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1. Comparison of five different RNA sources to examine the lactating bovine mammary gland transcriptome using RNA-Sequencing.

Author

Cánovas, Angela, Rincón, Gonzalo, Bevilacqua, Claudia, Islas-Trejo, Alma, Brenaut, Pauline, Hovey, Russell C, Boutinaud, Marion, Morgenthaler, Caroline, VanKlompenberg, Monica K, Martin, Patrice, and Medrano, Juan F

Subjects
Mammary Glands, Animal, Milk, Animals, Cattle, Transcription Factors, RNA, Sequence Analysis, RNA, Base Sequence, Lactation, Algorithms, Molecular Sequence Data, Transcriptome, Mammary Glands, Animal, Sequence Analysis
Abstract

The objective of this study was to examine five different sources of RNA, namely mammary gland tissue (MGT), milk somatic cells (SC), laser microdissected mammary epithelial cells (LCMEC), milk fat globules (MFG) and antibody-captured milk mammary epithelial cells (mMEC) to analyze the bovine mammary gland transcriptome using RNA-Sequencing. Our results provide a comparison between different sampling methods (invasive and non-invasive) to define the transcriptome of mammary gland tissue and milk cells. This information will be of value to investigators in choosing the most appropriate sampling method for different research applications to study specific physiological states during lactation. One of the simplest procedures to study the transcriptome associated with milk appears to be the isolation of total RNA directly from SC or MFG released into milk during lactation. Our results indicate that the SC and MFG transcriptome are representative of MGT and LCMEC and can be used as effective and alternative samples to study mammary gland expression without the need to perform a tissue biopsy.

Published
2014

2. Importance du phénotypage pour maintenir la précision des prédictions génomiques des caractères mesurés en station

Author

Carillier-Jacquin, Céline, Bouquet, Alban, BRENAUT, Pauline, Simon, Chris, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Institut du Porc (IFIP)

Subjects
[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], phénotypage, génétique, génomique, porc
Abstract

National audience; Genomic evaluation of French maternal lines, set up in 2016, has helped increase genetic progress, especially for reproductive traits. However, computational problems have emerged for genomic evaluation of certain production traits for which phenotyping capacity is limited. This particularly concerns genotyped candidates on breeding farms that have no phenotypes and only a few phenotyped relatives. This data structure seems to pose convergence problems for predicting genomic breeding values. To check this hypothesis, we simulated such a situation, based on a set of actual phenotype data measured for all farm candidates and genotypes. The simulation consisted of deleting phenotypes of the animals measured on-farm in order to reproduce the data structure encountered for the traits recorded at the FGPorc/INRAE test station in Le Rheu. Phenotypes were then progressively added in different scenarios to identify whether prediction accuracy improved and to estimate the number of phenotypes required. The simulations showed that the unbalanced structure between genotypes and phenotypes was responsible for the computational problems that led to low accuracy of genomic predictions. Phenotyping 12% of all pigs phenotyped at 100 kg each year made it possible to solve the computational problems observed and to recover 61% of the maximum expected accuracy. In conclusion, these results highlight the importance of collecting large-scale phenotypes in the context of genomic selection schemes. Further studies will be conducted to study the impact of genotyping animals measured at the station.

Published
2020

3. Utilisation d’une puce très basse densité (1 100 SNP) pour la sélection génomique chez 3 races porcines françaises

Author

Carillier-Jacquin, Céline, Bouquet, Alban, Labrune, Yann, BRENAUT, Pauline, Riquet, Juliette, Larzul, Catherine, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Institut du Porc (IFIP)

Subjects
[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], sélection, génétique, génomique
Abstract

National audience; To reduce genotyping costs for genomic selection, a Low-Density SNP (LD) chip, designed in 2016, is now used routinely. This panel is composed of approximately 1100 equidistant SNPs. The relevance of this chip has been studied in French populations of the Landrace, Large White and Pietrainpig breeds. The quality of imputation was estimated by the correlation between actual and imputed genotypes and error rates. The impact of imputation on the genomic evaluations was estimatedby the correlation between the genomic values obtained for the candidates with imputed genotypes, and those obtained with the high-densitygenotypes. Average error rates of imputation estimated on all the chromosomes were 0.03, 0.11 and 0.14for Landrace, Large White and Pietrain, respectively. The estimated correlations between actual and imputed genotypes were relativelyhigh at 0.93, 0.92 and 0.88forLandrace, Large White and Pietrain populations,respectively. Correlations between genomicbreedingvalues predicted with high-density genomicdata or imputed genomic data from the LD SNP panel rangedfrom0.89-0.97 for Large White and Landrace populations for reproductivetraits. They were higher than those obtained for the Pietrain population (0.80and 0.97for production traits, respectively). In conclusion, despite the limited number of SNPs on the low-density panel used in this study, the imputation accuracyis sufficient to use the imputed genotypes in the genomic evaluations. In practice, genotyping candidates with aLD chip is a solution for selecting future breeding pigsat lower cost.

Published
2020

4. Utilisation d’une puce très basse densité (1 100 SNP) pour la sélection génomique chez 3 races de porcs françaises

Author

Carillier-Jacquin, Céline, Bouquet, Alban, Labrune, Yann, BRENAUT, Pauline, Larzul, Catherine, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut du Porc, Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Institut du Porc (IFIP)

Subjects
[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], génotypage, sélection, imputation, porc, génomique, Autre (Sciences du Vivant)
Abstract

To reduce genotyping costs for genomic selection, a Low-Density SNP (LD) chip, designed in 2016, is now used routinely. This panel is composed of approximately 1 100 equidistant SNPs. The relevance of this chip has been studied in French populations of the Landrace, Large White and Pietrain pig breeds. The quality of imputation was estimated by the correlation between actual and imputed genotypes and error rates. The impact of imputation on the genomic evaluations was estimated by the correlation between the genomic values obtained for the candidates with imputed genotypes, and those obtained with the high-density genotypes. Average error rates of imputation estimated on all the chromosomes were 0.03, 0.11 and 0.14 for Landrace, Large White and Pietrain, respectively. The estimated correlations between actual and imputed genotypes were relatively high at 0.93, 0.92 and 0.88 forLandrace, Large White and Pietrain populations, respectively. Correlations between genomic breeding values predicted with high-density genomic data or imputed genomic data from the LD SNP panel ranged from 0.89-0.97 for Large White and Landrace populations for reproductive traits. They were higher than those obtained for the Pietrain population (0.80 and 0.97 for production traits, r espectively). In conclusion, despite the limited number of SNPs on the low-density panel used in this study, the imputation accuracy is sufficient to use the imputed genotypes in the genomic evaluations. In practice, genotyping candidates with a LD chip isa solution for selecting future breeding pigs at lower cost

Published
2020

5. Intérêt des performances de truies croisées pour la sélection en race pure de caractères de reproduction de la lignée maternelle Large-White

Author

Boré, Raphaël, BRENAUT, Pauline, BADOUARD, Brigitte, Ligonesche, Bruno, Flatres-Grall, Loïc, Tusell, Llibertat, Bouquet, A., Institut du Porc, Ecole Supérieure d'Agricultures d'Angers (ESA d'Angers), NUCLEUS, Axiom, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], Institut du Porc (IFIP), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées

Subjects
[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], sélection, génétique
Abstract

51. Journées de la Recherche Porcine, 5 et 6 février 2019, Paris, p. 309-314,; Intérêt des performances de truies croisées pour la sélection en race pure de caractères de reproduction de la lignée maternelle Large-White. 51. Journées de la Recherche Porcine

Published
2019

6. Utilisation d’une puce très basse densité en sélection génomique porcine : Comparaison de qualité d’imputation et prédiction des valeurs génomiques pour deux design

Author

Carillier-Jacquin, Céline, Bouquet, Alban, Labrune, Yann, Brenaut, Pauline, Riquet, Juliette, Larzul, Catherine, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut du Porc (IFIP), and ProdInra, Migration

Subjects
[SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], [SDV.OT] Life Sciences [q-bio]/Other [q-bio.OT], sélection, ComputingMilieux_MISCELLANEOUS, corrélation, génomique, porc
Abstract

National audience

Published
2018

7. Using 1K panel in 3 French pig breeds for genomic selection: Accuracy of Imputation and estimation of genomic breeding values using 1K SNP panel, designed for several breeds in French pig populations

Author

Carillier-JACQUIN, Céline, Bouquet, Alban, Labrune, Yann, BRENAUT, Pauline, Riquet, Juliette, Larzul, Catherine, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, and Institut du Porc (IFIP)

Subjects
genomic, pig, [SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], breed, selection, genetic, ComputingMilieux_MISCELLANEOUS, Autre (Sciences du Vivant)
Abstract

International audience

Published
2018

8. Mise en place de la sélection génomique dans le schéma de sélection de la population Landrace Français

Author

Bouquet, Alban, Canaple, Marion, BRENAUT, Pauline, Bellec, Thierry, Flatres-Grall, Loïc, Ligonesche, B., Larzul, Catherine, Institut du Porc, Axiom, NUCLEUS, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], Institut du Porc (IFIP), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées

Subjects
[SDV]Life Sciences [q-bio], sélection, génétique, performance, génomique
Abstract

La sélection génomique est un nouvel outil permettant d’augmenter la précision du choix des reproducteurs porcins par la prise en compte de l’information de leur génome dans l’évaluation génétique. Une population de référence de 1348 reproducteurs génotypés sur puces SNP haute - densité (panels Illumina 60K etGeneSeek Genomic Profiler Porcine HD) a été constituée dans la population Collective Landrace Français. A partir de ces données, une étude de validation a permis de mettre en évidence des gains de précision substantiels dans le choix des reproducteurs à l’issue du contrôle en ferme par rapport à l’évaluation génétique conventionnelle de type BLUP Modèle Animal. Les gains de fiabilité des valeurs génétiques, de l’ordre de 30% à 50%, ont été estimés pour des critères de reproduction clés comme le nombre de porcelets nés vivants, le nombre de porcelets sevrés ou le poids moyen des porcelets à la naissance. En effet, sur ces critères, aucune performance propre n’est disponible pour les candidats au moment de la sélection. L’information génomique se révèle donc être une information importante pour identifier les meilleurs reproducteurs. Sur la base de ces résultats, la sélection génomique a été déployée dans le schéma de sélection Landrace en 2016. Chaque semaine, une évaluation génomique combinant performances, généalogies et génotypages est réalisée. Les candidats à la sélection sont d’abord triés sur valeur génétique conventionnelle avant d’être génotypés pour choisir sur valeur génomique les reproducteurs à conserver pour le noyau de sélection.

Published
2017

9. Comparaison de différentes sources d'ARN pour analyser le transcriptome mammaire bovin par RNAseq

Author

Canovas, Angela, Rincon, Gonzalo, Bevilacqua, Claudia, Islas-Trejo, Alma, BRENAUT, Pauline, Crapart, Nicolas, Hovey, Russel C., Boutinaud, Marion, Morgenthaler, Caroline, van Klompenberg, M.K., Medrano, Juan F., Martin, Patrice, University of California [Davis] (UC Davis), University of California, Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Chercheur indépendant, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, AGROCAMPUS OUEST, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)

Subjects
congenital, hereditary, and neonatal diseases and abnormalities, [SDV]Life Sciences [q-bio]
Abstract

Comparaison de différentes sources d'ARN pour analyser le transcriptome mammaire bovin par RNAseq. 13. Journées de l'Animation transversale "Glande mammaire, lait"

Published
2014

10. Comparison of five different cellular fractions to examine the lactating bovine mammary gland transcriptome using RNA-sequencing

Author

Canovas, Angela, Rincon, Gonzalo, Bevilacqua, Claudia, Islas-Trejo, Alma, BRENAUT, Pauline, Hovey, Russel C., Boutinaud, Marion, Vanklompenberg, Monica K., Medrano, Juan F., Martin, Patrice, University of California [Davis] (UC Davis), University of California, Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, AGROCAMPUS OUEST, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)

Subjects
[SDV]Life Sciences [q-bio]
Abstract

absent

Published
2013

11. Comparison of five different cellular fractions to examine the cow mammay gland transcriptome using RNA-sequencing

Author

Canovas, Angela, Rincon, Gonzalo, Bevilacqua, Claudia, Islas-Trejo, Alma, BRENAUT, Pauline, Hovey, Russel C., Boutinaud, Marion, Vanklompenberg, Monica K., Medrano, Juan F., Martin, Patrice, University of California [Davis] (UC Davis), University of California, Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), ANR EpigRAni & Apis-Gene Grant, AgroParisTech-Institut National de la Recherche Agronomique (INRA), and AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA)

Subjects
[SDV.BA]Life Sciences [q-bio]/Animal biology
Abstract

The objective of this study was to examine the cow mammary gland transcriptome using RNA-Sequencing by comparing five different cellular fractions: mammary gland tissue (MGT), milk somatic cells (SC), laser microdissected mammary epithelial cells (LCMEC), milk fat globules (MFG) and epithelial cells from milk (MEC). These samples were collected from one Normande and two Jersey cows. An average of 32-million short-sequence reads was obtained for each sample, and were mapped to the annotated UMD3.1 bovine genome assembly. In all samples 60-70% of the reads were categorized as mapped reads, with the exception of one MFG and one MEC sample that mapped 44.6% and 32.7% reads, respectively. Gene expression in SC and LCMEC showed the highest correlation with MGT, ranging from 0.99 to 0.92. In general, all the highly expressed genes such as caseins (CSN1S1, CSN1S2, CSN2, CSN3) and lactoglobulins (BLG, LALBA) showed the same expression profile in MGT, SC and LCMEC. However, MFG and MEC showed a different profile, where PLIN2, TBA1B, HMOX1, S100A11 and RL10 genes were highly expressed. These genes represent markers of lipid accumulation and immunity. MFG membrane contains specific components such as phospholipids, proteins and glycophospholipids that are known to have an affinity for the bacterial cell surface. Analyzing all the MFG reads not mapping to the bovine genome (17-million), 500 different kinds of bacteria were identified. Milk SC were the most representative sample of the mammary gland transcriptome and can be used as an effective and easy way to study gene expression in the mammary gland.

Published
2013

15. Identification of MicroRNAs controlling human ovarian cell proliferation and apoptosis.

Author

SIROTKIN, ALEXANDER V., LAUKOVÁ, MARCELA, OVCHARENKO, DMITRIY, BRENAUT, PAULINE, and MLYNČEK, MILOŠ

Subjects
RNA, OVARIES, CELLS, APOPTOSIS, CELL death, CELL proliferation, IMMUNOCYTOCHEMISTRY
Abstract

Previous studies have shown that microRNAs (miRNAs) can control steroidogenesis in cultured granulosa cells. In this study we wanted to determine if miRNAs can also affect proliferation and apoptosis in human ovarian cells. The effect of transfection of cultured primary ovarian granulosa cells with 80 different constructs encoding human pre-miRNAs on the expression of the proliferation marker, PCNA, and the apoptosis marker, Bax was evaluated by immunocytochemistry. Eleven out of 80 tested miRNA constructs resulted in stimulation, and 53 miRNAs inhibited expression of PCNA. Furthermore, 11 of the 80 miRNAs tested promoted accumulation of Bax, while 46 miRNAs caused a reduction in Bax in human ovarian cells. In addition, two selected antisense constructs that block the corresponding miRNAs mir-15a and mir-188 were evaluated for their effects on expression of PCNA. An antisense construct inhibiting mir-15a (which precursor suppressed PCNA) increased PCNA, whereas an antisense construct for mir-188 (which precursor did not change PCNA) did not affect PCNA expression. Verification of effects of selected pre-mir-10a, mir-105, and mir-182 by using other markers of proliferation (cyclin B1) and apoptosis (TdT and caspase 3) confirmed specificity of miRNAs effects on these processes. This is the first direct demonstration of the involvement of miRNAs in controlling both proliferation and apoptosis by ovarian granulose cells, as well as the identification of miRNAs promoting and suppressing these processes utilizing a genome-wide miRNA screen. J. Cell. Physiol. 223: 49–56, 2010. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Published
2010
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16. Involvement of microRNA Mir15a in control of human ovarian granulosa cell proliferation, apoptosis, steroidogenesis, and response to FSH.

Author

Sirotkin AV, Kisová G, Brenaut P, Ovcharenko D, Grossmann R, and Mlyncek M

Subjects
Adult, Apoptosis, Cell Proliferation drug effects, Cells, Cultured, Female, Gene Expression Regulation drug effects, Humans, MicroRNAs antagonists & inhibitors, Follicle Stimulating Hormone pharmacology, Granulosa Cells physiology, Hormones metabolism, MicroRNAs genetics
Abstract

Our study aimed to examine the role of micro RNA Mir15a in control of basic ovarian cell functions: proliferation, apoptosis, and secretory activity. In the first series of experiments, primary human ovarian granulosa cells were transfected with antisense construct blocking Mir15a (anti-Mir15a) and cultured without hormonal treatments. Accumulation of markers of proliferation (MAPK/ERK1,2 and PCNA) and apoptosis (caspase 3 and bax), and release of steroid hormones (progesterone, testosterone, and estradiol) were evaluated by immunocytochemical analysis and by enzyme immunoassay. In the second series of experiments, granulosa cells were transfected with gene construct encoding Mir15a precursor (pre-Mir15a) and cultured with and without follicle-stimulating hormone (FSH; 0, 1, 10, and 100 ng/ml). Expression of markers of proliferation (MAPK/ERK1,2) apoptosis (caspase 3), and steroidogenesis (release of progesterone, testosterone, and estradiol) were evaluated. Transfection of cells with anti-Mir15a resulted in a significant increase in accumulation of both proliferation and apoptosis markers, a reduction in progesterone and testosterone release, and an increase in estradiol release. Transfection of cells with pre-Mir15a had an opposite effect: it reduced accumulation of proliferation- and apoptosis-related proteins MAPK/ERK1,2 and caspase 3, and promoted release of progesterone and testosterone, but not estradiol. Moreover, pre-Mir15a reversed the effect of FSH on caspase 3, progesterone, and testosterone, but not on MAPK/ERK1,2 and estradiol. Our observations demonstrate involvement of Mir15a in control of multiple ovarian functions: proliferation, apoptosis, release of progesterone, androgen, and estrogen, and response to gonadotropin. Moreover, this is the first demonstration that miRNAs can affect response of cells to hormonal regulators. We propose that Mir15 could potentially be used for control of different reproductive processes.

Published
2014
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