Understanding the genetic architecture of phenotypic variation in natural populations is a fundamental goal of evolutionary genetics. Wild Soay sheep (Ovis aries) have an inherited polymorphism for horn morphology in both sexes, controlled by a single autosomal locus, Horns. The majority of males have large normal horns, but a small number have vestigial, deformed horns, known as scurs; females have either normal horns, scurs or no horns (polled). Given that scurred males and polled females have reduced fitness within each sex, it is counterintuitive that the polymorphism persists within the population. Therefore, identifying the genetic basis of horn type will provide a vital foundation for understanding why the different morphs are maintained in the face of natural selection. We conducted a genome-wide association study using ∼36000 single nucleotide polymorphisms (SNPs) and determined the main candidate for Horns as RXFP2, an autosomal gene with a known involvement in determining primary sex characters in humans and mice. Evidence from additional SNPs in and around RXFP2 supports a new model of horn-type inheritance in Soay sheep, and for the first time, sheep with the same horn phenotype but different underlying genotypes can be identified. In addition, RXFP2 was shown to be an additive quantitative trait locus (QTL) for horn size in normal-horned males, accounting for up to 76% of additive genetic variation in this trait. This finding contrasts markedly from genome-wide association studies of quantitative traits in humans and some model species, where it is often observed that mapped loci only explain a modest proportion of the overall genetic variation.

The objective of this study was to determine the genetic parameters of methane (CH4) emissions and their genetic correlations with key production traits. The trial measured the CH4 emissions, at 5-min intervals, from 1225 sheep placed in respiration chambers for 2 days, with repeat measurements 2 weeks later for another 2 days. They were fed in the chambers, based on live weight, a pelleted lucerne ration at 2.0 times estimated maintenance requirements. Methane outputs were calculated for g CH4/day and g CH4/kg dry matter intake (DMI) for each of the 4 days. Single trait models were used to obtain estimates of heritability and repeatability. Heritability of g CH4/day was 0.29 ± 0.05, and for g CH4/kg DMI 0.13 ± 0.03. Repeatability between measurements 14 days apart were 0.55 ± 0.02 and 0.26 ± 0.02, for the two traits. The genetic and phenotypic correlations of CH4 outputs with various production traits (weaning weight, live weight at 8 months of age, dag score, muscle depth and fleece weight at 12 months of age) measured in the first year of life, were estimated using bivariate models. With the exception of fleece weight, correlations were weak and not significantly different from zero for the g CH4/kg DMI trait. For fleece weight the phenotypic and genetic correlation estimates were −0.08 ± 0.03 and −0.32 ± 0.11 suggesting a low economically favourable relationship. These results indicate that there is genetic variation between animals for CH4 emission traits even after adjustment for feed intake and that these traits are repeatable. Current work includes the establishment of selection lines from these animals to investigate the physiological, microbial and anatomical changes, coupled with investigations into shorter and alternative CH4 emission measurement and breeding value estimation techniques; including genomic selection.

Methane (CH4) emission traits were previously found to be heritable and repeatable in sheep fed alfalfa pellets in respiration chambers (RC). More rapid screening methods are, however, required to increase genetic progress and to provide a cost-effective method to the farming industry for maintaining the generation of breeding values in the future. The objective of the current study was to determine CH4 and carbon dioxide (CO2) emissions using several 1-h portable accumulation chamber (PAC) measurements from lambs and again as ewes while grazing ryegrass-based pasture. Many animals with PAC measurements were also measured in RC while fed alfalfa pellets at 2.0 × maintenance metabolizable energy requirements (MEm). Heritability estimates from mixed models for CH4 and CO2 production (g/d) were 0.19 and 0.16, respectively, when measured using PAC with lambs; 0.20 and 0.27, respectively, when measured using PAC with ewes; and 0.23 and 0.34, respectively, when measured using RC with lambs. For measured gas traits, repeatabilities of measurements collected 14 d apart ranged from 0.33 to 0.55 for PAC (combined lambs and ewes) and were greater at 0.65 to 0.76 for the same traits measured using RC. Genetic correlations (rg) between PAC in lambs and ewes were 0.99 for CH4, 0.93 for CH4 + CO2, and 0.85 for CH4/(CH4 + CO2), suggesting that CH4 emissions in lambs and ewes are the same trait. Genetic correlations between PAC and RC measurements were lower, at 0.62 to 0.67 for CH4 and 0.41 to 0.42 for CH4 + CO2, likely reflecting different environmental conditions associated with the protocols used with the 2 measurement methods. The CH4/(CH4 + CO2) ratio was the most similar genetic trait measured using PAC (both lambs and ewes, 63% and 66% selection efficiency, respectively) compared with CH4 yield (g/kg DMI) measured using RC. These results suggest that PAC measurements have considerable value as a rapid low-cost method to estimate breeding values for CH4 emissions in sheep.

Measuring and mitigating methane (CH 4 ) emissions from livestock is of increasing importance for the environment and for policy making. Potentially, the most sustainable way of reducing enteric CH 4 emission from ruminants is through the estimation of genomic breeding values to facilitate genetic selection. There is potential for adopting genetic selection and in the future genomic selection, for reduced CH 4 emissions from ruminants. From this review it has been observed that both CH 4 emissions and production (g/day) are a heritable and repeatable trait. CH 4 emissions are strongly related to feed intake both in the short term (minutes to several hours) and over the medium term (days). When measured over the medium term, CH 4 yield (MY, g CH 4 /kg dry matter intake) is a heritable and repeatable trait albeit with less genetic variation than for CH 4 emissions. CH 4 emissions of individual animals are moderately repeatable across diets, and across feeding levels, when measured in respiration chambers. Repeatability is lower when short term measurements are used, possibly due to variation in time and amount of feed ingested prior to the measurement. However, while repeated measurements add value; it is preferable the measures be separated by at least 3 to 14 days. This temporal separation of measurements needs to be investigated further. Given the above issue can be resolved, short term (over minutes to hours) measurements of CH 4 emissions show promise, especially on systems where animals are fed ad libitum and frequency of meals is high. However, we believe that for short-term measurements to be useful for genetic evaluation, a number (between 3 and 20) of measurements will be required over an extended period of time (weeks to months). There are opportunities for using short-term measurements in standardised feeding situations such as breath 'sniffers' attached to milking parlours or total mixed ration feeding bins, to measure CH 4 . Genomic selection has the potential to reduce both CH 4 emissions and MY, but measurements on thousands of individuals will be required. This includes the need for combined resources across countries in an international effort, emphasising the need to acknowledge the impact of animal and production systems on measurement of the CH 4 trait during design of experiments.Keywords: genetics, greenhouse gases, enteric methane, ruminants ImplicationMeasuring and mitigating methane (CH 4 ) emissions from livestock is of increasing importance for the environment and for policy making. Potentially, the most sustainable way of reducing enteric CH 4 emission from ruminants is through the estimation of genomic breeding values to facilitate genetic selection. Enteric CH 4 emissions are difficult and expensive to measure, thus genomic prediction could provide significant, † E-mail: Yvette IntroductionClimate change is of growing international concern and it is well established that the release of greenhouse gases (GHG) is the driving factor (IPCC, 2006). Globally, livestock farming contributes...

Recent scholarship indicates that people who view their work as a calling are more satisfied with their work and their lives. Historically, calling has been regarded as a religious experience, although modern researchers frequently have adopted a more expansive and secular conceptualization of calling, emphasizing meaning and personal fulfillment in work. The assumption that calling can be easily secularized and applied has not been tested. Therefore, we tested whether calling was related to psychological adjustment and positive work attitudes of both highly religious and less religious college students (N ¼ 242). We also tested whether these positive relations were mediated by people's intrinsic religiousness or by a broader, secular construct, meaning in life. Moderationmediation analyses supported views of calling centering on people's experience of meaning in their work rather than more constrained religious views. Implications for future research and practical applications of calling to positive work attitudes are discussed.

Enteric ruminant methane is the most important greenhouse gas emitted from the pastoral agricultural systems. Genetic improvement of livestock provides a cumulative and permanent impact on performance, and using high-density SNP panels can increase the speed of improvement for most traits. In this study, a data set of 1,726 dairy cows, collected since 1990, was used to calculate a predicted methane emission (PME) trait from feed and energy intake and requirements based on milk yield, live weight, feed intake, and condition score data. Repeated measurements from laser methane detector (LMD) data were also available from 57 cows. The estimated heritabilities for PME, milk yield, DMI, live weight, condition score, and LMD data were 0.13, 0.25, 0.11, 0.92, 0.38, and 0.05, respectively. There was a high genetic correlation between DMI and PME. No SNP reached the Bonferroni significance threshold for the PME traits. One SNP was within the 3 best SNP for PME at wk 10, 20, 30, and 40. Genomic prediction accuracies between dependent variable and molecular breeding value ranged between 0.26 and 0.30. These results are encouraging; however, more work is required before a PME trait can be implemented in a breeding program.

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BackgroundNew Zealand has some unique Terminal Sire composite sheep breeds, which were developed in the last three decades to meet commercial needs. These composite breeds were developed based on crossing various Terminal Sire and Maternal breeds and, therefore, present high genetic diversity compared to other sheep breeds. Their breeding programs are focused on improving carcass and meat quality traits. There is an interest from the industry to implement genomic selection in this population to increase the rates of genetic gain. Therefore, the main objectives of this study were to determine the accuracy of predicted genomic breeding values for various growth, carcass and meat quality traits using a HD SNP chip and to evaluate alternative genomic relationship matrices, validation designs and genomic prediction scenarios. A large multi-breed population (n = 14,845) was genotyped with the HD SNP chip (600 K) and phenotypes were collected for a variety of traits.ResultsThe average observed accuracies (± SD) for traits measured in the live animal, carcass, and, meat quality traits ranged from 0.18 ± 0.07 to 0.33 ± 0.10, 0.28 ± 0.09 to 0.55 ± 0.05 and 0.21 ± 0.07 to 0.36 ± 0.08, respectively, depending on the scenario/method used in the genomic predictions. When accounting for population stratification by adjusting for 2, 4 or 6 principal components (PCs) the observed accuracies of molecular breeding values (mBVs) decreased or kept constant for all traits. The mBVs observed accuracies when fitting both G and A matrices were similar to fitting only G matrix. The lowest accuracies were observed for k-means cross-validation and forward validation performed within each k-means cluster.ConclusionsThe accuracies observed in this study support the feasibility of genomic selection for growth, carcass and meat quality traits in New Zealand Terminal Sire breeds using the Ovine HD SNP chip. There was a clear advantage on using a mixed training population instead of performing analyzes per genomic clusters. In order to perform genomic predictions per breed group, genotyping more animals is recommended to increase the size of the training population within each group and the genetic relationship between training and validation populations. The different scenarios evaluated in this study will help geneticists and breeders to make wiser decisions in their breeding programs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-017-0476-8) contains supplementary material, which is available to authorized users.