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Transcriptome dataset of human corneal endothelium based on ribosomal RNA-depleted RNA-Seq data
The corneal endothelium maintains corneal transparency; consequently, damage to this endothelium by a number of pathological conditions results in severe vision loss. Publicly available expression databases of human tissues are useful for investigating the pathogenesis of diseases and for developing...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680133/ https://www.ncbi.nlm.nih.gov/pubmed/33219220 http://dx.doi.org/10.1038/s41597-020-00754-1 |
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author | Tokuda, Yuichi Okumura, Naoki Komori, Yuya Hanada, Naoya Tashiro, Kei Koizumi, Noriko Nakano, Masakazu |
author_facet | Tokuda, Yuichi Okumura, Naoki Komori, Yuya Hanada, Naoya Tashiro, Kei Koizumi, Noriko Nakano, Masakazu |
author_sort | Tokuda, Yuichi |
collection | PubMed |
description | The corneal endothelium maintains corneal transparency; consequently, damage to this endothelium by a number of pathological conditions results in severe vision loss. Publicly available expression databases of human tissues are useful for investigating the pathogenesis of diseases and for developing new therapeutic modalities; however, databases for ocular tissues, and especially the corneal endothelium, are poor. Here, we have generated a transcriptome dataset from the ribosomal RNA-depleted total RNA from the corneal endothelium of eyes from seven Caucasians without ocular diseases. The results of principal component analysis and correlation coefficients (ranged from 0.87 to 0.96) suggested high homogeneity of our RNA-Seq dataset among the samples, as well as sufficient amount and quality. The expression profile of tissue-specific marker genes indicated only limited, if any, contamination by other layers of the cornea, while the Smirnov-Grubbs test confirmed the absence of outlier samples. The dataset presented here should be useful for investigating the function/dysfunction of the cornea, as well as for extended transcriptome analyses integrated with expression data for non-coding RNAs. |
format | Online Article Text |
id | pubmed-7680133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76801332020-11-24 Transcriptome dataset of human corneal endothelium based on ribosomal RNA-depleted RNA-Seq data Tokuda, Yuichi Okumura, Naoki Komori, Yuya Hanada, Naoya Tashiro, Kei Koizumi, Noriko Nakano, Masakazu Sci Data Data Descriptor The corneal endothelium maintains corneal transparency; consequently, damage to this endothelium by a number of pathological conditions results in severe vision loss. Publicly available expression databases of human tissues are useful for investigating the pathogenesis of diseases and for developing new therapeutic modalities; however, databases for ocular tissues, and especially the corneal endothelium, are poor. Here, we have generated a transcriptome dataset from the ribosomal RNA-depleted total RNA from the corneal endothelium of eyes from seven Caucasians without ocular diseases. The results of principal component analysis and correlation coefficients (ranged from 0.87 to 0.96) suggested high homogeneity of our RNA-Seq dataset among the samples, as well as sufficient amount and quality. The expression profile of tissue-specific marker genes indicated only limited, if any, contamination by other layers of the cornea, while the Smirnov-Grubbs test confirmed the absence of outlier samples. The dataset presented here should be useful for investigating the function/dysfunction of the cornea, as well as for extended transcriptome analyses integrated with expression data for non-coding RNAs. Nature Publishing Group UK 2020-11-20 /pmc/articles/PMC7680133/ /pubmed/33219220 http://dx.doi.org/10.1038/s41597-020-00754-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Tokuda, Yuichi Okumura, Naoki Komori, Yuya Hanada, Naoya Tashiro, Kei Koizumi, Noriko Nakano, Masakazu Transcriptome dataset of human corneal endothelium based on ribosomal RNA-depleted RNA-Seq data |
title | Transcriptome dataset of human corneal endothelium based on ribosomal RNA-depleted RNA-Seq data |
title_full | Transcriptome dataset of human corneal endothelium based on ribosomal RNA-depleted RNA-Seq data |
title_fullStr | Transcriptome dataset of human corneal endothelium based on ribosomal RNA-depleted RNA-Seq data |
title_full_unstemmed | Transcriptome dataset of human corneal endothelium based on ribosomal RNA-depleted RNA-Seq data |
title_short | Transcriptome dataset of human corneal endothelium based on ribosomal RNA-depleted RNA-Seq data |
title_sort | transcriptome dataset of human corneal endothelium based on ribosomal rna-depleted rna-seq data |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680133/ https://www.ncbi.nlm.nih.gov/pubmed/33219220 http://dx.doi.org/10.1038/s41597-020-00754-1 |
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