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      miR-26 Deficiency Causes Alterations in Lens Transcriptome and Results in Adult-Onset Cataract

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          Abstract

          Purpose

          Despite strong evidence demonstrating that normal lens development requires regulation governed by microRNAs (miRNAs), the functional role of specific miRNAs in mammalian lens development remains largely unexplored.

          Methods

          A comprehensive analysis of miRNA transcripts in the newborn mouse lens, exploring both differential expression between lens epithelial cells and lens fiber cells and overall miRNA abundance, was conducted by miRNA sequencing. Mouse lenses lacking each of three abundantly expressed lens miRNAs (miR-184, miR-26, and miR-1) were analyzed to explore the role of these miRNAs in lens development.

          Results

          Mice lacking all three copies of miR-26 ( miR-26 TKO ) developed postnatal cataracts as early as 4 to 6 weeks of age. RNA sequencing analysis of neonatal lenses from miR-26 TKO mice exhibited abnormal reduced expression of a cohort of genes found to be lens enriched and linked to cataract (e.g., Foxe3, Hsf4, Mip, Tdrd7, and numerous crystallin genes) and abnormal elevated expression of genes related to neural development ( Lhx3, Neurod4, Shisa7, Elavl3), inflammation ( Ccr1, Tnfrsf12a, Csf2ra), the complement pathway, and epithelial to mesenchymal transition ( Tnfrsf1a, Ccl7, Stat3, Cntfr).

          Conclusions

          miR-1, miR-184, and miR-26 are each dispensable for normal embryonic lens development. However, loss of miR-26 causes lens transcriptome changes and drives cataract formation.

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          Most cited references79

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

            Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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              Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

              DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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                Author and article information

                Journal
                Invest Ophthalmol Vis Sci
                Invest Ophthalmol Vis Sci
                IOVS
                Investigative Ophthalmology & Visual Science
                The Association for Research in Vision and Ophthalmology
                0146-0404
                1552-5783
                29 April 2024
                April 2024
                : 65
                : 4
                : 42
                Affiliations
                [1 ]Cell, Molecular and Structural Biology Program, Miami University, Oxford, Ohio, United States
                [2 ]Department of Biology and Center for Visual Sciences, Miami University, Oxford, Ohio, United States
                [3 ]Department of Biology, University of Dayton, Dayton, Ohio, United States
                [4 ]Department of Biological Sciences, University of Delaware, Newark, Delaware, United States
                [5 ]Center for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware, United States
                Author notes
                [# ]Correspondence: Michael L. Robinson, 256 Pearson Hall, 700 E High St, Oxford, OH 45056, USA; robinsm5@ 123456miamioh.edu .
                [*]

                PAT Deceased September 3, 2016.

                Article
                IOVS-24-39702
                10.1167/iovs.65.4.42
                11059818
                38683565
                4743f947-e99d-4023-8fe9-8078ba909ffc
                Copyright 2024 The Authors

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

                History
                : 25 March 2024
                : 31 January 2024
                Page count
                Pages: 15
                Categories
                Lens
                Lens

                microrna,mir-26,cataract,lens,transcriptome
                microrna, mir-26, cataract, lens, transcriptome

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