Unknown,Transcriptomics,Genomics,Proteomics

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Identification of discriminant genes and gene networks involved in pig ovarian follicular atresia

ABSTRACT: Folliculogenesis corresponds to the development of follicles leading to either ovulation or degeneration (a process called atresia). Even if atresia involves an apoptosis process, this mechanism is not well understood. The objective of this experiment was : 1) to analyse gene expression in pig granulosa cells of ovarian follicles during atresia using transcriptome analysis with a 9 024 cDNAs microarray, 2) the identification of gene networks involved in pig ovarian follicular atresia. Granulosa cells were isolated from atretic follicles (small, medium or large). Gene expression was analysed by hybridization of nylon cDNA microarrays. The images were quantified using Bzscan software and the data were managed with BASE software. Statistical analysis was performed using R software. Keywords: pig ovary, folliculogenesis, atresia, gene expression, cDNA microarray, bio-analysis Calibrated follicles were isolated from porcine ovaries after ovariectomy (24h ou 96h after the end of progestagen treatment: Regumate 18 days, 20 mg/days). The follicular status was determined by histological criteria using Feulgen coloration (Monget et al. 1993, Besnard et al. 1996). Healthy follicle is characterized by frequent mitosis and pyknosis absence in granulosa cells. Presence of frequent pyknotic bodies in granulosa cells and no mitosis were allocated to atretic cells. Two cross-classified biological factors of pig ovarian follicles are considered : 1) the stage of development of the follicular growth : small (1-2 mm of diameter), medium (3 mm) and large (>5 mm) follicles; 2) the follicular status: healthy (S1) vs beginning (A2) or advanced (A3) atresia. Gene expression was analysed by hybridization of nylon cDNA microarrays (GPL3729). After hybridisation the data analysis using BASE software and statistical analysis was performed to identify regulated genes. For each of three follicle class and three follicle status combination 4 biological replicates were considered. Total 36 membranes were first hybridized with a vector oligonucleotide labeled (T7 probe 5'-taatacgactcactataggga-3') with gamma33P ATP at 42Â°C during 12h to determine the quality of the spotting process. After being washed, the arrays were exposed 6 or 24 hours to radioisotopic-sensitive imaging plates (BAS-2025, Fujifilm, Raytest France S.A.R.L., Courbevoie, France). The imaging plates were scanned thereafter with a phosphor imaging system at a 25 ÃÂµm resolution (BAS-5000, Fujifilm, Raytest France S.A.R.L., Courbevoie, France). Data were acquired with help of a microarray image processing software - AGScan (Cathelin, 2006, http://mulcyber.toulouse.inra.fr/projects/agscan/). Fixed circle segmentation, i.e. a grid process with a fixed spot diameter was applied. The hybridization images were quantified by the extraction of the intensity for each spot. Arrays images and data were stored using BASE software (Saal LH, Troein C, Vallon-Christersson J, Gruvberger S, Borg A, and Peterson C. BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data. Genome Biol 3: SOFTWARE0003, 2002) adapted by Sigenae (http://www.sigenae.org) for analysis and storage of radioactitive microarray data

ORGANISM(S): Sus scrofa

SUBMITTER: Agnes Bonnet

PROVIDER: E-GEOD-7635 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:In mammals, ovarian folliculogenesis leading to the ovulation of completely mature oocytes is a long and complex process that is regulated at different levels. The mechanisms that underlie the selection of one or several dominant follicles as well as the regulation of the number of ovulating follicles are largely unknown. In this project, we proposed to study the genetic determinism that underlies the difference of ovulation rate between species (cattle and pigs), by studying two processes that exist in ovary: follicular development and follicular atresia. Towards this purpose, we made a comparative transcriptomics study on granulosa cells. Pig and cattle comparison was achieved by a transcriptome analysis with a 9K nylon pig microarray (GPL3729) on granulosa cells from either small healthy antral follicles (SHF), small atretic follicles (SAF) or large healthy antral follicles (LHF). The images were quantified using AGscan software and the data were managed with BASE software. Statistical analysis was performed using R software. Transcriptomic analysis on pig and cattle evidenced 997 differentially expressed genes (FDR1%) between the three follicle classes and/or the two species. This research project which implicated three laboratories from INRA: "Laboratoire de Genetique Cellulaire" (UMR444-LGC) , "Station d'Amelioration Genetique des Animaux" (UR 631-SAGA) and "Physiologie des Comportements et de la reproduction" (UMR 85-PRC) benefited from both European funding through SABRE project and French ANR funding through GenOvul project. Keywords: transcriptome analysis, pig, cattle, ovary, folliculogenesis, gene expression, cDNA microarray The data were obtained from 34 RNA samples: 10 small healthy follicles samples (6 for sows and 4 for cows), 13 small atretic follicles samples (7 for sows and 6 for cows) and 11 samples for large healthy follicles (6 for sows and 5 for cows). They were hybridized on a 9K pig nylon microarray (GPL3729).

Project description:The aim of this study is the identification of genes and gene networks involved in pig ovarian follicular development. cDNA nylon micro-arrays (2849 sequenced clones) were designed from different libraries : four subtractive suppressive hybridization libraries (generated from small versus large and small versus medium follicles) and a pig multi-tissue cDNA library. Granulosa cells were isolated from healthy follicles (small, medium or large), 24 h or 96 h after the end of a progestagen treatment. The RNA isolated from these cells was used to hybridize the micro-arrays and hybridisations were performed in duplicate. The images were quantified using Bzscan software and the data were managed with BASE software. Statistical analysis was performed using R software. Keywords: cell type comparison Granulosa cells were isolated from healthy follicles (small, medium or large). The RNA isolated from these cells was used to hybridize nylon micro-arrays. The arrays contained PCR products from 2848 pig cDNA clones (GPL3978), spotted in duplicate on two separate fields of the same membrane (last number 1 of the local ID corresponds to the left field and 2 corresponds to right field). The data have been generated from 14 RNA follicle pools (five Large, five Medium and four Small follicles pools). For each follicle pool, 2 radioactive labellings were performed (before last number of the local ID corresponds to the duplicate number). Each membrane was exposed 6, 12 or 24 hours (depending on the saturation signal) to radioisotopic-sensitive imaging plates (BAS-2025, Fujifilm, Raytest France S.A.R.L., Courbevoie, France). The imaging plates were scanned thereafter with a phosphor imaging system at a 25 µm resolution (BAS-5000, Fujifilm, Raytest France S.A.R.L., Courbevoie, France). The images were quantified using semi-automated software, BZScan (Lopez F, Rougemont J, Loriod B, Bourgeois A, Loi L, Bertucci F, Hingamp P, Houlgatte R, and Granjeaud S. Feature extraction and signal processing for nylon DNA microarrays. BMC Genomics 5: 38, 2004). Fixed circle segmentation, i.e. a grid process with a fixed spot diameter was applied. The hybridization images were quantified by the extraction of the intensity for each spot. A new version of BZsan (AGscan solfware) is available at : http://mulcyber.toulouse.inra.fr/projects/agscan/ The experimental data were managed using the free BASE software (Saal LH, Troein C, Vallon-Christersson J, Gruvberger S, Borg A, and Peterson C. BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data. Genome Biol 3: SOFTWARE0003, 2002.) modified by Sigenae team to accept radioactive experiments. Finally, data consisted in (14 RNA x 2 labellings x 2 fields) 14 probes, 28 hybridisations, 42 images (14 images were filtred out for background too hight).

Project description:These vector oligonucleotide hybridizations were performed to determine the quality of the spotting process. EST with low signal values of the vector array were excluded from the analysis, since they probably were mis-amplified or mis-spotted Keywords: spotting control cDNA arrays (GPL3978) were first hybridized with a vector oligonucleotide labeled (T7 probe) with 33P-ATP. After washing, the arrays were exposed 6 hours to radioisotopic-sensitive imaging plates (BAS-2025, Fujifilm, Raytest France S.A.R.L., Courbevoie, France). The imaging plates were scanned thereafter with a phosphor imaging system at a 25 µm resolution (BAS-5000, Fujifilm, Raytest France S.A.R.L., Courbevoie, France). The images were quantified using semi-automated software, BZScan (Lopez F, Rougemont J, Loriod B, Bourgeois A, Loi L, Bertucci F, Hingamp P, Houlgatte R, and Granjeaud S. Feature extraction and signal processing for nylon DNA microarrays. BMC Genomics 5: 38, 2004). Fixed circle segmentation, i.e. a grid process with a fixed spot diameter was applied. The hybridization images were quantified by the extraction of the intensity for each spot. A new version of BZsan (AGscan solfware) is available at : http://mulcyber.toulouse.inra.fr/projects/agscan/ The experimental data were managed using the free BASE software (Saal LH, Troein C, Vallon-Christersson J, Gruvberger S, Borg A, and Peterson C. BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data. Genome Biol 3: SOFTWARE0003, 2002.) modified by Sigenae team to accept radioactive experiments. After stripping, the arrays were hybridized with a complex target. The data correspond to the hybridization of the first membrane DEV-1 and the last one DEV-20. The arrays contained PCR products from 2848 pig cDNA clones (GPL3978), spotted in duplicate on two separate fields of the same membrane (last number 1 of the local ID corresponds to the left field and 2 corresponds to right field). Finally, data consisted in four data files and were used to delete clones with a bad quality of spotting.

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Identification of discriminant genes and gene networks involved in pig ovarian follicular atresia

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