Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of mouse dormant and activated blastocysts

ABSTRACT: Delayed implantation occurs in many mammals, but the underlying mechanisms that direct this process remain largely unknown. In mice, ovariectomy prior to the preimplantation ovarian estrogen secretion on day 4 of pregnancy initiates blastocyst dormancy, which can be maintained for more than 200 days by continued progesterone treatment. An injection of estrogen activates blastocysts rapidly and makes them to implant in the progesterone-primed uterus. Recent establishment of a 60-mer oligo microarray platform, enriched for genes expressed in stem cells and early embryos including preimplantation embryos (7), fulfills this objective. With an optimized labeling reaction for a small amount of RNA with two rounds of cRNA linear amplification, we compared gene expression differences between dormant and activated blastocysts with validation of microarray data of several key genes at protein expression level using immunohistochemistry.

ORGANISM(S): Mus musculus

SUBMITTER: Minoru Ko

PROVIDER: E-MEXP-132 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Global gene expression analysis identifies molecular pathways distinguishing blastocyst dormancy and activation.

Hamatani Toshio T Daikoku Takiko T Wang Haibin H Matsumoto Hiromichi H Carter Mark G MG Ko Minoru S H MS Dey Sudhansu K SK

Proceedings of the National Academy of Sciences of the United States of America 20040701 28

Delayed implantation (embryonic diapause) occurs when the embryo at the blastocyst stage achieves a state of suspended animation. During this period, blastocyst growth is very slow, with minimal or no cell division. Nearly 100 mammals in seven different orders undergo delayed implantation, but the underlying molecular mechanisms that direct this process remain largely unknown. In mice, ovariectomy before preimplantation ovarian estrogen secretion on day 4 of pregnancy initiates blastocyst dorman ...[more]

PMID: 15232000

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Project description:Microarray data analysis Intensity of 21,939 gene features per array was extracted from scanned microarray images using Feature Extraction 5.1.1 software (Agilent Technologies), which performs background subtractions and dye normalization. This normalization method is targeted at detecting changes in relative expression of individual genes rather than global expression. Global expression change would require external normalization controls (van de Peppel et al., 2003). Text output was processed using an application developed in-house to perform ANOVA analysis (http://lgsun.grc.nia.nih.gov/ANOVA/). Intensity of features measured with a >50% error were replaced with missing values except features with very low intensity. Surrogate values equal to mean error were inserted for values that were negative or less than the probe error. Data were analyzed using ANOVA with embryonic stage as a factor. The small number of biological replications typical in expression profiling experiments results in a highly variable error variance, and this problem is usually addressed by log-ratio thresholds (Schena et al., 1995) that require subjective decisions about biological significance, or by Bayesian adjustment of error variance (Baldi and Long, 2001), which may still underestimate error variance and result in false positive results. To reduce false-positives, we opted for a very conservative error model in which error variance that is used for estimating F-statistics is the maximum of the actual error variance for this gene and the average error variance in 500 genes with similar average intensity. Statistical significance was determined using the False Discovery Rate (FDR = 10%) method (Benjamini and Hochberg, 1995). Pair-wise mean comparison was done with t-statistics and FDR=10%. Further data processing including scatter plots, hierarchical clustering, and principal component analysis (PCA) were also performed through NIA microarray analysis tool (http://lgsun.grc.nia.nih.gov/ANOVA/). The input file for NIA microarray analysis tool is available at http://lgsun.grc.nia.nih.gov/microarray/data.html

Project description:Feature Extraction 5.1.1 software (Agilent Technologies) performs background subtractions and dye normalization. This normalization method is targeted at detecting changes in relative expression of individual genes rather than global expression. Global expression change would require external normalization controls (van de Peppel et al., 2003). Text output was processed using an application developed in-house to perform ANOVA analysis (http://lgsun.grc.nia.nih.gov/ANOVA/). Intensity of features measured with a >50% error were replaced with missing values except features with very low intensity. Surrogate values equal to mean error were inserted for values that were negative or less than the probe error. Data were analyzed using ANOVA with embryonic stage as a factor. The small number of biological replications typical in expression profiling experiments results in a highly variable error variance, and this problem is usually addressed by log-ratio thresholds (Schena et al., 1995) that require subjective decisions about biological significance, or by Bayesian adjustment of error variance (Baldi and Long, 2001), which may still underestimate error variance and result in false positive results. To reduce false-positives, we opted for a very conservative error model in which error variance that is used for estimating F-statistics is the maximum of the actual error variance for this gene and the average error variance in 500 genes with similar average intensity. Statistical significance was determined using the False Discovery Rate (FDR = 10%) method (Benjamini and Hochberg, 1995). Pair-wise mean comparison was done with t-statistics and FDR=10%. Further data processing including scatter plots, hierarchical clustering, and principal component analysis (PCA) were also performed through NIA microarray analysis tool (http://lgsun.grc.nia.nih.gov/ANOVA/). Details are described in the publication (Hamatani T. et al., Developmental Cell. Published online Dec. 18, 2003).

Project description:Postplasmic/PEM RNAs constitute a large class of cortical maternal RNAs with include at least 2 determinants (Macho1 and PEM1) involved in muscle differentiation, unequal cleavage and posterior patterning of the embryo. Two main classes have been defined - type I (localized in oocytes) and type II (localizing in embryos). Based on the fact that Vasa RNA - the only type II recognized in Ciona - segregates into B8.12 (germ) and sister B8.11 cells, while many others (including Macho1 and PEM1) segregate only into B8.11 (somatic) cells a first attempts at re-classifying these RNAs has been made. We have analyzed the associations of postplasmic/PEM RNAs with cortical structures in 2 ascidians species Ciona intestinalis and Phallusia mammillata using: - very high resolution fluorescent in situ hybridization localization in eggs and embryos and in their cortical fragments, - comparisons of RNAs extracted from whole oocytes and from isolated cortices using microarray analysis â screening of the Ciona intestinalis genome for the presence in 3â UTR regions of repeats containing the tri-nucleotide CAC motif (xCACx) followed by localization of xCACx rich RNAs using in situ hybridization. Based on our combined approaches we observe that: - 1) the vast majority of Ciona intestinalis postplasmic/PEM RNAs (including Ci-Vasa) are cortically localized in the eggs (type I) - 2) postplasmic/PEM RNAs are much more likely to contain xCACx motifs in their 3âUTR than other transcripts. Using this criterion we have found 2 new postplasmic/PEM RNAs: MnK and PSD - 3) some postplasmic/PEM RNAs are anchored to cER while others are located into granules. We therefore come to the conclusion that there are at least 2 distinct categories of postplasmic/PEM RNAs based on their cortical anchorage and cell fate: I) cER sub-domain associated postplasmic/PEM RNAs (Macho1 like) which segregate in the somatic B8.11 cells. II) postplasmic/PEM RNAs associated with (putative germ) granules (Vasa like) which in addition to B8.11 cells segregate into B8.12 germ cells. Two kinds of sample, Dye Swap design with 2 arrays

Dataset Information

Transcription profiling of mouse dormant and activated blastocysts

Publications

Global gene expression analysis identifies molecular pathways distinguishing blastocyst dormancy and activation.

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