Systems analysis of drug-induced receptor tyrosine kinase reprogramming following targeted mono- and combination anti-cancer therapy

The receptor tyrosine kinases (RTKs) are key drivers of cancer progression and targets for drug therapy. A major challenge in anti-RTK treatment is the dependence of drug effectiveness on co-expression of multiple RTKs which defines resistance to single drug therapy. Reprogramming of the RTK network leading to alteration in RTK co-expression in response to drug intervention is a dynamic mechanism of acquired resistance to single drug therapy in many cancers. One route to overcome this resistance is combination therapy. We describe the results of a joint in silico, in vitro, and in vivo investigations on the efficacy of trastuzumab, pertuzumab and their combination to target the HER2 receptors. Computational modelling revealed that these two drugs alone and in combination differentially suppressed RTK network activation depending on RTK co-expression. Analyses of mRNA expression in SKOV3 ovarian tumour xenograft showed up-regulation of HER3 following treatment. Considering this in a computational model revealed that HER3 up-regulation reprograms RTK kinetics from HER2 homodimerisation to HER3/HER2 heterodimerisation. The results showed synergy of the trastuzumab and pertuzumab combination treatment of the HER2 overexpressing tumour can be due to an independence of the combination effect on HER3/HER2 composition when it changes due to drug-induced RTK reprogramming

Exome sequencing of geographically diverse barley landraces and wild relatives gives insights into environmental adaptation

After domestication, during a process of widespread range extension, barley adapted to a broad spectrum of agricultural environments. To explore how the barley genome responded to the environmental challenges it encountered, we sequenced the exomes of a collection of 267 georeferenced landraces and wild accessions. A combination of genome-wide analyses showed that patterns of variation have been strongly shaped by geography and that variant-by-environment associations for individual genes are prominent in our data set. We observed significant correlations of days to heading (flowering) and height with seasonal temperature and dryness variables in common garden experiments, suggesting that these traits were major drivers of environmental adaptation in the sampled germplasm. A detailed analysis of known flowering-associated genes showed that many contain extensive sequence variation and that patterns of single- and multiple-gene haplotypes exhibit strong geographical structuring. This variation appears to have substantially contributed to range-wide ecogeographical adaptation, but many factors key to regional success remain unidentified.</p

Exome sequences and multi-environment field trials elucidate the genetic basis of adaptation in barley

Broadening the genetic base of crops is crucial for developing varieties to respond to global agricultural challenges such as climate change. Here, we analysed a diverse panel of 371 domesticated lines of the model crop of barley to explore the genetics of crop adaptation. We first collected exome sequence data and phenotypes of key life history traits from contrasting multi-environment common garden trials. Then we applied refined statistical methods, including based on exomic haplotype states, for genotype-by-environment (G 7E) modelling. Sub-populations defined from exomic profiles were coincident with barley's biology, geography and history, and explained a high proportion of trial phenotypic variance. Clear G 7E interactions indicated adaptation profiles that varied for landraces and cultivars. Exploration of circadian clock-related genes, associated with the environmentally-adaptive days to heading trait (crucial for the crop's spread from the Fertile Crescent), illustrated complexities in G 7E effect directions, and the importance of latitudinally-based genic context in the expression of large effect alleles. Our analysis supports a gene-level scientific understanding of crop adaption and leads to practical opportunities for crop improvement, allowing the prioritisation of genomic regions and particular sets of lines for breeding efforts seeking to cope with climate change and other stresses

Gap-Filling Sentinel-1 Offshore Wind Speed Image Time Series Using Multiple-Point Geostatistical Simulation and Reanalysis Data

Offshore wind is expected to play a key role in future energy systems. Wind energy resource studies often call for long-term and spatially consistent datasets to assess the wind potential. Despite the vast amount of available data sources, no current means can provide relevant sub-daily information at a fine spatial scale (~1 km). Synthetic aperture radar (SAR) delivers wind field estimates over the ocean at fine spatial resolution but suffers from partial coverage and irregular revisit times. Physical model outputs, which are the basis of reanalysis products, can be queried at any time step but lack fine-scale spatial variability. To combine the advantages of both, we use the framework of multiple-point geostatistics to realistically reconstruct wind speed patterns at time instances for which satellite information is absent. Synthetic fine-resolution wind speed images are generated conditioned to coregistered regional reanalysis information at a coarser scale. Available simultaneous data sources are used as training data to generate the synthetic image time series. The latter are then evaluated via cross validation and statistical comparison against reference satellite data. Multiple realizations are also generated to assess the uncertainty associated with the simulation outputs. Results show that the proposed methodology can realistically reproduce fine-scale spatiotemporal variability while honoring the wind speed patterns at the coarse scale and thus filling the satellite information gaps in space and time

Διαδραστική απεικόνιση και εκτίμηση του αιολικού δυναμικού στη θαλάσσια περιοχή της Κύπρου

Στα πλαίσια του ερευνητικού προγράμματος Interreg ΘΑΛ-ΧΩΡ 2, με τη συνδυασμένη χρήση μετεωρολογικών μετρήσεων σε όλο το νησί, προγνώσεων του ανέμου από μετεωρολογικά μοντέλα υψηλής ανάλυσης, και στοιχείων από δύο ευρωπαϊκές βάσεις μετεωρολογικών δεδομένων, δημιουργήθηκε βάση δεδομένων για την αποτύπωση μιας όσο το δυνατόν πιο αξιόπιστης εικόνας της χωρικής και χρονικής κατανομής του θαλάσσιου αιολικού δυναμικού, σε ετήσια και σε εποχική βάση. Η αποτυπωμένη πληροφορία αναλύθηκε, συνδυάστηκε και έγινε επέκτασή της σε υψηλότερη ανάλυση 1x1 km, σε ωριαία βάση, για ορίζοντα δεκαετίας. Τα αποτελέσματα κωδικοποιήθηκαν σε εύχρηστη πλατφόρμα Excel, η οποία μπορεί να δοθεί σε οποιονδήποτε ενδιαφερόμενο χρήστη για να εκτιμήσει το αιολικό δυναμικό σε οποιοδήποτε σημείο της Κύπρου, καθώς και της παράκτιας περιοχής της, με αυτόματη παρεμβολή μεταξύ των εκτιμήσεων. Η πλατφόρμα επιτρέπει την εξαγωγή ολικής εικόνας για τον άνεμο στην περιοχή της Κύπρου και, εκτός από τη χωρική εστίαση, δίνει τη δυνατότητα χρονικής επιλογής οποιασδήποτε περιόδου συγκεκριμένων διαστημάτων ωρών, μηνών και ετών, για την περίοδο 2008-2019. Επίσης, αποδίδονται στατιστικές πληροφορίες για τη μέση, μέγιστη, ελάχιστη τιμή, τη διακύμανση της ταχύτητας, καθώς και για τους συντελεστές της κατανομής Weibull. Παράλληλα, παρατίθενται αυτόματα και πληροφορίες για την ημερήσια, μηνιαία και ετήσια κατανομή της ταχύτητας, όπως και οι κατανομές Weibull. Σε μελλοντικό χρόνο, οι παραπάνω δυνατότητες θα προσφέρονται και διαδικτυακά

Geostatistical downscaling of offshore wind speed data derived from numerical weather prediction models using higher spatial resolution satellite products

Regional offshore wind assessment studies typically rely on forecasts from Numerical Weather Prediction (NWP) models. NWP products are typically available at fine temporal resolutions (e.g., on an hourly basis) but relatively coarse spatial resolutions (e.g., on the order of several kilometers) to be used directly for more detailed local assessments. Satellite data, e.g., SAR (Synthetic Aperture Radar) data, on the other hand have been widely used in the literature to reveal high spatial resolution wind fields along with their variations but are available only at a few instances within a month’s period. The C-Band SAR instrument onboard the Sentinel-1 platform, in particular, provides wind speed data at 10 m above sea surface with a repeat frequency of 6 days since 2016.Statistical downscaling techniques are often employed to obtain finer spatial resolution products from coarse NWP products for use in finely resolved impact assessment studies. This study investigates the application of a novel geostatistical approach for downscaling Regional Reanalysis wind speed data using SAR data in order to spatially enhance information captured by the former. The data used comprise Sentinel-1A and 1B VV-polarized SAR wind field measurements and Uncertainties in Ensembles of Regional Reanalyses (UERRA) data, both bias-corrected using in-situ data from local meteorological coastalstations. The reference data used for bias correction are generated via spatial interpolation and aggregation (upscaling) of the local meteorological station wind speed values within the closest Sentinel pixel(1 km) and UERRA cell (11 km).Prior to the downscaling procedure, Weibull distribution models are fitted to the wind speed time-series both at the coarse and fine spatial resolutions. Downscaled UERRA Weibull distributions parameters (scale (a) and shape (b)) are then generated via Area-To-Point Kriging with External Drift (ATPKED), whereby Weibull parameter values are computed at a finer spatial resolution as a weighted linear combination of neighboring coarse resolution attribute values. The fine resolution parameters are used as auxiliary variables. ATPKED is mass preserving, in that the average of the downscaled Weibull parameter values within a coarse cell reproduce the bias-corrected UERRA value at that cell. Once the fine scale parameters are estimated, the wind speed distribution at the pixel level can be extracted. Statistical comparison indicated that more than half of the wind speed variability in Sentinel images can be explained by the contemporaneous downscaled estimates. Geostatistical simulation is also employed to assess the uncertaintyin the fine resolution values.As an illustration of the methodology, offshore wind speed values are estimated at a spatial resolution of 1km for the coastal areas of the Republic of Cyprus at a 6-hour interval over a period of 1 year. The results imply that the downscaled products could furnish a basis for a more spatially resolved offshore wind power assessment for the region, provided the above procedure is generalized for a longer time period