The distribution of runs of homozygosity and selection signatures in six commercial meat sheep breeds

peer-reviewedDomestication and the subsequent selection of animals for either economic or morphological features can leave a variety of imprints on the genome of a population. Genomic regions subjected to high selective pressures often show reduced genetic diversity and frequent runs of homozygosity (ROH). Therefore, the objective of the present study was to use 42,182 autosomal SNPs to identify genomic regions in 3,191 sheep from six commercial breeds subjected to selection pressure and to quantify the genetic diversity within each breed using ROH. In addition, the historical effective population size of each breed was also estimated and, in conjunction with ROH, was used to elucidate the demographic history of the six breeds. ROH were common in the autosomes of animals in the present study, but the observed breed differences in patterns of ROH length and burden suggested differences in breed effective population size and recent management. ROH provided a sufficient predictor of the pedigree inbreeding coefficient, with an estimated correlation between both measures of 0.62. Genomic regions under putative selection were identified using two complementary algorithms; the fixation index and hapFLK. The identified regions under putative selection included candidate genes associated with skin pigmentation, body size and muscle formation; such characteristics are often sought after in modern-day breeding programs. These regions of selection frequently overlapped with high ROH regions both within and across breeds. Multiple yet uncharacterised genes also resided within putative regions of selection. This further substantiates the need for a more comprehensive annotation of the sheep genome as these uncharacterised genes may contribute to traits of interest in the animal sciences. Despite this, the regions identified as under putative selection in the current study provide an insight into the mechanisms leading to breed differentiation and genetic variation in meat production.This work was supported by MultiGS Research Stimulus Fund (11/S/112) and OviGen project (14/S/849) which are funded by the Department of Agriculture, Food and Marine, Ireland

Milk mid-infrared spectral data as a tool to predict feed intake in lactating Norwegian Red dairy cows

peer-reviewedMid-infrared (MIR) spectroscopy of milk was used to predict dry matter intake (DMI) and net energy intake (NEI) in 160 lactating Norwegian Red dairy cows. A total of 857 observations were used in leave-one-out cross-validation and external validation to develop and validate prediction equations using 5 different models. Predictions were performed using (multiple) linear regression, partial least squares (PLS) regression, or best linear unbiased prediction (BLUP) methods. Linear regression was implemented using just milk yield (MY) or fat, protein, and lactose concentration in milk (Mcont) or using MY together with body weight (BW) as predictors of intake. The PLS and BLUP methods were implemented using just the MIR spectral information or using the MIR together with Mcont, MY, BW, or NEI from concentrate (NEIconc). When using BLUP, the MIR spectral wavelengths were always treated as random effects, whereas Mcont, MY, BW, and NEIconc were considered to be fixed effects. Accuracy of prediction (R) was defined as the correlation between the predicted and observed feed intake test-day records. When using the linear regression method, the greatest R of predicting DMI (0.54) and NEI (0.60) in the external validation was achieved when the model included both MY and BW. When using PLS, the greatest R of predicting DMI (0.54) and NEI (0.65) in the external validation data set was achieved when using both BW and MY as predictors in combination with the MIR spectra. When using BLUP, the greatest R of predicting DMI (0.54) in the external validation was when using MY together with the MIR spectra. The greatest R of predicting NEI (0.65) in the external validation using BLUP was achieved when the model included both BW and MY in combination with the MIR spectra or when the model included both NEIconc and MY in combination with MIR spectra. However, although the linear regression coefficients of actual on predicted values for DMI and NEI were not different from unity when using PLS, they were less than unity for some of the models developed using BLUP. This study shows that MIR spectral data can be used to predict NEI as a measure of feed intake in Norwegian Red dairy cattle and that the accuracy is augmented if additional, often available data are also included in the prediction model

Effect of using internal teat sealant with or without antibiotic therapy at dry-off on subsequent somatic cell count and milk production

peer-reviewedThe objective of this study was to assess the effect of treating cows with teat sealant only compared with antibiotic plus teat sealant at drying off on weekly somatic cell count, potential intramammary infection, and milk production across the entire subsequent lactation. In 3 research herds in the south of Ireland, cows with SCC that did not exceed 200,000 cells/mL in the previous lactation (LowSCC) were randomly assigned to 1 of 2 treatments at drying off: internal teat sealant alone (ITS) or antibiotic plus teat sealant (AB+ITS). Cows with SCC that exceeded 200,000 cells/mL in the previous lactation were treated with AB+ITS and included in the analyses as a separate group (HighSCC). Weekly individual animal composite SCC records were available for 654 cow lactations and were transformed to somatic cell scores (SCS) for the purpose of analysis. Data were divided into 3 data sets to represent records obtained (1) up to 35 DIM, (2) up to 120 DIM, and (3) across the lactation. Foremilk secretions were taken from all quarters at drying off, at calving, 2 wk after calving, and in mid-lactation and were cultured to detect the presence of bacteria. The LowSCC cows treated with ITS alone had higher daily milk yield (0.67 kg/d) across lactation compared with LowSCC cows treated with AB+ITS. The LowSCC cows treated with ITS alone had higher SCS in early, up to mid, and across lactation compared with LowSCC cows treated with AB+ITS. We detected no difference in weekly SCS of LowSCC cows treated with ITS alone and SCS of HighSCC cows. The least squares means back-transformed SCC across lactation of the LowSCC cows treated with ITS alone, LowSCC cows treated with AB+ITS, and HighSCC cows were 41,523, 34,001, and 38,939 cells/mL respectively. The odds of LowSCC cows treated with ITS alone having bacteria present in their foremilk across lactation was 2.7 (95% confidence interval: 1.91 to 3.85) and 1.6 (1.22 to 2.03) times the odds of LowSCC cows treated with AB+ITS and of HighSCC cows treated with AB+ITS, respectively. In this study, Staphylococcus aureus was the most prevalent pathogen isolated from the population. Recategorizing the threshold for LowSCC cows as ≤150,000 cells/mL or ≤100,000 cells/mL in the previous lactation had no effect on the results. The results indicate that herds with good mastitis control programs may use ITS alone at dry-off in cows with SCC <200,000 cells/mL across lactation with only a small effect on herd SCC

The use of mid-infrared spectrometry to predict body energy status of Holstein cows

Energy balance, especially in early lactation, is known to be associated with subsequent health and fertility in dairy cows. However, its inclusion in routine management decisions or breeding programs is hindered by the lack of quick, easy, and inexpensive measures of energy balance. The objective of this study was to evaluate the potential of mid-infrared (MIR) analysis of milk, routinely available from all milk samples taken as part of large-scale milk recording and milk payment operations, to predict body energy status and related traits in lactating dairy cows. The body energy status traits investigated included energy balance and body energy content. The related traits of body condition score and energy intake were also considered. Measurements on these traits along with milk MIR spectral data were available on 17 different test days from 268 cows (418 lactations) and were used to develop the prediction equations using partial least squares regression. Predictions were externally validated on different independent subsets of the data and the results averaged. The average accuracy of predicting body energy status from MIR spectral data was as high as 75% when energy balance was measured across lactation. These predictions of body energy status were considerably more accurate than predictions obtained from the sometimes proposed fat-to-protein ratio in milk. It is not known whether the prediction generated from MIR data are a better reflection of the true (unknown) energy status than the actual energy status measures used in this study. However, results indicate that the approach described may be a viable method of predicting individual cow energy status for a large scale of application

Prediction of the individual enteric methane emission of dairy cows from milk mid-infrared spectra

peer reviewedThe livestock sector is considered the largest producer of methane (CH4) from anthropogenic sources, world wide contributing 37% of emissions (FAO, 2006). An important step to study and develop mitigation methods for livestock emissions is to be able to measure them on a large scale. However, it is difficult to obtain a large number of individual CH4 measurements with the currently available techniques (chambers or SF6). The aim of this study was to develop a high throughput tool for determination of CH4 emissions from dairy cows. Anaerobic fermentation of food in the reticulorumen is the basis of enteric CH4 production. End-products of that enteric fermentation can be found in the milk (e.g., volatile fatty acids). Therefore individual enteric CH4 emissions could be quantified from whole milk mid-infrared (MIR) spectra which reflect milk composition and can be obtained at low cost (e.g., national milk recording). Prediction equations of individual CH4 emissions (determined using the SF6 method) from milk MIR spectra have been established (Dehareng et al., 2012; Soyeurt et al., 2013). The results presented here are the improvement of this methodology by using a multiple breed and country approach

Crystal structure of monomeric human β-2- microglobulin reveals clues to its amyloidogenic properties

Dissociation of human β-2-microglobulin (β(2)m) from the heavy chain of the class I HLA complex is a critical first step in the formation of amyloid fibrils from this protein. As a consequence of renal failure, the concentration of circulating monomeric β(2)m increases, ultimately leading to deposition of the protein into amyloid fibrils and development of the disorder, dialysis-related amyloidosis. Here we present the crystal structure of a monomeric form of human β(2)m determined at 1.8-Å resolution that reveals remarkable structural changes relative to the HLA-bound protein. These involve the restructuring of a β bulge that separates two short β strands to form a new six-residue β strand at one edge of this β sandwich protein. These structural changes remove key features proposed to have evolved to protect β sheet proteins from aggregation [Richardson, J.&Richardson, D. (2002) Proc. Natl. Acad. Sci. USA 99, 2754–2759] and replaces them with an aggregationcompetent surface. In combination with solution studies using (1)H NMR, we show that the crystal structure presented here represents a rare species in solution that could provide important clues about the mechanism of amyloid formation from the normally highly soluble native protein

Mid-infrared spectrometry of milk as a predictor of energy intake and efficiency in lactating dairy cows

peer-reviewedInterest is increasing in the feed intake complex of individual dairy cows, both for management and animal breeding. However, energy intake data on an individual-cow basis are not routinely available. The objective of the present study was to quantify the ability of routinely undertaken mid-infrared (MIR) spectroscopy analysis of individual cow milk samples to predict individual cow energy intake and efficiency. Feed efficiency in the present study was described by residual feed intake (RFI), which is the difference between actual energy intake and energy used (e.g., milk production, maintenance, and body tissue anabolism) or supplied from body tissue mobilization. A total of 1,535 records for energy intake, RFI, and milk MIR spectral data were available from an Irish research herd across 36 different test days from 535 lactations on 378 cows. Partial least squares regression analyses were used to relate the milk MIR spectral data to either energy intake or efficiency. The coefficient of correlation (REX) of models to predict RFI across lactation ranged from 0.48 to 0.60 in an external validation data set; the predictive ability was, however, strongest (REX = 0.65) in early lactation (<60 d in milk). The inclusion of milk yield as a predictor variable improved the accuracy of predicting energy intake across lactation (REX = 0.70). The correlation between measured RFI and measured energy balance across lactation was 0.85, whereas the correlation between RFI and energy balance, both predicted from the MIR spectrum, was 0.65. Milk MIR spectral data are routinely generated for individual cows throughout lactation and, therefore, the prediction equations developed in the present study can be immediately (and retrospectively where MIR spectral data have been stored) applied to predict energy intake and efficiency to aid in management and breeding decisions

Risk factors associated with detailed reproductive phenotypes in dairy and beef cows

peer-reviewedThis article was first published in animal, Volume 8, Issue 05, May 2014, pp 695-703, © The Animal Consortium 2014The objective of this study was to identify detailed fertility traits in dairy and beef cattle from transrectal ultrasonography records and quantify the associated risk factors. Data were available on 148 947 ultrasound observations of the reproductive tract from 75 949 cows in 843 Irish dairy and beef herds between March 2008 and October 2012. Traits generated included (1) cycling at time of examination, (2) cystic structures, (3) early ovulation, (4) embryo death and (5) uterine score; the latter was measured on a scale of 1 (good) to 4 (poor) characterising the tone of the uterine wall and fluid present in the uterus. After editing, 72 773 records from 44 415 dairy and beef cows in 643 herds remained. Factors associated with the logit of the probability of a positive outcome for each of the binary fertility traits were determined using generalised estimating equations; linear mixed model analysis was used for the analysis of uterine score. The prevalence of cycling, cystic structures, early ovulation and embryo death was 84.75%, 3.87%, 7.47% and 3.84%, respectively. The occurrence of the uterine heath score of 1, 2, 3 and 4 was 70.63%, 19.75%, 8.36% and 1.26%, respectively. Cows in beef herds had a 0.51 odds (95% CI = 0.41 to 0.63, P<0.001) of cycling at the time of examination compared with cows in dairy herds; stage of lactation at the time of examination was the same in both herd types. Furthermore, cows in dairy herds had an inferior uterine score (indicating poorer tone and a greater quantity of uterine fluid present) compared with cows in beef herds. The likelihood of cycling at the time of examination increased with parity and stage of lactation, but was reduced in cows that had experienced dystocia in the previous calving. The presence of cystic structures on the ovaries increased with parity and stage of lactation. The likelihood of embryo/foetal death increased with parity and stage of lactation. Dystocia was not associated with the presence of cystic structures or embryo death. Uterine score improved with parity and stage of lactation, while cows that experienced dystocia in the previous calving had an inferior uterine score. Heterosis was the only factor associated with increased likelihood of early ovulation. The fertility traits identified, and the associated risk factors, provide useful information on the reproductive status of dairy and beef cows.Funding from the Department of Agriculture, Food and Marine Research Stimulus Fund (RSF 11/S/133) and the OptiMIR project is gratefully acknowledged

Methods for measuring fluoroscopic skin dose

This paper briefly reviews available technologies for measuring or estimating patient skin dose in the interventional fluoroscopic environment