RNA sequencing of transcriptomes in human brain regions: Protein-coding and non-coding RNAs, isoforms and alleles

Amy Webb, Audrey C. Papp, Amanda Curtis, Leslie C. Newman, Maciej Pietrzak, Michal Seweryn, Samuel K. Handelman, Grzegorz A. Rempala, Daqing Wang, Erica Graziosa, Rachel F. Tyndale, Caryn Lerman, John R. Kelsoe, Deborah C Mash, Wolfgang Sadee

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Background: We used RNA sequencing to analyze transcript profiles of ten autopsy brain regions from ten subjects. RNA sequencing techniques were designed to detect both coding and non-coding RNA, splice isoform composition, and allelic expression. Brain regions were selected from five subjects with a documented history of smoking and five non-smokers. Paired-end RNA sequencing was performed on SOLiD instruments to a depth of >40 million reads, using linearly amplified, ribosomally depleted RNA. Sequencing libraries were prepared with both poly-dT and random hexamer primers to detect all RNA classes, including long non-coding (lncRNA), intronic and intergenic transcripts, and transcripts lacking poly-A tails, providing additional data not previously available. The study was designed to generate a database of the complete transcriptomes in brain region for gene network analyses and discovery of regulatory variants. Results: Of 20,318 protein coding and 18,080 lncRNA genes annotated from GENCODE and lncipedia, 12 thousand protein coding and 2 thousand lncRNA transcripts were detectable at a conservative threshold. Of the aligned reads, 52 % were exonic, 34 % intronic and 14 % intergenic. A majority of protein coding genes (65 %) was expressed in all regions, whereas ncRNAs displayed a more restricted distribution. Profiles of RNA isoforms varied across brain regions and subjects at multiple gene loci, with neurexin 3 (NRXN3) a prominent example. Allelic RNA ratios deviating from unity were identified in > 400 genes, detectable in both protein-coding and non-coding genes, indicating the presence of cis-acting regulatory variants. Mathematical modeling was used to identify RNAs stably expressed in all brain regions (serving as potential markers for normalizing expression levels), linked to basic cellular functions. An initial analysis of differential expression analysis between smokers and nonsmokers implicated a number of genes, several previously associated with nicotine exposure. Conclusions: RNA sequencing identifies distinct and consistent differences in gene expression between brain regions, with non-coding RNA displaying greater diversity between brain regions than mRNAs. Numerous RNAs exhibit robust allele selective expression, proving a means for discovery of cis-acting regulatory factors with potential clinical relevance.

Original languageEnglish (US)
Article number990
JournalBMC Genomics
Volume16
Issue number1
DOIs
StatePublished - Nov 23 2015

Fingerprint

RNA Isoforms
RNA Sequence Analysis
Untranslated RNA
Transcriptome
Open Reading Frames
Alleles
Long Noncoding RNA
Brain
RNA
Genes
Proteins
Poly T
Messenger RNA
Gene Regulatory Networks
Genetic Association Studies
Nicotine
Autopsy
Smoking
Databases
Gene Expression

Keywords

  • Allelic expression imbalance
  • Brain regions
  • Differential expression
  • Isoform fraction
  • Non-coding RNA
  • RNA sequencing

ASJC Scopus subject areas

  • Biotechnology
  • Genetics

Cite this

Webb, A., Papp, A. C., Curtis, A., Newman, L. C., Pietrzak, M., Seweryn, M., ... Sadee, W. (2015). RNA sequencing of transcriptomes in human brain regions: Protein-coding and non-coding RNAs, isoforms and alleles. BMC Genomics, 16(1), [990]. https://doi.org/10.1186/s12864-015-2207-8

RNA sequencing of transcriptomes in human brain regions : Protein-coding and non-coding RNAs, isoforms and alleles. / Webb, Amy; Papp, Audrey C.; Curtis, Amanda; Newman, Leslie C.; Pietrzak, Maciej; Seweryn, Michal; Handelman, Samuel K.; Rempala, Grzegorz A.; Wang, Daqing; Graziosa, Erica; Tyndale, Rachel F.; Lerman, Caryn; Kelsoe, John R.; Mash, Deborah C; Sadee, Wolfgang.

In: BMC Genomics, Vol. 16, No. 1, 990, 23.11.2015.

Research output: Contribution to journalArticle

Webb, A, Papp, AC, Curtis, A, Newman, LC, Pietrzak, M, Seweryn, M, Handelman, SK, Rempala, GA, Wang, D, Graziosa, E, Tyndale, RF, Lerman, C, Kelsoe, JR, Mash, DC & Sadee, W 2015, 'RNA sequencing of transcriptomes in human brain regions: Protein-coding and non-coding RNAs, isoforms and alleles', BMC Genomics, vol. 16, no. 1, 990. https://doi.org/10.1186/s12864-015-2207-8
Webb, Amy ; Papp, Audrey C. ; Curtis, Amanda ; Newman, Leslie C. ; Pietrzak, Maciej ; Seweryn, Michal ; Handelman, Samuel K. ; Rempala, Grzegorz A. ; Wang, Daqing ; Graziosa, Erica ; Tyndale, Rachel F. ; Lerman, Caryn ; Kelsoe, John R. ; Mash, Deborah C ; Sadee, Wolfgang. / RNA sequencing of transcriptomes in human brain regions : Protein-coding and non-coding RNAs, isoforms and alleles. In: BMC Genomics. 2015 ; Vol. 16, No. 1.
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AU - Pietrzak, Maciej

AU - Seweryn, Michal

AU - Handelman, Samuel K.

AU - Rempala, Grzegorz A.

AU - Wang, Daqing

AU - Graziosa, Erica

AU - Tyndale, Rachel F.

AU - Lerman, Caryn

AU - Kelsoe, John R.

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N2 - Background: We used RNA sequencing to analyze transcript profiles of ten autopsy brain regions from ten subjects. RNA sequencing techniques were designed to detect both coding and non-coding RNA, splice isoform composition, and allelic expression. Brain regions were selected from five subjects with a documented history of smoking and five non-smokers. Paired-end RNA sequencing was performed on SOLiD instruments to a depth of >40 million reads, using linearly amplified, ribosomally depleted RNA. Sequencing libraries were prepared with both poly-dT and random hexamer primers to detect all RNA classes, including long non-coding (lncRNA), intronic and intergenic transcripts, and transcripts lacking poly-A tails, providing additional data not previously available. The study was designed to generate a database of the complete transcriptomes in brain region for gene network analyses and discovery of regulatory variants. Results: Of 20,318 protein coding and 18,080 lncRNA genes annotated from GENCODE and lncipedia, 12 thousand protein coding and 2 thousand lncRNA transcripts were detectable at a conservative threshold. Of the aligned reads, 52 % were exonic, 34 % intronic and 14 % intergenic. A majority of protein coding genes (65 %) was expressed in all regions, whereas ncRNAs displayed a more restricted distribution. Profiles of RNA isoforms varied across brain regions and subjects at multiple gene loci, with neurexin 3 (NRXN3) a prominent example. Allelic RNA ratios deviating from unity were identified in > 400 genes, detectable in both protein-coding and non-coding genes, indicating the presence of cis-acting regulatory variants. Mathematical modeling was used to identify RNAs stably expressed in all brain regions (serving as potential markers for normalizing expression levels), linked to basic cellular functions. An initial analysis of differential expression analysis between smokers and nonsmokers implicated a number of genes, several previously associated with nicotine exposure. Conclusions: RNA sequencing identifies distinct and consistent differences in gene expression between brain regions, with non-coding RNA displaying greater diversity between brain regions than mRNAs. Numerous RNAs exhibit robust allele selective expression, proving a means for discovery of cis-acting regulatory factors with potential clinical relevance.

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