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Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records

BACKGROUND: Conflicting results regarding alterations to sperm DNA methylation in cases of spermatogenesis defects, male infertility and poor developmental outcomes have been reported in humans. Bulls used for artificial insemination represent a relevant model in this field, as the broad disseminati...

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Autores principales: Costes, Valentin, Chaulot-Talmon, Aurélie, Sellem, Eli, Perrier, Jean-Philippe, Aubert-Frambourg, Anne, Jouneau, Luc, Pontlevoy, Charline, Hozé, Chris, Fritz, Sébastien, Boussaha, Mekki, Le Danvic, Chrystelle, Sanchez, Marie-Pierre, Boichard, Didier, Schibler, Laurent, Jammes, Hélène, Jaffrézic, Florence, Kiefer, Hélène
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9047354/
https://www.ncbi.nlm.nih.gov/pubmed/35477426
http://dx.doi.org/10.1186/s13148-022-01275-x
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author Costes, Valentin
Chaulot-Talmon, Aurélie
Sellem, Eli
Perrier, Jean-Philippe
Aubert-Frambourg, Anne
Jouneau, Luc
Pontlevoy, Charline
Hozé, Chris
Fritz, Sébastien
Boussaha, Mekki
Le Danvic, Chrystelle
Sanchez, Marie-Pierre
Boichard, Didier
Schibler, Laurent
Jammes, Hélène
Jaffrézic, Florence
Kiefer, Hélène
author_facet Costes, Valentin
Chaulot-Talmon, Aurélie
Sellem, Eli
Perrier, Jean-Philippe
Aubert-Frambourg, Anne
Jouneau, Luc
Pontlevoy, Charline
Hozé, Chris
Fritz, Sébastien
Boussaha, Mekki
Le Danvic, Chrystelle
Sanchez, Marie-Pierre
Boichard, Didier
Schibler, Laurent
Jammes, Hélène
Jaffrézic, Florence
Kiefer, Hélène
author_sort Costes, Valentin
collection PubMed
description BACKGROUND: Conflicting results regarding alterations to sperm DNA methylation in cases of spermatogenesis defects, male infertility and poor developmental outcomes have been reported in humans. Bulls used for artificial insemination represent a relevant model in this field, as the broad dissemination of bull semen considerably alleviates confounding factors and enables the precise assessment of male fertility. This study was therefore designed to assess the potential for sperm DNA methylation to predict bull fertility. RESULTS: A unique collection of 100 sperm samples was constituted by pooling 2–5 ejaculates per bull from 100 Montbéliarde bulls of comparable ages, assessed as fertile (n = 57) or subfertile (n = 43) based on non-return rates 56 days after insemination. The DNA methylation profiles of these samples were obtained using reduced representation bisulfite sequencing. After excluding putative sequence polymorphisms, 490 fertility-related differentially methylated cytosines (DMCs) were identified, most of which were hypermethylated in subfertile bulls. Interestingly, 46 genes targeted by DMCs are involved in embryonic and fetal development, sperm function and maturation, or have been related to fertility in genome-wide association studies; five of these were further analyzed by pyrosequencing. In order to evaluate the prognostic value of fertility-related DMCs, the sperm samples were split between training (n = 67) and testing (n = 33) sets. Using a Random Forest approach, a predictive model was built from the methylation values obtained on the training set. The predictive accuracy of this model was 72% on the testing set and 72% on individual ejaculates collected from an independent cohort of 20 bulls. CONCLUSION: This study, conducted on the largest set of bull sperm samples so far examined in epigenetic analyses, demonstrated that the sperm methylome is a valuable source of male fertility biomarkers. The next challenge is to combine these results with other data on the same sperm samples in order to improve the quality of the model and better understand the interplay between DNA methylation and other molecular features in the regulation of fertility. This research may have potential applications in human medicine, where infertility affects the interaction between a male and a female, thus making it difficult to isolate the male factor. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-022-01275-x.
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spelling pubmed-90473542022-04-29 Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records Costes, Valentin Chaulot-Talmon, Aurélie Sellem, Eli Perrier, Jean-Philippe Aubert-Frambourg, Anne Jouneau, Luc Pontlevoy, Charline Hozé, Chris Fritz, Sébastien Boussaha, Mekki Le Danvic, Chrystelle Sanchez, Marie-Pierre Boichard, Didier Schibler, Laurent Jammes, Hélène Jaffrézic, Florence Kiefer, Hélène Clin Epigenetics Research BACKGROUND: Conflicting results regarding alterations to sperm DNA methylation in cases of spermatogenesis defects, male infertility and poor developmental outcomes have been reported in humans. Bulls used for artificial insemination represent a relevant model in this field, as the broad dissemination of bull semen considerably alleviates confounding factors and enables the precise assessment of male fertility. This study was therefore designed to assess the potential for sperm DNA methylation to predict bull fertility. RESULTS: A unique collection of 100 sperm samples was constituted by pooling 2–5 ejaculates per bull from 100 Montbéliarde bulls of comparable ages, assessed as fertile (n = 57) or subfertile (n = 43) based on non-return rates 56 days after insemination. The DNA methylation profiles of these samples were obtained using reduced representation bisulfite sequencing. After excluding putative sequence polymorphisms, 490 fertility-related differentially methylated cytosines (DMCs) were identified, most of which were hypermethylated in subfertile bulls. Interestingly, 46 genes targeted by DMCs are involved in embryonic and fetal development, sperm function and maturation, or have been related to fertility in genome-wide association studies; five of these were further analyzed by pyrosequencing. In order to evaluate the prognostic value of fertility-related DMCs, the sperm samples were split between training (n = 67) and testing (n = 33) sets. Using a Random Forest approach, a predictive model was built from the methylation values obtained on the training set. The predictive accuracy of this model was 72% on the testing set and 72% on individual ejaculates collected from an independent cohort of 20 bulls. CONCLUSION: This study, conducted on the largest set of bull sperm samples so far examined in epigenetic analyses, demonstrated that the sperm methylome is a valuable source of male fertility biomarkers. The next challenge is to combine these results with other data on the same sperm samples in order to improve the quality of the model and better understand the interplay between DNA methylation and other molecular features in the regulation of fertility. This research may have potential applications in human medicine, where infertility affects the interaction between a male and a female, thus making it difficult to isolate the male factor. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-022-01275-x. BioMed Central 2022-04-27 /pmc/articles/PMC9047354/ /pubmed/35477426 http://dx.doi.org/10.1186/s13148-022-01275-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Costes, Valentin
Chaulot-Talmon, Aurélie
Sellem, Eli
Perrier, Jean-Philippe
Aubert-Frambourg, Anne
Jouneau, Luc
Pontlevoy, Charline
Hozé, Chris
Fritz, Sébastien
Boussaha, Mekki
Le Danvic, Chrystelle
Sanchez, Marie-Pierre
Boichard, Didier
Schibler, Laurent
Jammes, Hélène
Jaffrézic, Florence
Kiefer, Hélène
Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records
title Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records
title_full Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records
title_fullStr Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records
title_full_unstemmed Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records
title_short Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records
title_sort predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9047354/
https://www.ncbi.nlm.nih.gov/pubmed/35477426
http://dx.doi.org/10.1186/s13148-022-01275-x
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