The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index.
Polycystic ovary syndrome is transmitted via a transgenerational epigenetic process
Open accessAbstract
Polycystic ovary syndrome (PCOS) is the most common reproductive and metabolic disorder affecting women of reproductive age. PCOS has a strong heritable component, but its pathogenesis has been unclear. Here, we performed RNA sequencing and genome-wide DNA methylation profiling of ovarian tissue from control and third-generation PCOS-like mice. We found that DNA hypomethylation regulates key genes associated with PCOS and that several of the differentially methylated genes are also altered in blood samples from women with PCOS compared with healthy controls. Based on this insight, we treated the PCOS mouse model with the methyl group donor S-adenosylmethionine and found that it corrected their transcriptomic, neuroendocrine, and metabolic defects. These findings show that the transmission of PCOS traits to future generations occurs via an altered landscape of DNA methylation and propose methylome markers as a possible diagnostic landmark for the condition, while also identifying potential candidates for epigenetic-based therapy.
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Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
Livak, K. J., & Schmittgen, T. D. (2001) · Methods · doi:10.1006/meth.2001.1262 · Cited by 180,860
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Cutadapt removes adapter sequences from high-throughput sequencing reads
Martin, M. (2011) · EMBnet.journal · doi:10.14806/ej.17.1.200 · Cited by 33,889
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
HTSeq—a Python framework to work with high-throughput sequencing data
Anders, S., Pyl, P. T., & Huber, W. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu638 · Cited by 21,464
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
Differential expression analysis for sequence count data
Anders, S., & Huber, W. (2010) · Genome Biology · doi:10.1186/gb-2010-11-10-r106 · Cited by 15,581
Cited by
Joham, A. E., Norman, R. J., Stener-Victorin, E., Legro, R. S., Franks, S., Moran, L. J., Boyle, J., & Teede, H. J. (2022) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(22)00163-2 · Cited by 838
Polycystic Ovary Syndrome: Etiology, Current Management, and Future Therapeutics
Singh, S., Pal, N., Shubham, S., Sarma, D. K., Verma, V., Marotta, F., & Kumar, M. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12041454 · Cited by 521
Stener-Victorin, E., Teede, H., Norman, R. J., Legro, R., Goodarzi, M. O., Dokras, A., Laven, J., Hoeger, K., & Piltonen, T. T. (2024) · Nature Reviews Disease Primers · doi:10.1038/s41572-024-00511-3 · Cited by 495
Deconstructing a Syndrome: Genomic Insights Into PCOS Causal Mechanisms and Classification
Dapas, M., & Dunaif, A. (2022) · Endocrine Reviews · doi:10.1210/endrev/bnac001 · Cited by 300
Polycystic ovary syndrome as a plausible evolutionary outcome of metabolic adaptation
Dumesic, D. A., Padmanabhan, V., Chazenbalk, G. D., & Abbott, D. H. (2022) · Reproductive Biology and Endocrinology · doi:10.1186/s12958-021-00878-y · Cited by 63
Metadata
- Authors
- Mimouni, N. E. H., Paiva, I., Barbotin, A.-L., Timzoura, F. E., Plassard, D., Le Gras, S., Ternier, G., Pigny, P., Catteau-Jonard, S., Simon, V., Prevot, V., Boutillier, A.-L., & Giacobini, P.
- Venue
- Cell Metabolism
- Publisher
- Elsevier BV
- Published
- 2021-03
- Volume
- 33
- Issue
- 3
- Pages
- 513-530.e8
- ISSN
- 1550-4131 (ISSN-L)
- OpenAlex
- W3126884841
- Cited by
- 253
- References
- 86
- FWCI
- 28.17
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Mimouni, N. E. H., Paiva, I., Barbotin, A.-L., Timzoura, F. E., Plassard, D., Le Gras, S., Ternier, G., Pigny, P., Catteau-Jonard, S., Simon, V., Prevot, V., Boutillier, A.-L., & Giacobini, P. (2021). Polycystic ovary syndrome is transmitted via a transgenerational epigenetic process. Cell Metabolism. https://doi.org/10.1016/j.cmet.2021.01.004
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