Computational RNA Biology Group
The purpose of our group is to apply state-of-the-art computational and genomic methods to address fundamental questions in RNA biology. The focus is on quantitatively describing and functionally characterizing animal transcriptomes, and methods include next-generation sequencing of single and pooled cells, as well as development of source code and custom wet-lab protocols.
Of particular interest to us is the biogenesis and function of microRNAs (miRNAs). These are 22 nucleotide RNAs which down-regulate the expression of target protein coding genes. miRNAs are found in all animals studied, in numbers which largely correlate with organismal complexity. For instance, nematodes have around 200 miRNA genes, while humans have more than 3000. Mutant animals that are deficient in miRNAs generally exhibit gross developmental defects or embryonic lethality, underlining the importance of these regulators. Given that most animal mRNAs are likely targets, it is not surprising that miRNAs are involved in numerous biological processes, ranging from formation of cell identity to development and human disease. Even though miRNAs have been systematically studied for more than ten years, fundamental questions regarding their biogenesis and function remain unanswered. These include:
Structure and sequence features determining miRNA biogenesis
The human transcriptome contains more than 100,000 hairpin RNA structures, more than half of which are located in mRNAs. These hairpins are potential entry points into miRNA biogenesis, and thus constitute cross-roads for nuclear transcripts. They can either be cleaved into regulatory miRNAs or they can avoid cleavage and function as full-length transcripts, for instance through cytoplasmic transport and translation. Currently little is understood of the features that determine this critical decision, and attempts to elucidate them are hampered by the lack of genomic methods in the field of miRNA biogenesis. We are currently developing the first method to test hairpin cleavage transcriptome-wide. We will use this method to profile the vast majority of human hairpin structures, and will apply machine-learning approaches to extract the structure and sequence features which license or block the miRNA biogenesis.
miRNA functions in single cells
It is well established that miRNAs can strongly down-regulate their mRNA targets during dynamic processes such as development. However, the functions of miRNAs in steady-state conditions are not well understood, although there is emerging evidence that they can buffer oscillations of their target mRNA expression, thus stabilizing transcriptional profiles. Since many oscillations are not synchronized between cells, such information is lost when thousands of cells are profiled at the same time. We will study the expression of miRNA targets in single cells using state-of-the-art next generation sequencing protocols. Comparing the behavior of the target mRNAs in wild-type cells and in mutant cells void of miRNAs, we will estimate and model the impact of miRNAs on single-cell transcriptomes.
Kang W, Bang-Berthelsen CH, Holm A, Houben AJ, Müller AH, Thymann T, Pociot F, Estivill X, Friedländer MR (2017), ‘Survey of 800+ data sets from human tissue and body fluid reveals xenomiRs are likely artifacts’, RNA, 23(4):433-445.
Friedländer MR, Lizano E, Houben A, Bezdan D, Bañez-Coronel M, Kudla G, Mateu-Huertas E, Kagerbauer B, González J, Chen KC, LeProust EM, Martí E, Estivill X. (2014), ‘Evidence for the biogenesis of more than 1,000 novel human microRNAs’, Genome Biology, 15(4):R57.
Lappalainen T, Sammeth M, Friedländer MR, ‘t Hoen PA, Monlong J, Rivas MA, Gonzàlez-Porta M, Kurbatova N, Griebel T, Ferreira PG, Barann M, Wieland T, Greger L, van Iterson M, Almlöf J, Ribeca P, Pulyakhina I, Esser D, Giger T, Tikhonov A, Sultan M, Bertier G, MacArthur DG, Lek M, Lizano E, Buermans HP, Padioleau I, Schwarzmayr T, Karlberg O, Ongen H, Kilpinen H, Beltran S, Gut M, Kahlem K, Amstislavskiy V, Stegle O, Pirinen M, Montgomery SB, Donnelly P, McCarthy MI, Flicek P, Strom TM; Geuvadis Consortium, Lehrach H, Schreiber S, Sudbrak R, Carracedo A, Antonarakis SE, Häsler R, Syvänen AC, van Ommen GJ, Brazma A, Meitinger T, Rosenstiel P, Guigó R, Gut IG, Estivill X, Dermitzakis ET. (2013), ‘Transcriptome and genome sequencing uncovers functional variation in human populations’, Nature, 501(7468):506-11.
Friedländer MR, Mackowiak SD, Li N, Chen W, Rajewsky N. (2012), ‘miRDeep2 accurately identifies known and hundreds of novel miRNAs in seven animal clades’, Nucleic Acids Research, 40(1):37-52.
Friedländer MR, Chen W, Adamidi C, Maaskola J, Einspanier R, Knespel S, Rajewsky N. (2008), ‘Discovering microRNAs from deep sequencing data using miRDeep.‘, Nature Biotechnology, 26(4):407-15.