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Alternative Splicing: Regulation, Function and Evolution

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Alternative Splicing: Regulation, Function and Evolution Alternative splicing: regulation, function and evolution by Carlos Mart´ıG´omez-Aldarav´ı Licenciado en Biotecnolog´ıa PhD Program in Molecular Biosciences Departamento de Bioqu´ımica,Facultad de Ciencias Universidad Autonoma de Madrid (UAM) 2016-2020 Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC) Thesis supervisors: Enrique Lara Pezzi F´atimaS´anchez Cabo Abstract Introns populate eukaryotic genes to a variable extent across species, being widespread in vertebrates and mammals. While the evolutionary advantages, if any, of introns, remain unclear, their expansion has provided the opportunity to splice genes in more than a single way, allowing the production of different mRNAs from a single gene through Alternative splicing (AS). AS patterns change during the development of complex organisms and diverge across different tissues and experimental conditions. These highly reproducible changes evidences the existence of a regulatory network that ensures repeatable responses to certain stimuli and suggest that, at least some of them, play a role in the overall physiological response or adaptation. Not surprisingly, perturbation of some elements of this network is often associated with pathological conditions. However, not only we are far from a complete characterization of the molecular mechanisms that drive AS changes in most pathologies like those affecting the heart, but the computational tools that are currently used to study these regulatory networks are limiting our ability to extract all the information that is hidden in the data. It has been long hypothesized that AS contributes to a great expansion of the proteome and facilitates the evolution of new functions from pre-existing ones without gene duplication. While there are very well known examples of how AS enables the production of different functional proteins or mRNAs, the proportion of AS isoforms that are actually functional remains large unknown. Indeed, recent studies from different perspectives, including both transcriptomic, proteomics and sequence evolutionary analysis suggest that this percentage may be rather small and that much of the observed transcriptomic diversity is driven by non-functional noise in the splicing process. In this thesis, we have studied global AS patterns through computational analysis of large RNA-seq datasets to characterize the causes and consequences of AS changes from different perspectives. First, we have analyzed how AS global patterns change during heart development and disease using data from a variety of mouse models. We found that AS changes modulate different biological processes than gene expression ones and are associated to isoform specific protein-protein interactions. Disease patterns partially recapitulate developmental patterns probably through the upregulation of PTBP1, which is sufficient to induce pathological changes in the heart. Second, in an attempt to improve computational tools for identification of regulatory elements, we have developed dSreg. This tool leverages the power of bayesian inference and hierarchical models to pool information across the whole transcriptome to infer, not only the changes in the activities of the underlying regulatory elements, but also the changes in inclusion rates, outperforming competing methods and tools made for both purposes separately. Finally, we have studied the evolutionary process driving AS divergence during mammalian evolution using models of phenotypic evolution in a phylogenetic framework. We found that AS patterns have evolved under weak stabilizing selection that allows widespread variability in AS patterns across species, with only about 5% of the genes probably encoding AS isoforms with different functions. Rates of neutral evolution are high, preventing the identification of adaptive changes at this long evolutionary scale. In summary, this thesis provides new computational tools and knowledge about the evolution and regulation of AS in different biological conditions and helps to better understand its relevance from different persepectives. 2 Resumen Una gran parte de los genes eucariotas est´ancompuestos por exones e intrones. Aunque las ventajas evolutivas de la fragmentaci´onde los genes, en caso de haberlas, no se conocen del todo bien, su ex- pansi´onha permitido procesar los transcritos primarios de varias diferentes maneras, y por tanto, de producir diferentes ARN mensajeros maduros. Potencialmente, esto permite la producci´onde prote´ınas con diferentes funciones mediante splicing alternativo (SA) a partir de un ´unico gen. Los patrones de SA cambian de forma din´amicadurante el desarrollo de los organismos complejos y se diferencian en distintos tejidos y condiciones experimentales. Esto sugiere la existencia de un programa de regulaci´on espec´ıficopara la reproducci´onde estos cambios en diferentes individuos y en respuesta a est´ımulos con- cretos, que dif´ıcilmente se habr´agenerado en ausencia de funci´ony selecci´on.De hecho, la perturbaci´on de algunos de los elementos que forman parte de esta red de regulaci´onse asocia frecuentemente con el desarrollo de diversas patolog´ıas. No obstante, estamos lejos de una completa caracterizaci´onde los mecanismos de regulaci´onque dirigen los cambios en los patrones de SA en la mayur´ıade las patolog´ıas, como las cardiacas. Adem´as,las herramientas computacionales disponibles para estudiar estas redes de regulaci´onpresentan una serie de limitaciones que reducen nuestra capacidad para extraer informaci´on completamente fiable de los datos de transcript´omica. Desde el descubrimiento de los intrones, se ha hipotetizado que el SA permite la expansi´ondel pro- teoma y facilita la evoluci´onde nuevas funciones moleculares a partir de algunas ya existentes sin que haya duplicaci´ong´enica.Aunque se ha caracterizado una importante cantidad de genes que producen iso- formas con diferentes funciones mediante SA, a´unse desconoce c´omo de general es este mecanismo a nivel gen´omico.De hecho, estudios recientes desde diferentes persepectivas, incluyendo tanto transcript´omica como prote´omicay an´alisisevolutivo de las secuencias implicadas, parecen indicar que el porcentaje de genes que generan diferentes isoformas funcionales mediante SA es m´asbien peque~no,y que por tanto gran parte de la diversidad transcripcional se debe a errores en el proceso de splicing. En esta tesis doctoral, se han estudiado los patrones globales de SA mediante an´alisiscomputacional de grandes conjuntos de datos de RNA-seq. Esto ha permitido la caracterizaci´ontanto de las causas como de las consecuencias del SA y sus cambios desde diferentes perspectivas. En primer lugar, se ha analizado c´omoestos patrones cambian durante el desarrollo y la enfermedad cardiaca, empleando datos de rat´oncomo modelo animal. Se ha visto que los cambios en los patrones de SA afectan a diferentes funciones biol´ogicascomparados con la modulaci´onde la expresi´ong´enica.Estos cambios cuantitatives suelen afectar a isoformas de SA con distintos patrones de interacci´onprote´ına-prote´ına. Los patrones de SA en enfermedad recapitulan parcialmente los observados durante el desarrollo, posiblemente mediante la re-expresi´onde la prote´ınareguladora PTBP1, cuya sobre-expresi´onen corazones de ratones sanos es suficiente para inducir cambios patol´ogicos.En segundo lugar, en un intento de mejorar las herramientas computacionales disponibles para la identificaci´onde las prote´ınasreguladoras actuando en diferentes contextos, se ha desarrollado dSreg. Esta herramienta aprovecha el poder la inferencia bayesiana y los modelos jer´arquicospara aunar la informaci´oncontenida a lo largo del transcriptoma e inferir, no s´olo los cambios cuantitativos en los niveles de inclusi´onde eventos concretos, sino tambi´enlos cambios en la 3 actividad de las prote´ınasreguladoras subyacentes a esos cambios de SA. dSreg funciona mejor en ambos aspectos que los m´etodos previamente empleados para cada aplicaci´onpor separado. Finalmente, se han estudiado las fuerzas gen´eticasque dirigen la evoluci´ondel SA como car´actercuantitativo empleando, por primera vez, modelos de evoluci ´onfenot´ıpicaa lo largo de la historia evolutiva de diferentes especies de mam´ıferos.Estos resultados indican que los patrones de SA evolucionan bajo una selecci´onestabilizadora d´ebil,que permite una gran variaci´onen los patrones de SA entre diferentes especies. De este modo, apenas un 5% de los genes codifican isoformas de SA con diferentes funciones. La tasa de evoluci´onneutral es tan alta que impide distinguir cambios aleatorios mediados por la mutaci´ony la deriva gen´etica de aquellos que suponen una adaptaci´on,al menos en esta escala evolutiva tan grande. En resumen, esta tesis proporciona nuevas herramientas computacionales y conocimiento sobre la evoluci´ony la regulaci´on del SA en diferentes condiciones biol´ogicas,y ayuda a entender mejor su relevancia desde diferentes perspectivas. 4 Acknowledgements En primer lugar, me gustar´ıaagradecer a mis directores Enrique y F´atimapor haberme dado la opor- tunidad de hacer la tesis bajo su supervisi´on,por haberme dado libertad y apoyo para desarrollar mis propias ideas e intereses cient´ıficosm´asall´ade los planteados inicialmente, y por haberme acompa~nado a lo largo de este periodo de crecimiento personal y, posiblemente, hasta cient´ıfico. Gracias por vuestro optimismo y buen humor ante mi a veces reinante negatividad. Me gustar´adar las gracias tambi´ena Claus, mi supervisor en Viena, por el tiempo que ha dedicado a ayudarme y ense~narmesobre
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