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Background Most genomic predictions use a unique population that is split into a training and a validation set. However, genomic prediction using genetically heterogeneous training sets could provide more flexibility when constructing the training sets in small populations. The aim of our study was to investigate the potential of genomic prediction of feed efficiency related traits using training sets that combine animals from two different, but genetically-related lines. We compared realized prediction accuracy and prediction bias for different training set compositions for five production traits. Results Genomic breeding values (GEBV) were predicted using the single-step genomic best linear unbiased prediction method in six scenarios applied iteratively to two genetically-related lines (i.e. 12 scenarios). The objective for all scenarios was to predict GEBV of pigs in the last three generations (~ 400 pigs, G7 to G9) of a given line. For each line, a control scenario was set up with a training set that included only animals from that line (target line). For all traits, adding more animals from the other line to the training set did not increase prediction accuracy compared to the control scenario. A small decrease in prediction accuracies was found for average daily gain, backfat thickness, and daily feed intake as the number of animals from the target line decreased in the training set. Including more animals from the other line did not decrease prediction accuracy for feed conversion ratio and residual feed intake, which were both highly affected by selection within lines. However, prediction biases were systematic for these cases and might be reduced with bivariate analyses. Conclusions Our results show that genomic prediction using a training set that includes animals from genetically-related lines can be as accurate as genomic prediction using a training set from the target population. With combined reference sets, accuracy increased for traits that were highly affected by selection. Our results provide insights into the design of reference populations, especially to initiate genomic selection in small-sized lines, for which the number of historical samples is small and that are developed simultaneously. This applies especially to poultry and pig breeding and to other crossbreeding schemes.

Non‐genetic information (epigenetic, microbiota, behaviour) that results in different phenotypes in animals can be transmitted from one generation to the next and thus is potentially involved in the inheritance of traits. However, in livestock species, animals are selected based on genetic inheritance only. The objective of the present study was to determine whether non‐genetic inherited effects play a role in the inheritance of residual feed intake (RFI) in two species: pigs and rabbits. If so, the path coefficients of the information transmitted from sire and dam to offspring would differ from the expected transmission factor of 0.5 that occurs if inherited information is of genetic origin only. Two pigs (pig1, pig2) and two rabbits (rabbit1, rabbit2) datasets were used in this study (1,603, 3,901, 5,213 and 4,584 records, respectively). The test of the path coefficients to 0.5 was performed for each dataset using likelihood ratio tests (null model: transmissibility model with both path coefficients equal to 0.5, full model: unconstrained transmissibility model). The path coefficients differed significantly from 0.5 for one of the pig datasets (pig2). Although not significant, we observed, as a general trend, that sire path coefficients of transmission were lower than dam path coefficients in three of the datasets (0.46 vs 0.53 for pig1, 0.39 vs 0.44 for pig2 and 0.38 vs 0.50 for rabbit1). These results suggest that phenomena other than genetic sources of inheritance explain the phenotypic resemblance between relatives for RFI, with a higher transmission from the dam's side than from the sire's side.

Background Feed efficiency is a major driver of the sustainability of pig production systems. Understanding the biological mechanisms that underlie these agronomic traits is an important issue for environment questions and farms' economy. This study aimed at identifying genomic regions that affect residual feed intake (RFI) and other production traits in two pig lines divergently selected for RFI during nine generations (LRFI, low RFI; HRFI, high RFI). Results We built a whole dataset of 570,447 single nucleotide polymorphisms (SNPs) in 2426 pigs with records for 24 production traits after both imputation and prediction of genotypes using pedigree information. Genome-wide association studies (GWAS) were performed including both lines (global-GWAS) or each line independently (LRFI-GWAS and HRFI-GWAS). Forty-five chromosomal regions were detected in the global-GWAS, whereas 28 and 42 regions were detected in the HRFI-GWAS and LRFI-GWAS, respectively. Among these 45 regions, only 13 were shared between at least two analyses, and only one was common between the three GWAS but it affects different traits. Among the five quantitative trait loci (QTL) detected for RFI, two were close to QTL for meat quality traits and two pinpointed novel genomic regions that harbor candidate genes involved in cell proliferation and differentiation processes of gastrointestinal tissues or in lipid metabolism-related signaling pathways. In most cases, different QTL regions were detected between the three designs, which suggests a strong impact of the dataset structure on the detection power and could be due to the changes in allelic frequencies during the establishment of lines. Conclusions In addition to efficiently detecting known and new QTL regions for feed efficiency, the combination of GWAS carried out per line or simultaneously using all individuals highlighted chromosomal regions that affect production traits and presented significant changes in allelic frequencies across generations. Further analyses are needed to estimate whether these regions correspond to traces of selection or result from genetic drift. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-021-00642-1.

Background The objective of the present study was to investigate how variation in the faecal microbial composition is associated with variation in average daily gain (ADG), backfat thickness (BFT), daily feed intake (DFI), feed conversion ratio (FCR), and residual feed intake (RFI), using data from two experimental pig lines that were divergent for feed efficiency. Estimates of microbiability were obtained by a Bayesian approach using animal mixed models. Microbiome-wide association analyses (MWAS) were conducted by single-operational taxonomic units (OTU) regression and by back-solving solutions of best linear unbiased prediction using a microbiome covariance matrix. In addition, accuracy of microbiome predictions of phenotypes using the microbiome covariance matrix was evaluated. Results Estimates of heritability ranged from 0.31 ± 0.13 for FCR to 0.51 ± 0.10 for BFT. Estimates of microbiability were lower than those of heritability for all traits and were 0.11 ± 0.09 for RFI, 0.20 ± 0.11 for FCR, 0.04 ± 0.03 for DFI, 0.03 ± 0.03 for ADG, and 0.02 ± 0.03 for BFT. Bivariate analyses showed a high microbial correlation of 0.70 ± 0.34 between RFI and FCR. The two approaches used for MWAS showed similar results. Overall, eight OTU with significant or suggestive effects on the five traits were identified. They belonged to the genera and families that are mainly involved in producing short-chain fatty acids and digestive enzymes. Prediction accuracy of phenotypes using a full model including the genetic and microbiota components ranged from 0.60 ± 0.19 to 0.78 ± 0.05. Similar accuracies of predictions of the microbial component were observed using models that did or did not include an additive animal effect, suggesting no interaction with the genetic effect. Conclusions Our results showed substantial associations of the faecal microbiome with feed efficiency related traits but negligible effects with growth traits. Microbiome data incorporated as a covariance matrix can be used to predict phenotypes of animals that do not (yet) have phenotypic information. Connecting breeding environment between training sets and predicted populations could be necessary to obtain reliable microbiome predictions.

In this article, the structural phase stability of the KXP (X = Cr & Mo) compounds in the half-Heusler structure were investigated. The stability of the KXP compound was taken into account in the three phases α, β, and γ of the half-Heusler structure within various ferromagnetic (FM), antiferromagnetic (AFM), and nonmagnetic (NM) states. Total energy calculations, as well as cohesive energy calculations, indicated that for each KXP compound the β phase of the half-Heusler structure in the FM state has the lowest energy compared to the other phases α and γ . For all structural phases of the KMoP compound, the positive amount of the formation energy predicts that the compound cannot be grown in the hypothetical half-Heusler structure and prefers to decompose into stable phases of the constituent elements. The hull distance calculations justify that, unlike KMoP, the β and γ phases of the half-Heusler KCrP compound can be considered to be thermodynamically stable and suitable for experimental synthesis. Based on the elastic results, it can be argued that, unlike α phase, both β and γ phases of the KCrP compound in the FM state satisfy the conditions of mechanical stability. Moreover, γ phase of the KCrP compound is stiffer than β phase, while β phase has a more ductile nature compared to γ phase. In agreement with the elastic results, the phonon scattering calculations showed that both β and γ phases of the half-Heusler KCrP compound are dynamically stable and can be synthesized, while the α phase is regarded to be an unstable phase. The electronic calculations indicated that the KCrP compound in the different phases β and γ possess a half-metallic property with the highly desired Curie temperature, making it a potential candidate for use in spintronic devices.

In this paper, structural, electronic, elastic, phononic, and thermal properties of YC in both rock-salt (B1) and CsCl (B2) phases are studied. Calculations have been performed by using QUANTUM-ESPRESSO/PWSCF computational package which is based on density functional theory (DFT) and pseudo-potential method. Local density approximation (LDA) and generalized gradient approximation (GGA) have been used for modeling the exchange and correlation effects. According to the total energy diagram versus unit cell volume, the YC compound in the B1 phase is more stable than that of the B2 phase at ambient pressure. The computed elastic parameters indicated that the B2 phase did not satisfy the mechanical stability conditions at ambient pressure and is considered to be an unstable phase of the YC structure. The analysis of the enthalpy versus pressure diagram predicts that the structural phase transition from the B1 phase to the B2 phase occurs at pressures 51 GPa and 71.5 GPa, for various LDA and GGA approximations, respectively. Based on the phonon dispersion curves at ambient pressure, the B1 phase of the YC compound is dynamically stable, while at high pressure, the YC compound in the B2 phase has shown stability. Using calculated elastic constants, the small amount of Zener anisotropy factor A shows a strongly anisotropic nature of the YC structure. The higher amount of the calculated Poisson's ratio (~0.40) than that of the corresponding critical value (~0.33) together with the positive values of Cauchy pressure within the LDA and GGA approximations present the ductility and metallic behavior of the YC compound in the B1 phase. The band structure and total density of states calculations also verify the metallic behavior of the YC compound in the stable B1 phase. From PDOS calculations, overlapping the 4d orbital of the Y atom and 2p orbital of the C atom near the Fermi level indicates that these orbitals have significant contributions to the bonding between the Y and C atoms. This bonding is substantiated by the corresponding electron density distribution. The thermodynamic calculations indicated that the heat capacity increases regularly and continuously with the increase in temperature T, toward the classical Dulong-Petit value of 6R for the bulk structure of the YC compound with two atoms in the primitive cell. It can also be predicted for the YC compound that the smaller lattice parameter within the LDA approximation compared to the GGA approximation causes stiffness increases, followed by an increase in the Debye temperature. The increasing trend of entropy versus temperature indicates the endothermic behavior of the YC compound.

We study the adsorption of the conducting polymer poly-para-phenylene (PPP) on graphene using first-principles electronic structure calculations. In this article, we decided to investigate the role of polarization of the polymer on the band gap renormalization of the graphene sheet. For this purpose, we supposed that the polymer is lying flat on the sheet of graphene. The polymer adsorption has caused the polarization of graphene and vice versa. We demonstrate the anisotropic polarization of the polymer significantly affects the energy band structure of graphene by opening a gap at the Dirac point. Upon polymer adsorption, the conical shape of the graphene at the Dirac point is partially transformed and leads to opening the band gap about 260 meV at this point. This finding can change the metallic property of the graphene and created semiconducting property inside the compound. This result can only be explained by many-body effects which are treated within the G0W0 quasi-particle approximation while the Kohn-Sham single-particle band structure of graphene is hardly modified by the presence of the polymer. Our findings can be understood as a renormalization due to image charge effects on the anisotropic polymer chain.

Objectives: The domestic violence rate is increasing. It is influenced by many factors. The present study aimed to determine the domestic violence level among Iranian women in Bandar Abbas in 2015. Materials and Methods: The present study is an analytical cross-sectional research based on non-random sampling. The study was performed on 400 women who referred to the health centers in Bandar Abbas, from January to the end of September 2015. The study data were collected using demographic, obstetric and domestic violence questionnaires and were analyzed using SPSS version 22.0. Results: The total degree of domestic violence was 54%. The most prevalent physical, psychological and sexual violence were shouting and swearing (41.4%) followed by request to have intercourse without your consent (30.8%) and slapping (25.7%). A significant relationship was observed between domestic violence and husband’s age, marital duration, the wife’s independent income as well as the family’s income, wife’s educational degree and wife’s job, husband’s addiction, marital satisfaction, a record of criminal conviction, and experience of violence in childhood (P

In recent years, metabolomics has been used to clarify the biology underlying biological samples. In the field of animal breeding, investigating the magnitude of genetic control on the metabolomic profiles of animals and their relationships with quantitative traits adds valuable information to animal improvement schemes. In this study, we analyzed metabolomic features (MFs) extracted from the metabolomic profiles of 843 male Holstein calves. The metabolomic profiles were obtained using nuclear magnetic resonance (NMR) spectroscopy. We investigated 2 alternative methods to control for peak shifts in the NMR spectra, binning and aligning, to determine which approach was the most efficient for assessing genetic variance. Series of univariate analyses were implemented to elucidate the heritability of each MF. Furthermore, records on BW and ADG from 154 to 294 d of age (ADG154–294), 294 to 336 d of age (ADG294–336), and 154 to 336 d of age (ADG154–336) were used in a series of bivariate analyses to establish the genetic and phenotypic correlations with MFs. Bivariate analyses were only performed for MFs that had a heritability significantly different from zero. The heritabilities obtained in the univariate analyses for the MFs in the binned data set were low (

Background & Aim: Given the importance of mothers’ health and considering that developmental delay in children affects their mothers’ mental health this study aimed to compare stress and perceived social support in mothers of 6-18 month old children with and without developmental delay. Methods & Materials: This cross-sectional, analytical study was performed on 610 mothers and their 6-18 month-old infants in health centers affiliated to Shahid Beheshti University of Medical Sciences. The participants were selected through the multi-stage random sampling. To collect data, the following questionnaires were used: obstetric and demographic characteristics, socio-economic status, infants’ characteristics, the Cohen perceived stress scale, perceived social support, and Ages and Stages questionnaire to determine the children’s development status. The data were analyzed by SPSS v.19 software and using descriptive statistics, Pearson correlation, chi-square, independent t-test and Man-Whitney statistical tests. Results: The mean age of infants were 10.68±4.5 months. Independent t-test revealed a significant difference between mothers’ perceived stress (P=0.004) and social support (P=0.01) in the two groups. In addition, a relationship was observed between the mother’s social support and stress (P