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Robust transcriptional signatures for low-input RNA samples based on relative expression orderings
BACKGROUND: It is often difficult to obtain sufficient quantity of RNA molecules for gene expression profiling under many practical situations. Amplification from low-input samples may induce artificial signals. RESULTS: We compared the expression measurements of low-input mRNA samples, from 25 pg t...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5704640/ https://www.ncbi.nlm.nih.gov/pubmed/29179677 http://dx.doi.org/10.1186/s12864-017-4280-7 |
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author | Liu, Huaping Li, Yawei He, Jun Guan, Qingzhou Chen, Rou Yan, Haidan Zheng, Weicheng Song, Kai Cai, Hao Guo, You Wang, Xianlong Guo, Zheng |
author_facet | Liu, Huaping Li, Yawei He, Jun Guan, Qingzhou Chen, Rou Yan, Haidan Zheng, Weicheng Song, Kai Cai, Hao Guo, You Wang, Xianlong Guo, Zheng |
author_sort | Liu, Huaping |
collection | PubMed |
description | BACKGROUND: It is often difficult to obtain sufficient quantity of RNA molecules for gene expression profiling under many practical situations. Amplification from low-input samples may induce artificial signals. RESULTS: We compared the expression measurements of low-input mRNA samples, from 25 pg to 1000 pg mRNA, which were amplified and profiled by Smart-seq, DP-seq and CEL-seq techniques using the Illumina HiSeq 2000 platform, with those of the paired high-input (50 ng) mRNA samples. Even with 1000 pg mRNA input, we found that thousands of genes had at least 2 folds-change of expression levels in the low-input samples compared with the corresponding paired high-input samples. Consequently, a transcriptional signature based on quantitative expression values and determined from high-input RNA samples cannot be applied to low-input samples, and vice versa. In contrast, the within-sample relative expression orderings (REOs) of approximately 90% of all the gene pairs in the high-input samples were maintained in the paired low-input samples with 1000 pg input mRNA molecules. Similar results were observed in the low-input total RNA samples amplified and profiled by the Whole-Genome DASL technique using the Illumina HumanRef-8 v3.0 platform. As a proof of principle, we developed REOs-based signatures from high-input RNA samples for discriminating cancer tissues and showed that they can be robustly applied to low-input RNA samples. CONCLUSIONS: REOs-based signatures determined from the high-input RNA samples can be robustly applied to samples profiled with the low-input RNA samples, as low as the 1000 pg and 250 pg input samples but no longer stable in samples with less than 250 pg RNA input to a certain degree. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-017-4280-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5704640 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57046402017-12-05 Robust transcriptional signatures for low-input RNA samples based on relative expression orderings Liu, Huaping Li, Yawei He, Jun Guan, Qingzhou Chen, Rou Yan, Haidan Zheng, Weicheng Song, Kai Cai, Hao Guo, You Wang, Xianlong Guo, Zheng BMC Genomics Research Article BACKGROUND: It is often difficult to obtain sufficient quantity of RNA molecules for gene expression profiling under many practical situations. Amplification from low-input samples may induce artificial signals. RESULTS: We compared the expression measurements of low-input mRNA samples, from 25 pg to 1000 pg mRNA, which were amplified and profiled by Smart-seq, DP-seq and CEL-seq techniques using the Illumina HiSeq 2000 platform, with those of the paired high-input (50 ng) mRNA samples. Even with 1000 pg mRNA input, we found that thousands of genes had at least 2 folds-change of expression levels in the low-input samples compared with the corresponding paired high-input samples. Consequently, a transcriptional signature based on quantitative expression values and determined from high-input RNA samples cannot be applied to low-input samples, and vice versa. In contrast, the within-sample relative expression orderings (REOs) of approximately 90% of all the gene pairs in the high-input samples were maintained in the paired low-input samples with 1000 pg input mRNA molecules. Similar results were observed in the low-input total RNA samples amplified and profiled by the Whole-Genome DASL technique using the Illumina HumanRef-8 v3.0 platform. As a proof of principle, we developed REOs-based signatures from high-input RNA samples for discriminating cancer tissues and showed that they can be robustly applied to low-input RNA samples. CONCLUSIONS: REOs-based signatures determined from the high-input RNA samples can be robustly applied to samples profiled with the low-input RNA samples, as low as the 1000 pg and 250 pg input samples but no longer stable in samples with less than 250 pg RNA input to a certain degree. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-017-4280-7) contains supplementary material, which is available to authorized users. BioMed Central 2017-11-28 /pmc/articles/PMC5704640/ /pubmed/29179677 http://dx.doi.org/10.1186/s12864-017-4280-7 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Liu, Huaping Li, Yawei He, Jun Guan, Qingzhou Chen, Rou Yan, Haidan Zheng, Weicheng Song, Kai Cai, Hao Guo, You Wang, Xianlong Guo, Zheng Robust transcriptional signatures for low-input RNA samples based on relative expression orderings |
title | Robust transcriptional signatures for low-input RNA samples based on relative expression orderings |
title_full | Robust transcriptional signatures for low-input RNA samples based on relative expression orderings |
title_fullStr | Robust transcriptional signatures for low-input RNA samples based on relative expression orderings |
title_full_unstemmed | Robust transcriptional signatures for low-input RNA samples based on relative expression orderings |
title_short | Robust transcriptional signatures for low-input RNA samples based on relative expression orderings |
title_sort | robust transcriptional signatures for low-input rna samples based on relative expression orderings |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5704640/ https://www.ncbi.nlm.nih.gov/pubmed/29179677 http://dx.doi.org/10.1186/s12864-017-4280-7 |
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