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The changing mouse embryo transcriptome at whole tissue and single-cell resolution
Nature ( IF 64.8 ) Pub Date : 2020-07-29 , DOI: 10.1038/s41586-020-2536-x
Peng He 1, 2 , Brian A Williams 1 , Diane Trout 1 , Georgi K Marinov 3 , Henry Amrhein 1 , Libera Berghella 1 , Say-Tar Goh 1 , Ingrid Plajzer-Frick 4 , Veena Afzal 4 , Len A Pennacchio 4, 5, 6 , Diane E Dickel 4 , Axel Visel 4, 5, 7 , Bing Ren 8 , Ross C Hardison 9 , Yu Zhang 10 , Barbara J Wold 1
Affiliation  

During mammalian embryogenesis, differential gene expression gradually builds the identity and complexity of each tissue and organ system1. Here we systematically quantified mouse polyA-RNA from day 10.5 of embryonic development to birth, sampling 17 tissues and organs. The resulting developmental transcriptome is globally structured by dynamic cytodifferentiation, body-axis and cell-proliferation gene sets that were further characterized by the transcription factor motif codes of their promoters. We decomposed the tissue-level transcriptome using single-cell RNA-seq (sequencing of RNA reverse transcribed into cDNA) and found that neurogenesis and haematopoiesis dominate at both the gene and cellular levels, jointly accounting for one-third of differential gene expression and more than 40% of identified cell types. By integrating promoter sequence motifs with companion ENCODE epigenomic profiles, we identified a prominent promoter de-repression mechanism in neuronal expression clusters that was attributable to known and novel repressors. Focusing on the developing limb, single-cell RNA data identified 25 candidate cell types that included progenitor and differentiating states with computationally inferred lineage relationships. We extracted cell-type transcription factor networks and complementary sets of candidate enhancer elements by using single-cell RNA-seq to decompose integrative cis-element (IDEAS) models that were derived from whole-tissue epigenome chromatin data. These ENCODE reference data, computed network components and IDEAS chromatin segmentations are companion resources to the matching epigenomic developmental matrix, and are available for researchers to further mine and integrate. RNA expression is quantified at a tissue level in seventeen mouse tissues across embryonic development, and at the single-cell level in the developing limb.

中文翻译:

整个组织和单细胞分辨率下不断变化的小鼠胚胎转录组

在哺乳动物胚胎发生过程中,差异基因表达逐渐建立了每个组织和器官系统的特性和复杂性。在这里,我们系统地量化了从胚胎发育第 10.5 天到出生的小鼠 polyA-RNA,对 17 个组织和器官进行了采样。由此产生的发育转录组由动态细胞分化、体轴和细胞增殖基因组构成,这些基因组进一步由其启动子的转录因子基序代码表征。我们使用单细胞 RNA-seq(逆转录为 cDNA 的 RNA 测序)分解组织水平的转录组,发现神经发生和造血在基因和细胞水平上均占主导地位,共同占差异基因表达的三分之一等超过 40% 的已识别细胞类型。通过将启动子序列基序与伴随的 ENCODE 表观基因组图谱相结合,我们确定了神经元表达簇中一种显着的启动子去抑制机制,该机制可归因于已知和新的抑制因子。专注于发育中的肢体,单细胞 RNA 数据确定了 25 种候选细胞类型,包括祖细胞和具有计算推断的谱系关系的分化状态。我们通过使用单细胞 RNA-seq 分解源自全组织表观基因组染色质数据的整合顺式元件 (IDEAS) 模型来提取细胞类型转录因子网络和互补的候选增强子元件集。这些 ENCODE 参考数据、计算的网络组件和 IDEAS 染色质分割是匹配的表观基因组发育矩阵的伴随资源,并可供研究人员进一步挖掘和整合。在整个胚胎发育过程中,在 17 种小鼠组织中的组织水平以及发育中肢体的单细胞水平上对 RNA 表达进行量化。
更新日期:2020-07-29
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