Análisis de la expresión alternativa de isoformas en el tiempo mediante datos de RNA-seq

[ES] Los avances en tecnologías de secuenciación masiva han dado lugar al desarrollo de la transcriptómica por secuenciación, que permite analizar la expresión de genes e isoformas. El laboratorio de Genómica de la Expresión Génica participa en el proyecto STATegra, en el que se han generado datos de RNA-seq de una serie de diferenciación de células B en ratón que posibilita el análisis de expresión de isoformas. Sin embargo, estos análisis siguen siendo difíciles ya que los problemas de anotación y expresión diferencial de isoformas no están resueltos completamente para estos datos. El objetivo del trabajo es analizar diferentes métodos de cuantificación de isoformas (con eXpress y RSEM) que se anotarán para estudiar diferencias funcionales asociadas a su expresión alternativa. También se estudiará la expresión diferencial de isoformas y se analizarán cambios en la cromatina (medidos también en el proyecto) que se asocien significativamente con los cambios de expresión.[EN] The innovations in massive sequencing technologies have resulted in the development of sequencing transcriptomics that allows for the analysis of gene and isoform expression. The Genomics of Gene Expression laboratory participates in the STATegra project, in which RNASeq data have been generated for a B cell differentiation system. These data make it possible to study isoform expression and splicing variants, which is very interesting in superior eukaryotic organisms because it is the cause of regulation and transcriptional complexity. However, these analyses are still difficult because the annotation and isoform differential expression problems are not completely solved for these data yet. The objective of this work is to compare different methods for isoform quantification (eXpress and RSEM), analyze differential expression and interpret the results in order to understand the functional differences associated to alternative expression.Martorell Marugán, J. (2015). Análisis de la expresión alternativa de isoformas en el tiempo mediante datos de RNA-seq. http://hdl.handle.net/10251/54311.TFG

Protocol for large scale whole blood immune monitoring by mass cytometry and Cyto Quality Pipeline

Support has been received (PI: M.E.A.) from the IMI2-JU project GA No 831434 (3TR) and IMI-JU project GA No 115565 (PRECISESADS). P.R. has received support from EMBO (7966) and from Consejería de Salud de Junta de Andalucía (EF-0091-2018). C.M. acknowledges funding from Programa Nicolas Monardes (C2-0002-2019). J.M.M. is funded by European Union-NextGenerationEU, Ministry of Universities (Spain’s Government) and the Recovery, Transformation and Resilience Plan. These results form a part of the P.R. PhD thesis in Biomedicine at the University of Granada. We are grateful to Olivia Santiago and Jose Diaz Cuéllar for technical support as a Core facility in Genyo research center. Also, we would like to express our gratitude to the donors. The figures in this paper were created with BioRender.comMass cytometry (MC) is a powerful large-scale immune monitoring technology. To maximize MC data quality, we present a protocol for whole blood analysis together with an R package, Cyto Quality Pipeline (CytoQP), which minimizes the experimental artifacts and batch effects to ensure data reproducibility. We describe the steps to stimulate, fix, and freeze blood samples before acquisition to make them suitable for retrospective studies. We then detail the use of bar-coding and reference samples to facilitate multicenter and multi-batch experiments.For complete details on the use and execution of this protocol, please refer to Rybakowska et al. (2021a) and (2021b).IMI2-JU project GA 831434IMI-JUproject GA 115565European Molecular Biology Organization (EMBO) 7966Junta de Andalucía EF-0091-2018Programa Nicolás Monardes C2-0002-2019European Union-NextGenerationEUMinistry of Universities (Spain's Government) and the Recovery, Transformation and Resilience Pla

NoMeplot: analysis of DNA methylation and nucleosome occupancy at the single molecule

Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-019-44597-2.We are very grateful to Peter A. Jones for sharing protocols and advice and we thank Serafin Moral for constructive and useful discussion.Recent technical advances highlight that to understand mammalian development and human disease we need to consider transcriptional and epigenetic cell-to-cell differences within cell populations. This is particularly important in key areas of biomedicine like stem cell differentiation and intratumor heterogeneity. The recently developed nucleosome occupancy and methylome (NOMe) assay facilitates the simultaneous study of DNA methylation and nucleosome positioning on the same DNA strand. NOMe-treated DNA can be sequenced by sanger (NOMe-PCR) or high throughput approaches (NOMe-seq). NOMe-PCR provides information for a single locus at the single molecule while NOMe-seq delivers genome-wide data that is usually interrogated to obtain population-averaged measures. Here, we have developed a bioinformatic tool that allow us to easily obtain locus-specific information at the single molecule using genome-wide NOMe-seq datasets obtained from bulk populations. We have used NOMePlot to study mouse embryonic stem cells and found that polycomb-repressed bivalent gene promoters coexist in two different epigenetic states, as defined by the nucleosome binding pattern detected around their transcriptional start site.This study was supported by the Spanish ministry of economy and competitiveness (SAF2013-40891-R; BFU2016-75233-P) and the andalusian regional government (PC-0246-2017). David Landeira is a Ramón y Cajal researcher of the Spanish ministry of economy and competitiveness (RYC-2012- 10019)

Polycomb regulation is coupled to cell cycle transition in pluripotent stem cells

When self-renewing pluripotent cells receive a differentiation signal, ongoing cell duplication needs to be coordinated with entry into a differentiation program. Accordingly, transcriptional activation of lineage specifier genes and cell differentiation is confined to the G1 phase of the cell cycle by unknown mechanisms. We found that Polycomb repressive complex 2 (PRC2) subunits are differentially recruited to lineage specifier gene promoters across cell cycle in mouse embryonic stem cells (mESCs). Jarid2 and the catalytic subunit Ezh2 are markedly accumulated at target promoters during S and G2 phases, while the transcriptionally activating subunits EPOP and EloB are enriched during G1 phase. Fluctuations in the recruitment of PRC2 subunits promote changes in RNA synthesis and RNA polymerase II binding that are compromised in Jarid2 −/− mESCs. Overall, we show that differential recruitment of PRC2 subunits across cell cycle enables the establishment of a chromatin state that facilitates the induction of cell differentiation in G1 phase.This study was supported by the Spanish Ministry of Economy and Competitiveness (SAF2013-40891-R and BFU2016-75233-P) and the Andalusian Regional Government (PC-0246-2017). D.L. is a Ramón y Cajal researcher of the Spanish Ministry of Economy and Competitiveness (RYC-2012-10019)

DExMA: An R Package for Performing Gene Expression Meta-Analysis with Missing Genes

Meta-analysis techniques allow researchers to jointly analyse different studies to determine common effects. In the field of transcriptomics, these methods have gained popularity in recent years due to the increasing number of datasets that are available in public repositories. Despite this, there is a limited number of statistical software packages that implement proper meta-analysis functionalities for this type of data. This article describes DExMA, an R package that provides a set of functions for performing gene expression meta-analyses, from data downloading to results visualization. Additionally, we implemented functions to control the number of missing genes, which can be a major issue when comparing studies generated with different analytical platforms. DExMA is freely available in the Bioconductor repository.Teaching Staff Programme by the Ministerio de Universidades FPU19/01999 MCIN/AEI PID2020119032RB-I00FEDER/Junta de Andalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades P20_00335 B-CTS-40-UGR20'Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades' (CTEICU)European Union through the European Social Fund (ESF) named 'Andalucia se mueve con Europa" European Union-NextGenerationEU, Ministerio de Universidades (Spain's Government)Recovery, Transformation and Resilience Plan, through a call from the University of Granad

A meta-analysis of pre-pregnancy maternal body mass index and placental DNA methylation identifies 27 CpG sites with implications for mother-child health

Higher maternal pre-pregnancy body mass index (ppBMI) is associated with increased neonatal morbidity, as well as with pregnancy complications and metabolic outcomes in offspring later in life. The placenta is a key organ in fetal development and has been proposed to act as a mediator between the mother and different health outcomes in children. The overall aim of the present work is to investigate the association of ppBMI with epigenomewide placental DNA methylation (DNAm) in 10 studies from the PACE consortium, amounting to 2631 mother-child pairs. We identify 27 CpG sites at which we observe placental DNAm variations of up to 2.0% per 10 ppBMI-unit. The CpGs that are differentially methylated in placenta do not overlap with CpGs identified in previous studies in cord blood DNAm related to ppBMI. Many of the identified CpGs are located in open sea regions, are often close to obesity-related genes such as GPX1 and LGR4 and altogether, are enriched in cancer and oxidative stress pathways. Our findings suggest that placental DNAm could be one of the mechanisms by which maternal obesity is associated with metabolic health outcomes in newborns and children, although further studies will be needed in order to corroborate these findings.French Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences de l'Univers (INSU)Swiss National Science Foundation (SNSF)European CommissionMinistry of Science and Innovation, Spain (MICINN)Spanish Government FJC2018-036729European Development FundEuropean Social Fund (ESF

Exploring the interplay between climate, population immunity and SARS-CoV-2 transmission dynamics in Mediterranean countries

The relationship between SARS-CoV-2 transmission and environmental factors has been analyzed in numerous studies since the outbreak of the pandemic, resulting in heterogeneous results and conclusions. This may be due to differences in methodology, considered variables, confounding factors, studied periods and/or lack of adequate data. Furthermore, previous works have reported that the lack of population immunity is the fundamental driver in transmission dynamics and can mask the potential impact of environmental variables. In this study, we aimed to investigate the association between climate variables and COVID-19 transmission considering the influence of population immunity. We analyzed two different periods characterized by the absence of vaccination (low population immunity) and a high degree of vaccination (high level of population immunity), respectively. Although this study has some limitations, such us the restriction to a specific climatic zone and the omission of other environmental factors, our results indicate that transmission of SARSCoV-2 may increase independently of temperature and specific humidity in periods with low levels of population immunity while a negative association is found under conditions with higher levels of population immunity in the analyzed regions

Scoring personalized molecular portraits identify Systemic Lupus Erythematosus subtypes and predict individualized drug responses, symptomatology and disease progression

Objectives Systemic Lupus Erythematosus is a complex autoimmune disease that leads to significant worsening of quality of life and mortality. Flares appear unpredictably during the disease course and therapies used are often only partially effective. These challenges are mainly due to the molecular heterogeneity of the disease, and in this context, personalized medicine-based approaches offer major promise. With this work we intended to advance in that direction by developing MyPROSLE, an omic-based analytical workflow for measuring the molecular portrait of individual patients to support clinicians in their therapeutic decisions. Methods Immunological gene-modules were used to represent the transcriptome of the patients. A dysregulation score for each gene-module was calculated at the patient level based on averaged z-scores. Almost 6100 Lupus and 750 healthy samples were used to analyze the association among dysregulation scores, clinical manifestations, prognosis, flare and remission events and response to Tabalumab. Machine learning-based classification models were built to predict around 100 different clinical parameters based on personalized dysregulation scores. Results MyPROSLE allows to molecularly summarize patients in 206 gene-modules, clustered into nine main lupus signatures. The combination of these modules revealed highly differentiated pathological mechanisms. We found that the dysregulation of certain gene-modules is strongly associated with specific clinical manifestations, the occurrence of relapses or the presence of long-term remission and drug response. Therefore, MyPROSLE may be used to accurately predict these clinical outcomes. Conclusions MyPROSLE (https://myprosle.genyo.es) allows molecular characterization of individual Lupus patients and it extracts key molecular information to support more precise therapeutic decisions.PID2020-119032RB-I00 supported by MCIN/AEI/10.13039/501100011033FEDER and the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 831434 (3TR)European Union’s Horizon 2020EFPIAFEDER/Junta de Andalucía-Consejer’a de Transformación Económica, Industria, Conocimiento y Universidades (grants P20_00335 and B-CTS-40-UGR20)‘Consejería de Transformación Económica, Industria, Conocimiento y Universidades’ (CTEICU)European Union through the European Social Fund (ESF) named ‘Andalucía se mueve con Europa”Andalusian ESF Operational Program 2014–2020ISCIII CD18/00149Ministerio de Universidades (Spain’s Government) and the European Union – NextGenerationE

The molecular clock protein Bmal1 regulates cell differentiation in mouse embryonic stem cells

Mammals optimize their physiology to the light–dark cycle by synchronization of the master circadian clock in the brain with peripheral clocks in the rest of the tissues of the body. Circadian oscillations rely on a negative feedback loop exerted by the molecular clock that is composed by transcriptional activators Bmal1 and Clock, and their negative regulators Period and Cryptochrome. Components of the molecular clock are expressed during early development, but onset of robust circadian oscillations is only detected later during embryogenesis. Here, we have used na¨ıve pluripotent mouse embryonic stem cells (mESCs) to study the role of Bmal1 during early development. We found that, compared to wild-type cells, Bmal12/2 mESCs express higher levels of Nanog protein and altered expression of pluripotencyassociated signalling pathways. Importantly, Bmal12/2 mESCs display deficient multi-lineage cell differentiation capacity during the formation of teratomas and gastrula-like organoids. Overall, we reveal that Bmal1 regulates pluripotent cell differentiation and propose that the molecular clock is an hitherto unrecognized regulator of mammalian development.Ramon y Cajal grant of the Spanish ministry of economy and competitiveness RYC2012-10019Spanish ministry of economy and competitiveness BFU2016-75233-PAndalusian regional government PC-0246-2017Fundacion Progreso y Salud (FPS)Instituto de Salud Carlos III European Union (EU) CPII17/00032 PI17/01574University of Granad