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. 2015 Nov 23:16:990.
doi: 10.1186/s12864-015-2207-8.

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

Amy Webb  1   2 , Audrey C Papp  3 , Amanda Curtis  4 , Leslie C Newman  5 , Maciej Pietrzak  6   7 , Michal Seweryn  8 , Samuel K Handelman  9 , Grzegorz A Rempala  10 , Daqing Wang  11 , Erica Graziosa  12 , Rachel F Tyndale  13 , Caryn Lerman  14 , John R Kelsoe  15   16 , Deborah C Mash  17 , Wolfgang Sadee  18   19   20   21
Affiliations

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

Amy Webb et al. BMC Genomics. .

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.

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Figures

Fig. 1
Fig. 1
Read alignment across genomic regions. Presents the percentage of aligned reads falling within genomic regions of different types--exonic, intronic, and intergenic as annotated by GENCODE and lncipedia; any reads aligning to the mitochondrial chromosome; and ribosomal reads filtered by during alignment (18S, 28S, and 5.8S only)
Fig. 2
Fig. 2
Brain region specificity of RNA classes. Presented is the percentage of different RNA types, as annotated in GENCODE/lncipedia, detectable across brain regions. Detectability is defined as FPKM > 2 in 2+ samples. This includes 10,680 protein coding genes, 242 pseudogenes, and 945 noncoding. A higher percentage of protein coding RNAs are detectable across all 10 regions compared to non-coding RNAs and pseudogenes
Fig. 3
Fig. 3
Number of detectable RNAs at different FPKM cutoffs. The average number of detectable protein coding and non-coding RNAs is shown at different expression cutoff levels. This illustrates the working pool of RNAs available depending of expression cutoff
Fig. 4
Fig. 4
NRXN3 isoform representation across brain region. NRXN3 was found to be a gene with extreme differences in isoform representation. The top panel shows 5 isoforms annotated by RefSeq and the middle panel focuses on the difference between the major isoforms (Dup0 and Dup5). The bottom panel shows the representation of all isoforms as a fraction of the whole gene expression, combining Dup1 and Dup2 into “minor isoforms”. Dup0 is the major isoform in all Broadmann’s areas, insula, amygdala, and hippocampus. Dup5 is the major isoform in cerebellum and raphae nuclei. Samples from the posterior putamen are mixed
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