Comparative Analysis of Mouse Decidualization Models at the Molecular Level
Comparative Analysis of Mouse Decidualization Models at the Molecular Level
复制标题
小鼠蜕膜化模型的分子水平比较分析
DOI:
10.3390/genes11080935
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发表时间:
2020-08
期刊:
影响因子:
--
通讯作者:
Liu Ji-Long
中科院分区:
文献类型:
--
作者:
Wang Chong;Zhao Miao;Zhang Wen-Qian;Huang Ming-Yu;Zhu Can;He Jia-Peng;Liu Ji-Long
The mouse is widely used to study decidualization and there are three well-established mouse models of decidualization, namely natural pregnancy decidualization (NPD), artificial decidualization (AD), and in vitro decidualization (IVD). However, the extent of similarity and difference between these models at the molecular level remains largely unknown. Here, we performed a comparative analysis using the RNA-seq approach. In the NPD model, which is thought to be the golden standard of mouse decidualization, we found a total of 5277 differentially expressed genes, with 3158 genes being up-regulated and 2119 genes being down-regulated. A total of 4294 differentially expressed genes were identified in the AD model: 1127 up-regulated genes and 3167 down-regulated genes. In comparison to NPD, 1977 genes were consistently expressed, whereas only 217 genes were inconsistently expressed, indicating that AD is a reliable model for mouse decidualization. In the IVD model, RNA-seq analysis revealed that 513 genes were up-regulated and 988 genes were down-regulated. Compared to NPD, 310 genes were consistently expressed, whereas 456 genes were inconsistently expressed. Moreover, although the decidualization marker Prl8a2 (prolactin family 8 subfamily a member 2) was up-regulated, the widely-used marker Alpl (alkaline phosphatase liver/bone/kidney) was down-regulated in the IVD model. Therefore, we suggest that the IVD model should be optimized to mimic NPD at the transcriptomic level. Our study contributes to an increase in the knowledge about mouse models of decidualization.
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影响因子:
3.5
作者:
Chakraborty, I;Das, SK;Dey, SK
通讯作者:
Dey, SK
影响因子:
4.5
作者:
Large MJ;Wetendorf M;Lanz RB;Hartig SM;Creighton CJ;Mancini MA;Kovanci E;Lee KF;Threadgill DW;Lydon JP;Jeong JW;DeMayo FJ
通讯作者:
DeMayo FJ
影响因子:
46.9
作者:
Trapnell C;Williams BA;Pertea G;Mortazavi A;Kwan G;van Baren MJ;Salzberg SL;Wold BJ;Pachter L
通讯作者:
Pachter L
DOI:
10.1073/pnas.1508056112
发表时间:
2015-11
期刊:
Proceedings of the National Academy of Sciences
影响因子:
--
作者:
Shannon D. Whirledge;R. Oakley;P. Myers;J. Lydon;F. DeMayo;J. Cidlowski
通讯作者:
Shannon D. Whirledge;R. Oakley;P. Myers;J. Lydon;F. DeMayo;J. Cidlowski
影响因子:
4.8
作者:
Li, Quanxi;Kannan, Athilakshmi;Bagchi, Indrani C.
通讯作者:
Bagchi, Indrani C.