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The Endometrial Transcription Landscape of MRKH Syndrome

The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome (OMIM 277000) is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. While genetic causes have been identified for a small subset of patients and epigenetic mechanisms presumably contribute t...

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Detalles Bibliográficos
Autores principales: Hentrich, Thomas, Koch, André, Weber, Nico, Kilzheimer, Alexander, Maia, Ana, Burkhardt, Simone, Rall, Katharina, Casadei, Nicolas, Kohlbacher, Oliver, Riess, Olaf, Schulze-Hentrich, Julia Maria, Brucker, Sara Yvonne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7542331/
https://www.ncbi.nlm.nih.gov/pubmed/33072755
http://dx.doi.org/10.3389/fcell.2020.572281
Descripción
Sumario:The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome (OMIM 277000) is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. While genetic causes have been identified for a small subset of patients and epigenetic mechanisms presumably contribute to the pathogenic unfolding, too, the etiology of the syndrome has remained largely enigmatic. A comprehensive understanding of gene activity in the context of the disease is crucial to identify etiological components and their potential interplay. So far, this understanding is lacking, primarily due to the scarcity of samples and suitable tissue. In order to close this gap, we profiled endometrial tissue of uterus rudiments in a large cohort of MRKH patients using RNA-seq and thereby provide a genome-wide view on the altered transcription landscape of the MRKH syndrome. Differential and co-expression analyses of the data identified cellular processes and candidate genes that converge on a core network of interconnected regulators that emerge as pivotal for the perturbed expression space. With these results and browsable access to the rich data through an online tool we seek to accelerate research to unravel the underlying biology of the syndrome.