Identification of epigenetic memory candidates associated with gestational age at birth through analysis of methylome and transcriptional data
Abstract Preterm birth is known to be associated with chronic disease risk in adulthood whereby epigenetic memory may play a mechanistic role in disease susceptibility. Gestational age (GA) is the most important prognostic factor for preterm infants, and numerous DNA methylation alterations associat...
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2021
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oai:doaj.org-article:d19953f3e7764855b55f244b17ba277f2021-12-02T12:09:32ZIdentification of epigenetic memory candidates associated with gestational age at birth through analysis of methylome and transcriptional data10.1038/s41598-021-83016-32045-2322https://doaj.org/article/d19953f3e7764855b55f244b17ba277f2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83016-3https://doaj.org/toc/2045-2322Abstract Preterm birth is known to be associated with chronic disease risk in adulthood whereby epigenetic memory may play a mechanistic role in disease susceptibility. Gestational age (GA) is the most important prognostic factor for preterm infants, and numerous DNA methylation alterations associated with GA have been revealed by epigenome-wide association studies. However, in human preterm infants, whether the methylation changes relate to transcription in the fetal state and persist after birth remains to be elucidated. Here, we identified 461 transcripts associated with GA (range 23–41 weeks) and 2093 candidate CpG sites for GA-involved epigenetic memory through analysis of methylome (110 cord blood and 47 postnatal blood) and transcriptional data (55 cord blood). Moreover, we discovered the trends of chromatin state, such as polycomb-binding, among these candidate sites. Fifty-four memory candidate sites showed correlation between methylation and transcription, and the representative corresponding gene was UCN, which encodes urocortin.Kohei KashimaTomoko KawaiRiki NishimuraYuh ShiwaKevin Y. UrayamaHiromi KamuraKazue TakedaSaki AotoAtsushi ItoKeiko MatsubaraTakeshi NagamatsuTomoyuki FujiiIsaku OmoriMitsumasa ShimizuHironobu HyodoKoji KuguKenji MatsumotoAtsushi ShimizuAkira OkaMasashi MizuguchiKazuhiko NakabayashiKenichiro HataNaoto TakahashiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-16 (2021) |
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Medicine R Science Q Kohei Kashima Tomoko Kawai Riki Nishimura Yuh Shiwa Kevin Y. Urayama Hiromi Kamura Kazue Takeda Saki Aoto Atsushi Ito Keiko Matsubara Takeshi Nagamatsu Tomoyuki Fujii Isaku Omori Mitsumasa Shimizu Hironobu Hyodo Koji Kugu Kenji Matsumoto Atsushi Shimizu Akira Oka Masashi Mizuguchi Kazuhiko Nakabayashi Kenichiro Hata Naoto Takahashi Identification of epigenetic memory candidates associated with gestational age at birth through analysis of methylome and transcriptional data |
| description |
Abstract Preterm birth is known to be associated with chronic disease risk in adulthood whereby epigenetic memory may play a mechanistic role in disease susceptibility. Gestational age (GA) is the most important prognostic factor for preterm infants, and numerous DNA methylation alterations associated with GA have been revealed by epigenome-wide association studies. However, in human preterm infants, whether the methylation changes relate to transcription in the fetal state and persist after birth remains to be elucidated. Here, we identified 461 transcripts associated with GA (range 23–41 weeks) and 2093 candidate CpG sites for GA-involved epigenetic memory through analysis of methylome (110 cord blood and 47 postnatal blood) and transcriptional data (55 cord blood). Moreover, we discovered the trends of chromatin state, such as polycomb-binding, among these candidate sites. Fifty-four memory candidate sites showed correlation between methylation and transcription, and the representative corresponding gene was UCN, which encodes urocortin. |
| format |
article |
| author |
Kohei Kashima Tomoko Kawai Riki Nishimura Yuh Shiwa Kevin Y. Urayama Hiromi Kamura Kazue Takeda Saki Aoto Atsushi Ito Keiko Matsubara Takeshi Nagamatsu Tomoyuki Fujii Isaku Omori Mitsumasa Shimizu Hironobu Hyodo Koji Kugu Kenji Matsumoto Atsushi Shimizu Akira Oka Masashi Mizuguchi Kazuhiko Nakabayashi Kenichiro Hata Naoto Takahashi |
| author_facet |
Kohei Kashima Tomoko Kawai Riki Nishimura Yuh Shiwa Kevin Y. Urayama Hiromi Kamura Kazue Takeda Saki Aoto Atsushi Ito Keiko Matsubara Takeshi Nagamatsu Tomoyuki Fujii Isaku Omori Mitsumasa Shimizu Hironobu Hyodo Koji Kugu Kenji Matsumoto Atsushi Shimizu Akira Oka Masashi Mizuguchi Kazuhiko Nakabayashi Kenichiro Hata Naoto Takahashi |
| author_sort |
Kohei Kashima |
| title |
Identification of epigenetic memory candidates associated with gestational age at birth through analysis of methylome and transcriptional data |
| title_short |
Identification of epigenetic memory candidates associated with gestational age at birth through analysis of methylome and transcriptional data |
| title_full |
Identification of epigenetic memory candidates associated with gestational age at birth through analysis of methylome and transcriptional data |
| title_fullStr |
Identification of epigenetic memory candidates associated with gestational age at birth through analysis of methylome and transcriptional data |
| title_full_unstemmed |
Identification of epigenetic memory candidates associated with gestational age at birth through analysis of methylome and transcriptional data |
| title_sort |
identification of epigenetic memory candidates associated with gestational age at birth through analysis of methylome and transcriptional data |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/d19953f3e7764855b55f244b17ba277f |
| work_keys_str_mv |
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1718394659186671616 |