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Identifying novel regulators of placental development using time-series transcriptome data
The placenta serves as a connection between the mother and the fetus during pregnancy, providing the fetus with oxygen, nutrients, and growth hormones. However, the regulatory mechanisms and dynamic gene interaction networks underlying early placental development are understudied. Here, we generated...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Life Science Alliance LLC
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748866/ https://www.ncbi.nlm.nih.gov/pubmed/36622342 http://dx.doi.org/10.26508/lsa.202201788 |
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author | Vu, Ha TH Kaur, Haninder Kies, Kelby R Starks, Rebekah R Tuteja, Geetu |
author_facet | Vu, Ha TH Kaur, Haninder Kies, Kelby R Starks, Rebekah R Tuteja, Geetu |
author_sort | Vu, Ha TH |
collection | PubMed |
description | The placenta serves as a connection between the mother and the fetus during pregnancy, providing the fetus with oxygen, nutrients, and growth hormones. However, the regulatory mechanisms and dynamic gene interaction networks underlying early placental development are understudied. Here, we generated RNA-sequencing data from mouse fetal placenta at embryonic days 7.5, 8.5, and 9.5 to identify genes with timepoint-specific expression, then inferred gene interaction networks to analyze highly connected network modules. We determined that timepoint-specific gene network modules were associated with distinct developmental processes, and with similar expression profiles to specific human placental cell populations. From each module, we identified hub genes and their direct neighboring genes, which were predicted to govern placental functions. We confirmed that four novel candidate regulators identified through our analyses regulate cell migration in the HTR-8/SVneo cell line. Overall, we predicted several novel regulators of placental development expressed in specific placental cell types using network analysis of bulk RNA-sequencing data. Our findings and analysis approaches will be valuable for future studies investigating the transcriptional landscape of early development. |
format | Online Article Text |
id | pubmed-9748866 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Life Science Alliance LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-97488662022-12-15 Identifying novel regulators of placental development using time-series transcriptome data Vu, Ha TH Kaur, Haninder Kies, Kelby R Starks, Rebekah R Tuteja, Geetu Life Sci Alliance Research Articles The placenta serves as a connection between the mother and the fetus during pregnancy, providing the fetus with oxygen, nutrients, and growth hormones. However, the regulatory mechanisms and dynamic gene interaction networks underlying early placental development are understudied. Here, we generated RNA-sequencing data from mouse fetal placenta at embryonic days 7.5, 8.5, and 9.5 to identify genes with timepoint-specific expression, then inferred gene interaction networks to analyze highly connected network modules. We determined that timepoint-specific gene network modules were associated with distinct developmental processes, and with similar expression profiles to specific human placental cell populations. From each module, we identified hub genes and their direct neighboring genes, which were predicted to govern placental functions. We confirmed that four novel candidate regulators identified through our analyses regulate cell migration in the HTR-8/SVneo cell line. Overall, we predicted several novel regulators of placental development expressed in specific placental cell types using network analysis of bulk RNA-sequencing data. Our findings and analysis approaches will be valuable for future studies investigating the transcriptional landscape of early development. Life Science Alliance LLC 2022-12-13 /pmc/articles/PMC9748866/ /pubmed/36622342 http://dx.doi.org/10.26508/lsa.202201788 Text en © 2022 Vu et al. https://creativecommons.org/licenses/by/4.0/This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Articles Vu, Ha TH Kaur, Haninder Kies, Kelby R Starks, Rebekah R Tuteja, Geetu Identifying novel regulators of placental development using time-series transcriptome data |
title | Identifying novel regulators of placental development using time-series transcriptome data |
title_full | Identifying novel regulators of placental development using time-series transcriptome data |
title_fullStr | Identifying novel regulators of placental development using time-series transcriptome data |
title_full_unstemmed | Identifying novel regulators of placental development using time-series transcriptome data |
title_short | Identifying novel regulators of placental development using time-series transcriptome data |
title_sort | identifying novel regulators of placental development using time-series transcriptome data |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748866/ https://www.ncbi.nlm.nih.gov/pubmed/36622342 http://dx.doi.org/10.26508/lsa.202201788 |
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