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BMC Med Genomics. 2017 Oct 6;10(1):58. doi: 10.1186/s12920-017-0295-9.

RNA sequencing identifies novel non-coding RNA and exon-specific effects associated with cigarette smoking.

Author information

1
Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, USA.
2
Harvard Medical School, Boston, MA, 02115, USA.
3
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
4
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA.
5
Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
6
Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, USA. repjc@channing.harvard.edu.
7
Harvard Medical School, Boston, MA, 02115, USA. repjc@channing.harvard.edu.
8
Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA. repjc@channing.harvard.edu.

Abstract

BACKGROUND:

Cigarette smoking is the leading modifiable risk factor for disease and death worldwide. Previous studies quantifying gene-level expression have documented the effect of smoking on mRNA levels. Using RNA sequencing, it is possible to analyze the impact of smoking on complex regulatory phenomena (e.g. alternative splicing, differential isoform usage) leading to a more detailed understanding of the biology underlying smoking-related disease.

METHODS:

We used whole-blood RNA sequencing to describe gene and exon-level expression differences between 229 current and 286 former smokers in the COPDGene study. We performed differential gene expression and differential exon usage analyses using the voom/limma and DEXseq R packages. Samples from current and former smokers were compared while controlling for age, gender, race, lifetime smoke exposure, cell counts, and technical covariates.

RESULTS:

At an adjusted p-value <0.05, 171 genes were differentially expressed between current and former smokers. Differentially expressed genes included 7 long non-coding RNAs that have not been previously associated with smoking: LINC00599, LINC01362, LINC00824, LINC01624, RP11-563D10.1, RP11-98G13.1, AC004791.2. Secondary analysis of acute smoking (having smoked within 2-h) revealed 5 of the 171 smoking genes demonstrated an acute response above the baseline effect of chronic smoking. Exon-level analyses identified 9 exons from 8 genes with significant differential usage by smoking status, suggesting smoking-induced changes in isoform expression.

CONCLUSIONS:

Transcriptomic changes at the gene and exon levels from whole blood can refine our understanding of the molecular mechanisms underlying the response to smoking.

KEYWORDS:

Cigarette smoking; Differential expression; Exon usage; Isoforms; RNA-seq

PMID:
28985737
DOI:
10.1186/s12920-017-0295-9
[Indexed for MEDLINE]
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