Estimation of genetic parameters for cheese-making traits in Spanish Churra sheep

Artículo de investigaciónThe global production of sheep milk is growing, and the main industrial use of sheep milk is cheese making. The Spanish Churra sheep breed is one of the most important native dairy breeds in Spain. The present study aimed to estimate genetic parameters for a wide range of traits influencing the cheese-making ability of Churra sheep milk. Using a total of 1,049 Churra ewes, we studied the following cheese-making traits: 4 traits related to milk coagulation properties (rennet coagulation time, curd-firming time, and curd firmness at 30 and 60 min after addition of rennet), 2 traits related to cheese yield (individual laboratory cheese yield and individual laboratory dried curd yield), and 3 traits measuring curd firmness over time (maximum curd firmness, time to attain maximum curd firmness, and syneresis). In addition, a list of milk traits, including the native pH of the milk and several milk production and composition traits (milk yield; the fat, protein, and dried extract percentages; and the somatic cell count), were also analyzed for the studied animals. After discarding the noncoagulating samples (only 3.7%), data of 1,010 ewes were analyzed with multiple-trait animal models by using the restricted maximum likelihood method to estimate (co)variance components, heritabilities, and genetic correlations. In general, the heritability estimates were low to moderate, ranging from 0.08 (for the individual laboratory dried curd yield trait) to 0.42 (for the fat percentage trait). High genetic correlations were found within pairs of related traits (i.e., 0.93 between fat and dried extract percentages, −0.93 between the log of the curd-firming time and curd firmness at 30 min, 0.70 between individual laboratory cheese yield and individual laboratory dried curd yield, and −0.94 between time to attain maximum curd firmness and syneresis). Considering all the information provided here, we suggest that in addition to the current consideration of the protein percentage trait for improving cheese yield traits, the inclusion of the pH of milk as a measured trait in the Churra dairy breeding program would represent an efficient strategy for improving the cheese-making ability of milk from this breed.S

Análisis del genoma ovino para la identificación de QTL con influencia sobre caracteres de morfología mamaria: resultados preliminares

Ponencia publicada en ITEA, vol.104El objetivo del presente estudio es la localización de regiones genómicas con influencia sobre caracteres de morfología mamaria en ganado ovino, utilizando la metodología de genome scan, o barrido genómico. Con este fin, se ha analizado una población comercial de ganado ovino de raza Churra, organizada en un diseño hija compuesto por 8 familias de medio-hermanas. Un total de 182 marcadores genéticos, distribuidos uniformemente a lo largo del genoma ovino autosómico, fueron genotipados en la población objeto de estudio. Como medidas cuantitativas se utilizaron las desviaciones calculadas para los caracteres de morfología mamaria considerados en el programa de mejora genética de la raza ovina Churra: inserción de la ubre, posición de los pezones, tamaño de los pezones, profundidad y forma global de la ubre. Para la identificación de los QTL se realizó un análisis de regresión de los fenotipos con marcadores flanqueantes. El análisis del genoma para el conjunto de la población permitió la identificación de 11 regiones asociadas con estos caracteres, al nivel chromosome-wise, en los siguientes cromosomas: 4, 6, 7, 8, 10, 14, 15, 20, 22, 23 y 26. Para las asociaciones significativas se debe realizar una verificación previamente al abordaje del mapeo fino.Analysing the ovine genome to detect QTL for mammary morphology: preliminary results The objective of this work was the identification of chromosomal regions influencing udder morphology traits in dairy sheep by using the genome scan approach. For this purpose, we have analyzed a commercial population of Spanish Churra sheep organized according a daughter design, which included 8 half-sib families. A total of 182 genetic markers, evenly distributed along the ovine autosome, were genotyped in the studied population. As quantitative measurements for the analysis, we used the yield deviations calculated for each of the udder traits considered in the breeding program of Churra sheep: udder attachment, teat position and teat size, udder depth and udder shape. A multimarker regression analysis was used to detect QTL. The whole genome analysis allowed the identification of 11 chromosome-wide significant regions associated with the traits analyzed in the following chromosomes: 4, 6, 7, 8, 10, 14, 15, 20, 22, 23 y 26. Confirmation of the detected effects is required before attempting future fine mapping studies on these regions

Primordial to extremely metal-poor AGB and Super-AGB stars: White dwarf or supernova progenitors?

Getting a better understanding of the evolution and nucleosynthetic yields of the most metal-poor stars ( Z ¿ 10 ¿5 ) is critical because they are part of the big picture of the history of the primitive universe. Yet many of the remaining unknowns of stellar evolution lie in the birth, life, and death of these objects. We review stellar evolution of intermediate-mass Z = 10 ¿5 models existing in the literature, with a particular focus on the problem of their final fates. We emphasise the importance of the mixing episodes between the stellar envelope and the nuclearly processed core, which occur after stars exhaust their central He (second dredge-up and dredge-out episodes). The depth and efficiency of these episodes are critical to determine the mass limits for the formation of electron-capture SNe. Our knowledge of these phenomena is not complete because they are strongly affected by the choice of input physics. These uncertainties affect stars in all mass and metallicity ranges. However, difficulties in calibration pose additional challenges in the case of the most metal-poor stars. We also consider the alternative SN I1/2 channel to form SNe out of the most metal-poor intermediate-mass objects. In this case, it is critical to understand the thermally pulsing Asymptotic Giant Branch evolution until the late stages. Efficient second dredge-up and, later, third dredge-up episodes could be able to pollute stellar envelopes enough for the stars to undergo thermal pulses in a way very similar to that of higher initial Z objects. Inefficient second and/or third dredge-up may leave an almost pristine envelope, unable to sustain strong stellar winds. This may allow the H-exhausted core to grow to the Chandrasekhar mass before the envelope is completely lost, and thus let the star explode as an SN I1/2. After reviewing the information available on these two possible channels for the formation of SNe, we discuss existing nucleosynthetic yields of stars of metallicity Z = 10 ¿5 and present an example of nucleosynthetic calculations for a thermally pulsing Super-Asymptotic Giant Branch star of Z = 10 ¿5 . We compare theoretical predictions with observations of the lowest [Fe/H] objects detected. The review closes by discussing current open questions as well as possible fruitful avenues for future research.Peer ReviewedPostprint (author's final draft

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Genome-wide association studies (GWAS) and post-GWAS analyses for technological traits in Assaf and Churra dairy breeds

20 p.This study aimed to perform a GWAS to identify genomic regions associated with milk and cheese-making traits in Assaf and Churra dairy sheep breeds; second, it aimed to identify possible positional and functional candidate genes and their interactions through post-GWAS studies. For 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra), milk samples were collected and analyzed to determine 6 milk production and composition traits and 6 traits related to milk coagulation properties and cheese yield. The genetic profiles of the ewes were obtained using a genotyping chip array that included 50,934 SNP markers. For both milk and cheese-making traits, separate single-breed GWAS were performed using GCTA software. The set of positional candidate genes identified via GWAS was subjected to guilt-by-association-based prioritization analysis with ToppGene software. Totals of 84 and 139 chromosome-wise significant associations for the 6 milk traits and the 6 cheese-making traits were identified in this study. No significant SNPs were found in common between the 2 studied breeds, possibly due to their genetic heterogeneity of the phenotypes under study. Additionally, 63 and 176 positional candidate genes were located in the genomic intervals defined as confidence regions in relation to the significant SNPs identified for the analyzed traits for Assaf and Churra breeds. After the functional prioritization analysis, 71 genes were identified as promising positional and functional candidate genes and proposed as targets of future research to identify putative causative variants in relation to the traits under examination. In addition, this multitrait study allowed us to identify variants that have a pleiotropic effect on both milk production and cheese-related traits. The incorporation of variants among the proposed functional and positional candidate genes into genomic selection strategies represent an interesting approach for achieving rapid genetic gains, specifically for those traits difficult to measure, such as cheese-making traits.S

Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning

The theoretical prediction of drug-decorated nanoparticles (DDNPs) has become a very important task in medical applications. For the current paper, Perturbation Theory Machine Learning (PTML) models were built to predict the probability of different pairs of drugs and nanoparticles creating DDNP complexes with anti-glioblastoma activity. PTML models use the perturbations of molecular descriptors of drugs and nanoparticles as inputs in experimental conditions. The raw dataset was obtained by mixing the nanoparticle experimental data with drug assays from the ChEMBL database. Ten types of machine learning methods have been tested. Only 41 features have been selected for 855,129 drug-nanoparticle complexes. The best model was obtained with the Bagging classifier, an ensemble meta-estimator based on 20 decision trees, with an area under the receiver operating characteristic curve (AUROC) of 0.96, and an accuracy of 87% (test subset). This model could be useful for the virtual screening of nanoparticle-drug complexes in glioblastoma. All the calculations can be reproduced with the datasets and python scripts, which are freely available as a GitHub repository from authors. View Full-TextThe APC was funded by IKERDATA, S.L. under grant 3/12/DP/2021/00102—Area 1: Development of innovative business projects, from Provincial Council of Vizcaya (BEAZ for the Creation of Innovative Business Innovative business ventures)

NEXT-100 Technical Design Report (TDR). Executive Summary

In this Technical Design Report (TDR) we describe the NEXT-100 detector that will search for neutrinoless double beta decay (bbonu) in Xe-136 at the Laboratorio Subterraneo de Canfranc (LSC), in Spain. The document formalizes the design presented in our Conceptual Design Report (CDR): an electroluminescence time projection chamber, with separate readout planes for calorimetry and tracking, located, respectively, behind cathode and anode. The detector is designed to hold a maximum of about 150 kg of xenon at 15 bar, or 100 kg at 10 bar. This option builds in the capability to increase the total isotope mass by 50% while keeping the operating pressure at a manageable level. The readout plane performing the energy measurement is composed of Hamamatsu R11410-10 photomultipliers, specially designed for operation in low-background, xenon-based detectors. Each individual PMT will be isolated from the gas by an individual, pressure resistant enclosure and will be coupled to the sensitive volume through a sapphire window. The tracking plane consists in an array of Hamamatsu S10362-11-050P MPPCs used as tracking pixels. They will be arranged in square boards holding 64 sensors (8 times8) with a 1-cm pitch. The inner walls of the TPC, the sapphire windows and the boards holding the MPPCs will be coated with tetraphenyl butadiene (TPB), a wavelength shifter, to improve the light collection.Comment: 32 pages, 22 figures, 5 table

Lipid Metabolites Enhance Secretion Acting on SNARE Microdomains and Altering the Extent and Kinetics of Single Release Events in Bovine Adrenal Chromaffin Cells

Lipid molecules such as arachidonic acid (AA) and sphingolipid metabolites have been implicated in modulation of neuronal and endocrine secretion. Here we compare the effects of these lipids on secretion from cultured bovine chromaffin cells. First, we demonstrate that exogenous sphingosine and AA interact with the secretory apparatus as confirmed by FRET experiments. Examination of plasma membrane SNARE microdomains and chromaffin granule dynamics using total internal reflection fluorescent microscopy (TIRFM) suggests that sphingosine production promotes granule tethering while arachidonic acid promotes full docking. Our analysis of single granule release kinetics by amperometry demonstrated that both sphingomyelinase and AA treatments enhanced drastically the amount of catecholamines released per individual event by either altering the onset phase of or by prolonging the off phase of single granule catecholamine release kinetics. Together these results demonstrate that the kinetics and extent of the exocytotic fusion pore formation can be modulated by specific signalling lipids through related functional mechanisms