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Robust transcriptional signatures for low-input RNA samples based on relative expression orderings
by
Guo, Zheng
, Zheng, Weicheng
, Song, Kai
, Cai, Hao
, Yan, Haidan
, Wang, Xianlong
, He, Jun
, Guo, You
, Guan, Qingzhou
, Liu, Huaping
, Li, Yawei
, Chen, Rou
in
Amplification
/ Animal Genetics and Genomics
/ Bias
/ Biomedical and Life Sciences
/ Cancer
/ Datasets
/ Gene expression
/ Genomes
/ Genomics
/ Life Sciences
/ Low-input RNA samples - amplification artificial signals - relative expression orderings - transcriptional signatures
/ Messenger RNA
/ Microarrays
/ Microbial Genetics and Genomics
/ Plant Genetics and Genomics
/ Proteomics
/ Research Article
/ Ribonucleic acid
/ RNA
/ RNA sequencing
/ Signatures
/ Transcription
/ Transcriptomic methods
2017
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Robust transcriptional signatures for low-input RNA samples based on relative expression orderings
by
Guo, Zheng
, Zheng, Weicheng
, Song, Kai
, Cai, Hao
, Yan, Haidan
, Wang, Xianlong
, He, Jun
, Guo, You
, Guan, Qingzhou
, Liu, Huaping
, Li, Yawei
, Chen, Rou
in
Amplification
/ Animal Genetics and Genomics
/ Bias
/ Biomedical and Life Sciences
/ Cancer
/ Datasets
/ Gene expression
/ Genomes
/ Genomics
/ Life Sciences
/ Low-input RNA samples - amplification artificial signals - relative expression orderings - transcriptional signatures
/ Messenger RNA
/ Microarrays
/ Microbial Genetics and Genomics
/ Plant Genetics and Genomics
/ Proteomics
/ Research Article
/ Ribonucleic acid
/ RNA
/ RNA sequencing
/ Signatures
/ Transcription
/ Transcriptomic methods
2017
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Robust transcriptional signatures for low-input RNA samples based on relative expression orderings
by
Guo, Zheng
, Zheng, Weicheng
, Song, Kai
, Cai, Hao
, Yan, Haidan
, Wang, Xianlong
, He, Jun
, Guo, You
, Guan, Qingzhou
, Liu, Huaping
, Li, Yawei
, Chen, Rou
in
Amplification
/ Animal Genetics and Genomics
/ Bias
/ Biomedical and Life Sciences
/ Cancer
/ Datasets
/ Gene expression
/ Genomes
/ Genomics
/ Life Sciences
/ Low-input RNA samples - amplification artificial signals - relative expression orderings - transcriptional signatures
/ Messenger RNA
/ Microarrays
/ Microbial Genetics and Genomics
/ Plant Genetics and Genomics
/ Proteomics
/ Research Article
/ Ribonucleic acid
/ RNA
/ RNA sequencing
/ Signatures
/ Transcription
/ Transcriptomic methods
2017
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Robust transcriptional signatures for low-input RNA samples based on relative expression orderings
Journal Article
Robust transcriptional signatures for low-input RNA samples based on relative expression orderings
2017
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Overview
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.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
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