Inviting an author to review:
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
39
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Functional genomics analysis identifies loss of HNF1B function as a cause of Mayer–Rokitansky–Küster–Hauser syndrome

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Mayer–Rokitansky–Küster–Hauser (MRKH) syndrome is a congenital condition characterized by aplasia or hypoplasia of the uterus and vagina in women with a 46,XX karyotype. This condition can occur as type I when isolated or as type II when associated with extragenital anomalies including kidney and skeletal abnormalities. The genetic basis of MRKH syndrome remains unexplained and several candidate genes have been proposed to play a role in its etiology, including HNF1B, LHX1 and WNT4. Here, we conducted a microarray analysis of 13 women affected by MRKH syndrome, resulting in the identification of chromosomal changes, including the deletion at 17q12, which contains both HNF1B and LHX1. We focused on HNF1B for further investigation due to its known association with, but unknown etiological role in, MRKH syndrome. We ablated Hnf1b specifically in the epithelium of the Müllerian ducts in mice and found that this caused hypoplastic development of the uterus, as well as kidney anomalies, closely mirroring the MRKH type II phenotype. Using single-cell RNA sequencing of uterine tissue in the Hnf1b-ablated embryos, we analyzed the molecules and pathways downstream of Hnf1b, revealing a dysregulation of processes associated with cell proliferation, migration and differentiation. Thus, we establish that loss of Hnf1b function leads to an MRKH phenotype and generate the first mouse model of MRKH syndrome type II. Our results support the investigation of HNF1B in clinical genetic settings of MRKH syndrome and shed new light on the molecular mechanisms underlying this poorly understood condition in women’s reproductive health.

          Related collections

          Most cited references90

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

            Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              voom: precision weights unlock linear model analysis tools for RNA-seq read counts

              New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods.
                Bookmark

                Author and article information

                Contributors
                Journal
                Hum Mol Genet
                Hum Mol Genet
                hmg
                Human Molecular Genetics
                Oxford University Press
                0964-6906
                1460-2083
                15 March 2023
                25 October 2022
                25 October 2022
                : 32
                : 6
                : 1032-1047
                Affiliations
                Centre for Clinical Research, The University of Queensland , Brisbane, QLD, Australia
                Institute for Molecular Bioscience, The University of Queensland , Brisbane, QLD, Australia
                Institute for Molecular Bioscience, The University of Queensland , Brisbane, QLD, Australia
                Reproductive Development, Murdoch Children's Research Institute , Melbourne, VIC, Australia
                Reproductive Development, Murdoch Children's Research Institute , Melbourne, VIC, Australia
                Department of Paediatrics, The University of Melbourne , Melbourne, VIC, Australia
                Reproductive Development, Murdoch Children's Research Institute , Melbourne, VIC, Australia
                Centre for Clinical Research, The University of Queensland , Brisbane, QLD, Australia
                Faculty of Health and Medical Sciences, The University of Adelaide , Adelaide, SA, Australia
                Institut de Biologie Paris-Seine, Sorbonne Université , Paris, France
                Division of Pediatric and Adolescent Gynecology, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine , New Haven, CT, USA
                Center for American Indian and Rural Health Equity, Montana State University , Bozeman, MT, USA
                MRKH Australia , Melbourne, VIC, Australia
                Institute for Molecular Bioscience, The University of Queensland , Brisbane, QLD, Australia
                Reproductive Development, Murdoch Children's Research Institute , Melbourne, VIC, Australia
                Department of Paediatrics, The University of Melbourne , Melbourne, VIC, Australia
                Institute for Molecular Bioscience, The University of Queensland , Brisbane, QLD, Australia
                Centre for Clinical Research, The University of Queensland , Brisbane, QLD, Australia
                Institute for Molecular Bioscience, The University of Queensland , Brisbane, QLD, Australia
                Author notes
                To whom correspondence should be addressed. Tel: +61 7 3346 6073; Email: p.pelosi@ 123456uq.edu.au

                The authors wish it to be known that, in their opinion, Peter Koopman and Emanuele Pelosi should be regarded as joint First Authors.

                Author information
                https://orcid.org/0000-0002-6840-3186
                https://orcid.org/0000-0003-1890-9821
                Article
                ddac262
                10.1093/hmg/ddac262
                9990990
                36282544
                1bba2626-1bec-4b63-94f1-682b5898330a
                © The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 21 August 2022
                : 4 October 2022
                : 17 October 2022
                : 25 November 2022
                Page count
                Pages: 16
                Funding
                Funded by: National Health and Medical Research Council of Australia;
                Categories
                Original Article
                AcademicSubjects/SCI01140

                Genetics
                Genetics

                Comments

                Comment on this article