59 research outputs found

    Transcriptome profiling of grapevine seedless segregants during berry development reveals candidate genes associated with berry weight

    Get PDF
    Indexación: Web of Science; PubMedBackground Berry size is considered as one of the main selection criteria in table grape breeding programs. However, this is a quantitative and polygenic trait, and its genetic determination is still poorly understood. Considering its economic importance, it is relevant to determine its genetic architecture and elucidate the mechanisms involved in its expression. To approach this issue, an RNA-Seq experiment based on Illumina platform was performed (14 libraries), including seedless segregants with contrasting phenotypes for berry weight at fruit setting (FST) and 6–8 mm berries (B68) phenological stages. Results A group of 526 differentially expressed (DE) genes were identified, by comparing seedless segregants with contrasting phenotypes for berry weight: 101 genes from the FST stage and 463 from the B68 stage. Also, we integrated differential expression, principal components analysis (PCA), correlations and network co-expression analyses to characterize the transcriptome profiling observed in segregants with contrasting phenotypes for berry weight. After this, 68 DE genes were selected as candidate genes, and seven candidate genes were validated by real time-PCR, confirming their expression profiles. Conclusions We have carried out the first transcriptome analysis focused on table grape seedless segregants with contrasting phenotypes for berry weight. Our findings contributed to the understanding of the mechanisms involved in berry weight determination. Also, this comparative transcriptome profiling revealed candidate genes for berry weight which could be evaluated as selection tools in table grape breeding programs.http://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-016-0789-

    Coxiella burnetii Phagocytosis Is Regulated by GTPases of the Rho Family and the RhoA Effectors mDia1 and ROCK

    Get PDF
    The GTPases belonging to the Rho family control the actin cytoskeleton rearrangements needed for particle internalization during phagocytosis. ROCK and mDia1 are downstream effectors of RhoA, a GTPase involved in that process. Coxiella burnetii, the etiologic agent of Q fever, is internalized by the hostÂŽs cells in an actin-dependent manner. Nevertheless, the molecular mechanism involved in this process has been poorly characterized. This work analyzes the role of different GTPases of the Rho family and some downstream effectors in the internalization of C. burnetii by phagocytic and non-phagocytic cells. The internalization of C. burnetii into HeLa and RAW cells was significantly inhibited when the cells were treated with Clostridium difficile Toxin B which irreversibly inactivates members of the Rho family. In addition, the internalization was reduced in HeLa cells that overexpressed the dominant negative mutants of RhoA, Rac1 or Cdc42 or that were knocked down for the Rho GTPases. The pharmacological inhibition or the knocking down of ROCK diminished bacterium internalization. Moreover, C. burnetii was less efficiently internalized in HeLa cells overexpressing mDia1-N1, a dominant negative mutant of mDia1, while the overexpression of the constitutively active mutant mDia1-ΔN3 increased bacteria uptake. Interestingly, when HeLa and RAW cells were infected, RhoA, Rac1 and mDia1 were recruited to membrane cell fractions. Our results suggest that the GTPases of the Rho family play an important role in C. burnetii phagocytosis in both HeLa and RAW cells. Additionally, we present evidence that ROCK and mDia1, which are downstream effectors of RhoA, are involved in that processFil: Salinas Ojeda, Romina Paola. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Mendoza. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas MĂ©dicas. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Ortiz Flores, Rodolfo Matias. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Mendoza. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas MĂ©dicas. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Distel, JesĂșs SebastiĂĄn. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Mendoza. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas MĂ©dicas. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Aguilera, Milton Osmar. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Mendoza. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas MĂ©dicas. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Colombo, Maria Isabel. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Mendoza. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas MĂ©dicas. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Beron, Walter. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Mendoza. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas MĂ©dicas. Instituto de HistologĂ­a y EmbriologĂ­a de Mendoza Dr. Mario H. Burgos; Argentin

    Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

    Get PDF
    We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC00100

    Global maps of soil temperature

    Get PDF
    Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-kmÂČ resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-kmÂČ pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

    The 16th Data Release of the Sloan Digital Sky Surveys : First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

    Get PDF
    This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17).Peer reviewe

    Termite sensitivity to temperature affects global wood decay rates.

    Get PDF
    Deadwood is a large global carbon store with its store size partially determined by biotic decay. Microbial wood decay rates are known to respond to changing temperature and precipitation. Termites are also important decomposers in the tropics but are less well studied. An understanding of their climate sensitivities is needed to estimate climate change effects on wood carbon pools. Using data from 133 sites spanning six continents, we found that termite wood discovery and consumption were highly sensitive to temperature (with decay increasing >6.8 times per 10°C increase in temperature)-even more so than microbes. Termite decay effects were greatest in tropical seasonal forests, tropical savannas, and subtropical deserts. With tropicalization (i.e., warming shifts to tropical climates), termite wood decay will likely increase as termites access more of Earth's surface

    The fifteenth data release of the Sloan Digital Sky Surveys : first release of MaNGA derived quantities, data visualization tools and stellar library

    Get PDF
    Twenty years have passed since first light for the Sloan Digital SkySurvey (SDSS). Here, we release data taken by the fourth phase of SDSS(SDSS-IV) across its first three years of operation (July 2014-July2017). This is the third data release for SDSS-IV, and the fifteenth from SDSS (Data Release Fifteen; DR15). New data come from MaNGA - we release 4824 datacubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g. stellar and gas kinematics, emission line, andother maps) from the MaNGA Data Analysis Pipeline (DAP), and a new data visualisation and access tool we call "Marvin". The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials and examples of data use. While SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V(2020-2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data.Publisher PDFPeer reviewe
    • 

    corecore