A multi-omics dataset of human transcriptome and proteome stable reference
Abstract The development of high-throughput omics technology has greatly promoted the development of biomedicine. However, the poor reproducibility of omics techniques limits their application. It is necessary to use standard reference materials of complex RNAs or proteins to test and calibrate the...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02359-w |
| _version_ | 1797779022274363392 |
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| author | Shaohua Lu Hong Lu Tingkai Zheng Huiming Yuan Hongli Du Youhe Gao Yongtao Liu Xuanzhen Pan Wenlu Zhang Shuying Fu Zhenghua Sun Jingjie Jin Qing-Yu He Yang Chen Gong Zhang |
| author_facet | Shaohua Lu Hong Lu Tingkai Zheng Huiming Yuan Hongli Du Youhe Gao Yongtao Liu Xuanzhen Pan Wenlu Zhang Shuying Fu Zhenghua Sun Jingjie Jin Qing-Yu He Yang Chen Gong Zhang |
| author_sort | Shaohua Lu |
| collection | DOAJ |
| description | Abstract The development of high-throughput omics technology has greatly promoted the development of biomedicine. However, the poor reproducibility of omics techniques limits their application. It is necessary to use standard reference materials of complex RNAs or proteins to test and calibrate the accuracy and reproducibility of omics workflows. The transcriptome and proteome of most cell lines shift during culturing, which limits their applicability as standard samples. In this study, we demonstrated that the human hepatocellular cell line MHCC97H has a very stable transcriptome (r = 0.983~0.997) and proteome (r = 0.966~0.988 for data-dependent acquisition, r = 0.970~0.994 for data-independent acquisition) after 9 subculturing generations, which allows this steady standard sample to be consistently produced on an industrial scale in long term. Moreover, this stability was maintained across labs and platforms. In sum, our study provides omics standard reference material and reference datasets for transcriptomic and proteomics research. This helps to further standardize the workflow and data quality of omics techniques and thus promotes the application of omics technology in precision medicine. |
| first_indexed | 2024-03-12T23:25:47Z |
| format | Article |
| id | doaj.art-035d00060d924140930963c89177b3b2 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-03-12T23:25:47Z |
| publishDate | 2023-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-035d00060d924140930963c89177b3b22023-07-16T11:09:10ZengNature PortfolioScientific Data2052-44632023-07-0110111210.1038/s41597-023-02359-wA multi-omics dataset of human transcriptome and proteome stable referenceShaohua Lu0Hong Lu1Tingkai Zheng2Huiming Yuan3Hongli Du4Youhe Gao5Yongtao Liu6Xuanzhen Pan7Wenlu Zhang8Shuying Fu9Zhenghua Sun10Jingjie Jin11Qing-Yu He12Yang Chen13Gong Zhang14Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan UniversityKey Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan UniversityKey Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan UniversityCAS Key Laboratory of Separation Science for Analytical Chemistry, National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of ScienceSchool of Biology and Biological Engineering, South China University of TechnologyDepartment of Biochemistry and Molecular Biology, Beijing Key Laboratory of Gene Engineering Drug and Biotechnology, Beijing Normal UniversityDepartment of Biochemistry and Molecular Biology, Beijing Key Laboratory of Gene Engineering Drug and Biotechnology, Beijing Normal UniversityDepartment of Biochemistry and Molecular Biology, Beijing Key Laboratory of Gene Engineering Drug and Biotechnology, Beijing Normal UniversitySchool of Biology and Biological Engineering, South China University of TechnologySchool of Biology and Biological Engineering, South China University of TechnologyKey Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan UniversityKey Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan UniversityKey Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan UniversityKey Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan UniversityKey Laboratory of Functional Protein Research of Guangdong Higher Education Institutes and MOE Key Laboratory of Tumor Molecular Biology, Institute of Life and Health Engineering, Jinan UniversityAbstract The development of high-throughput omics technology has greatly promoted the development of biomedicine. However, the poor reproducibility of omics techniques limits their application. It is necessary to use standard reference materials of complex RNAs or proteins to test and calibrate the accuracy and reproducibility of omics workflows. The transcriptome and proteome of most cell lines shift during culturing, which limits their applicability as standard samples. In this study, we demonstrated that the human hepatocellular cell line MHCC97H has a very stable transcriptome (r = 0.983~0.997) and proteome (r = 0.966~0.988 for data-dependent acquisition, r = 0.970~0.994 for data-independent acquisition) after 9 subculturing generations, which allows this steady standard sample to be consistently produced on an industrial scale in long term. Moreover, this stability was maintained across labs and platforms. In sum, our study provides omics standard reference material and reference datasets for transcriptomic and proteomics research. This helps to further standardize the workflow and data quality of omics techniques and thus promotes the application of omics technology in precision medicine.https://doi.org/10.1038/s41597-023-02359-w |
| spellingShingle | Shaohua Lu Hong Lu Tingkai Zheng Huiming Yuan Hongli Du Youhe Gao Yongtao Liu Xuanzhen Pan Wenlu Zhang Shuying Fu Zhenghua Sun Jingjie Jin Qing-Yu He Yang Chen Gong Zhang A multi-omics dataset of human transcriptome and proteome stable reference Scientific Data |
| title | A multi-omics dataset of human transcriptome and proteome stable reference |
| title_full | A multi-omics dataset of human transcriptome and proteome stable reference |
| title_fullStr | A multi-omics dataset of human transcriptome and proteome stable reference |
| title_full_unstemmed | A multi-omics dataset of human transcriptome and proteome stable reference |
| title_short | A multi-omics dataset of human transcriptome and proteome stable reference |
| title_sort | multi omics dataset of human transcriptome and proteome stable reference |
| url | https://doi.org/10.1038/s41597-023-02359-w |
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