Novoa Lab

Novoa LabNovoa Lab

Gene Regulation, Stem Cells and Cancer

Novoa Lab
Epitranscriptomics and RNA Dynamics
Group leader

Novoa Lab

Epitranscriptomics and RNA Dynamics
Group leader

2007 - B.Sc. in Biochemistry, University of Barcelona (UB), Barcelona (Spain)
2009 - M.Sc. in Bioinformatics, University Pompeu Fabra (UPF), Barcelona (Spain)
2012 - Ph.D. in Biomedicine, Institute for Research in Biomedicine (IRB), Barcelona (Spain)
2013 - EMBO Postdoctoral Fellow, Massachusetts Institute of Technology (MIT) and Broad Institute of MIT and Harvard, Boston (USA)
2014 - HSFP Postdoctoral Fellow, Massachusetts Institute of Technology (MIT) and Broad Institute of MIT and Harvard, Boston (USA)
2016 - Group Leader/Senior Postdoctoral Fellow at Garvan Institute of Medical Research, Sydney (Australia)
2018 - Group Leader at the Centre for Genomic Regulation (CRG), Barcelona (Spain)

Job Opportunities

Bioinformatician (please submit your applications by 30th August 2021)
We are seeking a talented and highly motivated Bioinformatician to join the Epitranscriptomics and RNA Dynamics group, to work on algorithm development and implementation of novel methods to accurately detect, map and study RNA modification dynamics from direct RNA Oxford Nanopore sequencing data. You will also perform data analysis of different nanopore sequencing datasets that are generated in the lab and study the interplay between RNA modifications and other regulatory layer (polyA tail dynamics, mRNA decay, splicing, etc) [...]


Measuring RNA modifications opens new research avenues for cancer detection (14/05/2021)
Researchers at the Centre for Genomic Regulation (CRG) have developed a new method to measure the abundance of RNA modifications in much finer detail than previously possible. 

Direct RNA sequencing made applicable to patient-derived samples (09/09/2020)
Researchers have developed a method to detect diverse RNA molecules, such as viral RNAs, in samples with minimal biological material. 

New therapeutic targets for infertility and cancer revealed (08/05/2020)
CRG researchers share the result of the most comprehensive evolutionary analysis of RNA modification proteins to date.

Our Genome Biology paper highlighted in the media (El Diario, 07/05/20:

CRG standardises COVID-19 data analysis to aid international research efforts (27/03/2020)
Researchers from the Centre for Genomic Regulation (CRG) have launched a new database to advance the international research efforts studying COVID-19. 

Our efforts to create a SARS-CoV-2 direct RNA sequencing analysis repository have been highlighted in the press (Diari Ara, 27/03/20:
Further info related to these efforts can be found here.

Special feature of RNA modification detection methods in Science, including our work in bioRxiv (now published in Nature Comm) (Science, 17/05/2019:


A current major challenge in biology is to understand how gene expression is regulated with surgical precision in a tissue-dependent, spatial and temporal dimension. Historically, genome-wide studies of gene expression have typically measured mRNA abundance rather than protein synthesis, in large part because such data are much easier to obtain. However, the correlation between mRNA levels and protein abundance is as low as r=0.35-0.40, suggesting that transcriptional regulation alone is not sufficient to unveil the complex orchestration of gene expression. In the last few decades, the scientific community has started to acknowledge the pivotal role that post-transcriptional regulatory mechanisms play in gene expression, however, we are still far from understanding how gene expression is finely tuned and regulated across tissues and conditions, suggesting that we are missing variables in the equation.

In our lab, we are employing a combination of experimental (RNASeq, polysome profiling, mouse/cell knockouts, Oxford Nanopore direct RNA sequencing) and computational techniques (NGS data analysis, algorithm development, machine learning), to unveil the secrets of three post-transcriptional regulatory layers: the epitranscriptome, RNA structure and ribosome specialization.

(Illustrations adapted from: Novoa et al., Nat Rev Mol Cell Biol 2017; Imanishi et al., Chem Communic 2017; Li et al., Nature Methods 2017; Hauenschild et al., Nucl Acids Res 2015; Stoecklin and Diederichs, EMBO J 2014)