Marc Friedländer

Marc Friedländer
Tenured Associate Professor
Head of Quantitative RNA Biology Group
Stockholm University

Research Interests

The Friedländer group applies state-of-the-art computational and genomic methods to address fundamental questions in RNA biology. The focus is on quantitatively describing and functionally characterizing mammalian transcriptomes, and methods include next-generation sequencing of single and pooled cells, as well as development of source code, databases and wet-lab protocols.

Of particular interest to us are microRNAs: 22 nucleotide long RNA molecules that regulate the levels of protein-coding genes in all animals. Since they confer regulation on the majority of human genes, it is not surprising that microRNAs are involved in numerous biological processes, including diseases such as cardiovascular, immunological, neurodegenerative, and psychiatric disorders and cancer. Even though miRNAs have been systematically studied for more than fifteen years, fundamental questions regarding their evolution, biogenesis and function remain unanswered.

We study microRNA function by profiling these regulators and their gene targets in the single cells where the interactions between them occur. From the measurements we infer copy-per-cell numbers for the transcripts, and we develop mathematical models to describe the kinetics of regulation. For this purpose we apply single-cell sequencing methods and single-molecule FISH. To study microRNA biogenesis we have developed a method to measure processing of thousands of RNA structures simultaneously in mammalian cells. To adress evolutionary aspects of microRNAs, we compare microRNAs between representatives of all animal groups, using our highly curated reference database.

We work closely with the research groups of Claudia Kutter and Vicent Pelechano, for instance having joint lab meetings and journal clubs. Among our other collaborators are Rory Johnson (University of Bern), Kevin J. Peterson (Dartmouth), Rickard Sandberg, Magda Bienko, Nicola Crosetto (Karolinska Institutet) and the SciLifeLab Eukaryotic Single Cell Genomics facility. Our research is funded by SFO, by VR and an ERC starting grant.

The Friedländer group is balanced between researchers with wet-lab and dry-lab expertise. We focus on wet-lab methods that concern (small) RNA biology and mammalian cell culture experiments. We extensively generate standard and custom next-generation sequencing libraries that we sequence on our Illumina NextSeq instrument, which is shared with four other junior groups. Our dry-lab expertise is focused on sequence analysis, with special focus on next-generation sequencing transcriptome analyses. We apply standard software and also develop our own solutions for custom data. MicroRNA prediction and annotation is one of the key strengths of the Friedländer lab: members of our group have developed miRDeep, which is the most widely used software tool for microRNA prediction. The Friedländer lab is host of, the curated microRNA gene database.

Group members

Inna Biryukova
Bastian Fromm
Wenjing Kang
Vaishnovi Sekar
Marcel Tarbier
Morteza Aslanzadeh

Key publications

Kang W; Eldfjell Y; Fromm B; Estivill X; Biryukova I; Friedländer MR†, 2018. miRTrace reveals the organismal origins of microRNA sequencing data. Genome Biology (accepted)

Bonath F; Domingo-Prim J; Tarbier M; Friedländer MR†; Visa N†, 2018. Next-generation sequencing reveals two populations of damage-induced small RNAs at endogenous DNA double-strand breaks. Nucleic Acids Research (accepted)

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

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; 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 humans.  Nature 501(7468):506-11

Friedländer MR; Chen W; Adamidi C; Maaskola J; Einspanier R; Knespel S; Rajewsky N, 2008. Discovering microRNAs from deep sequencing data using miRDeep.  Nat Biotechnol 26(4):407-15


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