Evaluation of TRAP-sequencing technology with a versatile conditional mouse model.
Evaluation of TRAP-sequencing technology with a versatile conditional mouse model.
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DOI：
10.1093/nar/gkt995
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发表时间：
2014-01
影响因子：
14.9
通讯作者：
Stenman JM
中科院分区：
文献类型：
--
作者：
Hupe M;Li MX;Gertow Gillner K;Adams RH;Stenman JM
各种细胞谱系的基因表达谱分析为调节细胞发育和分化的分子机制提供了宝贵的见解。然而，罕见的和散布的细胞群体，如内皮细胞的体内分子谱分析仍然具有挑战性。我们已经产生了一个通用的floxed翻译核糖体亲和纯化（TRAP）小鼠模型，mCherryTRAP，从完整组织的不同细胞系的Cre依赖性翻译谱。为了使用TRAP鉴定细胞类型特异性转录物，必须过滤数据以去除未在所分析的细胞类型中表达的背景转录物和在组织/器官的所有细胞群体中表达的转录物。先前已使用来自组织/器官的转录RNA实现过滤。使用mCherryTRAP模型，我们证明了胚胎大脑和肾脏的翻译组和转录组之间广泛的RNA差异表达。我们评估了这些数据对TRAP研究丰富和稀有细胞群的影响。最后，我们证明了该技术的适用性，研究器官特异性内皮细胞分化。
Gene expression profiling of various cell lineages has provided invaluable insights into the molecular mechanisms regulating cellular development and differentiation. However, in vivo molecular profiling of rare and interspersed cell populations, such as endothelial cells, has remained challenging. We have generated a versatile floxed translating ribosome affinity purification (TRAP) mouse model, mCherryTRAP, for Cre-dependent translational profiling of distinct cell lineages from intact tissues. To identify cell type–specific transcripts using TRAP, the data have to be filtered to remove both background transcripts not expressed in the profiled cell type and transcripts expressed in all cell populations of the tissue/organ. Filtering has previously been achieved using transcribed RNA from the tissue/organ. Using the mCherryTRAP model, we demonstrate extensive differential expression of RNAs between the translatome and transcriptome of embryonic brains and kidneys. We evaluate the implications of these data for TRAP studies of abundant and rare cell populations. Finally, we demonstrate the applicability of the technology to study organ-specific endothelial cell differentiation.
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影响因子：
14.9
作者：
Dougherty JD;Schmidt EF;Nakajima M;Heintz N
通讯作者：
Heintz N
宏非编码RNA Meg8和Irm在小鼠胚胎发育中的表达
影响因子：
2.5
作者：
Gu, Tiantian;He, Hongjuan;Wu, Qiong
通讯作者：
Wu, Qiong
影响因子：
2.6
作者：
Hayashi, Shigemi;Lewis, Paula;McMahon, Andrew P.
通讯作者：
McMahon, Andrew P.
影响因子：
3.7
作者：
Daneman R;Zhou L;Agalliu D;Cahoy JD;Kaushal A;Barres BA
通讯作者：
Barres BA
影响因子：
5.4
作者：
Aird, William C.
通讯作者：
Aird, William C.