Genetic regulatory variation in populations informs transcriptome analysis in rare disease

Transcriptome data can facilitate the interpretation of the effects of rare genetic variants. Here, we introduce ANEVA (analysis of expression variation) to quantify genetic variation in gene dosage from allelic expression (AE) data in a population. Application of ANEVA to the Genotype-Tissues Expression (GTEx) data showed that this variance estimate is robust and correlated with selective constraint in a gene. Using these variance estimates in a dosage outlier test (ANEVA-DOT) applied to AE data from 70 Mendelian muscular disease patients showed accuracy in detecting genes with pathogenic variants in previously resolved cases and led to one confirmed and several potential new diagnoses. Using our reference estimates from GTEx data, ANEVA-DOT can be incorporated in rare disease diagnostic pipelines to use RNA-sequencing data more effectively

Angiocrine polyamine production regulates adiposity.

Reciprocal interactions between endothelial cells (ECs) and adipocytes are fundamental to maintain white adipose tissue (WAT) homeostasis, as illustrated by the activation of angiogenesis upon WAT expansion, a process that is impaired in obesity. However, the molecular mechanisms underlying the crosstalk between ECs and adipocytes remain poorly understood. Here, we show that local production of polyamines in ECs stimulates adipocyte lipolysis and regulates WAT homeostasis in mice. We promote enhanced cell-autonomous angiogenesis by deleting Pten in the murine endothelium. Endothelial Pten loss leads to a WAT-selective phenotype, characterized by reduced body weight and adiposity in pathophysiological conditions. This phenotype stems from enhanced fatty acid β-oxidation in ECs concomitant with a paracrine lipolytic action on adipocytes, accounting for reduced adiposity. Combined analysis of murine models, isolated ECs and human specimens reveals that WAT lipolysis is mediated by mTORC1-dependent production of polyamines by ECs. Our results indicate that angiocrine metabolic signals are important for WAT homeostasis and organismal metabolism.We thank members of the Endothelial Pathobiology and Microenvironment Group for helpful discussions. We thank the CERCA Program/Generalitat de Catalunya and the Josep Carreras Foundation for institutional support. The research leading to these results has received funding from la Fundación BBVA (Ayuda Fundacion BBVA a Equipos de Investigación Científica 2019, PR19BIOMET0061) and from SAF2017-82072-ERC from Ministerio de Ciencia, Innovación y Universidades (MCIU) (Spain). The laboratory of M.G. is also supported by the research grants SAF2017-89116R-P (FEDER/EU) co-funded by European Regional Developmental Fund (ERDF), a Way to Build Europe and PID2020-116184RB-I00 from MCEI; by the Catalan Government through the project 2017-SGR; PTEN Research Foundation (BRR-17-001); La Caixa Foundation (HR19-00120 and HR21-00046); by la Asociación Española contra el Cancer-Grupos Traslacionales (GCTRA18006CARR, also to A.C.); European Foundation for the Study of Diabetes/Lilly research grant, also to M.C.); and by the People Programme (Marie Curie Actions; grant agreement 317250) of the European Union’s Seventh Framework Programme FP7/2007-2013 and the Marie Skłodowska-Curie (grant agreement 675392) of the European Union’s Horizon 2020 research. The laboratory of A.C. is supported by the Basque Department of Industry, Tourism and Trade (Elkartek) and the department of education (IKERTALDE IT1106-16), the MCIU (PID2019-108787RB-I00 (FEDER/ EU); Severo Ochoa Excellence Accreditation SEV-2016-0644; Excellence Networks SAF2016-81975-REDT), La Caixa Foundation (ID 100010434), under the agreement LCF/PR/HR17, the Vencer el Cancer foundation and the European Research Council (ERC) (consolidator grant 819242). CIBERONC was co-funded with FEDER funds and funded by Instituto de Salud Carlos III (ISCIII). The laboratory of M.C. is supported by the ERC under the European Union’s Horizon 2020 research and innovation programme (grant agreement 725004) and CERCA Programme/Generalitat de Catalunya (M.C.). The laboratory of D.S. is supported by research grants from MINECO (SAF2017- 83813-C3-1-R, also to L.H., cofounded by the ERDF), CIBEROBN (CB06/03/0001), Government of Catalonia (2017SGR278) and Fundació La Marató de TV3 (201627- 30). The laboratory of R.N. is supported by FEDER/Ministerio de Ciencia, Innovación y Universidades-Agencia Estatal de Investigación (RTI2018-099413-B-I00 and and RED2018-102379-T), Xunta de Galicia (2016-PG057 and 2020-PG015), ERC under the European Union’s Horizon 2020 research and innovation programme (grant agreement 810331), Fundación BBVA, Fundacion Atresmedia and CIBEROBN, which is an initiative of the ISCIII of Spain, which is supported by FEDER funds. The laboratory of J.A.V. is supported by research grants from MICINN (RTI2018-099250-B100) and by La Caixa Foundation (ID 100010434, LCF/PR/HR17/52150009). P.M.G.-R. is supported by ISCIII grant PI15/00701 cofinanced by the ERDF, A Way to Build Europe. Personal support was from Marie Curie ITN Actions (E.M.), Juan de la Cierva (IJCI-2015-23455, P.V.), CONICYT fellowship from Chile (S.Z.), Vetenskapsradet (Swedish Research Council, 2018-06591, L.G.) and NCI K99/R00 Pathway to Independence Award (K99CA245122, P. Castel).S

Correction to: Pharmacokinetic profile of amodiaquine and its active metabolite desethylamodiaquine in Ghanaian patients with uncomplicated falciparum malaria

An amendment to this paper has been published and can be accessed via the original article

Exploring Functional β-Cell Heterogeneity In Vivo Using PSA-NCAM as a Specific Marker

BACKGROUND:The mass of pancreatic beta-cells varies according to increases in insulin demand. It is hypothesized that functionally heterogeneous beta-cell subpopulations take part in this process. Here we characterized two functionally distinct groups of beta-cells and investigated their physiological relevance in increased insulin demand conditions in rats. METHODS:Two rat beta-cell populations were sorted by FACS according to their PSA-NCAM surface expression, i.e. beta(high) and beta(low)-cells. Insulin release, Ca(2+) movements, ATP and cAMP contents in response to various secretagogues were analyzed. Gene expression profiles and exocytosis machinery were also investigated. In a second part, beta(high) and beta(low)-cell distribution and functionality were investigated in animal models with decreased or increased beta-cell function: the Zucker Diabetic Fatty rat and the 48 h glucose-infused rat. RESULTS:We show that beta-cells are heterogeneous for PSA-NCAM in rat pancreas. Unlike beta(low)-cells, beta(high)-cells express functional beta-cell markers and are highly responsive to various insulin secretagogues. Whereas beta(low)-cells represent the main population in diabetic pancreas, an increase in beta(high)-cells is associated with gain of function that follows sustained glucose overload. CONCLUSION:Our data show that a functional heterogeneity of beta-cells, assessed by PSA-NCAM surface expression, exists in vivo. These findings pinpoint new target populations involved in endocrine pancreas plasticity and in beta-cell defects in type 2 diabetes

Evaluation of adherence measures of antiretroviral prophylaxis in HIV exposed infants in the first 6 weeks of life.

CAPRISA, 2015.Abstract available in pdf

The origins and spread of domestic horses from the Western Eurasian steppes

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: All collapsed and paired-end sequence data for samples sequenced in this study are available in compressed fastq format through the European Nucleotide Archive under accession number PRJEB44430, together with rescaled and trimmed bam sequence alignments against both the nuclear and mitochondrial horse reference genomes. Previously published ancient data used in this study are available under accession numbers PRJEB7537, PRJEB10098, PRJEB10854, PRJEB22390 and PRJEB31613, and detailed in Supplementary Table 1. The genomes of ten modern horses, publicly available, were also accessed as indicated in their corresponding original publications57,61,85-87.NOTE: see the published version available via the DOI in this record for the full list of authorsDomestication of horses fundamentally transformed long-range mobility and warfare. However, modern domesticated breeds do not descend from the earliest domestic horse lineage associated with archaeological evidence of bridling, milking and corralling at Botai, Central Asia around 3500 BC. Other longstanding candidate regions for horse domestication, such as Iberia and Anatolia, have also recently been challenged. Thus, the genetic, geographic and temporal origins of modern domestic horses have remained unknown. Here we pinpoint the Western Eurasian steppes, especially the lower Volga-Don region, as the homeland of modern domestic horses. Furthermore, we map the population changes accompanying domestication from 273 ancient horse genomes. This reveals that modern domestic horses ultimately replaced almost all other local populations as they expanded rapidly across Eurasia from about 2000 BC, synchronously with equestrian material culture, including Sintashta spoke-wheeled chariots. We find that equestrianism involved strong selection for critical locomotor and behavioural adaptations at the GSDMC and ZFPM1 genes. Our results reject the commonly held association between horseback riding and the massive expansion of Yamnaya steppe pastoralists into Europe around 3000 BC driving the spread of Indo-European languages. This contrasts with the scenario in Asia where Indo-Iranian languages, chariots and horses spread together, following the early second millennium BC Sintashta culture

Genetic effects on gene expression across human tissues

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 diseas

Genetic effects on gene expression across human tissues

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