Genetic parameters for bull effects on in vitro embryo production (IVP) and relationship between semen quality traits and IVP performance.

In vitro production of embryos (IVP) is increasingly applied in dairy cattle breeding and promises widespread use of females of superior genetic merits. One of the current challenges with implementation of IVP is the variability in blastocyst rates. Several factors contribute to these variabilities, among which is known to be the bull used for oocytes fertilization. The extent of genetic control of bulls' effect on IVP performances is yet to be investigated. This study estimates genetic parameters for bull effects on IVP performance traits including blastocyst rate, hatching rate and an index trait combining Blastocyst rate, Kinetic Score, and Morphology score (BL_M_K). The IVP experiments were performed using oocytes aspirated from slaughterhouse ovaries from Holstein cows, fertilized with semen from 123 Holstein bulls. A total of 77 in vitro fertilization (IVF) experiments with 163 records (different IVF groups) were available for the analysis. The results indicate low to moderate heritability and moderate to high repeatability estimates for bull effects on IVP performance traits. Our study also showed that some semen quality traits had significant effects on IVP performance. This included strong genetic correlations between pre-cryopreservation sperm viability and blastocyst rate as well as BL_M_K score at days 7 and 8. Despite the generally weak bull effect correlations and the high standard errors of the estimates, our results provide initial evidence of a measurable genetic component in the bull's impact on IVP performance traits. However, the high standard errors underscore the need for further studies with a larger sample size.

Age-dependent genetic and environmental variance of semen quality in Nordic Holstein bulls.

The aim of this study was to estimate genetic and environmental parameters, across bull's age, for semen quality traits including pre- and postcryopreservation semen concentration, sperm motility, and sperm viability as well as ejaculate volume and number of doses per ejaculate. A data set on 96,595 ejaculates from 2,831 Nordic Holstein bulls collected between 2006 and 2019 was used. Genetic and environmental parameters were estimated using a random regression model and applying the average-information REML approach. Spline functions were chosen to fit the additive genetic and permanent environmental effects across bull's age, and the optimal number of knots was chosen using cross validation. Residual variance heterogeneity was assumed in different bull age classes. The estimated repeatabilities of semen quality traits ranged from 0.16 to 0.85 across different ages of bulls. The estimated heritabilities of semen quality traits ranged from 0.02 to 0.56 across different ages of bulls. The results indicate possibilities for genetic improvement of semen quality traits through selective breeding.

Sn3C2monolayer with transition metal adatom for gas sensing: a density functional theory studies.

The gas sensing properties of pristine Sn3C2monolayer and different transition metal adatom (TM-Sn3C2, where TM = Fe, Co, Ni, Cu, Ru, Rh, Pd and Ag) was investigated using van der Waals corrected density functional theory. The understanding and potential of use of Sn3C2monolayers as sensors or adsorbent for CO, CO2, NO, NO2and SO2gaseous molecules is evaluated by calculating the adsorption and desorption energetics. From the calculated adsorption energies, we found that the pristine Sn3C2monolayer and 3dTM has desirable properties for removal of the considered molecules based on their high adsorption energy, however the 4dTM is applicable as recoverable sensors. We applied an Arrhenius-type equation to evaluate the recovery time for the desorption of the molecules on the pristine and TM adatom on Sn3C2monolayer. We found that the negative adsorption energies from -1 to -2 eV of the molecules resulted in easier recovery of the adsorbed gases at reasonable temperatures compared to adsorption energies in between 0 and -1 eV (weakly physiosorbed) and below -2 eV (strongly chemisorbed). Hence, we obtained that the Rh-Sn3C2, Ru-Sn3C2, Pd-Sn3C2, Pd-Sn3C2, and Rh-Sn3C2monolayers are good recoverable scavengers for the CO, CO2, NO, NO2, and SO2molecules. The current theoretical calculations provide new insight on the effect of TM adatoms on the structural, electronic, and magnetic properties of the Sn3C2monolayer and different transition metal adatom as well as shed light on their application as gas sensors/scavengers.

Controlling the electronic and optical properties of HfS2 mono-layers via lanthanide substitutional doping: a DFT+U study.

Two dimensional HfS2 is a material with potential applications in the field of photo-catalysis and advanced solid state devices. Density functional theory with the Hubbard U parameter (DFT+U) calculations were carried out to investigate the structural, electronic and optical properties of lanthanide dopant atoms (LN = La, Ce, Pr, Nd, Pm, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu) in the HfS2 mono-layer. The calculated electronic band gap for a pristine HfS2 mono-layer is 1.30 eV with a non-magnetic ground state. The dopant substitutional energies under both Hf-rich and S-rich conditions were evaluated, with the S-rich condition for the dopant atoms being negative. This implies that the incorporation of these LN dopant atoms in the HfS2 is feasible and experimental realization possible. The introduction of LN dopant atoms in the HfS2 mono-layer resulted in a significant change of the material properties. We found that the presence of LN dopant atoms in the HfS2 mono-layer significantly alters its electronic ground states by introducing defect states as well as changes in the overall density of states profile resulting in a metallic ground state for the doped mono-layers. The doped mono-layers are all magnetic with the exception of La and Lu dopant atoms. We found that LN dopant atoms in the HfS2 mono-layer influence the absorption and reflectivity spectra with the introduction of states in the lower frequency range (<1.30 eV). Furthermore, we showed that the applicability of doped HfS2 mono-layers as photo-catalysts is very different compared with the pristine HfS2 mono-layer.

Combining multi-population datasets for joint genome-wide association and meta-analyses: The case of bovine milk fat composition traits.

In genome-wide association studies (GWAS), sample size is the most important factor affecting statistical power that is under control of the investigator, posing a major challenge in understanding the genetics underlying difficult-to-measure traits. Combining data sets available from different populations for joint or meta-analysis is a promising alternative to increasing sample sizes available for GWAS. Simulation studies indicate statistical advantages from combining raw data or GWAS summaries in enhancing quantitative trait loci (QTL) detection power. However, the complexity of genetics underlying most quantitative traits, which itself is not fully understood, is difficult to fully capture in simulated data sets. In this study, population-specific and combined-population GWAS as well as a meta-analysis of the population-specific GWAS summaries were carried out with the objective of assessing the advantages and challenges of different data-combining strategies in enhancing detection power of GWAS using milk fatty acid (FA) traits as examples. Gas chromatography (GC) quantified milk FA samples and high-density (HD) genotypes were available from 1,566 Dutch, 614 Danish, and 700 Chinese Holstein Friesian cows. Using the joint GWAS, 28 additional genomic regions were detected, with significant associations to at least 1 FA, compared with the population-specific analyses. Some of these additional regions were also detected using the implemented meta-analysis. Furthermore, using the frequently reported variants of the diacylglycerol acyltransferase 1 (DGAT1) and stearoyl-CoA desaturase (SCD1) genes, we show that significant associations were established with more FA traits in the joint GWAS than the remaining scenarios. However, there were few regions detected in the population-specific analyses that were not detected using the joint GWAS or the meta-analyses. Our results show that combining multi-population data set can be a powerful tool to enhance detection power in GWAS for seldom-recorded traits. Detection of a higher number of regions using the meta-analysis, compared with any of the population-specific analyses also emphasizes the utility of these methods in the absence of raw multi-population data sets to undertake joint GWAS.

New 2D Structural Materials: Carbon-Gallium Nitride (CC-GaN) and Boron-Gallium Nitride (BN-GaN) Heterostructures-Materials Design Through Density Functional Theory.

New class of ternary nanohetrostructures have been proposed by mixing 2D gallium nitride (GaN) with graphene and 2D hexagonal boron nitride (BN) with an aim towards desgining innovative 2D materials for applications in electronics and other industries. The structural stability and electronic properties of these nanoheterostructures have been analyzed using first-principles based calculations done in the framework of density functional theory. Different structure patterns have been analyzed to identify the most stable structures. It is found to be more energetically favorable that the carbon atoms occupy the positions of the nitrogen atoms in a clustered pattern in CC-GaN heterostructures, whereas boron doping is preferred in the reverse order, where isolated BN and GaN layered configurations are preferred in BN-GaN heterostructures. These 2D nanoheterostructures are energetically favored materials with direct band gap and have potential application in nanoscale semiconducting and nanoscale optoelectronic devices.

Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition.

BACKGROUND: The power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis. Milk fatty acid (FA) traits are scarcely recorded due to expensive and time-consuming analytical techniques. Combining multi-population datasets can enhance the power of GWAS enabling detection of genomic region explaining medium to low proportions of the genetic variation. GWAS often detect broader genomic regions containing several positional candidate genes making it difficult to untangle the causative candidates. Post-GWAS analyses with data on pathways, ontology and tissue-specific gene expression status might allow prioritization among positional candidate genes. RESULTS: Multi-population GWAS for 16 FA traits quantified using gas chromatography (GC) in sample populations of the Chinese, Danish and Dutch Holstein with high-density (HD) genotypes detects 56 genomic regions significantly associated to at least one of the studied FAs; some of which have not been previously reported. Pathways and gene ontology (GO) analyses suggest promising candidate genes on the novel regions including OSBPL6 and AGPS on Bos taurus autosome (BTA) 2, PRLH on BTA 3, SLC51B on BTA 10, ABCG5/8 on BTA 11 and ALG5 on BTA 12. Novel genes in previously known regions, such as FABP4 on BTA 14, APOA1/5/7 on BTA 15 and MGST2 on BTA 17, are also linked to important FA metabolic processes. CONCLUSION: Integration of multi-population GWAS and enrichment analyses enabled detection of several novel genomic regions, explaining relatively smaller fractions of the genetic variation, and revealed highly likely candidate genes underlying the effects. Detection of such regions and candidate genes will be crucial in understanding the complex genetic control of FA metabolism. The findings can also be used to augment genomic prediction models with regions collectively capturing most of the genetic variation in the milk FA traits.

Short communication: Multi-trait estimation of genetic parameters for milk protein composition in the Danish Holstein.

Genetic parameters were estimated for the major milk proteins using bivariate and multi-trait models based on genomic relationships between animals. The analyses included, apart from total protein percentage, αS1-casein (CN), αS2-CN, ß-CN, κ-CN, α-lactalbumin, and ß-lactoglobulin, as well as the posttranslational sub-forms of glycosylated κ-CN and αS1-CN-8P (phosphorylated). Standard errors of the estimates were used to compare the models. In total, 650 Danish Holstein cows across 4 parities and days in milk ranging from 9 to 481d were selected from 21 herds. The multi-trait model generally resulted in lower standard errors of heritability estimates, suggesting that genetic parameters can be estimated with high accuracy using multi-trait analyses with genomic relationships for scarcely recorded traits. The heritability estimates from the multi-trait model ranged from low (0.05 for ß-CN) to high (0.78 for κ-CN). Genetic correlations between the milk proteins and the total milk protein percentage were generally low, suggesting the possibility to alter protein composition through selective breeding with little effect on total milk protein percentage.

Parametric amplification of vacuum fluctuations in a spinor condensate.

Parametric amplification of vacuum fluctuations is crucial in modern quantum optics, enabling the creation of squeezing and entanglement. We demonstrate the parametric amplification of vacuum fluctuations for matter waves using a spinor F=2 87Rb condensate. Interatomic interactions lead to correlated pair creation in the mF=±1 states from an initial mF=0 condensate, which acts as a vacuum for mF≠0. Although this pair creation from a pure mF=0 condensate is ideally triggered by vacuum fluctuations, unavoidable spurious initial mF=±1 atoms induce a classical seed which may become the dominant triggering mechanism. We show that pair creation is insensitive to a classical seed for sufficiently large magnetic fields, demonstrating the dominant role of vacuum fluctuations. The presented system thus provides a direct path towards the generation of nonclassical states of matter.

Spontaneous breaking of spatial and spin symmetry in spinor condensates.

Parametric amplification of quantum fluctuations constitutes a fundamental mechanism for spontaneous symmetry breaking. In our experiments, a spinor condensate acts as a parametric amplifier of spin modes, resulting in a twofold spontaneous breaking of spatial and spin symmetry in the amplified clouds. Our experiments permit a precise analysis of the amplification in specific spatial Bessel-like modes, allowing for the detailed understanding of the double symmetry breaking. On resonances that create vortex-antivortex superpositions, we show that the cylindrical spatial symmetry is spontaneously broken, but phase squeezing prevents spin-symmetry breaking. If, however, nondegenerate spin modes contribute to the amplification, quantum interferences lead to spin-dependent density profiles and hence spontaneously formed patterns in the longitudinal magnetization.

Multiresonant spinor dynamics in a Bose-Einstein condensate.

We analyze the spinor dynamics of a 87Rb F=2 condensate initially prepared in the m(F) = 0 Zeeman sublevel. We show that this dynamics, characterized by the creation of correlated atomic pairs in m(F) = +/-1, presents an intriguing multiresonant magnetic-field dependence induced by the trap inhomogeneity. This dependence is directly linked to the most unstable Bogoliubov spin excitations of the initial m(F) = 0 condensate, showing that, in general, even a qualitative understanding of the pair-creation efficiency in a spinor condensate requires a careful consideration of the confinement.