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

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 regul...

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Main Authors: Margaret M. Parker (Author), Robert P. Chase (Author), Andrew Lamb (Author), Alejandro Reyes (Author), Aabida Saferali (Author), Jeong H. Yun (Author), Blanca E. Himes (Author), Edwin K. Silverman (Author), Craig P. Hersh (Author), Peter J. Castaldi (Author)
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Published: BMC, 2017-10-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Margaret M. Parker  |e author 
700 1 0 |a Robert P. Chase  |e author 
700 1 0 |a Andrew Lamb  |e author 
700 1 0 |a Alejandro Reyes  |e author 
700 1 0 |a Aabida Saferali  |e author 
700 1 0 |a Jeong H. Yun  |e author 
700 1 0 |a Blanca E. Himes  |e author 
700 1 0 |a Edwin K. Silverman  |e author 
700 1 0 |a Craig P. Hersh  |e author 
700 1 0 |a Peter J. Castaldi  |e author 
245 0 0 |a RNA sequencing identifies novel non-coding RNA and exon-specific effects associated with cigarette smoking 
260 |b BMC,   |c 2017-10-01T00:00:00Z. 
500 |a 10.1186/s12920-017-0295-9 
500 |a 1755-8794 
520 |a 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. 
546 |a EN 
690 |a RNA-seq 
690 |a Differential expression 
690 |a Cigarette smoking 
690 |a Exon usage 
690 |a Isoforms 
690 |a Internal medicine 
690 |a RC31-1245 
690 |a Genetics 
690 |a QH426-470 
655 7 |a article  |2 local 
786 0 |n BMC Medical Genomics, Vol 10, Iss 1, Pp 1-10 (2017) 
787 0 |n http://link.springer.com/article/10.1186/s12920-017-0295-9 
787 0 |n https://doaj.org/toc/1755-8794 
856 4 1 |u https://doaj.org/article/8a7fa65ce2df415b8b50fc1f9c82a943  |z Connect to this object online.