Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Feb 13;20(1):134.
doi: 10.1186/s12864-019-5502-y.

Identification and characterization of genes with absolute mRNA abundances changes in tumor cells with varied transcriptome sizes

Hao Cai  1 , Xiangyu Li  2 , Jun He  2 , Wenbin Zhou  3 , Kai Song  3 , You Guo  1 , Huaping Liu  1 , Qingzhou Guan  2 , Haidan Yan  2 , Xianlong Wang  4 , Zheng Guo  5   6
Affiliations

Identification and characterization of genes with absolute mRNA abundances changes in tumor cells with varied transcriptome sizes

Hao Cai et al. BMC Genomics. .

Abstract

Background: The amount of RNA per cell, namely the transcriptome size, may vary under many biological conditions including tumor. If the transcriptome size of two cells is different, direct comparison of the expression measurements on the same amount of total RNA for two samples can only identify genes with changes in the relative mRNA abundances, i.e., cellular mRNA concentration, rather than genes with changes in the absolute mRNA abundances.

Results: Our recently proposed RankCompV2 algorithm identify differentially expressed genes (DEGs) through comparing the relative expression orderings (REOs) of disease samples with that of normal samples. We reasoned that both the mRNA concentration and the absolute abundances of these DEGs must have changes in disease samples. In simulation experiments, this method showed excellent performance for identifying DEGs between normal and disease samples with different transcriptome sizes. Through analyzing data for ten cancer types, we found that a significantly higher proportion of the DEGs with absolute mRNA abundance changes overlapped or directly interacted with known cancer driver genes and anti-cancer drug targets than that of the DEGs only with mRNA concentration changes alone identified by the traditional methods. The DEGs with increased absolute mRNA abundances were enriched in DNA damage-related pathways, while DEGs with decreased absolute mRNA abundances were enriched in immune and metabolism associated pathways.

Conclusions: Both the mRNA concentration and the absolute abundances of the DEGs identified through REOs comparison change in disease samples in comparison with normal samples. In cancers these genes might play more important upstream roles in carcinogenesis.

Keywords: Absolute mRNA abundances; Cellular mRNA concentration; Differentially expressed gene; Relative expression ordering.

PubMed Disclaimer

Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Reproducibility evaluation of DEGs identified by RankCompV2. a Comparison of DEGs identified by RankCompV2 with DEGs identified by SAM or edgeR in the same dataset. POG12 (or POG21) denotes the ratio of consistently detected DEGs by the two methods to DEGs identified by RankCompV2 (or by SAM or edgeR) for the same dataset. b Comparison of RankCompV2 DEGs identified from different datasets. POG12 (or POG21) denotes the ratio of consistently detected DEGs from two datasets to DEGs detected from the first dataset (or the second dataset) for each cancer type. The concordance score denotes the percentage of consistently detected DEGs that display the same dysregulation directions to the overlapped DEGs between two DEG lists
Fig. 2
Fig. 2
Association between the identified absolute and relative DEGs with known cancer driver genes or drug targets. a 616 cancer driver genes from COSMIC; b cancer driver genes from DriverDBv2; c anti-cancer drug targets. Statistically significant differences (p < 0.05) were found in all the ratios between absolute DEGs and relative DEGs
Fig. 3
Fig. 3
The pathways significantly enriched with absolute and relative DEGs, respectively, in each cancer type and commonly enriched in at least five cancer types
See this image and copyright information in PMC

References

    1. Loven J, Orlando DA, Sigova AA, Lin CY, Rahl PB, Burge CB, Levens DL, Lee TI, Young RA. Revisiting global gene expression analysis. Cell. 2012;151(3):476–482. - PMC - PubMed
    1. Nie Z, Hu G, Wei G, Cui K, Yamane A, Resch W, Wang R, Green DR, Tessarollo L, Casellas R, et al. c-Myc is a universal amplifier of expressed genes in lymphocytes and embryonic stem cells. Cell. 2012;151(1):68–79. - PMC - PubMed
    1. Weaver DA, Nestor-Kalinoski AL, Craig K, Gorris M, Parikh T, Mabry H, Allison DC. Corrections for mRNA extraction and sample normalization errors find increased mRNA levels may compensate for cancer haplo-insufficiency. Genes Chromosomes Cancer. 2014;53(2):194–210. - PMC - PubMed
    1. Birchler JA. Facts and artifacts in studies of gene expression in aneuploids and sex chromosomes. Chromosoma. 2014;123(5):459–469. - PubMed
    1. Stevens JB, Horne SD, Abdallah BY, Ye CJ, Heng HH. Chromosomal instability and transcriptome dynamics in cancer. Cancer Metastasis Rev. 2013;32(3–4):391–402. - PubMed

LinkOut - more resources