scholarly journals Meta-analysis of gene expression profiles in granulosa cells during folliculogenesis

Reproduction ◽  
2016 ◽  
Vol 151 (6) ◽  
pp. R103-R110 ◽  
Author(s):  
Daulat Raheem Khan ◽  
Éric Fournier ◽  
Isabelle Dufort ◽  
François J Richard ◽  
Jaswant Singh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Granulosa Cell ◽  
Granulosa Cells ◽  
Expression Profiles ◽  
Post Partum ◽  
Meta Analysis ◽  
Expression Patterns ◽  
Comprehensive Overview ◽  
Experimental Conditions ◽  
Physiological Conditions

Abstract Folliculogenesis involves coordinated profound changes in different follicular compartments and significant modifications of their gene expression patterns, particularly in granulosa cells. Huge datasets have accumulated from the analyses of granulosa cell transcriptomic signatures in predefined physiological contexts using different technological platforms. However, no comprehensive overview of folliculogenesis is available. This would require integration of datasets from numerous individual studies. A prerequisite for such integration would be the use of comparable platforms and experimental conditions. The EmbryoGENE program was created to study bovine granulosa cell transcriptomics under different physiological conditions using the same platform. Based on the data thus generated so far, we present here an interactive web interface called GranulosaIMAGE (Integrative Meta-Analysis of Gene Expression), which provides dynamic expression profiles of any gene of interest and all isoforms thereof in granulosa cells at different stages of folliculogenesis. GranulosaIMAGE features two kinds of expression profiles: gene expression kinetics during bovine folliculogenesis from small (6 mm) to pre-ovulatory follicles under different hormonal and physiological conditions and expression profiles of granulosa cells of dominant follicles from post-partum cows in different metabolic states. This article provides selected examples of expression patterns along with suggestions for users to access and generate their own patterns using GranulosaIMAGE. The possibility of analysing gene expression dynamics during the late stages of folliculogenesis in a mono-ovulatory species such as bovine should provide a new and enriched perspective on ovarian physiology.

scholarly journals RankerGUI: A Computational Framework to Compare Differential Gene Expression Profiles Using Rank Based Statistics

2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Differential Gene Expression ◽  
Web Application ◽  
Cellular Response ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Experimental Conditions ◽  
Differential Gene

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.

scholarly journals Targeted Disruption of Mapk14 (p38MAPKα) in Granulosa Cells and Cumulus Cells Causes Cell-Specific Changes in Gene Expression Profiles that Rescue COC Expansion and Maintain Fertility

2010 ◽  
Vol 24 (9) ◽  
pp. 1794-1804 ◽  
Author(s):  
Zhilin Liu ◽  
Heng-Yu Fan ◽  
Yibin Wang ◽  
JoAnne S. Richards
Keyword(s):  
Gene Expression ◽  
Granulosa Cells ◽  
Knockout Mice ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Cumulus Cells ◽  
Mutant Mice ◽  
Prostaglandin E

Abstract MAPK14 (p38MAPKα) is critical for FSH and prostaglandin E (PGE)2 signaling cascades in granulosa cells (GCs) and cumulus cell-oocyte complexes (COCs) in culture, indicating that this kinase might impact follicular development and COC expansion in vivo. Because Mapk14 knockout mice are embryonic lethal, we generated GC specific Mapk14 knockout mice (Mapk14gc−/−) by mating Mapk14fl/fl and Cyp19-Cre mice. Unexpectedly, the Mapk14gc−/− female mice were fertile. Analyses of gene expression patterns showed that amphiregulin (Areg) and epiregulin (Ereg), two key regulators of ovulation and COC expansion, were up-regulated in the GCs but down-regulated in cumulus cells of the mutant mice in vivo. COCs from the mutant mice expanded and expressed matrix-related genes, if cultured with AREG, but not when cultured with forskolin or PGE2, the latter being a key factor regulating MAPK14 activity in cumulus cells. Conversely, when GCs from the Mapk14gc−/− mice were cultured with forskolin, they produced more Areg and Ereg mRNA than did wild-type GCs. These results indicate that disruption of Mapk14 selectively alters the expression of Areg and other genes in each cell type. Greater AREG and EREG produced by the GCs appears to by-pass and compensate for the critical need for MAPK14 signaling and induction of Areg/Ereg (and hence matrix genes) by PGE2 in cumulus cells of the mutant mice. In conclusion, although MAPK14 is not overtly essential for preovulatory follicle development or events associated with ovulation and luteinization in vivo, it does impact gene expression profiles.

scholarly journals Open TG-GATEs: a large-scale toxicogenomics database

2014 ◽  
Vol 43 (D1) ◽  
pp. D921-D927 ◽  
Author(s):  
Yoshinobu Igarashi ◽  
Noriyuki Nakatsu ◽  
Tomoya Yamashita ◽  
Atsushi Ono ◽  
Yasuo Ohno ◽  
...  
Keyword(s):  
Gene Expression ◽  
Drug Safety ◽  
Evaluation System ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Comprehensive Overview ◽  
Experimental Conditions ◽  
The Public ◽  
Target Organs

Abstract Toxicogenomics focuses on assessing the safety of compounds using gene expression profiles. Gene expression signatures from large toxicogenomics databases are expected to perform better than small databases in identifying biomarkers for the prediction and evaluation of drug safety based on a compound's toxicological mechanisms in animal target organs. Over the past 10 years, the Japanese Toxicogenomics Project consortium (TGP) has been developing a large-scale toxicogenomics database consisting of data from 170 compounds (mostly drugs) with the aim of improving and enhancing drug safety assessment. Most of the data generated by the project (e.g. gene expression, pathology, lot number) are freely available to the public via Open TG-GATEs (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System). Here, we provide a comprehensive overview of the database, including both gene expression data and metadata, with a description of experimental conditions and procedures used to generate the database. Open TG-GATEs is available from https://toxico.nibiohn.go.jp/english/index.html.

scholarly journals Meta-Analysis of RNA-Seq Studies Reveals Genes With Dominant Functions During Flower Bud Endo- To Eco-Dormancy Transition in Prunus Species

2021 ◽  
Author(s):  
Monica Canton ◽  
Cristian Forestan ◽  
Claudio Bonghi ◽  
Serena Varotto
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Fruit Trees ◽  
Day Length ◽  
Specific Gene ◽  
Flower Buds ◽  
Flower Bud

Abstract In deciduous fruit trees, entrance into dormancy occurs in later summer/fall, concomitantly with the shortening of day length and decrease in temperature. Dormancy can be divided into endodormancy, ecodormancy and paradormancy. In Prunus species flower buds, entrance into the dormant stage occurs when the apical meristem is partially differentiated; during dormancy, flower verticils continue their growth and differentiation. Each species and/or cultivar requires exposure to low winter temperature followed by warm temperatures, quantified as chilling and heat requirements, to remove the physiological blocks that inhibit budburst. A comprehensive meta-analysis of transcriptomic studies on flower buds of sweet cherry, apricot and peach was conducted, by investigating the gene expression profiles during bud endo- to ecodormancy transition in genotypes differing in chilling requirements. Conserved and distinctive expression patterns were observed, allowing the identification of gene specifically associated with endodormancy or ecodormancy. In addition to the MADS-box transcription factor family, hormone-related genes, chromatin modifiers, macro- and micro-gametogenesis related genes and environmental integrators, were identified as novel biomarker candidates for flower bud development during winter in stone fruits. In parallel, flower bud differentiation processes were associated to dormancy progression and termination and to environmental factors triggering dormancy phase-specific gene expression.

scholarly journals Granulosa cell biomarkers to predict pregnancy in ART: pieces to solve the puzzle

Reproduction ◽  
2017 ◽  
Vol 153 (2) ◽  
pp. R69-R83 ◽  
Author(s):  
Richard J Kordus ◽  
Holly A LaVoie
Keyword(s):  
Gene Expression ◽  
Granulosa Cell ◽  
Live Birth ◽  
Granulosa Cells ◽  
Expression Profiles ◽  
Ovarian Follicle ◽  
Critical Discussion ◽  
Developmental Competence ◽  
Published Data

Cumulus and mural granulosa cells of the ovarian follicle surround and interact with the developing oocyte. These follicular cells reflect the oocyte’s overall health and may indicate subsequent developmental competence of embryos. Biomarkers of granulosa cells associated with individual oocytes could potentially be used in assisted reproduction to indicate which embryos have the best chance of implanting in the uterus and completing gestation. In this review, we have performed a comprehensive assessment of the recent literature for human cumulus and mural granulosa cell mRNA biomarkers as they relate to pregnancy and live birth. A critical discussion of variables affecting granulosa gene expression profiles for in vitro fertilization patients, including patient demographics and ovarian stimulation regimens, is presented. Although studies with microarray data were evaluated, this synopsis focuses on expressed genes that have been validated by quantitative RT-PCR. Furthermore, we summarize the current published data that support or refute identified granulosa expressed genes as potential biomarkers of embryos that give rise to ongoing pregnancy and live birth. Finally, we review studies that offer predictive models for embryo selection for uterine transfer based on biomarkers that show differential gene expression.

scholarly journals Meta-Analysis of Hypoxic Transcriptomes from Public Databases

Biomedicines ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 10 ◽  
Author(s):  
Hidemasa Bono ◽  
Kiichi Hirota
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Data Driven ◽  
Transcriptome Data ◽  
Rna Seq ◽  
Experimental Conditions ◽  
Oxygen Homeostasis ◽  
Before And After

Hypoxia is the insufficiency of oxygen in the cell, and hypoxia-inducible factors (HIFs) are central regulators of oxygen homeostasis. In order to obtain functional insights into the hypoxic response in a data-driven way, we attempted a meta-analysis of the RNA-seq data from the hypoxic transcriptomes archived in public databases. In view of methodological variability of archived data in the databases, we first manually curated RNA-seq data from appropriate pairs of transcriptomes before and after hypoxic stress. These included 128 human and 52 murine transcriptome pairs. We classified the results of experiments for each gene into three categories: upregulated, downregulated, and unchanged. Hypoxic transcriptomes were then compared between humans and mice to identify common hypoxia-responsive genes. In addition, meta-analyzed hypoxic transcriptome data were integrated with public ChIP-seq data on the known human HIFs, HIF-1 and HIF-2, to provide insights into hypoxia-responsive pathways involving direct transcription factor binding. This study provides a useful resource for hypoxia research. It also demonstrates the potential of a meta-analysis approach to public gene expression databases for selecting candidate genes from gene expression profiles generated under various experimental conditions.

scholarly journals Targeted Disruption of Mapk14 (p38MAPKα) in Granulosa Cells and Cumulus Cells Causes Cell-Specific Changes in Gene Expression Profiles that Rescue Cell-Oocyte Complex Expansion and Maintain Fertility

2010 ◽  
Vol 31 (4) ◽  
pp. 606-606
Author(s):  
Zhilin Liu ◽  
Heng-Yu Fan ◽  
Yibin Wang ◽  
JoAnne S. Richards
Keyword(s):  
Gene Expression ◽  
Granulosa Cells ◽  
Knockout Mice ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Cumulus Cells ◽  
Mutant Mice ◽  
Prostaglandin E

Abstract MAPK14 (p38MAPKα) is critical for FSH and prostaglandin E (PGE)2 signaling cascades in granulosa cells (GCs) and cumulus cell-oocyte complexes (COCs) in culture, indicating that this kinase might impact follicular development and COC expansion in vivo. Because Mapk14 knockout mice are embryonic lethal, we generated GC specific Mapk14 knockout mice (Mapk14gc−/−) by mating Mapk14fl/fl and Cyp19a1-Cre mice. Unexpectedly, the Mapk14gc−/− female mice were fertile. Analyses of gene expression patterns showed that amphiregulin (Areg) and epiregulin (Ereg), two key regulators of ovulation and COC expansion, were up-regulated in the GCs but down-regulated in cumulus cells of the mutant mice in vivo. COCs from the mutant mice expanded and expressed matrix-related genes, if cultured with AREG, but not when cultured with forskolin or PGE2, the latter being a key factor regulating MAPK14 activity in cumulus cells. Conversely, when GCs from the Mapk14gc−/− mice were cultured with forskolin, they produced more Areg and Ereg mRNA than did wild-type GCs. These results indicate that disruption of Mapk14 selectively alters the expression of Areg and other genes in each cell type. Greater AREG and EREG produced by the GCs appears to by-pass and compensate for the critical need for MAPK14 signaling and induction of Areg/Ereg (and hence matrix genes) by PGE2 in cumulus cells of the mutant mice. In conclusion, although MAPK14 is not overtly essential for preovulatory follicle development or events associated with ovulation and luteinization in vivo, it does impact gene expression profiles.

scholarly journals Meta-analysis of hypoxic transcriptomes from public databases

2018 ◽  
Author(s):  
Hidemasa Bono ◽  
Kiichi Hirota
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Data Driven ◽  
Transcriptome Data ◽  
Rna Seq ◽  
Experimental Conditions ◽  
Oxygen Homeostasis ◽  
Before And After

AbstractHypoxia is the insufficiency of oxygen in the cell, and hypoxia-inducible factors (HIFs) are central regulators of oxygen homeostasis. In order to obtain functional insights into the hypoxic response in a data-driven way, we attempted a meta-analysis of the RNA-seq data from the hypoxic transcriptomes archived in public databases. In view of methodological variability of archived data in the databases, we first manually curated RNA-seq data from appropriate pairs of transcriptomes before and after hypoxic stress. These included 128 human and 52 murine transcriptome pairs. We classified the results of experiments for each gene into three categories: upregulated, downregulated, and unchanged. Hypoxic transcriptomes were then compared between humans and mice to identify common hypoxia-responsive genes. In addition, meta-analyzed hypoxic transcriptome data were integrated with public ChIP-seq data on the known human HIFs HIF-1 and HIF-2 to provide insights into hypoxia-responsive pathways involving direct transcription factor binding. This study provides a useful resource for hypoxia research. It also demonstrates the potential of a meta-analysis approach to public gene expression databases for selecting candidate genes from gene expression profiles generated under various experimental conditions.

scholarly journals Meta-analysis of RNA-Seq studies reveals genes with dominant functions during flower bud endo- to eco-dormancy transition in Prunus species

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Monica Canton ◽  
Cristian Forestan ◽  
Claudio Bonghi ◽  
Serena Varotto
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Fruit Trees ◽  
Day Length ◽  
Specific Gene ◽  
Flower Buds ◽  
Flower Bud

AbstractIn deciduous fruit trees, entrance into dormancy occurs in later summer/fall, concomitantly with the shortening of day length and decrease in temperature. Dormancy can be divided into endodormancy, ecodormancy and paradormancy. In Prunus species flower buds, entrance into the dormant stage occurs when the apical meristem is partially differentiated; during dormancy, flower verticils continue their growth and differentiation. Each species and/or cultivar requires exposure to low winter temperature followed by warm temperatures, quantified as chilling and heat requirements, to remove the physiological blocks that inhibit budburst. A comprehensive meta-analysis of transcriptomic studies on flower buds of sweet cherry, apricot and peach was conducted, by investigating the gene expression profiles during bud endo- to ecodormancy transition in genotypes differing in chilling requirements. Conserved and distinctive expression patterns were observed, allowing the identification of gene specifically associated with endodormancy or ecodormancy. In addition to the MADS-box transcription factor family, hormone-related genes, chromatin modifiers, macro- and micro-gametogenesis related genes and environmental integrators, were identified as novel biomarker candidates for flower bud development during winter in stone fruits. In parallel, flower bud differentiation processes were associated to dormancy progression and termination and to environmental factors triggering dormancy phase-specific gene expression.

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