9 research outputs found
A basal lithostrotian titanosaur (Dinosauria: Sauropoda) with a complete skull: Implications for the evolution and paleobiology of titanosauria
We describe Sarmientosaurus musacchioi gen. et sp. nov., a titanosaurian sauropod dinosaur from the Upper Cretaceous (Cenomanian - Turonian) Lower Member of the Bajo Barreal Formation of southern Chubut Province in central Patagonia, Argentina. The holotypic and only known specimen consists of an articulated, virtually complete skull and part of the cranial and middle cervical series. Sarmientosaurus exhibits the following distinctive features that we interpret as autapomorphies: (1) maximum diameter of orbit nearly 40% rostrocaudal length of cranium; (2) complex maxilla - lacrimal articulation, in which the lacrimal clasps the ascending ramus of the maxilla; (3) medial edge of caudal sector of maxillary ascending ramus bordering bony nasal aperture with low but distinct ridge; (4) ÂŽtongue-likeÂŽ ventral process of quadratojugal that overlaps quadrate caudally; (5) separate foramina for all three branches of the trigeminal nerve; (6) absence of median venous canal connecting infundibular region to ventral part of brainstem; (7) subvertical premaxillary, procumbent maxillary, and recumbent dentary teeth; (8) cervical vertebrae with ÂŽstrut-likeÂŽ centroprezygapophyseal laminae; (9) extremely elongate and slender ossified tendon positioned ventrolateral to cervical vertebrae and ribs. The cranial endocast of Sarmientosaurus preserves some of the most complete information obtained to date regarding the brain and sensory systems of sauropods. Phylogenetic analysis recovers the new taxon as a basal member of Lithostrotia, as the most plesiomorphic titanosaurian to be preserved with a complete skull. Sarmientosaurus provides a wealth of new cranial evidence that reaffirms the close relationship of titanosaurs to Brachiosauridae. Moreover, the presence of the relatively derived lithostrotian Tapuiasaurus in Aptian deposits indicates that the new Patagonian genus represents a ÂŽghost lineageÂŽ with a comparatively plesiomorphic craniodental form, the evolutionary history of which is missing for at least 13 million years of the Cretaceous. The skull anatomy of Sarmientosaurus suggests that multiple titanosaurian species with dissimilar cranial structures coexisted in the early Late Cretaceous of southern South America. Furthermore, the new taxon possesses a number of distinctive morphologies - such as the ossified cervical tendon, extremely pneumatized cervical vertebrae, and a habitually downward- facing snout - that have rarely, if ever, been documented in other titanosaurs, thus broadening our understanding of the anatomical diversity of this remarkable sauropod clade. The latter two features were convergently acquired by at least one penecontemporaneous diplodocoid, and may represent mutual specializations for consuming low-growing vegetation.Fil: MartĂnez, RubĂ©n DarĂo. Universidad Nacional de la Patagonia; ArgentinaFil: Lamanna, Matthew C.. Carnegie Museum Of Natural History; Estados UnidosFil: Novas, Fernando Emilio. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "bernardino Rivadavia"; ArgentinaFil: Ridgely, Ryan C.. Ohio University College Of Osteopathic Medicine; Estados UnidosFil: Casal, Gabriel. Universidad Nacional de la Patagonia; ArgentinaFil: MartĂnez, Javier E.. Hospital Regional de Comodoro Rivadavia; ArgentinaFil: Vita, Javier R.. Resonancia MagnĂ©tica Borelli; ArgentinaFil: Witmer, Lawrence M.. Ohio University College Of Osteopathic Medicine; Estados Unido
The presence of Microlobius foetidus cause changes in the antioxidant defense of Urochloa decumbens?
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GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19
Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title âMonocyte gene expression dataâ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European GenomeâPhenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability:
Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita BaldiĂłn-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana MarĂa Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyteâmacrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientistâs Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) âA way of making Europeâ, FundaciĂłn Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 âApuestas cientĂficas del ITER para colaborar en la lucha contra la COVID-19â to C.F.) and FundaciĂłn Canaria Instituto de InvestigaciĂłn Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de SupercomputaciĂłn de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)