Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of Bubalus bubalis periovulatory follicle

ABSTRACT: Gonadotropin surge acts on the preovulatory follicle of the ovary to induce luteinization of follicular cells, oocyte meiotic maturation, cumulus expansion and follicular rupture leading to ovulation. These processes are brought about by spatial and temporal changes in transcriptional regulation of genes in the follicular cells in response to the gonadotropin surge. Analysis of gene expression changes in the periovulatory follicular cells will help in delineating the signal transduction pathways involved in the above mentioned processes. In monoovulatory species like bovines, the time interval of 24-28 hours between gonadotropin surge and ovulation provides distinct advantage for studying the temporal changes in the gene expression pattern. Thus, in the present study, we attempt to identify the temporal changes in the global gene expression profile in the periovulatory follicle of buffalo cows in response to gonadotropin surge and the results suggest the involvement of Insulin-like Growth Factor 1 and cytokine signaling pathways in the periovulatory events. Experiment Overall Design: To study the periovulatory gene expression changes in buffalo cows, an induced-ovulation model system involving sequential treatment with PGF2alpha and GnRH was standardized. The follicular wave containing at least one large follicle of ~7mm size was determined by ultrasonography on day 7 of the estrous cycle before administering exogenous PGF2alpha to induce luteolysis and follicular growth. Exogenous GnRH (100Âµg i.m) was administered 36h post PGF2alpha to induce LH surge. The time course of increase in LH levels post GnRH injection was monitored. Since peak LH levels are attained 2 h post GnRH administration, the time intervals of 3 h post GnRH (corresponding to1 h post LH surge) and 24 h post GnRH (corresponding to 22 h post LH surge) were chosen to identify the gene expression profile associated with immediate early and delayed changes in periovulatory follicle respectively. Thus ovaries were collected before, 1 h and 22 h post LH surge and follicle wall and granulosa cells were isolated from the ovaries and snap frozen for the purpose of RNA isolation.

ORGANISM(S): Bubalus bubalis

SUBMITTER: jyotsna rao

PROVIDER: E-GEOD-11312 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Direct exposure to physiologically-relevant elevated temperatures during the first half of in vitro maturation heightens cumulus-derived progesterone production, suppresses matrix metallopeptidase 9 secretion, and alters cumulus transcriptome. We hypothesized that heat-induced perturbations in cumulus cells enveloping maturing oocyte may extend to the mural granulosa of the periovulatory follicle in the heat-stressed cow to subsequently follicular fluid proteome. Lactating Holsteins were pharmacologically stimulated to produce a dominant follicle then given GnRH to induce an LH surge. Following GnRH administration, cows were maintained at ~67 temperature humidity index (THI; thermoneutral conditions) or exposed to conditions simulating an acute heat stress event (71 to 86 THI; heat stress for ~12 h). Fluid was aspirated from periovulatory follicle ~16 h after GnRH. Follicular fluid proteome from thermoneutral (n = 5) and hyperthermic (n = 5) cows was evaluated by quantitative tandem mass spectrometry (nano LC-MS/MS). We identified 35 differentially-abundant proteins. Functional annotation revealed numerous immune-related proteins. Subsequent efforts revealed an increase in levels of the proinflammatory mediator bradykinin in follicular fluid (P = 0.0456) but not in serum (P = 0.9319) of hyperthermic cows. Intrafollicular increases in transferrin (negative acute phase protein) in hyperthermic cows (P = 0.0181) coincided with a tendency for levels to be increased in the circulation (P = 0.0683). Nine out of 15 cytokines evaluated were detected in follicular fluid. Heat stress increased intrafollicular IL6 levels (P = 0.0160). Whether hyperthermia-induced changes in the heat-stressed cow’s follicular fluid milieu reflect changes in mural granulosa, cumulus, other cell types secretions, and/or transudative changes from circulation remains unclear. Regardless of origin, heat stress/hyperthermia related changes in the follicular fluid milieu may have an impact on components important for ovulation and competence of the cumulus-oocyte complex contained within the periovulatory follicle

Project description:The molecular mechanisms that regulate the pivotal transformation processes observed in the follicular wall following the pre-ovulatory LH-surge, are still not established, particularly for cells of the thecal layer. To elucidate thecal and granulosa cell type-specific biological functions and signaling pathways, large dominant bovine follicles were collected before and 21 hrs after an exogenous GnRH induced LH surge. Because LH receptor density varies within the granulosa cell populations, antral granulosa (aGC; those aspirated by follicular puncture) and membrane associated granulosa (mGC; those scraped from the follicular wall) were compared to thecal cell expression profiles determined by mRNA microarrays. Thecal cell gene expression was less affected in the peri-ovulatory follicle when compared to granulosa cells, as evidenced by only 2% versus 25% of the ~11,000 genes expressed changing in response to the LH surge, respectively. The majority of the 203 LH-regulated thecal genes were also LH regulated in granulosa cells, leaving a total of 58 genes as LH-regulated theca cell specific genes. Most of the 58 genes (i.e., 74%) thecal specific genes including several known thecal markers (CYP17A1, NR5A1) were downregulated, while most genes identified are new to theca. Many of the newly identified upregulated thecal genes (e.g., PTX3, RND3, PPP4R4) were also upregulated in granulosa. Minimal expression differences were observed between aGC and mGC, however, transcripts encoding extracellular proteins (NID2) and matrix modulators (ADAMTS1, SASH1) predominated these differences. We also identified large numbers of unknown LH-regulated granulosa cell genes and discuss their putative roles in ovarian function. The single dominant ovarian follicle was collected from each cow before the LH surge or 22 hours after GnRH (used to induce LH surge). RNA was extracted from three independent cells within each follicle and there were hybridized on Affymetrix microarrays.

Project description:Purpose: Preovualtory follicle diameter influences embryo quality in beef cattle that rely on a gonadotropin releasing hormone (GnRH) injection to induce the preovualtory gonadotropin surge and subsequent ovualtion. The goals of this study are to compare transcriptome profiles of pools of four oocytes or associated cumulus cells collected from small (≤11.7mm) and large follicles (≥12.7 mm) exposed to a GnRH-induced gonadotropin surge and follicles (11.7-14.0 mm) exposed to an endogenous gonadotropin surge (spontaneous follicles). Methods: Oocyte and cumulus cell mRNA profiles of pools of four oocytes or associated cumulus cells collected from small (≤11.7mm) and large follicles (≥12.7 mm) exposed to a GnRH-induced gonadotropin surge or spontaneous follicles (11.7-14.0 mm) which were exposed to an endogenous gonadotropin surge were generated by deep sequencing (n=6 small follicle oocyte, 6 small follicle cumulus, 6 large follicle oocyte, 6 large follicle cumulus, 4 spontaneous follcile oocyte, and 5 spontaneous follicle cumulus pools), using Illumina HiSeq 2000 . The sequence reads that passed quality filters were aligned to the Bos taurus reference genome UMD3.1 using Hisat2mapper. FeatureCounts was used to quantify transcript abundance in each library using Bos taurus gene annotation from Ensembl. Differences in gene transcript expression were then analyzed amoung oocyte or cumulus cell follcile classifications using the packages edgeR and DESeq2 in R software. Results: We mapped an average of 30 million sequence reads per sample to the Bos taurus reference genome UMD3.1 and identified 69, 94, and 83 differentially expressed gene transcripts (DEG) among oocyte libraries from small versus large, small versus spontaneous, and large versus spontaneous follicle classifications, respectively. We also identified 128, 98, and 80 DEG among cumulus cell libraries from small versus large, small versus spontaneous, and large versus spontaneous follicles, respectively. Conclusions: Our study represents detailed analysis of RNA-sequencing data generated from in vivo produced cumulus and oocyte samples collected from preovualtory follicles of varied physiological status after exposure to an endogenous or exogenously stimulated gonadotropin surge. The results of our study highlight key differences in the transcriptome of samples from small, large, or spontaneous follicles and provide insight into the reduced embryo quality observed when small follicles undergo a GnRH induced gonadotropin surge.

Project description:Roblitz2013 - Menstrual Cycle following GnRH analogue administration The model describes the menstrual cycle feedback mechanisms. GnRH, FSH, LH, E2, P4, inbibins A and B, and follicular development are modelled. The model predicts hormonal changes following GnRH analogue administration. Simulation results agree with measurements of hormone blood concentrations. The model gives insight into mechanisms underlying gonadotropin supression. This model is described in the article: A mathematical model of the human menstrual cycle for the administration of GnRH analogues. Röblitz S, Stötzel C, Deuflhard P, Jones HM, Azulay DO, van der Graaf PH, Martin SW. J. Theor. Biol. 2013 Mar; 321: 8-27 Abstract: The paper presents a differential equation model for the feedback mechanisms between gonadotropin-releasing hormone (GnRH), follicle-stimulating hormone (FSH), luteinizing hormone (LH), development of follicles and corpus luteum, and the production of estradiol (E2), progesterone (P4), inhibin A (IhA), and inhibin B (IhB) during the female menstrual cycle. Compared to earlier human cycle models, there are three important differences: The model presented here (a) does not involve any delay equations, (b) is based on a deterministic modeling of the GnRH pulse pattern, and (c) contains less differential equations and less parameters. These differences allow for a faster simulation and parameter identification. The focus is on modeling GnRH-receptor binding, in particular, by inclusion of a pharmacokinetic/pharmacodynamic (PK/PD) model for a GnRH agonist, Nafarelin, and a GnRH antagonist, Cetrorelix, into the menstrual cycle model. The final mathematical model describes the hormone profiles (LH, FSH, P4, E2) throughout the menstrual cycle of 12 healthy women. It correctly predicts hormonal changes following single and multiple dose administration of Nafarelin or Cetrorelix at different stages in the cycle. This model is hosted on BioModels Database and identified by: BIOMD0000000494 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Transcription profiling of Bubalus bubalis periovulatory follicle

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