Sperm Methylome Profiling Can Discern Fertility Levels in the Porcine Biomedical Model
A combined Genotyping By Sequencing (GBS) and methylated DNA immunoprecipitation (MeDIP) protocol was used to identify—in parallel—genetic variation (Genomic-Wide Association Studies (GWAS) and epigenetic differences of Differentially Methylated Regions (DMR) in the genome of spermatozoa from the po...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-03-01
|
| Series: | International Journal of Molecular Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1422-0067/22/5/2679 |
| _version_ | 1797412834844344320 |
|---|---|
| author | Fabio Pértille Manuel Alvarez-Rodriguez Arthur Nery da Silva Isabel Barranco Jordi Roca Carlos Guerrero-Bosagna Heriberto Rodriguez-Martinez |
| author_facet | Fabio Pértille Manuel Alvarez-Rodriguez Arthur Nery da Silva Isabel Barranco Jordi Roca Carlos Guerrero-Bosagna Heriberto Rodriguez-Martinez |
| author_sort | Fabio Pértille |
| collection | DOAJ |
| description | A combined Genotyping By Sequencing (GBS) and methylated DNA immunoprecipitation (MeDIP) protocol was used to identify—in parallel—genetic variation (Genomic-Wide Association Studies (GWAS) and epigenetic differences of Differentially Methylated Regions (DMR) in the genome of spermatozoa from the porcine animal model. Breeding boars with good semen quality (<i>n</i> = 11) and specific and well-documented differences in fertility (farrowing rate, FR) and prolificacy (litter size, LS) (<i>n</i> = 7) in artificial insemination programs, using combined FR and LS, were categorized as High Fertile (HF, <i>n</i> = 4) or Low Fertile (LF, <i>n</i> = 3), and boars with Unknown Fertility (UF, <i>n</i> = 4) were tested for eventual epigenetical similarity with those fertility-proven. We identified 165,944 Single Nucleotide Polymorphisms (SNPs) that explained 14–15% of variance among selection lines. Between HF and LF individuals (<i>n</i> = 7, 4 HF and 3 LF), we identified 169 SNPs with <i>p</i> ≤ 0.00015, which explained 58% of the variance. For the epigenetic analyses, we considered fertility and period of ejaculate collection (late-summer and mid-autumn). Approximately three times more DMRs were observed in HF than in LF boars across these periods. Interestingly, UF boars were clearly clustered with one of the other HF or LF groups. The highest differences in DMRs between HF and LF experimental groups across the pig genome were located in the chr 3, 9, 13, and 16, with most DMRs being hypermethylated in LF boars. In both HF and LF boars, DMRs were mostly hypermethylated in late-summer compared to mid-autumn. Three overlaps were detected between SNPs (<i>p</i> ≤ 0.0005, <i>n</i> = 1318) and CpG sites within DMRs. In conclusion, fertility levels in breeding males including FR and LS can be discerned using methylome analyses. The findings in this biomedical animal model ought to be applied besides sire selection for andrological diagnosis of idiopathic sub/infertility. |
| first_indexed | 2024-03-09T05:08:57Z |
| format | Article |
| id | doaj.art-4b39be2d14de4b1daf8c843115188fb7 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-09T05:08:57Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-4b39be2d14de4b1daf8c843115188fb72023-12-03T12:51:35ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672021-03-01225267910.3390/ijms22052679Sperm Methylome Profiling Can Discern Fertility Levels in the Porcine Biomedical ModelFabio Pértille0Manuel Alvarez-Rodriguez1Arthur Nery da Silva2Isabel Barranco3Jordi Roca4Carlos Guerrero-Bosagna5Heriberto Rodriguez-Martinez6Department of Physics, Chemistry and Biology, Linköping University, SE-58183 Linköping, SwedenDepartment of Biomedical & Clinical Sciences (BKV), Linköping University, SE-58185 Linköping, SwedenDepartment of Physics, Chemistry and Biology, Linköping University, SE-58183 Linköping, SwedenDepartment of Biomedical & Clinical Sciences (BKV), Linköping University, SE-58185 Linköping, SwedenDepartment of Medicine and Animal Surgery, University of Murcia, 30100 Murcia, SpainDepartment of Physics, Chemistry and Biology, Linköping University, SE-58183 Linköping, SwedenDepartment of Biomedical & Clinical Sciences (BKV), Linköping University, SE-58185 Linköping, SwedenA combined Genotyping By Sequencing (GBS) and methylated DNA immunoprecipitation (MeDIP) protocol was used to identify—in parallel—genetic variation (Genomic-Wide Association Studies (GWAS) and epigenetic differences of Differentially Methylated Regions (DMR) in the genome of spermatozoa from the porcine animal model. Breeding boars with good semen quality (<i>n</i> = 11) and specific and well-documented differences in fertility (farrowing rate, FR) and prolificacy (litter size, LS) (<i>n</i> = 7) in artificial insemination programs, using combined FR and LS, were categorized as High Fertile (HF, <i>n</i> = 4) or Low Fertile (LF, <i>n</i> = 3), and boars with Unknown Fertility (UF, <i>n</i> = 4) were tested for eventual epigenetical similarity with those fertility-proven. We identified 165,944 Single Nucleotide Polymorphisms (SNPs) that explained 14–15% of variance among selection lines. Between HF and LF individuals (<i>n</i> = 7, 4 HF and 3 LF), we identified 169 SNPs with <i>p</i> ≤ 0.00015, which explained 58% of the variance. For the epigenetic analyses, we considered fertility and period of ejaculate collection (late-summer and mid-autumn). Approximately three times more DMRs were observed in HF than in LF boars across these periods. Interestingly, UF boars were clearly clustered with one of the other HF or LF groups. The highest differences in DMRs between HF and LF experimental groups across the pig genome were located in the chr 3, 9, 13, and 16, with most DMRs being hypermethylated in LF boars. In both HF and LF boars, DMRs were mostly hypermethylated in late-summer compared to mid-autumn. Three overlaps were detected between SNPs (<i>p</i> ≤ 0.0005, <i>n</i> = 1318) and CpG sites within DMRs. In conclusion, fertility levels in breeding males including FR and LS can be discerned using methylome analyses. The findings in this biomedical animal model ought to be applied besides sire selection for andrological diagnosis of idiopathic sub/infertility.https://www.mdpi.com/1422-0067/22/5/2679spermatozoagenotyping by sequencing (GBS)methylated DNA immunoprecipitation (MeDIP)artificial inseminationfertilityprolificacy |
| spellingShingle | Fabio Pértille Manuel Alvarez-Rodriguez Arthur Nery da Silva Isabel Barranco Jordi Roca Carlos Guerrero-Bosagna Heriberto Rodriguez-Martinez Sperm Methylome Profiling Can Discern Fertility Levels in the Porcine Biomedical Model International Journal of Molecular Sciences spermatozoa genotyping by sequencing (GBS) methylated DNA immunoprecipitation (MeDIP) artificial insemination fertility prolificacy |
| title | Sperm Methylome Profiling Can Discern Fertility Levels in the Porcine Biomedical Model |
| title_full | Sperm Methylome Profiling Can Discern Fertility Levels in the Porcine Biomedical Model |
| title_fullStr | Sperm Methylome Profiling Can Discern Fertility Levels in the Porcine Biomedical Model |
| title_full_unstemmed | Sperm Methylome Profiling Can Discern Fertility Levels in the Porcine Biomedical Model |
| title_short | Sperm Methylome Profiling Can Discern Fertility Levels in the Porcine Biomedical Model |
| title_sort | sperm methylome profiling can discern fertility levels in the porcine biomedical model |
| topic | spermatozoa genotyping by sequencing (GBS) methylated DNA immunoprecipitation (MeDIP) artificial insemination fertility prolificacy |
| url | https://www.mdpi.com/1422-0067/22/5/2679 |
| work_keys_str_mv | AT fabiopertille spermmethylomeprofilingcandiscernfertilitylevelsintheporcinebiomedicalmodel AT manuelalvarezrodriguez spermmethylomeprofilingcandiscernfertilitylevelsintheporcinebiomedicalmodel AT arthurnerydasilva spermmethylomeprofilingcandiscernfertilitylevelsintheporcinebiomedicalmodel AT isabelbarranco spermmethylomeprofilingcandiscernfertilitylevelsintheporcinebiomedicalmodel AT jordiroca spermmethylomeprofilingcandiscernfertilitylevelsintheporcinebiomedicalmodel AT carlosguerrerobosagna spermmethylomeprofilingcandiscernfertilitylevelsintheporcinebiomedicalmodel AT heribertorodriguezmartinez spermmethylomeprofilingcandiscernfertilitylevelsintheporcinebiomedicalmodel |