Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression data for mouse embryogenesis from oocyte to newborn

ABSTRACT: Studies in mouse have led to enormous progress in our understanding of early human development. The identification of genes and the signaling pathways involved in mouse embryogenesis have helped us to better understand fertilization, morulation, gastrulation, organogenesis and embryonic development in mammals. We report a detailed analysis of the global gene expression profiles from oocyte to the end of organogenesis in mouse. Our studies revealed distinct temporal regulation patterns for genes belonging to different functional categories, supporting their roles during organogenesis. Mouse embryos were selected at successive stage for for RNA extraction and hybridization on Affymetrix microarrays. We sought to obtain homogeneous populations of embryos at each developmental stage in order to increase the temporal resolution of expression profiles. To that end, we hand-selected embryos according to morphological criteria at 12 time-points from embryos to newborn

ORGANISM(S): Mus musculus

SUBMITTER: Wenxin Li

PROVIDER: E-GEOD-39897 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Global expression profiling reveals genetic programs underlying the developmental divergence between mouse and human embryogenesis.

Xue Lu L Cai Jin-Yang JY Ma Jian J Huang Zan Z Guo Ming-Xiong MX Fu Lie-Zhen LZ Shi Yun-Bo YB Li Wen-Xin WX

BMC genomics 20130820

<h4>Background</h4>Mouse has served as an excellent model for studying human development and diseases due to its similarity to human. Advances in transgenic and knockout studies in mouse have dramatically strengthened the use of this model and significantly improved our understanding of gene function during development in the past few decades. More recently, global gene expression analyses have revealed novel features in early embryogenesis up to gastrulation stages and have indeed provided mole ...[more]

PMID: 23961710

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Project description:We here report transcriptome profiling of human embryos at six successive developmental stages (i.e., Carnegie Stages 9 to 14), representing the first comprehensive gene expression database of early human organogenesis. Through a series of data mining and comparisons with the transcriptome during mouse embryogenesis and the disparate genomic data in human embryonic stem cells, we revealed that development potential during early human organogenesis is orchestrated by two dominant categories of genes. Specifically, most gradually induced genes are largely differentiation related whereas those gradually repressed are involved in both stemness- and differentiation-relevant aspects of the developmental potential. Further through integrative mining we uncovered a molecular network that well characterizes stemness- and differentiation-relevant aspects of developmental potentials during early human organogenesis. Analysis of published data showed that the network could serve to evaluate various differentiation models. Our results make a significant step towards understanding of human embryogenesis at a molecular level and suggest that developmental potentials are under control of shared regulatory events. With the consent of subjects and of the Ethical Review Board of the Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine,we collected human post-implantation embryos at six successive time periods: Carnegie Stages 9 to 14 (E20 to E32), covering the first third of organogenesis. Using the Affymetrix HG-U133A Genechip microarrays, three replicates were independently profiled for each stage to minimize the influence of the embryo-to-embryo variation. Raw expression data were normalized using Robust Multi-array Averaging (RMA) with quantile normalization. The resultant expression data were imported into Extraction of Differential Gene Expression (EDGE) software for the detection of probesets exhibiting the consistent changes within the triplicates and differential expression (denoted as hORG expression matrix). The hORG expression matrix was subjected to Linear Models for Microarray Data (LIMMA) bioconductor library for identification of stage-transitive transcriptome changes, and self-organizing map combined with singular value decomposition (SOM-SVD) as well as SOM-based two-phase gene clustering for the topology-preserving extraction of temporal expression patterns. Hypergeometric distribution-based enrichment analyses were performed to explore the underlying biological relevance of gene groups of interest using diverse external annotated databases. The Cytoscape plug-in jActiveModules was modified to identify expression-active connected subnetworks in the compiled human interaction/association network.

Dataset Information

Expression data for mouse embryogenesis from oocyte to newborn

Publications

Global expression profiling reveals genetic programs underlying the developmental divergence between mouse and human embryogenesis.

Similar Datasets

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