides insights into a realistic risk assessment of facial sheet masks in Chinese population.

11 January 2024 in Chemosphere
Verified
Journal Article
Closed access
Chen TianChen Tian
Chen Tian
XLXiaohua Liu
Xiaohua Liu
JZJianghua Zhang
Jianghua Zhang
LWLulu Wang
Lulu Wang
JSJin Su
Jin Su
PXPing Xiao
Ping Xiao

16 March 2020 in Skin Research and Technology
Verified
Journal Article
Closed access
PDF file
YMYafeng Ma
Yafeng Ma
LLLulu Li
Lulu Li
JCJia Chen
Jia Chen
Chen TianChen Tian
Chen Tian
CYChao Yuan
Chao Yuan