EPITRANSCRIPTOMICS AND RNA DYNAMICS
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. Although we have started to acknowledge the pivotal role that post-transcriptional regulatory mechanisms play in gene expression, such as the role of miRNAs in mRNA degradation and translation inhibition, 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 this regard, RNA is decorated with over 100 modifications, the majority of which affect non-coding RNA species. Multiple RNA modifications have been linked to human disease, however, the vast majority of the modification repertoire remains largely uncharacterised. Recently, next-generation sequencing technologies have revealed the central role that these reversible marks play in major cellular processes, such as splicing or cell fate transition. Here we aim to expand our understanding of the human epitranscriptome beyond currently characterised modifications, in order to understand their function and evolution, as well as the effects of their dysregulation in disease.
On the other hand, we also aim to build the foundations of an under-explored post-transcriptional regulatory layer: ribosome specialisation. Although ribosomes have been historically thought of as uniform entities, recent evidence suggests that its composition might be regulated. Using genome-wide high-throughput techniques, we aim to decipher human ribosome composition across tissues and conditions, and see how its composition, and consequently its activity, might be regulated in a tissue-dependent, spatial and temporal manner.
Barsacchi M, Novoa EM, Kellis M, Bechini A. SwiSpot: Modeling riboswitches by spotting out switching sequences. Bioinformatics 2016 (advance access: 10.1093/bioinformatics/btw401)
Saint-Leger A, Bello-Cabrera C, Dans PD, Torres AG, Novoa EM, Camacho C, Orozco M, Kondrashov FA and Ribas de Pouplana L. Saturation of recognition elements blocks evolution of new tRNA identities. Science Advances 2016, 2(4):e1501860
The Anopheles Genomes Cluster Consortium. Highly evolvable malaria vectors: the genomes of 16 Anopheles mosquitoes. Science 2015, 347(6217):1258522.
Novoa EM, Vargas-Rodriguez O, Lange S, Goto Y, Suga H, Musier-Forsyth K and Ribas de Pouplana, L. Ancestral AlaX editing enzymes for control of genetic code fidelity are not tRNA specific. J Biol Chem 2015. pii: jbc.M115.640060
Novoa EM* and Ribas de Pouplana L*. Cooperation for better inhibiting. Chem & Biol 2015, 22: 685-686. (*co-corresponding authors)
Liu Z, Vargas-Rodriguez O, Goto Y, Novoa EM, Ribas de Pouplana L, Suga H and Musier-Forsyth. K. Homologous trans-editing factors with broad tRNA specificity prevent mistranslation caused by serine/threonine misactivation. Proc. Natl. Acad. Sci. USA 2015, 112(19):6027-6032.
Novoa EM, Camacho C, Tor A, Wilkinson B, Moss S, Marin-Garcia P, Azcarate IG, Bautista JM, Mirando AC, Francklyn C, Varon S, Royo M, Cortés A, Ribas de Pouplana L. Analogs of natural aminoacyl-tRNA synthetase inhibitors clear malaria in vivo. Proc. Natl. Acad. Sci. USA 2014, 111(51):5508-17.
Hoen R*, Novoa EM*, López A, Camacho C, Martin P, Bautista JM, Vieira P, Santos M, Cortés A, Royo M, Ribas de Pouplana L. Selective inhibition of the apicoplastic lysyl-tRNA synthetase of Plasmodium falciparum. ChemBioChem, 2013, 14: 499-509. * equal contribution.
Novoa EM, Pavon-Eternod M, Pan T and Ribas de Pouplana L. A role for tRNA modifications in genome structure and codon usage. Cell 2012, 149: 202-213.
Novoa EM and Ribas de Pouplana L. Speeding with control: codon usage, tRNAs and ribosomes. Trends Genet. 2012, 28(11):574-581.
Novoa EM, Ribas de Pouplana L and Orozco M. Small molecule docking from theoretical structural models. In: "Computational Modeling of Biological Systems: From Molecules to Pathways". Ed. Springer, New York (USA); Vol 4, pp 75-96.
Novoa EM, Ribas de Pouplana L, Barril X, and Orozco M. Ensemble docking in homology models. J. Chem. Theory Comput., 2010, 6 (8): 2547-2557.
Novoa EM, Castro de Moura M, Orozco M and Ribas de Pouplana L. A genomics method to identify pathogenicity-related proteins. Application to aminoacyl-tRNA synthetase-like proteins. FEBS Lett 2010, 584(2): 460-6.
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