Non-sequential and multi-step splicing of the dystrophin transcript

<p>The dystrophin protein encoding DMD gene is the longest human gene. The 2.2 Mb long human dystrophin transcript takes 16 hours to be transcribed and is co-transcriptionally spliced. It contains long introns (24 over 10kb long, 5 over 100kb long) and the heterogeneity in intron size makes it an ideal transcript to study different aspects of the human splicing process. Splicing is a complex process and much is unknown regarding the splicing of long introns in human genes.</p> <p>Here, we used ultra-deep transcript sequencing to characterize splicing of the dystrophin transcripts in 3 different human skeletal muscle cell lines, and explored the order of intron removal and multi-step splicing. Coverage and read pair analyses showed that around 40% of the introns were not always removed sequentially. Additionally, for the first time, we report that non-consecutive intron removal resulted in 3 or more joined exons which are flanked by unspliced introns and we defined these joined exons as an exon block. Lastly, computational and experimental data revealed that, for the majority of dystrophin introns, multistep splicing events are used to splice out a single intron.</p> <p>Overall, our data show for the first time in a human transcript, that multi-step intron removal is a general feature of mRNA splicing.</p

Additional file 2: of Full-length mRNA sequencing uncovers a widespread coupling between transcription initiation and mRNA processing

Reviewer reports and authors’ response to reviewers. (DOCX 30 kb

Trait-associated SNPs affecting DeepSAGE tags of 94 peripheral blood samples, but not detected in an array-based eQTL dataset of 1,469 peripheral blood samples.

<p>Trait-associated SNPs affecting DeepSAGE tags of 94 peripheral blood samples, but not detected in an array-based eQTL dataset of 1,469 peripheral blood samples.</p

<i>Cis-</i>regulating SNPs significantly^* affecting multiple tags of the same gene in opposite directions.

*<p>Only significant eQTLs with FDR<0.05 for both <i>cis-</i>regulated tags were used.</p

The number of <i>cis-</i>regulated tags per gene.

<p>The percentages of cis-regulated tags mapping into the same gene are indicated (781 genes overall). For nearly half of the genes (48%) only one tag shows an eQTL effect. If multiple tags map within the same gene, only one eQTL tag should pass the FDR<0.05 significance threshold while the other tag could be less significant. For these eQTLs the allelic direction is shown: same allelic direction (multiple tags within the same gene are cis-regulated by a SNP in the same direction), significantly opposite allelic direction (multiple tags within the same gene are cis-regulated by a SNP but with opposite directions and the difference between the correlation coefficients is significant), or opposite allelic direction but not significant (if the difference between correlation coefficients is not significant).</p

Description of RNA next generation sequencing datasets.

<p>Description of RNA next generation sequencing datasets.</p

Fraction of <i>cis-</i>regulated genes in bins by mean gene expression levels for DeepSAGE and Affymetrix data.

<p>For each dataset, all genes were sorted by their mean gene expression levels, and divided into ten equal bins. The X-axis reflects these bins, which are sorted by increasing mean gene expression levels. The Y-axis reflects the fraction of <i>cis</i>-regulated genes that fall into each bin.</p

Number of <i>cis-</i>regulated tags mapping to different genomic regions in tag-wise DeepSAGE eQTL mapping.

<p>Number of <i>cis-</i>regulated tags mapping to different genomic regions in tag-wise DeepSAGE eQTL mapping.</p

Trait-associated SNPs detected in the sequencing-based transcript-wise meta-analysis, but not detected in array-based eQTL dataset of 1,469 peripheral blood samples.

<p>Trait-associated SNPs detected in the sequencing-based transcript-wise meta-analysis, but not detected in array-based eQTL dataset of 1,469 peripheral blood samples.</p

The choice of proximal/distal polyadenylation site in genes <i>IRF5</i> and <i>HPS1</i> depends on the genotypes of rs10488630 and rs11189600, respectively.

<p>The ratio between the abundance of transcripts with proximal and distal 3′-UTR RT-qPCR products in <i>IRF5</i> (left) and <i>HPS1</i> (right) depends on the genotypes of <i>cis-</i>regulating SNPs rs10488630 and rs11189600, respectively. N denotes the number of individuals included in the analysis. These results indicate allele-specific preference for use of a proximal and distal polyadenlyation site.</p