Objective:

Gene expression profiles have been mainly determined by analysis of transcript abundance. Overcoming this, recently by combining ribosome profiling (Ribo-seq) with a ribosome-tagging approach (Ribo-tag), it was possible to determine the translated transcriptome in specific cell types from the heart. Therefore, a mouse line in where the ribosome was tagged only in cardiomyocytes gave the possible to pull down the cell-type-specific ribosome including attached mRNA out of a total RNA sample from an isolated heart. However, in terms of alternative splicing and differential isoform usage including not previously annotated transcripts, this method has shortcomings. By combing the Ribo-Seq/Ribo-Tag approach with full-length sequencing (SMRT), it is possible to get the full-length-transcriptome with 99% accuracy of only those mRNA-Sequences which are associated to the ribosome, giving insights into the complex mechanism of translated splice variants directly.

Methods and Results:

Both cardiomyocyte-specific total RNA and ribosomal-bound RNA from the same mice were used for long-read mRNA sequencing, resulting in full-length transcriptomes with 99% sequence accuracy. While in total RNA 79760 mRNA isoforms could be found, this was significantly lower in the ribosomal-bound mRNA, where only 1698 mRNA isoforms were detectable (Figure 1, A). Quality control parameters including RIN-Score, intra-priming and isoform distribution per gene were comparable. From those transcripts that were detected in totalRNA and previously known (n = 12051), 795 could be detected in the ribosomal-bound mRNA as well (7%). Additionally, after excluding possible artifacts (antisense, intergenic, incomplete splice match) we could identify 17895 novel transcripts (“Novel Not in Catalog”, NNC and “Novel in Catalog”, NIC) in totalRNA, with 979 (6%) also found in the ribosomal mRNA. Differential usage of isoform expression takes place, shown for actin-related gene Actg1 as example for structural cardiac genes (Figure 1, B): While in total RNA, isoform usage divides to more than one transcript, only one predominant isoform can be found in the ribosomal mRNA dataset.

Conclusions:

Combining RiboTag-Seq and SMRT-Seq, we were able to detect the cardiomyocyte-specific full-length transcriptome bound to the ribosome, coming closer to the real translatome. Additionally, comparing this to the corresponding total mRNA, we gathered information on the percentage of isoform usage in not only known but also novel transcripts, making it possible to target specifically those isoforms which are translated. Additionally, as these mRNA-Sequences are cell-type-specific, it gives also the opportunity to distinguish in future between differences in translation across different tissue (e.g. cardiomyocytes, fibroblasts, endothelial cells, macrophages).