Droplet digital PCR quantification of selected microRNAs in raw mastitic cow's milk from the west of Poland.

Introduction: MicroRNAs (miRNAs), a class of noncoding small RNAs, have been recognised as potential biomarkers of mammary gland conditions, including bovine mastitis diagnosis. The aim of this study was to quantify selected miRNAs in the milk of mastitic cows. Material and Methods: Milk samples (n = 90) were collected from healthy and mastitic dairy cows originating from local dairy cattle farms located in the west of Poland. MicroRNAs of the miR-21a, miR-92a, miR-146a and miR-383 species were quantified using the highly sensitive droplet digital PCR method. Direct measurement of somatic cell count (SCC) was performed using a cell counter. Cows were divided into three groups: those with an SCC below 200,000/mL were designated Low (n = 25), those with an SCC between 200,000 and 999,999 were Medium (n = 34), and those with an SCC of 1,000,000 or higher were High (n = 31). Microbiological analyses were performed using standard culture testing. Results: The level of miR-383 was very low and this miRNA was excluded from analysis. The miR-92a was used to normalise miR-21a and miR-146a expression levels. The obtained results of expression of miR-21a and miR-146a correlated with somatic cell number (R = 0.53 and 0.79, respectively). Conclusion: These results show that ddPCR is a useful method for quantifying miRNAs in raw cow milk. It seems that miR-146a is a promising marker for bovine mastitis, although further studies are needed to select a panel of miRNAs that can be used in mastitis monitoring in Poland.

Droplet Digital PCR Quantification of Selected Intracellular and Extracellular microRNAs Reveals Changes in Their Expression Pattern during Porcine In Vitro Adipogenesis.

Extracellular miRNAs have attracted considerable interest because of their role in intercellular communication, as well as because of their potential use as diagnostic and prognostic biomarkers for many diseases. It has been shown that miRNAs secreted by adipose tissue can contribute to the pathophysiology of obesity. Detailed knowledge of the expression of intracellular and extracellular microRNAs in adipocytes is thus urgently required. The system of in vitro differentiation of mesenchymal stem cells (MSCs) into adipocytes offers a good model for such an analysis. The aim of this study was to quantify eight intracellular and extracellular miRNAs (miR-21a, miR-26b, miR-30a, miR-92a, miR-146a, miR-148a, miR-199, and miR-383a) during porcine in vitro adipogenesis using droplet digital PCR (ddPCR), a highly sensitive method. It was found that only some miRNAs associated with the inflammatory process (miR-21a, miR-92a) were highly expressed in differentiated adipocytes and were also secreted by cells. All miRNAs associated with adipocyte differentiation were highly abundant in both the studied cells and in the cell culture medium. Those miRNAs showed a characteristic expression profile with upregulation during differentiation.

Supporting the diagnosis of infantile colic by a point of care measurement of fecal calprotectin.

Background: Infantile colic (IC) is a condition characterized by extensive crying which affects about 20% of all infants during their first months of life. Most pediatricians diagnose IC only based on their clinical experience. Aim: Investigating if a measurement of fecal calprotectin can support the diagnosis of IC. Methods: The crying behavior of newborns was assessed using the Wessel's criteria. Fecal calprotectin levels were measured in non-colicky and colicky babies using a standard test that can be used at the time and place of patient care (point of care (PoC) measurement). Results: Colicky babies were found to have significantly elevated fecal calprotectin levels. Calprotectin levels were not influenced by gender, type of feeding, gestation age or birth weight. However, significantly elevated fecal calprotectin levels were found in cesarean section born babies. Fecal calprotectin ≥100 µg/g correlated with a colicky status of an infant while those <100 µg/g indicated a non-colicky status the error margin was 11.2 and 13.2%, respectively. Combining data of fecal calprotectin with information about the type of delivery made it possible to determine the colicky status in vaginally-born infants with fecal calprotectin ≥100 µg/g with an accuracy of 97.8%. As elevated fecal calprotectin levels in cesarean-born infants can be caused by IC, but also by the disturbed gut microbiota commonly found in these babies, the accuracy of diagnosing the colicky status of a cesarean-born infant with calprotectin levels ≥100 µg/g was less accurate (accuracy rate of 76.5%). Conclusion: Data from the study suggest that measuring fecal calprotectin should be considered by pediatricians to support the diagnosis of IC.The study was registered at ClinicalTrials.gov under NCT04666324.

Prevalence and characterisation of antimicrobial resistance genes and class 1 and 2 integrons in multiresistant Escherichia coli isolated from poultry production.

A global increase in the populations of drug resistant bacteria exerts negative effects on animal production and human health. Our study has been focused on the assessment of resistance determinants in relation to phenotypic resistance of the 74 commensal E. coli isolates present in different ecological environments. The samples were collected from poultry litter, feces, and neck skin. Among the microorganisms isolated from the poultry litter (group A), the highest resistance was noted against AMP and DOX (100%). In the E. coli extracts from the cloacal swabs (group B), the highest resistance was observed against AMP (100%) and CIP (92%). The meat samples (group C) were characterized by resistance to AMP (100%) and STX (94.7%). Genes encoding resistance to ß-lactams (blaTEM, blaCTX-M), fluoroquinolones (qnrA, qnrB, qnrS), aminoglycosides (strA-strB, aphA1, aac(3)-II), sulfonamides (sul1, sul2, sul3), trimethoprim (dfr1, dfr5, dfr7/17) and tetracyclines (tetA, tetB) were detected in the studied bacterial isolates. The presence of class 1 and 2 integrons was confirmed in 75% of the MDR E. coli isolates (plasmid DNA), of which 60% contained class 1 integrons, 15% contained class 2 integrons, and 11.7% carried integrons of both classes. Thus, it may be concluded that integrons are the common mediators of antimicrobial resistance among commensal multidrug resistant Escherichia coli at important stages of poultry production.

Integrating heterogeneous across-country data for proxy-based random forest prediction of enteric methane in dairy cattle.

Direct measurements of methane (CH4) from individual animals are difficult and expensive. Predictions based on proxies for CH4 are a viable alternative. Most prediction models are based on multiple linear regressions (MLR) and predictor variables that are not routinely available in commercial farms, such as dry matter intake (DMI) and diet composition. The use of machine learning (ML) algorithms to predict CH4 emissions from across-country heterogeneous data sets has not been reported. The objectives were to compare performances of ML ensemble algorithm random forest (RF) and MLR models in predicting CH4 emissions from proxies in dairy cows, and assess effects of imputing missing data points on prediction accuracy. Data on CH4 emissions and proxies for CH4 from 20 herds were provided by 10 countries. The integrated data set contained 43,519 records from 3,483 cows, with 18.7% missing data points imputed using k-nearest neighbor imputation. Three data sets were created, 3k (no missing records), 21k (missing DMI imputed from milk, fat, protein, body weight), and 41k (missing DMI, milk fat, and protein records imputed). These data sets were used to test scenarios (with or without DMI, imputed vs. nonimputed DMI, milk fat, and protein), and prediction models (RF vs. MLR). Model predictive ability was evaluated within and between herds through 10-fold cross-validation. Prediction accuracy was measured as correlation between observed and predicted CH4, root mean squared error (RMSE) and mean normalized discounted cumulative gain (NDCG). Inclusion of DMI in the model improved within and between-herd prediction accuracy to 0.77 (RMSE = 23.3%) and 0.58 (RMSE = 31.9%) in RF and to 0.50 (RMSE = 0.327) and 0.13 (RMSE = 42.71) in MLR, respectively than when DMI was not included in the predictive model. When missing DMI records were imputed, within and between-herd accuracy increased to 0.84 (RMSE = 18.5%) and 0.63 (RMSE = 29.9%), respectively. In all scenarios, RF models out-performed MLR models. Results suggest routinely measured variables from dairy farms can be used in developing globally robust prediction models for CH4 if coupled with state-of-the-art techniques for imputation and advanced ML algorithms for predictive modeling.

Nine-Strain Bacterial Synbiotic Improves Crying and Lowers Fecal Calprotectin in Colicky Babies-An Open-Label Randomized Study.

The aim of this study (ClinicalTrials.gov registration NCT04666324) was to determine the effects of a nine-strain synbiotic and simethicone on the duration of crying and the gut inflammation marker calprotectin in colicky babies aged 3-6 weeks, diagnosed using the Wessel criteria. The open-label study comprised a control group of non-colicky babies (n = 20) and two parallel treatment groups (each n = 50) to which colicky babies were randomly and equally assigned to receive the multi-strain synbiotic or simethicone orally for 28 days. Primary outcome measures were the change in daily crying duration and the level of fecal calprotectin on days 1 and 28 of the study. Administration of the synbiotic resulted in a rechange of crying duration of -7.18 min/day of treatment, while simethicone had a significantly smaller effect (-5.74 min/day). Fecal calprotectin levels in colicky babies were significantly elevated compared to those in non-colicky babies. Treatment with the nine-strain synbiotic resulted in a significant lowering of fecal calprotectin at the end of the study, while no such effect was found for simethicone. No adverse effects were reported. Study results confirm earlier findings of crying duration reductions in colicky babies by the synbiotic, an effect that might be linked to its anti-inflammatory properties.

Genetic Variability of Methane Production and Concentration Measured in the Breath of Polish Holstein-Friesian Cattle.

The genetic architecture of methane (CH4) production remains largely unknown. We aimed to estimate its heritability and to perform genome-wide association studies (GWAS) for the identification of candidate genes associated with two phenotypes: CH4 in parts per million/day (CH4 ppm/d) and CH4 in grams/day (CH4 g/d). We studied 483 Polish Holstein-Friesian cows kept on two commercial farms in Poland. Measurements of CH4 and carbon dioxide (CO2) concentrations exhaled by cows during milking were obtained using gas analyzers installed in the automated milking system on the farms. Genomic analyses were performed using a single-step BLUP approach. The percentage of genetic variance explained by SNPs was calculated for each SNP separately and then for the windows of neighbouring SNPs. The heritability of CH4 ppm/d ranged from 0 to 0.14, with an average of 0.085. The heritability of CH4 g/d ranged from 0.13 to 0.26, with an average of 0.22. The GWAS detected potential candidate SNPs on BTA 14 which explained ~0.9% of genetic variance for CH4 ppm/d and ~1% of genetic variance for CH4 g/d. All identified SNPs were located in the TRPS1 gene. We showed that methane traits are partially controlled by genes; however, the detected SNPs explained only a small part of genetic variation-implying that both CH4 ppm/d and CH4 g/d are highly polygenic traits.

Changes in metabolic and hormonal profiles during transition period in dairy cattle - the role of spexin.

BACKGROUND: This study aimed to evaluate spexin as a novel blood marker and to describe the relationship of this peptide with selected biochemical metabolites measured during the transition period in dairy cows. Additionally, mRNA expression of the spexin gene as well as spexin receptors - galanin receptor type 2 and galanin receptor type 3, was investigated in several bovine tissues. Blood samples were collected at weekly intervals starting at 21 days before the estimated parturition day until 21 days in milk to determine concentrations of spexin, nonesterified fatty acids, ß-hydroxybutyrate acid, total and active ghrelin, progesterone, glucose, insulin, IGF-I, triglycerides, cholesterol, leptin, corticosterone and 17-ß-estradiol as well as the activity of aspartate transaminase, alkaline phosphatase and gamma-glutamyl transferase. RESULTS: Spexin concentration decreased from 21 d before parturition to calving day and next it rose during the first 14 d of lactation. The lowest concentration of spexin was recorded on the calving day and it differed from the mean level of this peptide before parturition as well as postpartum. Moreover, differences were observed between mean spexin concentrations before and after calving. Spexin levels were moderately negatively correlated with NEFA (r = - 0.39) and total ghrelin contents (r = - 0.41), weakly correlated with BHBA (r = - 0.35) while they showed a moderate positive relationship with progesterone concentrations (r = 0.42). Moreover, we detected that mRNA expression of GALR2, GALR3 and SPX is present in various bovine tissues (kidney, bowel, rumen, spinal cord, lung, skeletal muscle, liver, heart, fat and spleen). CONCLUSION: A negative correlation between spexin concentration and NEFA, BHBA and total ghrelin contents as well as a positive relationship with levels of progesterone, metabolites and hormones, which are key players in the dairy cow transition period, may confirm an important function of this peptide in metabolism regulation. Thus measurement of spexin concentration could provide useful supplementary information for dairy cow herd health monitoring.

Mitochondria Content and Activity Are Crucial Parameters for Bull Sperm Quality Evaluation.

Standard sperm evaluation parameters do not enable predicting their ability to survive cryopreservation. Mitochondria are highly prone to suffer injuries during freezing, and any abnormalities in their morphology or function are reflected by a decline of sperm quality. Our work focused on describing a link between the number and the activity of mitochondria, with an aim to validate its applicability as a biomarker of bovine sperm quality. Cryopreserved sperm collected from bulls with high (group 1) and low (group 2) semen quality was separated by swim up. The spermatozoa of group 1 overall retained more mitochondria (MitoTrackerGreen) and mtDNA copies, irrespective of the fraction. Regardless of the initial ejaculate quality, the motile sperm contained significantly more mitochondria and mtDNA copies. The same trend was observed for mitochondrial membrane potential (ΔΨm, JC-1), where motile sperm displayed high ΔΨm. These results stay in agreement with transcript-level evaluation (real-time polymerase chain reaction, PCR) of antioxidant enzymes (PRDX1, SOD1, GSS), which protect cells from the reactive oxygen species. An overall higher level of glutathione synthetase (GSS) mRNA was noted in group 1 bulls, suggesting higher ability to counteract free radicals. No differences were noted between basal oxygen consumption rate (OCR) (Seahorse XF Agilent) and ATP-linked respiration for group 1 and 2 bulls. In conclusion, mitochondrial content and activity may be used as reliable markers for bovine sperm quality evaluation.

Unraveling the actual background of second litter syndrome in pigs: based on Large White data.

Second litter syndrome (SLS) in sows is when fertility performance is lower in the second parity than in the first parity. The causes of SLS have been associated with lactation weight loss, premature first insemination, short lactation length, short weaning to insemination interval, season, and farm of farrowing. There is little known about the genetic background of SLS or if it is a real biological problem or just a statistical issue. Thus, we aimed to evaluate risk factors, investigate genetic background of SLS, and estimate the probability of SLS existing due to the statistical properties of the trait. The records of 246 799 litters (total number born, TNB) from 46 218 Large White sows were used. A total of 15 398 sows had SLS. Two traits were defined: first a binominal trait if a sow had SLS or not (biSLS) and second a continuous trait (Range) created by subtracting the total number of piglets born in the first parity (TNB1) from the piglets born in the second parity (TNB2). Lactation length, farm, and season of the farrowing had significant effects on SLS traits when tested as fixed effects in the genetic model. These effects are farm management-related factors. The age at first insemination and weaning to insemination interval were significant only for other reproduction traits (e.g., TNB1, TNB2, litter weight in parity 1 and 2). The heritability of biSLS was 0.05 (on observed scale), whereas heritability of Range was 0.03. To verify the existence of SLS data with records of 50 000 sows and 9 parities was simulated. The simulations showed that the average expected frequency of SLS across all the parities was 0.49 (±0.05) while the observed frequency in the actual data was 0.46 (±0.04). We compared this to SLS frequencies in 67 farms and only 2 farms had more piglets born in the first parity compared to the second. Therefore, on the individual sow level SLS is likely due to statistical properties of the trait, whereas on the farm level SLS is likely due to farm management. Thus, SLS should not be considered an abnormality nor a syndrome if on average the herd litter size in parity 2 is larger than in parity 1.

The Effect of Rumination Time on Milk Performance and Methane Emission of Dairy Cows Fed Partial Mixed Ration Based on Maize Silage.

The objective of this study was to determine the effect of the rumination time on milk yield and composition as well as methane emission during lactation in high-yielding dairy cows fed a partial mixed ration based on maize silage without pasture access. A total of 365 high-yielding Polish Holstein-Friesian multiparous dairy cows were included in the study covering 24 to 304 days of lactation. Methane emission, rumination time, and milk production traits were observed for the period of 12 months. Next, the data from the cows were assigned to three groups based on daily rumination time: low rumination up to 412 min/day (up to 25th rumination percentile), medium rumination from 412 to 527 min/day (between the 25th and 75th percentile), and high rumination above 527 min/day (from the 75th percentile). Rumination time had no effect on milk yield, energy-corrected milk yield, or fat and protein-corrected milk yield. High rumination time had an effect on lower fat concentration in milk compared with the medium and low rumination groups. The highest daily CH4 production was noted in low rumination cows, which emitted 1.8% more CH4 than medium rumination cows and 4.2% more than high rumination cows. Rumination time affected daily methane production per kg of milk. Cows from the high rumination group produced 2.9% less CH4 per milk unit compared to medium rumination cows and 4.6% in comparison to low rumination cows. Similar observations were noted for daily CH4 production per ECM unit. In conclusion, a longer rumination time is connected with lower methane emission as well as lower methane production per milk unit in high-yielding dairy cows fed a maize silage-based partial mixed ration without pasture access.

Infantile Colic-The Perspective of German and Polish Pediatricians in 2020.

The objective of the study was to characterize how infantile colic is perceived and managed by German and Polish pediatricians. Data in both countries were collected by using a paper questionnaire with seven questions and predefined and free text fields for the answers. Answers from 160 German and 133 Polish pediatricians were collected. The average of the occurrence rates estimated by both responder groups were at the higher end of published rates. The majority of pediatricians from both countries rated the parental burden caused by infantile colic to be high or very high. Pediatricians' awareness about the association between infantile colic and maternal depression and premature termination of breastfeeding is relatively well established in both countries. While more than 90% of German pediatricians stated knowledge of infantile colic being a major risk factor for shaken baby syndrome, this knowledge was only declared by half of the Polish responders. Pharmacological interventions, pro-/synbiotics or simethicone, are part of the treatment repertoire of nearly all responding pediatricians. In addition, non-pharmacological interventions (e.g., change of feeding, change of parental behavior) are also among the employed interventions. Results of this study will allow to better design and prioritize communication about infantile colic directed at pediatricians.

Colistin Resistance of Non-pathogenic Strains of Escherichia Coli Occurring as Natural Intestinal Flora in Broiler Chickens Treated and not Treated with Colistin Sulphate.

INTRODUCTION: A significant threat to public health is presented by antibiotic-resistant strains of bacteria, selective pressure on which results from antibiotic use. Colistin is an antibiotic commonly used in veterinary medicine, but also one of last resort in human medicine. Since the 2015 discovery in China of the mcr-1 gene encoding colistin resistance in Enterobacteriaceae, other countries have noted its presence. This study was to find the mcr-1 gene prevalence in E. coli isolated from poultry slaughtered in Poland. MATERIAL AND METHODS: Cloacal swabs were taken from December 2017 to October 2018 from broiler chickens in three regions. The samples (n = 158) were grouped as flocks treated with colistin sulphate (n = 87) and those not treated (n = 71). Resistance to antimicrobials commonly used in poultry was evaluated by minimum inhibitory concentration. The presence of the mcr-1 gene was confirmed by PCR. RESULTS: Isolates containing the mcr-1 gene were yielded by 11.27% of the samples from not treated flocks and 19.54% of those from treated flocks, but no statistically significant difference in the prevalence of the gene was seen between the groups. CONCLUSION: The results clearly preclude intensification of selective pressure for colistin resistance due to colistin sulphate treatment because they show that the avian gastrointestinal tract was already inhabited by colistin-resistant E. coli by the time the chickens came to the poultry house.

Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle.

Partners in Expert Working Group WG2 of the COST Action METHAGENE have used several methods for measuring methane output by individual dairy cattle under various environmental conditions. Methods included respiration chambers, the sulphur hexafluoride (SF6) tracer technique, breath sampling during milking or feeding, the GreenFeed system, and the laser methane detector. The aim of the current study was to review and compare the suitability of methods for large-scale measurements of methane output by individual animals, which may be combined with other databases for genetic evaluations. Accuracy, precision and correlation between methods were assessed. Accuracy and precision are important, but data from different sources can be weighted or adjusted when combined if they are suitably correlated with the 'true' value. All methods showed high correlations with respiration chambers. Comparisons among alternative methods generally had lower correlations than comparisons with respiration chambers, despite higher numbers of animals and in most cases simultaneous repeated measures per cow per method. Lower correlations could be due to increased variability and imprecision of alternative methods, or maybe different aspects of methane emission are captured using different methods. Results confirm that there is sufficient correlation between methods for measurements from all methods to be combined for international genetic studies and provide a much-needed framework for comparing genetic correlations between methods should these become available.

Enteric methane emission from Jersey cows during the spring transition from indoor feeding to grazing.

Organic dairy cows in Denmark are often kept indoors during the winter and outside at least part time in the summer. Consequently, their diet changes by the season. We hypothesized that grazing might affect enteric CH4 emissions due to changes in the nutrition, maintenance, and activity of the cows, and they might differentially respond to these factors. This study assessed the repeatability of enteric CH4 emission measurements for Jersey cattle in a commercial organic dairy herd in Denmark. It also evaluated the effects of a gradual transition from indoor winter feeding to outdoor spring grazing. Further, it assessed the individual-level correlations between measurements during the consecutive feeding periods (phenotype × environment, P × E) as neither pedigrees nor genotypes were available to estimate a genotype by environment effect. Ninety-six mixed-parity lactating Jersey cows were monitored for 30 d before grazing and for 24 d while grazing. The cows spent 8 to 11 h grazing each day and had free access to an in-barn automatic milking system (AMS). For each visit to the AMS, milk yield was recorded and logged along with date and time. Monitoring equipment installed in the AMS feed bins continuously measured enteric CH4 and CO2 concentrations (ppm) using a noninvasive "sniffer" method. Raw enteric CH4 and CO2 concentrations and their ratio (CH4:CO2) were derived from average concentrations measured during milking and per day for each cow. We used mixed models equations to estimate variance components and adjust for the fixed and random effects influencing the analyzed gas concentrations. Univariate models were used to precorrect the gas measurements for diurnal variation and to estimate the direct effect of grazing on the analyzed concentrations. A bivariate model was used to assess the correlation between the 2 periods (in-barn vs. grazing) for each gas concentration. Grazing had a weak P × E interaction for daily average CH4 and CO2 gas concentrations. Bivariate repeatability estimates for average CH4 and CO2 concentrations and CH4:CO2 were 0.77 to 0.78, 0.73 to 0.80, and 0.26, respectively. Repeatability for CH4:CO2 was low (0.26) but indicated some between-animal variation. In conclusion, grazing does not create significant shifts compared with indoor feeding in how animals rank for average CH4 and CO2 concentrations and CH4:CO2. We found no evidence that separate evaluation is needed to quantify enteric CH4 and CO2 emissions from Jersey cows during in-barn and grazing periods.

Interactions of bovine oocytes with follicular elements with respect to lipid metabolism.

Among many factors, lipid metabolism within the follicular environment emerges as an important indicator of oocyte quality. In the literature a crucial significance is described concerning follicular fluid (FF) composition as well as messenger RNA (mRNA) expression in follicular cells. The aim of this study was to describe the relationship between oocyte, FF and follicular cells with regard to lipid metabolism. The set of data originating from individual follicles comprised: lipid droplets (LD) number in oocytes (BODIPY staining), mRNA expression of seven genes in cumulus and granulosa cells (SCD, FADS2, ELOVL2, ELOVL5, GLUT1, GLUT3, GLUT8; real time polymerase chain reaction) and fatty acid (FA) composition in FF (gas chromatography). Obtained results demonstrate significant correlation between oocyte lipid droplets number and FA composition in FF. However, gene expression studies show significant correlation between LD number and GLUT1 gene only. Moreover, the present experiment revealed correlations between FA content in FF and expression of several genes (SCD, FADS2, ELOVL5, GLUT8) in granulosa cells, whereas only the SCD gene in cumulus cells. We suggest that the results of our experiment indicate the importance of glucose : lipid metabolism balance, which contributes to better understanding of energy metabolism conversion between oocytes and the maternal environment.

A comparison of principal component regression and genomic REML for genomic prediction across populations.

BACKGROUND: Genomic prediction faces two main statistical problems: multicollinearity and n ≪ p (many fewer observations than predictor variables). Principal component (PC) analysis is a multivariate statistical method that is often used to address these problems. The objective of this study was to compare the performance of PC regression (PCR) for genomic prediction with that of a commonly used REML model with a genomic relationship matrix (GREML) and to investigate the full potential of PCR for genomic prediction. METHODS: The PCR model used either a common or a semi-supervised approach, where PC were selected based either on their eigenvalues (i.e. proportion of variance explained by SNP (single nucleotide polymorphism) genotypes) or on their association with phenotypic variance in the reference population (i.e. the regression sum of squares contribution). Cross-validation within the reference population was used to select the optimum PCR model that minimizes mean squared error. Pre-corrected average daily milk, fat and protein yields of 1609 first lactation Holstein heifers, from Ireland, UK, the Netherlands and Sweden, which were genotyped with 50 k SNPs, were analysed. Each testing subset included animals from only one country, or from only one selection line for the UK. RESULTS: In general, accuracies of GREML and PCR were similar but GREML slightly outperformed PCR. Inclusion of genotyping information of validation animals into model training (semi-supervised PCR), did not result in more accurate genomic predictions. The highest achievable PCR accuracies were obtained across a wide range of numbers of PC fitted in the regression (from one to more than 1000), across test populations and traits. Using cross-validation within the reference population to derive the number of PC, yielded substantially lower accuracies than the highest achievable accuracies obtained across all possible numbers of PC. CONCLUSIONS: On average, PCR performed only slightly less well than GREML. When the optimal number of PC was determined based on realized accuracy in the testing population, PCR showed a higher potential in terms of achievable accuracy that was not capitalized when PC selection was based on cross-validation. A standard approach for selecting the optimal set of PC in PCR remains a challenge.

Genomic breeding value prediction and QTL mapping of QTLMAS2011 data using Bayesian and GBLUP methods.

BACKGROUND: The goal of this study was to apply Bayesian and GBLUP methods to predict genomic breeding values (GEBV), map QTL positions and explore the genetic architecture of the trait simulated for the 15th QTL-MAS workshop. METHODS: Three methods with models considering dominance and epistasis inheritances were used to fit the data: (i) BayesB with a proportion π = 0.995 of SNPs assumed to have no effect, (ii) BayesCπ, where π is considered as unknown, and (iii) GBLUP, which directly fits animal genetic effects using a genomic relationship matrix. RESULTS: BayesB, BayesCπ and GBLUP with various fitted models detected 6, 5, and 4 out of 8 simulated QTL, respectively. All five additive QTL were detected by Bayesian methods. When two QTL were in either coupling or repulsion phase, GBLUP only detected one of them and missed the other. In addition, GBLUP yielded more false positives. One imprinted QTL was detected by BayesB and GBLUP despite that only additive gene action was assumed. This QTL was missed by BayesCπ. None of the methods found two simulated additive-by-additive epistatic QTL. Variance components estimation correctly detected no evidence for dominance gene-action. Bayesian methods predicted additive genetic merit more accurately than GBLUP, and similar accuracies were observed between BayesB and BayesCπ. CONCLUSIONS: Bayesian methods and GBLUP mapped QTL to similar chromosome regions but Bayesian methods gave fewer false positives. Bayesian methods can be superior to GBLUP in GEBV prediction when genomic architecture is unknown.

Comparison of analyses of the QTLMAS XIV common dataset. I: genomic selection.

BACKGROUND: For the XIV QTLMAS workshop, a dataset for traits with complex genetic architecture has been simulated and released for analyses by participants. One of the tasks was to estimate direct genomic values for individuals without phenotypes. The aim of this paper was to compare results of different approaches used by the participants to calculate direct genomic values for quantitative trait (QT) and binary trait (BT). RESULTS: Participants applied 26 approaches for QT and 15 approaches for BT. Accuracy for QT was between 0.26 and 0.89 for males and between 0.31 and 0.89 for females, and for BT ranged from 0.27 to 0.85. For QT, percentage of lost response to selection varied from 8% to 83%, whereas for BT the loss was between 15% and 71%. CONCLUSIONS: Bayesian model averaging methods predicted breeding values slightly better than GBLUP in a simulated data set. The methods utilizing genomic information performed better than traditional pedigree based BLUP analyses. Bivariate analyses was slightly advantageous over single trait for the same method. None of the methods estimated the non-additivity of QTL affecting the QT, which may be one of the constrains in accuracy observed in real data.

Comparison of analyses of the QTLMAS XIV common dataset. II: QTL analysis.

BACKGROUND: A quantitative and a binary trait for the 14th QTLMAS 2010 workshop were simulated under a model which combined additive inheritance, epistasis and imprinting. This paper aimed to compare results submitted by the participants of the workshop. METHODS: The results were compared according to three criteria: the success rate (ratio of mapped QTL to the total number of simulated QTL), and the error rate (ratio of false positives to the number of reported positions), and mean distance between a true mapped QTL and the nearest submitted position. RESULTS: Seven groups submitted results for the quantitative trait and five for the binary trait. Among the 37 simulated QTL 17 remained undetected. Success rate ranged from 0.05 to 0.43, error rate was between 0.00 and 0.92, and the mean distance ranged from 0.26 to 0.77 Mb. CONCLUSIONS: Our comparison shows that differences among methods used by the participants increases with the complexity of genetic architecture. It was particularly visible for the quantitative trait which was determined partly by non-additive QTL. Furthermore, an imprinted QTL with a large effect may remain undetected if the applied model tests only for Mendelian genes.