COMPILATION OF A UNIFIED AND HOMOGENEOUS AEROMAGNETIC MAP OF THE GREEK MAINLAND

We present a unified and homogeneous digital aeromagnetic map of the Hellenic mainland, based on the 1:50,000 map series of IGME. These maps cover the areas A1, A2, B, C1, C2, C3, D1 compiled by Hunting Geology and Geophysics Ltd. and measured at nominal ground clearances (flight altitudes) 150m AGL, 150m AGL, 300m AGL, and 2300m AMSL respectively (part of C2 with 3000m AMSL). We also include the entire area of Northern Greece, measured by ABEM AB with nominal ground clearance 275±75m AGL. The original map sheets were digitally imaged, georeferenced, digitized along contour lines and interpolated onto regular 250´250m grids. The unified aeromagnetic map was constructed by collating the mosaic of the resulting gridded data. Using upward/ downward continuation techniques various homogeneous versions of the map, were compiled by referencing of the observed mosaic total magnetic field to a unique constant ground clearance or to a unique constant elevation above mean sea level. This is the first time there is a complete and unified image of the magnetic signature of the isopic zones and rock formations comprising the Hellenic mainland, with particular reference to the ophiolite suites, which provides additional insight into the Alpine and post-alpine tectonics of the area

Building up or out? Disparate sequence architectures along an active rift margin—Corinth rift, Greece

Early Pleistocene synrift deltas developed along the southern Corinth rift margin were deposited in a single, dominantly lacustrine depocenter and were subject to the same climate-related base-level and sediment supply cyclicity. Two synrift deltas, just 50 km apart, show markedly different sequence geometry and evolution related to their location along the evolving border fault. In the west, strongly aggradational fan deltas (>600 m thick; 2–4 km radius) deposited in the immediate hanging wall of the active border fault comprise stacked 30–100-m-thick stratal units bounded by flooding surfaces. Each unit evolves from aggradational to progradational with no evidence for abrupt subaerial exposure or fluvial incision. In contrast, in the central rift, the border fault propagated upward into an already deep lacustrine environment, locating rift-margin deltas 15 km into the footwall. The deltas here have a radius of >9 km and comprise northward downstepping and offlapping units, 50–200 m thick, that unconformably overlie older synrift sediments and are themselves incised. The key factors driving the marked variation in sequence stratigraphic architecture are: (1) differential uplift and subsidence related to position with respect to the border fault system, and (2) inherited topography that influenced shoreline position and offshore bathymetry. Our work illustrates that stratal units and their bounding surfaces may have only local (<10 km) extent, highlighting the uncertainty involved in assigning chronostratigraphic significance to systems tracts and in calculating base-level changes from stratigraphy where marked spatial variations in uplift and subsidence occur

Use and optimization of different sources of information for genomic prediction

Abstract Background Molecular data is now commonly used to predict breeding values (BV). Various methods to calculate genomic relationship matrices (GRM) have been developed, with some studies proposing regression of coefficients back to the reference matrix of pedigree-based relationship coefficients (A). The objective was to compare the utility of two GRM: a matrix based on linkage analysis (LA) and anchored to the pedigree, i.e. $${\mathbf{G}}_{{{\mathbf{LA}}}} ,$$ G LA , and a matrix based on linkage disequilibrium (LD), i.e. $${\mathbf{G}}_{{{\mathbf{LD}}}}$$ G LD , using genomic and phenotypic data collected on 5416 broiler chickens. Furthermore, the effects of regressing the coefficients of $${\mathbf{G}}_{{{\mathbf{LD}}}}$$ G LD back to A (LDA) and to $${\mathbf{G}}_{{{\mathbf{LA}}}}$$ G LA (LDLA) were evaluated, using a range of weighting factors. The performance of the matrices and their composite products was assessed by the fit of the models to the data, and the empirical accuracy and bias of the BV that they predicted. The sensitivity to marker choice was examined by using two chips of equal density but including different single nucleotide polymorphisms (SNPs). Results The likelihood of models using GRM and composite matrices exceeded the likelihood of models based on pedigree alone and was highest with intermediate weighting factors for both the LDA and LDLA approaches. For these data, empirical accuracies were not strongly affected by the weighting factors, although they were highest when different sources of information were combined. The optimum weighting factors depended on the type of matrices used, as well as on the choice of SNPs from which the GRM were constructed. Prediction bias was strongly affected by the chip used and less by the form of the GRM. Conclusions Our findings provide an empirical comparison of the efficacy of pedigree and genomic predictions in broiler chickens and examine the effects of fitting GRM with coefficients regressed back to a reference anchored to the pedigree, either A or $${\mathbf{G}}_{{{\mathbf{LA}}}}$$ G LA . For the analysed dataset, the best results were obtained when $${\mathbf{G}}_{{{\mathbf{LD}}}}$$ G LD was combined with relationships in A or $${\mathbf{G}}_{{{\mathbf{LA}}}}$$ G LA , with optimum weighting factors that depended on the choice of SNPs used. The optimum weighting factor for broiler body weight differed from weighting factors that were based on the density of SNPs and theoretically derived using generalised assumptions

Genome-wide analysis reveals the extent of EAV-HP integration in domestic chicken

Background: EAV-HP is an ancient retrovirus pre-dating Gallus speciation, which continues to circulate in modern chicken populations, and led to the emergence of avian leukosis virus subgroup J causing significant economic losses to the poultry industry. We mapped EAV-HP integration sites in Ethiopian village chickens, a Silkie, Taiwan Country chicken, red junglefowl Gallusgallus and several inbred experimental lines using whole-genome sequence data. Results: An average of 75.22 ± 9.52 integration sites per bird were identified, which collectively group into 279 intervals of which 5% are common to 90% of the genomes analysed and are suggestive of pre-domestication integration events. More than a third of intervals are specific to individual genomes, supporting active circulation of EAV-HP in modern chickens. Interval density is correlated with chromosome length (P<2.31−6), and 27 % of intervals are located within 5 kb of a transcript. Functional annotation clustering of genes reveals enrichment for immune-related functions (P<0.05). Conclusions: Our results illustrate a non-random distribution of EAV-HP in the genome, emphasising the importance it may have played in the adaptation of the species, and provide a platform from which to extend investigations on the co-evolutionary significance of endogenous retroviral genera with their hosts