Barcelona Institute of Science and Technology

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation. Specifically, we generate primary data, create bioinformatics tools and provide analysis to support the work of expert manual gene annotators and automated gene annotation pipelines. In addition, manual and computational annotation workflows use any and all publicly available data and analysis, along with the research literature to identify and characterise gene loci to the highest standard. GENCODE gene annotations are accessible via the Ensembl and UCSC Genome Browsers, the Ensembl FTP site, Ensembl Biomart, Ensembl Perl and REST APIs as well as https://www.gencodegenes.org.

Flexible solid-state supercapacitors (FSSCs) are frontrunners in energy storage device technology and have attracted extensive attention owing to recent significant breakthroughs in modern wearable electronics. In this study, we review the state-of-the-art advancements in FSSCs to provide new insights on mechanisms, emerging electrode materials, flexible gel electrolytes and novel cell designs. The review begins with a brief introduction on the fundamental understanding of charge storage mechanisms based on the structural properties of electrode materials. The next sections briefly summarise the latest progress in flexible electrodes (i.e., freestanding and substrate-supported, including textile, paper, metal foil/wire and polymer-based substrates) and flexible gel electrolytes (i.e., aqueous, organic, ionic liquids and redox-active gels). Subsequently, a comprehensive summary of FSSC cell designs introduces some emerging electrode materials, including MXenes, metal nitrides, metal-organic frameworks (MOFs), polyoxometalates (POMs) and black phosphorus. Some potential practical applications, such as the development of piezoelectric, photo-, shape-memory, self-healing, electrochromic and integrated sensor-supercapacitors are also discussed. The final section highlights current challenges and future perspectives on research in this thriving field.

The GENCODE project annotates human and mouse genes and transcripts supported by experimental data with high accuracy, providing a foundational resource that supports genome biology and clinical genomics. GENCODE annotation processes make use of primary data and bioinformatic tools and analysis generated both within the consortium and externally to support the creation of transcript structures and the determination of their function. Here, we present improvements to our annotation infrastructure, bioinformatics tools, and analysis, and the advances they support in the annotation of the human and mouse genomes including: the completion of first pass manual annotation for the mouse reference genome; targeted improvements to the annotation of genes associated with SARS-CoV-2 infection; collaborative projects to achieve convergence across reference annotation databases for the annotation of human and mouse protein-coding genes; and the first GENCODE manually supervised automated annotation of lncRNAs. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org.

Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.

and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.

Reversible phase separation underpins the role of FUS in ribonucleoprotein granules and other membrane-free organelles and is, in part, driven by the intrinsically disordered low-complexity (LC) domain of FUS. Here, we report that cooperative cation-π interactions between tyrosines in the LC domain and arginines in structured C-terminal domains also contribute to phase separation. These interactions are modulated by post-translational arginine methylation, wherein arginine hypomethylation strongly promotes phase separation and gelation. Indeed, significant hypomethylation, which occurs in FUS-associated frontotemporal lobar degeneration (FTLD), induces FUS condensation into stable intermolecular β-sheet-rich hydrogels that disrupt RNP granule function and impair new protein synthesis in neuron terminals. We show that transportin acts as a physiological molecular chaperone of FUS in neuron terminals, reducing phase separation and gelation of methylated and hypomethylated FUS and rescuing protein synthesis. These results demonstrate how FUS condensation is physiologically regulated and how perturbations in these mechanisms can lead to disease.

We report on the population properties of compact binary mergers inferred from gravitational-wave observations of these systems during the first three LIGO-Virgo observing runs. The Gravitational-Wave Transient Catalog 3 (GWTC-3) contains signals consistent with three classes of binary mergers: binary black hole, binary neutron star, and neutron star–black hole mergers. We infer the binary neutron star merger rate to be between 10 and <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:mrow><a:mn>1700</a:mn><a:mtext> </a:mtext><a:mtext> </a:mtext><a:msup><a:mrow><a:mi>Gpc</a:mi></a:mrow><a:mrow><a:mo>−</a:mo><a:mn>3</a:mn></a:mrow></a:msup><a:mtext> </a:mtext><a:msup><a:mrow><a:mi>yr</a:mi></a:mrow><a:mrow><a:mo>−</a:mo><a:mn>1</a:mn></a:mrow></a:msup></a:mrow></a:math> and the neutron star–black hole merger rate to be between 7.8 and <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" display="inline"><c:mrow><c:mn>140</c:mn><c:mtext> </c:mtext><c:mtext> </c:mtext><c:msup><c:mrow><c:mi>Gpc</c:mi></c:mrow><c:mrow><c:mo>−</c:mo><c:mn>3</c:mn></c:mrow></c:msup><c:mtext> </c:mtext><c:msup><c:mrow><c:mi>yr</c:mi></c:mrow><c:mrow><c:mo>−</c:mo><c:mn>1</c:mn></c:mrow></c:msup></c:mrow></c:math>, assuming a constant rate density in the comoving frame and taking the union of 90% credible intervals for methods used in this work. We infer the binary black hole merger rate, allowing for evolution with redshift, to be between 17.9 and <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" display="inline"><e:mrow><e:mn>44</e:mn><e:mtext> </e:mtext><e:mtext> </e:mtext><e:msup><e:mrow><e:mi>Gpc</e:mi></e:mrow><e:mrow><e:mo>−</e:mo><e:mn>3</e:mn></e:mrow></e:msup><e:mtext> </e:mtext><e:msup><e:mrow><e:mi>yr</e:mi></e:mrow><e:mrow><e:mo>−</e:mo><e:mn>1</e:mn></e:mrow></e:msup></e:mrow></e:math> at a fiducial redshift (<g:math xmlns:g="http://www.w3.org/1998/Math/MathML" display="inline"><g:mi>z</g:mi><g:mo>=</g:mo><g:mn>0.2</g:mn></g:math>). The rate of binary black hole mergers is observed to increase with redshift at a rate proportional to <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" display="inline"><i:mo stretchy="false">(</i:mo><i:mn>1</i:mn><i:mo>+</i:mo><i:mi>z</i:mi><i:msup><i:mo stretchy="false">)</i:mo><i:mi>κ</i:mi></i:msup></i:math> with <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" display="inline"><m:mi>κ</m:mi><m:mo>=</m:mo><m:mn>2.</m:mn><m:msubsup><m:mn>9</m:mn><m:mrow><m:mo>−</m:mo><m:mn>1.8</m:mn></m:mrow><m:mrow><m:mo>+</m:mo><m:mn>1.7</m:mn></m:mrow></m:msubsup></m:math> for <o:math xmlns:o="http://www.w3.org/1998/Math/MathML" display="inline"><o:mi>z</o:mi><o:mo>≲</o:mo><o:mn>1</o:mn></o:math>. Using both binary neutron star and neutron star–black hole binaries, we obtain a broad, relatively flat neutron star mass distribution extending from <q:math xmlns:q="http://www.w3.org/1998/Math/MathML" display="inline"><q:msubsup><q:mn>1.2</q:mn><q:mrow><q:mo>−</q:mo><q:mn>0.2</q:mn></q:mrow><q:mrow><q:mo>+</q:mo><q:mn>0.1</q:mn></q:mrow></q:msubsup></q:math> to <s:math xmlns:s="http://www.w3.org/1998/Math/MathML" display="inline"><s:msubsup><s:mn>2.0</s:mn><s:mrow><s:mo>−</s:mo><s:mn>0.3</s:mn></s:mrow><s:mrow><s:mo>+</s:mo><s:mn>0.3</s:mn></s:mrow></s:msubsup><s:msub><s:mi>M</s:mi><s:mo stretchy="false">⊙</s:mo></s:msub></s:math>. We confidently determine that the merger rate as a function of mass sharply declines after the expected maximum neutron star mass, but cannot yet confirm or rule out the existence of a lower mass gap between neutron stars and black holes. We also find the binary black hole mass distribution has localized over- and underdensities relative to a power-law distribution, with peaks emerging at chirp masses of <v:math xmlns:v="http://www.w3.org/1998/Math/MathML" display="inline"><v:msubsup><v:mn>8.3</v:mn><v:mrow><v:mo>−</v:mo><v:mn>0.5</v:mn></v:mrow><v:mrow><v:mo>+</v:mo><v:mn>0.3</v:mn></v:mrow></v:msubsup></v:math> and <x:math xmlns:x="http://www.w3.org/1998/Math/MathML" display="inline"><x:msubsup><x:mn>27.9</x:mn><x:mrow><x:mo>−</x:mo><x:mn>1.8</x:mn></x:mrow><x:mrow><x:mo>+</x:mo><x:mn>1.9</x:mn></x:mrow></x:msubsup><x:msub><x:mi>M</x:mi><x:mo stretchy="false">⊙</x:mo></x:msub></x:math>. While we continue to find that the mass distribution of a binary’s more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above approximately <ab:math xmlns:ab="http://www.w3.org/1998/Math/MathML" display="inline"><ab:mn>60</ab:mn><ab:msub><ab:mi>M</ab:mi><ab:mo stretchy="false">⊙</ab:mo></ab:msub></ab:math>, which would indicate the presence of a upper mass gap. Observed black hole spins are small, with half of spin magnitudes below <db:math xmlns:db="http://www.w3.org/1998/Math/MathML" display="inline"><db:msub><db:mi>χ</db:mi><db:mi>i</db:mi></db:msub><db:mo>≈</db:mo><db:mn>0.25</db:mn></db:math>. While the majority of spins are preferentially aligned with the orbital angular momentum, we infer evidence of antialigned spins among the binary population. We observe an increase in spin magnitude for systems with more unequal-mass ratio. We also observe evidence of misalignment of spins relative to the orbital angular momentum. Published by the American Physical Society 2023

BACKGROUND: Support vector machines (SVM) are a powerful tool to analyze data with a number of predictors approximately equal or larger than the number of observations. However, originally, application of SVM to analyze biomedical data was limited because SVM was not designed to evaluate importance of predictor variables. Creating predictor models based on only the most relevant variables is essential in biomedical research. Currently, substantial work has been done to allow assessment of variable importance in SVM models but this work has focused on SVM implemented with linear kernels. The power of SVM as a prediction model is associated with the flexibility generated by use of non-linear kernels. Moreover, SVM has been extended to model survival outcomes. This paper extends the Recursive Feature Elimination (RFE) algorithm by proposing three approaches to rank variables based on non-linear SVM and SVM for survival analysis. RESULTS: The proposed algorithms allows visualization of each one the RFE iterations, and hence, identification of the most relevant predictors of the response variable. Using simulation studies based on time-to-event outcomes and three real datasets, we evaluate the three methods, based on pseudo-samples and kernel principal component analysis, and compare them with the original SVM-RFE algorithm for non-linear kernels. The three algorithms we proposed performed generally better than the gold standard RFE for non-linear kernels, when comparing the truly most relevant variables with the variable ranks produced by each algorithm in simulation studies. Generally, the RFE-pseudo-samples outperformed the other three methods, even when variables were assumed to be correlated in all tested scenarios. CONCLUSIONS: The proposed approaches can be implemented with accuracy to select variables and assess direction and strength of associations in analysis of biomedical data using SVM for categorical or time-to-event responses. Conducting variable selection and interpreting direction and strength of associations between predictors and outcomes with the proposed approaches, particularly with the RFE-pseudo-samples approach can be implemented with accuracy when analyzing biomedical data. These approaches, perform better than the classical RFE of Guyon for realistic scenarios about the structure of biomedical data.

Carbon dioxide offers an accessible, cheap and renewable carbon feedstock for synthesis. Current interest in the area of carbon dioxide valorisation aims at new, emerging technologies that are able to provide new opportunities to turn a waste into value. Polymers are among the most widely produced chemicals in the world greatly affecting the quality of life. However, there are growing concerns about the lack of reuse of the majority of the consumer plastics and their after-life disposal resulting in an increasing demand for sustainable alternatives. New monomers and polymers that can address these issues are therefore warranted, and merging polymer synthesis with the recycling of carbon dioxide offers a tangible route to transition towards a circular economy. Here, an overview of the most relevant and recent approaches to CO2-based monomers and polymers are highlighted with particular emphasis on the transformation routes used and their involved manifolds.

Senescence is a form of cell cycle arrest induced by stress such as DNA damage and oncogenes. However, while arrested, senescent cells secrete a variety of proteins collectively known as the senescence-associated secretory phenotype (SASP), which can reinforce the arrest and induce senescence in a paracrine manner. However, the SASP has also been shown to favor embryonic development, wound healing, and even tumor growth, suggesting more complex physiological roles than currently understood. Here we uncover timely new functions of the SASP in promoting a proregenerative response through the induction of cell plasticity and stemness. We show that primary mouse keratinocytes transiently exposed to the SASP exhibit increased expression of stem cell markers and regenerative capacity in vivo. However, prolonged exposure to the SASP causes a subsequent cell-intrinsic senescence arrest to counter the continued regenerative stimuli. Finally, by inducing senescence in single cells in vivo in the liver, we demonstrate that this activates tissue-specific expression of stem cell markers. Together, this work uncovers a primary and beneficial role for the SASP in promoting cell plasticity and tissue regeneration and introduces the concept that transient therapeutic delivery of senescent cells could be harnessed to drive tissue regeneration.

The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci in cis (QTLs) for the majority of genes across a wide range of human tissues. However, the functional characterization of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. We mapped interactions between computational estimates of cell type abundance and genotype to identify cell type-interaction QTLs for seven cell types and show that cell type-interaction expression QTLs (eQTLs) provide finer resolution to tissue specificity than bulk tissue cis-eQTLs. Analyses of genetic associations with 87 complex traits show a contribution from cell type-interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue.

Biodiversity is a cornerstone of human health and well-being. However, while evidence of the contributions of nature to human health is rapidly building, research into how biodiversity relates to human health remains limited in important respects. In particular, a better mechanistic understanding of the range of pathways through which biodiversity can influence human health is needed. These pathways relate to both psychological and social processes as well as biophysical processes. Building on evidence from across the natural, social and health sciences, we present a conceptual framework organizing the pathways linking biodiversity to human health. Four domains of pathways-both beneficial as well as harmful-link biodiversity with human health: (i) reducing harm (e.g. provision of medicines, decreasing exposure to air and noise pollution); (ii) restoring capacities (e.g. attention restoration, stress reduction); (iii) building capacities (e.g. promoting physical activity, transcendent experiences); and (iv) causing harm (e.g. dangerous wildlife, zoonotic diseases, allergens). We discuss how to test components of the biodiversity-health framework with available analytical approaches and existing datasets. In a world with accelerating declines in biodiversity, profound land-use change, and an increase in non-communicable and zoonotic diseases globally, greater understanding of these pathways can reinforce biodiversity conservation as a strategy for the promotion of health for both people and nature. We conclude by identifying research avenues and recommendations for policy and practice to foster biodiversity-focused public health actions.

Alternative splicing (AS) generates remarkable regulatory and proteomic complexity in metazoans. However, the functions of most AS events are not known, and programs of regulated splicing remain to be identified. To address these challenges, we describe the Vertebrate Alternative Splicing and Transcription Database (VastDB), the largest resource of genome-wide, quantitative profiles of AS events assembled to date. VastDB provides readily accessible quantitative information on the inclusion levels and functional associations of AS events detected in RNA-seq data from diverse vertebrate cell and tissue types, as well as developmental stages. The VastDB profiles reveal extensive new intergenic and intragenic regulatory relationships among different classes of AS and previously unknown and conserved landscapes of tissue-regulated exons. Contrary to recent reports concluding that nearly all human genes express a single major isoform, VastDB provides evidence that at least 48% of multiexonic protein-coding genes express multiple splice variants that are highly regulated in a cell/tissue-specific manner, and that >18% of genes simultaneously express multiple major isoforms across diverse cell and tissue types. Isoforms encoded by the latter set of genes are generally coexpressed in the same cells and are often engaged by translating ribosomes. Moreover, they are encoded by genes that are significantly enriched in functions associated with transcriptional control, implying they may have an important and wide-ranging role in controlling cellular activities. VastDB thus provides an unprecedented resource for investigations of AS function and regulation.

Abstract Summary A new version of FoldX, whose main new features allows running classic FoldX commands on structures containing RNA molecules and includes a module that allows parametrization of ligands or small molecules (ParamX) that were not previously recognized in old versions, has been released. An extended FoldX graphical user interface has also being developed (available as a python plugin for the YASARA molecular viewer) allowing user-friendly parametrization of new custom user molecules encoded using JSON format. Availability and implementation http://foldxsuite.crg.eu/

GWTC-2.1 is a catalog of gravitational wave events from compact binary coalescences from the first half of the third observing run of Advanced LIGO and Advanced Virgo. It improves on GWTC-2, which covered the same period but with less refined analysis methods. GWTC-2.1 identifies 8 new events, all identified as sourced by binary black holes with one exception identified as a neutron star-black hole coalescence. These events expand significantly on the parameters characterizing the sources of observed gravitational-wave transients.

The production of metal-organic frameworks (MOFs) in the form of colloids has brought a paradigm shift in the design of new functional porous materials. Along with their intrinsic interest as porous solids, and contrary to their bulk powder counterparts, colloidal MOF particles can additionally be dispersed, shaped, functionalized, transformed and assembled in a controlled manner, conferring them further properties and applications. In this regard, zeolitic imidazolate framework-8 (ZIF-8) has become a pioneering MOF constituent of colloidal science. Today, the understanding of the role of synthetic parameters, learned after one decade of research, enables the production of monodisperse colloidal ZIF-8 particles with tunable dimensions and morphologies, offering the opportunity to develop new functional materials and composites with novel and promising functionalities. This tutorial review provides a useful guide to prepare ZIF-8 in its colloidal form, covering the published studies on the synthesis of homogeneous ZIF-8 particles with controlled size and shape. In addition, we present the most relevant advances in the development of colloidal ZIF-8 hybrid single-particles, reflecting the great potential and rapid development of this interdisciplinary research field. Finally, we highlight how formulation of ZIF-8 as colloids has led to the emergence of novel physicochemical phenomena that are useful for practical applications. This review aims at promoting the development of MOFs as colloids, taking ZIF-8 as a pioneering and successful case that clearly shows the benefits of bridging MOF chemistry and colloidal science.

Brain delivery is one of the major challenges in drug development because of the high number of patients suffering from neural diseases and the low efficiency of the treatments available. Although the blood-brain barrier (BBB) prevents most drugs from reaching their targets, molecular vectors - known as BBB shuttles - offer great promise to safely overcome this formidable obstacle. In recent years, peptide shuttles have received growing attention because of their lower cost, reduced immunogenicity, and higher chemical versatility than traditional Trojan horse antibodies and other proteins.

The GEOTRACES Intermediate Data Product 2017 (IDP2017) is the second publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2016. The IDP2017 includes data from the Atlantic, Pacific, Arctic, Southern and Indian oceans, with about twice the data volume of the previous IDP2014. For the first time, the IDP2017 contains data for a large suite of biogeochemical parameters as well asaerosol and rain data characterising atmospherictrace element and isotope (TEI) sources. The TEI data in the IDP2017 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at crossover stations. The IDP2017 consists of two parts: (1) a compilation of digital data for more than 450 TEIs as well as standard hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing an on-line atlas that includes more than 590 section plots and 130 animated 3D scenes. The digital data are provided in several formats, including ASCII, Excel spreadsheet, netCDF, and Ocean Data View collection. Users can download the full data packages or make their own custom selections with a new on-line data extraction service. In addition to the actual data values, the IDP2017 also contains data quality flags and 1-σ data error values where available. Quality flags and error values are useful for data filtering and for statistical analysis. Metadata about data originators, analytical methods and original publications related to the data are linked in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2017 as section plots and rotating 3D scenes. The basin-wide 3D scenes combine data from many cruises and provide quick overviews of large-scale tracer distributions. These 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of tracer plumes near ocean margins or along ridges. The IDP2017 is the result of a truly international effort involving 326 researchers from 25 countries. This publication provides the critical reference for unpublished data, as well as for studies that make use of a large cross-section of data from the IDP2017.

Abstract The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues, and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the v8 data, based on 17,382 RNA-sequencing samples from 54 tissues of 948 post-mortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans , showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue-specificity of genetic effects, and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.