Small RNA evolution and distribution patterns based on digital gene expression profiling

This thesis describes methods and applications for small RNA profiling methods. Firstly, we describe the qualification of digital gene expression (DGE) profiling for small RNAs. From a single RNA sample, we constructed cDNA libraries by three different library preparation methods. These libraries were sequenced on two deep-sequencing platforms, as well as by Sanger sequencing. Cross-comparison of profiles revealed that library preparation techniques are strongly biased, while sequencing platforms hardly affect the read distribution. However, the observed bias is highly reproducible. Whereas this disqualifies DGE profiling for measuring absolute levels of miRNAs, we show that DGE profiling is a robust method for quantifying relative expression of small RNAs. Next, we describe small RNA features of 4 different nematode species, spanning an evolutionary distance of max. 430M years. Almost half of the miRNAs that we clone are conserved at the seed level in all species, while the number of species-specific miRNAs increases with evolutionary distance. We describe various mechanisms by which miRNAs evolve from existing miRNAs. Furthermore, we identified 21U RNAs in all species. The distinct 5’ core motif “GTTTCA” that has been described in C. elegans appears to be conserved in the other species, while 21U sequence itself is fully diverged. A rat small RNA atlas has been constructed in chapter 4. We performed DGE profiling on 6 tissues and found a large number of tissue-specific miRNAs, while the number of tissue-avoidant miRNAs is low. Most of the miRNAs are conserved in mouse, but new miRNAs have been occasionally introduced in the rat. Tissue-specific profiles are highly similar between the Spontaneous Hypertensive Rat (SHR) and Brown Norway polydactyly-luxate syndrome (BN-Lx) strains; nevertheless we obtained evidence for strain-specific miRNA expression for 4 miRNAs in the liver. Finally, we created an in-depth overview of piRNA clusters in the rat. Finally we review the current and future applications of DGE profiling in miRNA-related research. Furthermore, the robustness of miRNA precursors is introduced and discussed in light of miRNA evolution.