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Information on dry matter intake (DMI) and energy balance (EB) at the animal and herd level is important for management and breeding decisions. However, routine recording of these traits at commercial farms can be challenging and costly. Fourier-transform mid-infrared (FT-MIR) spectroscopy is a noninvasive technique applicable to a large cohort of animals that is routinely used to analyze milk components and is convenient for predicting complex phenotypes that are typically difficult and expensive to obtain on a large scale. We aimed to develop prediction models for EB and use the predicted phenotypes for genetic analysis. First, we assessed prediction equations using 4,485 phenotypic records from 167 Holstein cows from an experimental station. The phenotypes available were body weight (BW), milk yield (MY) and milk components, weekly-averaged DMI, and FT-MIR data from all milk samples available. We implemented mixed models with Bayesian approaches and assessed them through 50 randomized replicates of a 5-fold cross-validation. Second, we used the best prediction models to obtain predicted phenotypes of EB (EBp) and DMI (DMIp) on 5 commercial farms with 2,365 phenotypic records of MY, milk components and FT-MIR data, and BW from 1,441 Holstein cows. Third, we performed a GWAS and estimated heritability and genetic correlations for energy content in milk (EnM), BW, DMIp, and EBp using the genomic information available on the cows from commercial farms. The highest correlation between the predicted and observed phenotype (r y,y^ ) was obtained with DMI (0.88) and EB (0.86), while predicting BW was, as anticipated, more challenging (0.69). In our study, models that included FT-MIR information performed better than models without spectra information in the 3 traits analyzed, with increments in prediction correlation ranging from 5% to 10%. For the predicted phenotypes calculated by the prediction equations and data from the commercial farms the heritability ranged between 0.11 and 0.16 for EnM, DMIp and EBp, and 0.42 for BW. The genetic correlation between EnM and BW was -0.17, with DMIp was 0.40 and with EBp was -0.39. From the GWAS, we detected one significant QTL region for EnM, and 3 for BW, but none for DMIp and EBp. The results obtained in our study support previous evidence that FT-MIR information from milk samples contribute to improve the prediction equations for DMI, BW, and EB, and these predicted phenotypes may be used for herd management and contribute to the breeding strategy for improving cow performance., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Milk fatty acid composition is gaining interest in the Danish dairy industry both to develop new dairy products and as a management tool. To be able to implement milk fatty acid (FA) composition in the breeding program, it is important to know the correlations with the traits in the breeding goal. To estimate these correlations, we measured milk fat composition in Danish Holstein (DH) and Danish Jersey (DJ) cattle breeds using mid-infrared spectroscopy. Breeding values were estimated for specific FA and for groups of FA. Correlations with the estimated breeding values (EBV) underlying the Nordic Total Merit index (NTM) were calculated within breed. For both DH and DJ, we showed that FA EBV had moderate correlations with the NTM and production traits. For both DH and DJ, the correlation of FA EBV and NTM were in the same direction, except for C16:0 (0 in DH, 0.23 in DJ). A few correlations differed between DH and DJ. The correlation between claw health index and C18:0 was negative in DH (-0.09) but positive in DJ (0.12). In addition, some correlations were not significant in DH but were significant in DJ. The correlations between udder health index and long-chain FA, trans FA, C16:0, and C18:0 were not significant in DH (-0.05 to 0.02), but were significant in DJ (-0.17, -0.15, 0.14, and -0.16, respectively). For both DH and DJ, the correlations between FA EBV and nonproduction traits were low. This implies that it is possible to breed for a different fat composition in the milk without affecting the nonproduction traits in the breeding goal., (© 2023, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The aim of this study was to estimate genetic parameters for milk urea (MU) content in 3 main Danish dairy breeds. As a part of the Danish milk recording system, milk samples from cows on commercial farms were analyzed for MU concentration (mmol/L) and the percentages of fat and protein. There were 323,800 Danish Holstein, 70,634 Danish Jersey, and 27,870 Danish Red cows sampled with a total of 1,436,580, 368,251, and 133,922 test-day records per breed, respectively, included in the data set. Heritabilities for MU were low to moderate (0.22, 0.18, and 0.24 for the Holstein, Jersey, and Red breeds, respectively). The genetic correlation was close to zero between MU and milk yield in Jersey and Red, and -0.14 for Holstein. The genetic correlations between MU and fat and protein percentages, respectively, were positive for all 3 dairy breeds. Herd-test-day explained 51%, 54%, and 49% of the variation in MU in Holstein, Jersey, and Red, respectively. This indicates that MU levels in milk can be reduced by farm management. The current study shows that there are possibilities to influence MU by genetic selection as well as by farm management., (© 2023, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Osteopontin (OPN) is a multifunctional protein abundantly present in human milk, whereas the concentration is significantly lower in bovine milk. Human and bovine milk OPN are structurally similar and both proteins resist gastric digestion and reach the intestines in a bioactive form. Intervention studies have indicated the beneficial effects of supplementing infant formula with bovine milk OPN and several in vivo and in vitro studies have shown that bovine milk OPN positively influences intestinal development. To investigate the functional relationship, we compared the effect of simulated gastrointestinal digested human and bovine milk OPN on gene expression in Caco-2 cells. After incubation, total RNA was extracted and sequenced and transcripts were mapped to the human genome. Human and bovine milk OPN regulated the expression of 239 and 322 genes, respectively. A total of 131 genes were similarly regulated by the OPNs. As a control, a whey protein fraction with a high content of alpha-lactalbumin had a very limited transcriptional impact on the cells. Enrichment data analysis showed that biological processes related to the ubiquitin system, DNA binding, and genes associated with transcription and transcription control pathways were affected by the OPNs. Collectively, this study shows that human and bovine milk OPN have a significant and highly comparable effect on the intestinal transcriptome.

Background: Milk yield and fine composition in sheep depend on the volatile and long-chain fatty acids, microbial proteins, vitamins produced through feedstuff digestion by the rumen microbiota. In cattle, the host genome has been shown to have a low to moderate genetic control on rumen microbiota abundance but a high control on dairy traits with heritabilities higher than 0.30. There is little information on the genetic correlations and quantitative trait loci (QTL) that simultaneously affect rumen microbiota abundance and dairy traits in ruminants, especially in sheep. Thus, our aim was to quantify the effect of the host genetics on rumen bacterial abundance and the genetic correlations between rumen bacterial abundance and several dairy traits, and to identify QTL that are associated with both rumen bacterial abundance and milk traits., Results: Our results in Lacaune sheep show that the heritability of rumen bacterial abundance ranges from 0 to 0.29 and that the heritability of 306 operational taxonomic units (OTU) is significantly different from 0. Of these 306 OTU, 96 that belong mainly to the Prevotellaceae, Lachnospiraceae and Ruminococcaceae bacterial families show strong genetic correlations with milk fatty acids and proteins (absolute values ranging from 0.33 to 0.99). Genome-wide association studies revealed a QTL for alpha-lactalbumin concentration in milk on Ovis aries chromosome (OAR) 11, and six QTL for rumen bacterial abundances i.e., for two OTU belonging to the genera Prevotella (OAR3 and 5), Rikeneleaceae_RC9_gut_group (OAR5), Ruminococcus (OAR5), an unknown genus of order Clostridia UCG-014 (OAR10), and CAG-352 (OAR11). None of these detected regions are simultaneously associated with rumen bacterial abundance and dairy traits, but the bacterial families Prevotellaceae, Lachnospiraceae and F082 show colocalized signals on OAR3, 5, 15 and 26., Conclusions: In Lacaune dairy sheep, rumen microbiota abundance is partially controlled by the host genetics and is poorly genetically linked with milk protein and fatty acid compositions, and three main bacterial families, Prevotellaceae, Lachnospiraceae and F082, show specific associations with OAR3, 5, 15 and 26., (© 2022. The Author(s).)

Many dairy herds use automatic milking stations (AMS), with cows in large herds often having access to 2 or more AMS, and must choose between them when they go for milking. Individual cows acquire routines of either consistently using a specific milking box or consistently using any available milking box. Here, we hypothesized that the degree of use of the same milking box was an expression of preference, and quantified it as preference consistency score (PCS). The PCS was calculated as a ratio between the excess frequencies of the first choice over the base frequency of "not first choice" over 15-d segments of lactation. This ratio was 0 if all choices were taken equally, and became 1.0 if only the first choice was taken in all events. We investigated the consistency of milking box preference in 2 cohorts (one Holstein and one Jersey) across 6 commercial dairy herds in Denmark (n = 4,665 cows total). In addition to PCS, we recorded and analyzed associated milking and behavior traits, including a time profile index showing use of specific clock hours when cows were milked (Time_profile, based on excess use of specific clock hours), milking frequency, time spent in the milking box, and milk yield. Records from each milking event were condensed into 15-d segments based on days in milk. The data were analyzed using a linear mixed model, with random genetic and individual cow effects, to estimate heritability (h 2 ), repeatability (t), and individual level correlations (r i ) between traits. The average PCS was 0.43 and 0.41 in Holstein and Jersey, respectively, showing that cows developed routines for consistently using the same milking box; however, some cows had lower preference (i.e., greater flexibility in use). The Time_profile indicated that some cows were milked in a few hour-bins, whereas others were more flexible. The PCS and Time_profile traits had low heritability (h 2 , PCS/Time_profile = 0.07 ± 0.02/0.11 ± 0.02 Holstein, 0.13 ± 0.03/0.04 ± 0.02 Jersey) and moderate repeatability (t, PCS/Time_profile = 0.47/0.40 Holstein, 0.50/0.42 Jersey). The 2 traits were weakly correlated with each other (r i = 0.18 and 0.17), and were weakly correlated with milk yield (r i range: 0.0 to -0.10). However, the time profile was strongly correlated with milking frequency (r i range: -0.81 to -0.73), and was moderately correlated with daily box time (r i range: -0.43 to -0.35). In general, Holstein and Jersey parameter estimates were of similar size, and thus in good agreement. Overall, individual cows covered a broad spectrum of preference consistency, both regarding the use of specific milking boxes and time profiles, with these 2 traits representing different aspects or dimensions of milking behavior. The findings that some cows have strong preferences for specific AMS may be most useful in herd management and farm design. The weak correlation to milk yield indicated that yield minimally affected these 2 milking associated behavior traits. In conclusion, although the traits were repeatable, heritability was low; thus, genetic selection for milk yield might minimally affect these 2 traits., (© 2022, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

A group of milk components that has shown potential to be predicted with milk spectra is milk minerals. Milk minerals are important for human health and cow health. Having an inexpensive and fast way to measure milk mineral concentrations would open doors for research, herd management, and selective breeding. The first aim of this study was to predict milk minerals with infrared milk spectra. Additionally, milk minerals were predicted with infrared-predicted fat, protein, and lactose content. The second aim was to perform a genetic analysis on infrared-predicted milk minerals, to identify QTL, and estimate variance components. For training and validating a multibreed prediction model for individual milk minerals, 264 Danish Jersey cows and 254 Danish Holstein cows were used. Partial least square regression prediction models were built for Ca, Cu, Fe, K, Mg, Mn, Na, P, Se, and Zn based on 80% of the cows, selected randomly. Prediction models were externally validated with 8 herds based on the remaining 20% of the cows. The prediction models were applied on a population of approximately 1,400 Danish Holstein cows with 5,600 infrared spectral records and 1,700 Danish Jersey cows with 7,200 infrared spectral records. Cows from this population had 50k imputed genotypes. Prediction accuracy was good for P and Ca, with external R 2 ≥ 0.80 and a relative prediction error of 5.4% for P and 6.3% for Ca. Prediction was moderately good for Na with an external R 2 of 0.63, and a relative error of 18.8%. Prediction accuracies of milk minerals based on infrared-predicted fat, protein, and lactose content were considerably lower than those based on the infrared milk spectra. This shows that the milk infrared spectrum contains valuable information on milk minerals, which is currently not used. Heritability for infrared-predicted Ca, Na, and P varied from low (0.13) to moderate (0.36). Several QTL for infrared-predicted milk minerals were observed that have been associated with gold standard milk minerals previously. In conclusion, this study has shown infrared milk spectra were good at predicting Ca, Na, and P in milk. Infrared-predicted Ca, Na, and P had low to moderate heritability estimates., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Our objective was to determine the content of the bioactive protein osteopontin (OPN) in bovine milk and identify factors influencing its concentration. OPN is expressed in many tissues and body fluids, with by far the highest concentrations in milk. OPN plays a role in immunological and developmental processes and it has been associated with several milk production traits and lactation persistency in cows. In the present study, we report the development of an enzyme linked immunosorbent assay (ELISA) for measurement of OPN in bovine milk. The method was used to determine the concentration of OPN in milk from 661 individual Danish Holstein cows. The median OPN level was determined to 21.9 mg/l with a pronounced level of individual variation ranging from 0.4 mg/l to 67.8 mg/l. Breeding for increased OPN in cow's milk is of significant interest, however, the heritability of OPN in milk was found to be relatively low, with an estimated value of 0.19 in the current dataset. The variation explained by the herd was also found to be low suggesting that OPN levels are not affected by farm management or feeding. Interestingly, the concentration of OPN was found to increase with days in milk and to decrease with parity.

Background: Studies suggest that indomethacin (Indo) exhibits detrimental changes in the small intestine (microvascular disorder, villus shortening, and epithelial disruption), mainly due to mitochondrial uncoupling. The effects of Indo on colon and liver tissue are unclear. The aim of this study was to determine the effects of Indo on mitochondrial respiration in colonic and hepatic tissue. Methods: Mitochondrial oxygen consumption was assessed in colon and liver homogenates from healthy rats. Homogenates were incubated without drug (control) or Indo (colon: 0.36, 1, 30, 179, 300, 1,000, 3,000 μM; liver: 0.36, 1, 3, 10, 30, 100, 179 μM; n = 6). State 2 (substrate-dependent) and state 3 (ADP-dependent respiration) were evaluated with respirometry. The respiratory control index (RCI) was derived and the ADP/O ratio was calculated. Statistics: Data presented as % of control, min/median/max, Kruskal-Wallis+Dunn's correction, * p < 0.05 vs. control. Results: Indo had no effect on RCI of colonic mitochondria. ADP/O ratio increased in complex I at concentrations of 1,000 and 3,000 μM (Indo 1,000 μM: 113.9/158.9/166.9% * ; Indo 3,000 μM: 151.5/183.0/361.5% * ) and in complex II at concentrations of 179 and 3,000 μM vs. control (179 μM: 111.3/73.1/74.9% * ; 3,000 μM: 132.4/175.0/339.4% * ). In hepatic mitochondria RCI decreased at 179 μM for both complexes vs. control (complex I: 25.6/40.7/62.9% * , complex II: 57.0/73.1/74.9% * ). The ADP/O ratio was only altered in complex I at a concentration of 179 μM Indo vs. control (Indo 179 μM: 589.9/993.7/1195.0 % * ). Conclusion: Indo affected parameters of mitochondrial function in an organ-specific and concentration-dependent manner. In colonic tissue, RCI remained unaltered whereas the ADP/O ratio increased. Indo at the highest concentration decreased the RCI for both complexes in hepatic mitochondria. The large increase in ADP/O ratio in complex I at the highest concentration likely reflects terminal uncoupling., (Copyright © 2020 Herminghaus, Buitenhuis, Schulz, Truse, Vollmer, Relja, Bauer and Picker.)

Fourier transform infrared spectral analysis is a cheap and fast method to predict milk composition. A not very well studied milk component is orotic acid. Orotic acid is an intermediate in the biosynthesis pathway of pyrimidine nucleotides and is an indicator for the metabolic cattle disorder deficiency of uridine monophosphate synthase. The function of orotic acid in milk and its effect on calf health, health of humans consuming milk or milk products, manufacturing properties of milk, and its potential as an indicator trait are largely unknown. The aims of this study were to determine if milk orotic acid can be predicted from infrared milk spectra and to perform a large-scale phenotypic and genetic analysis of infrared-predicted milk orotic acid. An infrared prediction model for orotic acid was built using a training population of 292 Danish Holstein and 299 Danish Jersey cows, and a validation population of 381 Danish Holstein cows. Milk orotic acid concentration was determined with nuclear magnetic resonance spectroscopy. For genetic analysis of infrared orotic acid, 3 study populations were used: 3,210 Danish Holstein cows, 3,360 Danish Jersey cows, and 1,349 Dutch Holstein Friesian cows. Using partial least square regression, a prediction model for orotic acid was built with 18 latent variables. The error of the prediction for the infrared model varied from 1.0 to 3.2 mg/L, and the accuracy varied from 0.68 to 0.86. Heritability of infrared orotic acid predicted with the standardized prediction model was 0.18 for Danish Holstein, 0.09 for Danish Jersey, and 0.37 for Dutch Holstein Friesian. We conclude that milk orotic acid can be predicted with moderate to good accuracy based on infrared milk spectra and that infrared-predicted orotic acid is heritable. The availability of a cheap and fast method to predict milk orotic acid opens up possibilities to study the largely unknown functions of milk orotic acid., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Prediction of detailed milk fatty acid (FA) composition by mid-infrared spectroscopy (MIRS) offers possibilities for high-throughput indirect measurements of detailed milk compositional parameters through the milk testing system, which can be used to differentiate the FA profile by genetics or specific management or on dairies for milk quality evaluation. Since 2015, milk samples from all Danish dairy cows under milk testing have been recorded using MIRS. The MIRS software from the FOSS Application Note 64 was used to predict contents of 7 FA groups and 4 individual FA. Data generated from the application note have been used to estimate breeding values for sires for percentage of saturated fat (SFA%) in milk. To investigate whether extreme SFA% breeding values of sires were reflected in the detailed milk FA profile from their daughters, milk samples from 194 cows in 7 organic herds were collected and the detailed FA composition measured by gas chromatography. From each cow, milk samples were collected twice to explore specific seasonal effects of pasture-based diets in relation to sires' estimated breeding value (EBV) for MIRS-predicted SFA% (MIRS-SFA%). The results showed a significant difference in SFA% measured from GC (GC-SFA%) in milk from daughters of sires having high SFA% EBV compared with daughters of sires having low SFA% EBV. The EBV group (low or high) also significantly affected most FA except C13:0, C15:0, C17:0, and C18:1 trans-11. Contents of SFA with even chain-lengths were all higher in the high EBV group, whereas C14:1, C16:1, and the other unsaturated C18 FA had a higher content in the low EBV group. All FA were significantly affected by season. The SFA% decreased from indoor spring feeding to summer pasture, as did FA with chain length ≤16 carbons, whereas long-chain FA (>C17) all increased during summer pasture. The results show that use of MIRS-predicted EBV for SFA% will most likely display a correlated response on the detailed FA composition in milk. In the current study, the combined action of feeding and genetics resulted in a 10 percentage-point difference on average when comparing milk SFA% from daughters of high SFA% EBV sires during indoor spring feeding from one farm to milk SFA% from daughters of low SFA% EBV sires during summer from another farm., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Background: Infrared spectral analysis of milk is cheap, fast, and accurate. Infrared light interacts with chemical bonds present inside the milk, which means that Fourier transform infrared milk spectra are a reflection of the chemical composition of milk. Heritability of Fourier transform infrared milk spectra has been analysed previously. Further genetic analysis of Fourier transform infrared milk spectra could give us a better insight in the genes underlying milk composition. Breed influences milk composition, yet not much is known about the effect of breed on Fourier transform infrared milk spectra. Improved understanding of the effect of breed on Fourier transform infrared milk spectra could enhance efficient application of Fourier transform infrared milk spectra. The aim of this study is to perform a genome wide association study on a selection of wavenumbers for Danish Holstein and Danish Jersey. This will improve our understanding of the genetics underlying milk composition in these two dairy cattle breeds., Results: For each breed separately, fifteen wavenumbers were analysed. Overall, more quantitative trait loci were observed for Danish Jersey compared to Danish Holstein. For both breeds, the majority of the wavenumbers was most strongly associated to a genomic region on BTA 14 harbouring DGAT1. Furthermore, for both breeds most quantitative trait loci were observed for wavenumbers that interact with the chemical bond C-O. For Danish Jersey, wavenumbers that interact with C-H were associated to genes that are involved in fatty acid synthesis, such as AGPAT3, AGPAT6, PPARGC1A, SREBF1, and FADS1. For wavenumbers which interact with -OH, associations were observed to genomic regions that have been linked to alpha-lactalbumin., Conclusions: The current study identified many quantitative trait loci that underlie Fourier transform infrared milk spectra, and thus milk composition. Differences were observed between groups of wavenumbers that interact with different chemical bonds. Both overlapping and different QTL were observed for Danish Holstein and Danish Jersey.

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., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

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 CH 4 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 CH 4 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 CH 4 and CO 2 concentrations (ppm) using a noninvasive "sniffer" method. Raw enteric CH 4 and CO 2 concentrations and their ratio (CH 4 :CO 2 ) 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 CH 4 and CO 2 gas concentrations. Bivariate repeatability estimates for average CH 4 and CO 2 concentrations and CH 4 :CO 2 were 0.77 to 0.78, 0.73 to 0.80, and 0.26, respectively. Repeatability for CH 4 :CO 2 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 CH 4 and CO 2 concentrations and CH 4 :CO 2 . We found no evidence that separate evaluation is needed to quantify enteric CH 4 and CO 2 emissions from Jersey cows during in-barn and grazing periods., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Evidence suggests that propofol infusion syndrome (PRIS) is caused by an altered mitochondrial function. The aim of this study was to examine the effects of propofol and the vehicle MCT on mitochondrial function in hepatic and colonic tissue. Mitochondrial oxygen consumption was determined in colon and liver homogenates after incubation with buffer (control), propofol (50, 75, 100, 500  μM) or the carrier substances DMSO and MCT. State 2 (substrate-dependent) and state 3 (ADP-dependent respiration) were assessed. RCI (respiratory control index) - an indicator for coupling between electron transport chain system (ETS) and oxidative phosphorylation (OXPHOS) and ADP/O ratio - a parameter for efficacy of OXPHOS were calculated. Data were presented as % of control. In hepatic mitochondria, 500  μM propofol reduced RCI formulation-independently (propofol/MCT 500 μM: complex I: 66.3 ± 8.7%*, complex II: 75.5 ± 9.2%*; propofol/DMSO 500 μM: complex I: 29.1 ± 8.8%*, complex II: 49.3 ± 15.5%*). 75  μM Propofol/MCT reduced ADP/O for complex I (73.5 ± 27.3%*). DMSO did not affect hepatic mitochondria whereas MCT reduced RCI for complex II (87.2 ± 9.8%*) and ADP/O for complex I (93.7 ± 31.7%*). In colon 50  μM Propofol/MCT increased RCI for complex I and II (complex I: 127.2 ± 10.7%*, complex II: 136.8 ± 33.9%*) and 100  μM Propofol/MCT for complex I (131.4 ± 18.7%*). 500  μM Propofol/DMSO increased ADP/O for complex I (139.4 ± 41.4%*). DMSO did not affect RCI but increased ADP/O for both complexes (complex I: 119.9 ± 25.8%*, complex II: 110.2 ± 14.2%*). MCT increased RCI for complex I (123.0 ± 31.6%*). In hepatic mitochondria propofol uncoupled ETS from OXPHOS formulation-independently and propofol/MCT reduced efficacy of OXPHOS. In colonic mitochondria, propofol/MCT strengthened the coupling and propofol/DMSO enhanced the efficacy of OXPHOS., (Copyright © 2019. Published by Elsevier B.V.)

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.

Fourier transform infrared milk spectral data are routinely used for milk quality control and have been revealed to be driven by genetics. This study aimed to (1) estimate heritability for 1,060 wavenumbers in the infrared region from 5,008 to 925 cm -1 , (2) estimate genomic correlations between wavenumbers with increased heritability, and (3) compare results between Danish Holstein and Danish Jersey cows. For Danish Holstein, 3,275 cows and 19,656 milk records were available. For Danish Jersey, 3,408 cows and 20,228 milk records were available. We used a hierarchical mixed model, with a Bayesian approach. Heritability of individual wavenumbers ranged from 0.00 to 0.31 in Danish Holstein, and from 0.00 to 0.30 in Danish Jersey. Genomic correlation was calculated between 15 selected wavenumbers, and varied from weak to very strong, in both Danish Holstein and Danish Jersey (0.03 to 0.97, and -0.11 to -0.97). Within the 15 selected wavenumbers, a subdivision into 2 groups of wavenumbers was observed, where genomic correlations were negative between groups, and positive within groups. Heritability and genomic correlations were higher in Danish Holstein compared with Danish Jersey, but followed a similar pattern in both breeds. Breed differences were most pronounced in the mid-infrared region that interacts with lactose and the spectral region that interacts with protein. In conclusion, heritability for individual wavenumbers of Fourier transform milk spectra was moderate, and strong genomic correlations were observed between wavenumbers across the spectrum. Heritability and genomic correlations were higher in Danish Holstein, with the strongest breed differences showing in spectral regions interacting with protein or lactose., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Viral hemorrhagic septicemia virus (VHSV), a rhabdovirus infecting teleost fish, has repeatedly crossed the boundary from marine fish species to freshwater cultured rainbow trout. These naturally replicated cross-species transmission events permit the study of general and repeatable evolutionary events occurring in connection with viral emergence in a novel host species. The purpose of the present study was to investigate the adaptive molecular evolution of the VHSV glycoprotein, one of the key virus proteins involved in viral emergence, following emergence from marine species into freshwater cultured rainbow trout. A comprehensive phylogenetic reconstruction of the complete coding region of the VHSV glycoprotein was conducted, and adaptive molecular evolution was investigated using a maximum likelihood approach to compare different codon substitution models allowing for heterogeneous substitution rate ratios among amino acid sites. Evidence of positive selection was detected at six amino acid sites of the VHSV glycoprotein, within the signal peptide, the confirmation-dependent major neutralizing epitope, and the intracellular tail. Evidence of positive selection was found exclusively in rainbow trout-adapted virus isolates, and amino acid combinations found at the six sites under positive selection pressure differentiated rainbow trout- from non-rainbow trout-adapted isolates. Furthermore, four adaptive sites revealed signs of recurring identical changes across phylogenetic groups of rainbow trout-adapted isolates, suggesting that repeated VHSV emergence in freshwater cultured rainbow trout was established through convergent routes of evolution that are associated with immune escape. IMPORTANCE This study is the first to demonstrate that VHSV emergence from marine species into freshwater cultured rainbow trout has been accompanied by bursts of adaptive evolution in the VHSV glycoprotein. Furthermore, repeated detection of the same adaptive amino acid sites across phylogenetic groups of rainbow trout-adapted isolates indicates that adaptation to rainbow trout was established through parallel evolution. In addition, signals of convergent evolution toward the maintenance of genetic variation were detected in the conformation-dependent neutralizing epitope or in close proximity to disulfide bonds involved in the structural conformation of the neutralizing epitope, indicating adaptation to immune response-related genetic variation across freshwater cultured rainbow trout., (Copyright © 2018 American Society for Microbiology.)

The objective of this study was to assess the genetic variability of the detailed fatty acid (FA) profiles of Danish Holstein (DH) and Danish Jersey (DJ) cattle populations. We estimated genetic parameters for 11 FA or groups of FA in milk samples from the Danish milk control system between May 2015 and October 2016. Concentrations of different FA and FA groups in milk samples were measured by mid-infrared spectroscopy. Data used for parameter estimation were from 132,732 first-parity DH cows and 21,966 first-parity DJ cows. We found the highest heritabilities for test day measurements in both populations for short-chain FA (DH = 0.16; DJ = 0.16) and C16:0 (DH = 0.14; DJ = 0.16). In DH, the highest heritabilities were also found for saturated FA and monounsaturated FA (both populations: 0.15). Genetic correlations between the fatty acid traits showed large differences between DH and DJ for especially short-chain FA with the other FA traits measured. Furthermore, genetic correlations of total fat with monounsaturated FA, polyunsaturated FA, short-chain FA, and C16:0 differed markedly between DH and DJ populations. In conclusion, we found genetic variation in the mid-infrared spectroscopy-predicted FA and FA groups of the DH and DJ cattle populations. This finding opens the possibility of using genetic selection to change the FA profiles of dairy cattle., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).)

Enteric methane (CH 4 ), a potent greenhouse gas, is among the main targets of mitigation practices for the dairy industry. A measurement technique that is rapid, inexpensive, easy to use, and applicable at the population level is desired to estimate CH 4 emission from dairy cows. In the present study, feasibility of milk Fourier transform mid-infrared (FT-IR) spectral profiles as a predictor for CH 4 :CO 2 ratio and CH 4 production (L/d) is explained. The partial least squares regression method was used to develop the prediction models. The models were validated using different random test sets, which are independent from the training set by leaving out records of 20% cows for validation and keeping records of 80% of cows for training the model. The data set consisted of 3,623 records from 500 Danish Holstein cows from both experimental and commercial farms. For both CH 4 :CO 2 ratio and CH 4 production, low prediction accuracies were found when models were obtained using FT-IR spectra. Validated coefficient of determination (R 2 Val ) = 0.21 with validated model error root mean squared error of prediction (RMSEP) = 0.0114 L/d for CH 4 :CO 2 ratio, and R 2 Val = 0.13 with RMSEP = 111 L/d for CH 4 production. The important spectral wavenumbers selected using the recursive partial least squares method represented major milk components fat, protein, and lactose regions of the spectra. When fat and protein predicted by FT-IR were used instead of full spectra, a low R 2 Val of 0.07 was obtained for both CH 4 :CO 2 ratio and CH 4 production prediction. Other spectral wavenumbers related to lactose (carbohydrate) or additional wavenumbers related to fat or protein (amide II) are providing additional variation when using the full spectral profile. For CH 4 :CO 2 ratio prediction, integration of FT-IR with other factors such as milk yield, herd, and lactation stage showed improvement in the prediction accuracy. However, overall prediction accuracy remained modest; R 2 Val increased to 0.31 with RMSEP = 0.0105. For prediction of CH 4 production, the added value of FT-IR along with the aforementioned traits was marginal. These results indicated that for CH 4 production prediction, FT-IR profiles reflect primarily information related to milk yield, herd, and lactation stage rather than individual milk fatty acids related to CH 4 emission. Thus, it is not feasible to predict CH 4 emission based on FT-IR spectra alone., (The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).)

The present study explored the effectiveness of Fourier transform mid-infrared (FT-IR) spectral profiles as a predictor for dry matter intake (DMI) and residual feed intake (RFI). The partial least squares regression method was used to develop the prediction models. The models were validated using different external test sets, one randomly leaving out 20% of the records (validation A), the second randomly leaving out 20% of cows (validation B), and a third (for DMI prediction models) randomly leaving out one cow (validation C). The data included 1,044 records from 140 cows; 97 were Danish Holstein and 43 Danish Jersey. Results showed better accuracies for validation A compared with other validation methods. Milk yield (MY) contributed largely to DMI prediction; MY explained 59% of the variation and the validated model error root mean square error of prediction (RMSEP) was 2.24kg. The model was improved by adding live weight (LW) as an additional predictor trait, where the accuracy R 2 increased from 0.59 to 0.72 and error RMSEP decreased from 2.24 to 1.83kg. When only the milk FT-IR spectral profile was used in DMI prediction, a lower prediction ability was obtained, with R 2 =0.30 and RMSEP=2.91kg. However, once the spectral information was added, along with MY and LW as predictors, model accuracy improved and R 2 increased to 0.81 and RMSEP decreased to 1.49kg. Prediction accuracies of RFI changed throughout lactation. The RFI prediction model for the early-lactation stage was better compared with across lactation or mid- and late-lactation stages, with R 2 =0.46 and RMSEP=1.70. The most important spectral wavenumbers that contributed to DMI and RFI prediction models included fat, protein, and lactose peaks. Comparable prediction results were obtained when using infrared-predicted fat, protein, and lactose instead of full spectra, indicating that FT-IR spectral data do not add significant new information to improve DMI and RFI prediction models. Therefore, in practice, if full FT-IR spectral data are not stored, it is possible to achieve similar DMI or RFI prediction results based on standard milk control data. For DMI, the milk fat region was responsible for the major variation in milk spectra; for RFI, the major variation in milk spectra was within the milk protein region., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

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, β-CN, κ-CN, α-lactalbumin, and β-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 β-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., (Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Rennet-induced milk coagulation is an important trait for cheese production. Recent studies have reported an alarming frequency of cows producing poorly coagulating milk unsuitable for cheese production. Several genetic factors are known to affect milk coagulation, including variation in the major milk proteins; however, recent association studies indicate genetic effects from other genomic regions as well. The aim of this study was to detect genetic variation affecting milk coagulation properties, measured as curd-firming rate (CFR) and milk pH. This was achieved by examining allele frequency differences between pooled whole-genome sequences of phenotypically extreme samples (pool-seq).. Curd-firming rate and raw milk pH were measured for 415 Danish Holstein cows, and each animal was sequenced at low coverage. Pools were created containing whole genome sequence reads from samples with "extreme" values (high or low) for both phenotypic traits. A total of 6,992,186 and 5,295,501 SNP were assessed in relation to CFR and milk pH, respectively. Allele frequency differences were calculated between pools and 32 significantly different SNP were detected, 1 for milk pH and 31 for CFR, of which 19 are located on chromosome 6. A total of 9 significant SNP, which were selected based on the possible function of proximal candidate genes, were genotyped in the entire sample set ( = 415) to test for an association. The most significant SNP was located proximal to , explaining 33% of the phenotypic variance. , coding for κ-casein, is the most studied in relation to milk coagulation due to its position on the surface of the casein micelles and the direct involvement in milk coagulation. Three additional SNP located on chromosome 6 showed significant associations explaining 7, 3.6, and 1.3% of the phenotypic variance of CFR. The significant SNP on chromosome 6 were shown to be in linkage disequilibrium with the SNP peaking proximal to ; however, after accounting for the genotype of the peak SNP within this QTL, significant effects (-value < 0.1) could still be detected for 2 of the SNP accounting for 2 and 1% of the phenotypic variance. These 2 interesting SNP were located within introns or proximal to the candidate genes-solute carrier family 4 (sodium bicarbonate cotransporter), member 4 () and LIM and calponin homology domains 1 (), respectively-making them interesting targets for further analysis.

Several studies have described associations between the diacylglycerol o-acyltransferase 1 (DGAT1) K232A polymorphism and routinely collected milk production traits but not much is known about effects of the DGAT1 polymorphism on detailed milk composition. The aim of this study was to estimate effects of the DGAT1 polymorphism on milk fatty acid, protein, and mineral composition. We looked for effects that were significant and consistent in Danish Holstein Friesian (HF), Danish Jersey, and Dutch HF as these are likely to be true effects of the DGAT1 K232A polymorphism rather than being effects of linked loci. For fatty acid composition, significant and consistent effects of the DGAT1 polymorphism were detected on C14:0, C16:0, C15:0, C16:1, C18:1 cis-9, conjugated linoleic acid (CLA) cis-9,trans-11, C18:2 cis-9,cis-12, and C18:3 cis-9,cis-12,cis-15 content (percent by weight, wt/wt %). For C16:0, C16:1, and C18:1 cis-9, the DGAT1 polymorphism explained more than 10% of the phenotypic variation. Significant effects on milk protein composition in Dutch HF could not be confirmed in Danish Jersey or Danish HF. For mineral content, significant and consistent effects of the DGAT1 polymorphism on calcium, phosphorus, and zinc were detected. In the Dutch HF population, the contribution of the DGAT1 K232A polymorphism to phenotypic variance was 12.0% for calcium, 8.3% for phosphorus, and 6.1% for zinc. Different from effects on fatty acid composition, effects of the DGAT1 polymorphism on yields of long-chain fatty acids C18:1 cis-9, CLA cis-9,trans-11, C18:2 cis-9,cis-12, and C18:3 cis-9,cis-12,cis-15 were not significant. This indicates that effects of DGAT1 on these fatty acids are indirect, not direct, effects: DGAT1 affects de novo synthesis of fatty acids and, consequently, the contribution of the long-chain fatty acids to total fat is decreased. In addition, effects of the DGAT1 polymorphism on yields of Ca, P, and Zn were not significant, which indicates that effects on these minerals are the result of indirect rather than direct effects of DGAT1: effects on calcium, phosphorus, and zinc content can be explained by effects of DGAT1 on milk volume. The reported effects of the DGAT1 polymorphism on fatty acid and mineral composition of milk are substantial and therefore relevant for milk quality., (Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The identification of causal genes or genomic regions associated with fatty acids (FA) will enhance our understanding of the pathways underlying FA synthesis and provide opportunities for changing milk fat composition through a genetic approach. The linkage disequilibrium between adjacent markers is highly consistent between the Chinese and Danish Holstein populations, such that a joint genome-wide association study (GWAS) can be performed. In this study, a joint GWAS was performed for 16 milk FA traits based on data of 784 Chinese and 371 Danish Holstein cows genotyped by a high-density bovine single nucleotide polymorphism (SNP) array. A total of 486,464 SNP markers on 29 bovine autosomes were used. Bonferroni corrections were applied to adjust the significance thresholds for multiple testing at the genome- and chromosome-wide levels. According to the analysis of either the Chinese or Danish data individually, the total numbers of overlapping SNP that were significant at the chromosome level were 94 for C14:1, 208 for the C14 index, and 1 for C18:0. Joint analysis using the combined data of the 2 populations detected greater numbers of significant SNP compared with either of the individual populations alone for 7 and 10 traits at the genome- and chromosome-wide significance levels, respectively. Greater numbers of significant SNP were detected for C18:0 and the C18 index in the Chinese population compared with the joint analysis. Sixty-five significant SNP across all traits had significantly different effects in the 2 populations. Ten FA were influenced by a quantitative trait loci (QTL) region including DGAT1. Both C14:1 and the C14 index were influenced by a QTL region including SCD1 in the combined population. Other QTL regions also showed significant associations with the studied FA. A large region (14.9-24.9 Mbp) in BTA26 significantly influenced C14:1 and the C14 index in both populations, mostly likely due to the SNP in SCD1. A QTL region (69.97-73.69 Mbp) on BTA9 showed a significantly different effect on C18:0 between the 2 populations. Detection of these important SNP and the corresponding QTL regions will be helpful for follow-up studies to identify causal mutations and their interaction with environments for milk FA in dairy cattle., (Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Several studies have shown that the diacylglycerol O-acyltransferase 1 (DGAT1) K232A polymorphism has a major effect on milk production traits. It is less clear how effects of DGAT1 on milk production traits change throughout lactation, if dominance effects of DGAT1 are relevant, and whether DGAT1 also affects lactose content, lactose yield, and total energy output in milk. Results from this study, using test-day records of 3 subsequent parities of around 1,800 cows, confirm previously reported effects of the DGAT1 polymorphism on milk, fat, and protein yield, as well as fat and protein content. In addition, we found significant effects of the DGAT1 polymorphism on lactose content and lactose yield. No significant effects on somatic cell score were detected. The effect of DGAT1 on total energy excreted in milk was only significant in parity 1 and is mainly due to a higher energy output in milk of heterozygous cows. Significant but relatively small dominance effects of DGAT1 on fat content and yield were detected, which are of little practical relevance. Significant DGAT1 by lactation stage interaction was detected for milk yield, lactose yield, fat content, and protein content, indicating that the effect of the DGAT1 polymorphism changes during lactation. In general, the DGAT1 effect shows a large increase during early lactation (from the start of lactation to d 50 to 150) and tends to decrease later in lactation. No DGAT1 by lactation stage interaction for fat yield was observed. Similar to DGAT1, effects of other genes also might vary throughout lactation and, therefore, using longitudinal models is recommended., (Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Riboflavin (vitamin B2) is an essential water-soluble vitamin; elderly people and adolescents in particular can have poor riboflavin status. In Western diets, milk and dairy products are primary sources of riboflavin, but little is known about the natural variation within and among bovine breeds, and how genetic and environmental factors can affect the riboflavin content in milk. As a part of the Danish-Swedish Milk Genomics Initiative, the aim of the study was to quantify milk riboflavin content using reverse-phase HPLC in 2 major Danish dairy breeds. The results showed substantial interbreed differences in milk riboflavin content. Milk from Danish Jersey cows contained significantly higher levels of riboflavin (1.93mg/L of milk) than milk from Danish Holstein cows (1.40mg/L of milk). Furthermore, genetic analyses revealed high heritabilities in both breeds (0.52 for Danish Holstein and 0.31 for Danish Jersey). A genomic association study found 35 significant single nucleotide polymorphisms (false discovery rate<0.10) to be associated with riboflavin content in milk in Jersey cows (all on BTA14 and BTA17), and 511 significant single nucleotide polymorphisms in Holstein cows spread over 25 different autosomes with BTA13 and BTA14 having the most promising quantitative trait loci. The best candidate gene found within the identified quantitative trait loci was SLC52A3, a riboflavin transporter gene, which was among the significant markers on BTA13 in Holstein cows., (Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The aim of this study was to examine milk composition and rennet-induced coagulation properties of milk from 892 individual Danish Holstein and Danish Jersey cows and determine the genetic influences on these properties by determining heritability and genomic correlations with single nucleotide polymorphisms identified by the bovine HD Beadchip (Illumina Inc., San Diego, CA). Despite no signs of clinical mastitis, milk from cows with somatic cell counts >500,000 cells/mL showed altered milk composition, indicating impaired barrier between the milk and the blood. Curd-firming rate (CFR) and rennet coagulation time (RCT) were used to describe milk coagulation properties (MCP). These traits describe the second phase of milk coagulation and were mutually negatively correlated, but only to some extent associated with the same compositional traits. In both breeds, CFR were highly correlated with protein content, whereas longer RCT were primarily associated with lower milk pH. Estimated heritabilities for milk production and compositional traits ranged from 0.09 for yield to 0.82 for citric acid in Danish Jersey cows, and from 0.21 for yield to 0.59 for citric acid in Danish Holstein cows. Heritabilities for MCP traits varied considerably between breeds, and were estimated to be 0.28 for RCT and 0.75 for CFR in Danish Holstein cows and 0.45 for RCT and 0.15 for CFR in Danish Jersey cows. This difference was further reflected in the genomic correlations between RCT and CFR which was -0.90 in Danish Holstein and 0.06 in Danish Jersey. These data suggest that potential for changing MCP through breeding exists, but the genetic background of the MCP traits might be different in different breeds; therefore, using Danish Holstein as background for Danish Jersey is not trivial. Thereby, the study underlines the need for breed-specific models., (Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

In selecting cows for higher milk yields and milk quality, it is important to understand how these traits are affected by the bovine genome. The major milk proteins exhibit genetic polymorphism and these genetic variants can serve as markers for milk composition, milk production traits, and technological properties of milk. The aim of this study was to investigate the relationships between casein (CN) genetic variants and detailed protein composition in Swedish and Danish dairy milk. Milk and DNA samples were collected from approximately 400 individual cows each of 3 Scandinavian dairy breeds: Swedish Red (SR), Danish Holstein (DH), and Danish Jersey (DJ). The protein profile with relative concentrations of α-lactalbumin, β-lactoglobulin, and α(S1)-, α(S2)-, κ-, and β-CN was determined for each milk sample using capillary zone electrophoresis. The genetic variants of the α(S1)- (CSN1S1), β- (CSN2), and κ-CN (CSN3) genes for each cow were determined using TaqMan SNP genotyping assays (Applied Biosystems, Foster City, CA). Univariate statistical models were used to evaluate the effects of composite genetic variants, α(S1)-β-κ-CN, on the protein profile. The 3 studied Scandinavian breeds differed from each other regarding CN genotypes, with DH and SR having similar genotype frequencies, whereas the genotype frequencies in DJ differed from the other 2 breeds. The similarities in genotype frequencies of SR and DH and differences compared with DJ were also seen in milk production traits, gross milk composition, and protein profile. Frequencies of the most common composite α(S1)-β-κ-CN genotype BB/A(2)A(2)/AA were 30% in DH and 15% in SR, and cows that had this genotype gave milk with lower relative concentrations of κ- and β-CN and higher relative concentrations of αS-CN, than the majority of the other composite genotypes in SR and DH. The effect of composite genotypes on relative concentrations of the milk proteins was not as pronounced in DJ. The present work suggests that a higher frequency of BB/A(1)A(2)/AB, together with a decrease in BB/A(2)A(2)/AA, could have positive effects on DH and SR milk regarding, for example, the processing of cheese., (Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Substantial variation in milk coagulation properties has been observed among dairy cows. Consequently, raw milk from individual cows and breeds exhibits distinct coagulation capacities that potentially affect the technological properties and milk processing into cheese. This variation is largely influenced by protein composition, which is in turn affected by underlying genetic polymorphisms in the major milk proteins. In this study, we conducted a large screening on 3 major Scandinavian breeds to resolve the variation in milk coagulation traits and the frequency of milk with impaired coagulation properties (noncoagulation). In total, individual coagulation properties were measured on morning milk collected from 1,299 Danish Holstein (DH), Danish Jersey (DJ), and Swedish Red (SR) cows. The 3 breeds demonstrated notable interbreed differences in coagulation properties, with DJ cows exhibiting superior coagulation compared with the other 2 breeds. In addition, milk samples from 2% of DH and 16% of SR cows were classified as noncoagulating. Furthermore, the cows were genotyped for major genetic variants in the αS1- (CSN1S1), β- (CSN2), and κ-casein (CSN3) genes, revealing distinct differences in variant frequencies among breeds. Allele I of CSN2, which had not formerly been screened in such a high number of cows in these Scandinavian breeds, showed a frequency around 7% in DH and DJ, but was not detected in SR. Genetic polymorphisms were significantly associated with curd firming rate and rennet coagulation time. Thus, CSN1S1 C, CSN2 B, and CSN3 B positively affected milk coagulation, whereas CSN2 A(2), in particular, had a negative effect. In addition to the influence of individual casein genes, the effects of CSN1S1-CSN2-CSN3 composite genotypes were also examined, and revealed strong associations in all breeds, which more or less reflected the single gene results. Overall, milk coagulation is under the influence of additive genetic variation. Optimal milk for future cheese production can be ensured by monitoring the frequency of unfavorable variants and thus preventing an increase in the number of cows producing milk with impaired coagulation. Selective breeding for variants associated with superior milk coagulation can potentially increase raw milk quality and cheese yield in all 3 Scandinavian breeds., (Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Small components and metabolites in milk are significant for the utilization of milk, not only in dairy food production but also as disease predictors in dairy cattle. This study focused on estimation of genetic parameters and detection of quantitative trait loci for metabolites in bovine milk. For this purpose, milk samples were collected in mid lactation from 371 Danish Holstein cows in first to third parity. A total of 31 metabolites were detected and identified in bovine milk by using (1)H nuclear magnetic resonance (NMR) spectroscopy. Cows were genotyped using a bovine high-density single nucleotide polymorphism (SNP) chip. Based on the SNP data, a genomic relationship matrix was calculated and used as a random factor in a model together with 2 fixed factors (herd and lactation stage) to estimate the heritability and breeding value for individual metabolites in the milk. Heritability was in the range of 0 for lactic acid to >0.8 for orotic acid and β-hydroxybutyrate. A single SNP association analysis revealed 7 genome-wide significant quantitative trait loci [malonate: Bos taurus autosome (BTA)2 and BTA7; galactose-1-phosphate: BTA2; cis-aconitate: BTA11; urea: BTA12; carnitine: BTA25; and glycerophosphocholine: BTA25]. These results demonstrate that selection for metabolites in bovine milk may be possible., (Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Heritability is a central element in quantitative genetics. New molecular markers to assess genetic variance and heritability are continually under development. The availability of molecular single nucleotide polymorphism (SNP) markers can be applied for estimation of variance components and heritability on population, where relationship information is unknown. In this study, we evaluated the capabilities of two Bayesian genomic models to estimate heritability in simulated populations. The populations comprised different family structures of either no or a limited number of relatives, a single quantitative trait, and with one of two densities of SNP markers. All individuals were both genotyped and phenotyped. Results illustrated that the two models were capable of estimating heritability, when true heritability was 0.15 or higher and populations had a sample size of 400 or higher. For heritabilities of 0.05, all models had difficulties in estimating the true heritability. The two Bayesian models were compared with a restricted maximum likelihood (REML) approach using a genomic relationship matrix. The comparison showed that the Bayesian approaches performed equally well as the REML approach. Differences in family structure were in general not found to influence the estimation of the heritability. For the sample sizes used in this study, a 10-fold increase of SNP density did not improve precision estimates compared with set-ups with a less dense distribution of SNPs. The methods used in this study showed that it was possible to estimate heritabilities on the basis of SNPs in animals with direct measurements. This conclusion is valuable in cases when quantitative traits are either difficult or expensive to measure.

Several quantitative trait loci (QTL) affecting mastitis incidence and mastitis-related traits such as somatic cell score exist in dairy cows. Previously, QTL haplotypes associated with susceptibility to Escherichia coli mastitis in Nordic Holstein-Friesian (HF) cows were identified on Bos taurus autosome 9. In the present study, we induced experimental E. coli mastitis in Danish HF cows to investigate the effect of 2 E. coli mastitis-associated QTL haplotypes on the cows' disease phenotypes and recovery in early lactation. Thirty-two cows were divided in 2 groups bearing haplotypes with either low (HL) or high (HH) susceptibility to E. coli. In addition, biopsies (liver and udder) were collected from half of the cows (n=16), resulting in a 2 × 2 factorial design, with haplotype being one factor (HL vs. HH) and biopsy being the other factor (biopsies vs. no biopsies). Each cow was inoculated with a low E. coli dose (20 to 40 cfu) in one front quarter at time 0 h. Liver biopsies were collected at -144, 12, 24, and 192 h; udder biopsies were collected at 24h and 192 h post-E. coli inoculation. The clinical parameters: feed intake, milk yield, body temperature, heart rate, respiration rate, rumen motility; and the paraclinical parameters: bacterial counts, somatic cell count (SCC), and milk amyloid A levels in milk; and white blood cell count, polymorphonuclear neutrophilic leukocyte (PMNL) count, and serum amyloid A levels in blood were recorded at different time points post-E. coli inoculation. Escherichia coli inoculation changed the clinical and paraclinical parameters in all cows except one that was not infected. Clinically, the HH group tended to have higher body temperature and heart rate than the HL group did. Paraclinically, the HL group had faster PMNL recruitment and SCC recovery than the HH group did. However, we also found interactions between the effects of haplotype and biopsy for body temperature, heart rate, and PMNL. In conclusion, when challenged with E. coli mastitis, HF cows with the specific Bos taurus autosome 9-located QTL haplotypes were associated with differences in leukocyte kinetics, with low-susceptibility cows having faster blood PMNL recruitment and SCC recovery and a tendency for a milder clinical response than the high-susceptibility cows did., (Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Changes in gene expression in response to selection were studied by comparing microarray expression profiles among a population of domestic chickens selected for high feather pecking (FP) with a control population and a population selected for low FP. No transcripts showed significant differences among populations with respect to mean expression scores, but numerous transcripts showed reduced variance in expression scores in the high FP population in comparison to control and low FP populations. The reduction in variance in the high FP population generally involved transcripts whose expression scores had a negatively skewed distribution in the control population but not in the high FP population. A certain number of these transcripts corresponded to genes whose expression was significantly associated with either severe FP (SFP) or gentle FP. The patterns of gene expression associated with SFP and gentle FP were distinct, suggesting that very distinct underlying neural mechanisms underlie these 2 behaviors, with SFP showing more signs of an association with synaptic plasticity and with an immunosuppressive stress response.

Before implementing selection based on quantitative trait loci (QTL) for fertility, it is important to determine the existence of correlated effects between the fertility QTL and QTL with effects on production traits. When a QTL is detected for a trait that is a composite of subtraits, it is of interest to validate which of the subtraits are affected by the QTL. Phenotypic and marker data were collected from 34 grandsire families from the Danish Holstein population. First, the trait data for "fertility treatments" were separated into their underlying subtraits: uterine infections, antibiotics placed in the placenta, and abortions. In addition, retained placenta was selected for analysis because it is related to uterine infections. A genome scan was performed using 416 microsatellite markers for the fertility treatment subtraits and retained placenta, and an additional genome scan for milk production traits conditional on the QTL regions for the subtraits and retained placenta was conducted. Second, we selected 24 genomic regions harboring QTL for fertility traits from a previous study. A QTL scan for milk production traits conditional on the selected regions was conducted. We found that 16 selected genomic regions containing a QTL for fertility (including the fertility treatment subtraits and retained placenta) also harbored QTL for milk yield or milk composition traits. Furthermore, 12 QTL regions corresponding to 9 different fertility traits (including the fertility treatment subtraits) did not harbor a QTL for milk production or milk composition traits; that is, the region was specific for the fertility trait. The genome scan for the fertility treatment subtraits did not correspond to the QTL found for fertility treatments. No QTL were detected for the subtrait abortion, however genome scans for retained placenta revealed 4 different QTL.

Even though feather pecking (FP) in laying hens has been extensively studied, a good solution to prevent chickens from this behavior under commercial circumstances has not been found. Selection against FP behavior is possible, but for a more effective selection across different populations, it is necessary to characterize the genetic mechanism associated with this behavior. In this study, we use a high FP selection line, which has been selected for 8 generations. We present evidence of the presence of a major dominant allele affecting the FP behavior by using an argument based on the presence of mixture in the distribution of the observed FP and by studying the evolution of the proportion of very high FP along the sequence of 8 generations. This hypothesis is further supported by the fact that the gene transcription profile of the birds performing high FP differs from the profile of the other birds performing FP (456 genes differentially expressed from a total of 14,077 investigated genes).

The aim of this study was to 1) detect QTL across the cattle genome that influence the incidence of clinical mastitis and somatic cell score (SCS) in Danish Holsteins, and 2) characterize these QTL for pleiotropy versus multiple linked quantitative trait loci (QTL) when chromosomal regions affecting clinical mastitis were also affecting other traits in the Danish udder health index or milk production traits. The chromosomes were scanned using a granddaughter design where markers were typed for 19 to 34 grandsire families and 1,373 to 2,042 sons. A total of 356 microsatellites covering all 29 autosomes were used in the scan. Among the across-family regression analyses, 16 showed chromosome-wide significance for the primary traits incidence of clinical mastitis in first (CM1), second (CM2), and third (CM3) lactations, and SCS. Regions of chromosomes 5, 6, 9, 11, 15, and 26 were found to affect CM and regions of chromosomes 5, 6, 8, 13, 22, 23, 24, and 25 affected SCS. Markers on chromosomes 6, 11, 15, and 26 can be used to perform marker-assisted selection on CM without a direct negative selection on milk yield, because no effects were detected on the milk traits. Comparing multi-trait models assuming either a pleiotropic QTL affecting 2 traits or 2 QTL each affecting 1 trait gave some evidence to distinguish between these models. For Bos taurus autosome 5, the most likely models were a pleiotropic QTL affecting CM2, CM3, and SCS, and a linked QTL affecting fat yield index. For Bos taurus autosome 9, the most likely model is a pleiotropic QTL affecting CM1 and CM2 at approximately 8 cM.

Lameness is an important factor for culling animals. Strong legs and feet improve herd life of dairy cows. Therefore, many countries include leg and feet conformation traits in their breeding programs, often as early predictors of longevity. However, few countries directly measure lameness related traits to include these in a breeding program. Lameness indices in 3 different lactations and 5 leg conformation traits (rear legs side view, rear legs rear view, hock quality, bone quality, and foot angle) were measured on granddaughters of 19 Danish Holstein grandsires with 33 to 105 sons. A genome scan was performed to detect quantitative trait loci (QTL) based on the 29 autosomes using microsatellite markers. Data were analyzed across and within families for QTL affecting lameness and leg conformation traits. A regression method and a variance component method were used for QTL detection. Two QTL each for lameness in the first [Bos taurus autosome (BTA); BTA5, BTA26] and second (BTA19, BTA22) lactations were detected. For the 5 different leg conformation traits, 7 chromosome-wise significant QTL were detected across families for rear legs side view, 5 for rear legs rear view, 4 for hock quality, 4 for bone quality, and 1 for foot angle. For those chromosomes where a QTL associated with 2 different traits was detected (BTA1, BTA11, BTA15, BTA26, and BTA27), a multitrait-1-QTL model and a multitrait-2-QTL model were performed to characterize these QTL as single QTL with pleiotropic effects or distinct QTL.

The aim of this study was to investigate the changes in immunological parameters as well as changes with respect to plasma levels of serotonin and tryptophan in lines selected for and against feather pecking (FP) behavior [high FP (HP) line and low FP (LP) line] for 5 generations. The hens from the HP line had a higher plasma serotonin level than those from the LP line (0.059 vs. 0.037 micromol/L, F(2,27) = 0.031, P < 0.05). The plasma level of tryptophan was, on average, 67.30 micromol/L and did not differ between the lines (68.3 vs. 66.3 micromol/L, F(2,28) = 0.36, P < 0.05). The HP line had a higher response to infectious bursal disease virus vaccination after 1 wk post-vaccination compared with the control and LP lines. The number of white blood cells (P < 0.0001) and the expression of MHC class I molecules on CD4 (P < 0.02), CD8beta (P < 0.006) and on B cells (P < 0.03) were highest in the LP line compared with the control and HP lines. Selection for or against FP, therefore, changes the number of white blood cells and the expression of MHC class I molecules on T and B cells, which may influence the health status of the birds.

The object of this research was to study the relationship between feather pecking and open-field activity in laying hens at two different ages. A population of 550 birds of a laying hen cross was subjected to an open-field test at 5 and 29 weeks of age and to a social feather pecking test at 6 and 30 weeks of age. Factor analysis was used to identify underlying factors for each test: pecking behavior (social test) and open-field activity (open-field test). In young birds, a positive phenotypic correlation of 0.24 was found between high open-field activity and high levels of pecking behavior (ground pecking, preening, gentle feather pecking, and wall pecking). In adults, a similar genetic correlation of 0.62 was found. At adult age, the factor pecking behavior consisted mainly of gentle and severe feather pecking. Between ages, a strong, negative genetic correlation of -0.65 was found between open-field activity at young age and pecking behavior at adult age, indicating that open-field activity levels in young birds may predict pecking behavior in adult hens., (Copyright 2004 Plenum Publishing Corporation)

The objective of the current study was to estimate genetic and phenotypic correlations among feather pecking (FP) behavior and stress response, immune response, and egg quality parameters. These traits have been measured in an F2 cross, coming from a cross between a high and a low FP line of laying hens. Heritabilities (h2) of stress response (32 wk), primary immune response to keyhole limpet hemocyanin (KLH) (36 wk) and Mycobacterium butyricum (39 wk), and egg quality parameters (35, 44, and 50 wk of age) were calculated. The h2 was 0.05 +/- 0.05 (SE) for stress response, 0.15 +/- 0.07 for antibody response to KLH, and 0.08 +/- 0.06 for antibody response to M. butyricum. The h2 for egg quality traits were in the range of 0.12 to 0.30. Significant phenotypic correlations were found between gentle FP in adult hens and stress response, egg weight at 44 and 50 wk, and egg deformation at 50 wk. Significant additive genetic correlations were found between severe FP in adult hens and antibody response to KLH (0.79 +/- 0.35), and between ground pecking in adult hens and egg deformation at 50 wk (0.63 +/- 0.26), and between ground pecking and eggshell strength at 35, 44, and 50 wk of age (-0.86 +/- 0.29, -0.81 +/- 0.20, -0.76 +/- 0.24, respectively).

Quantitative trait loci for BW at 4, 6, 8, 12, and 18 wk of age were detected in an experimental F2 cross of layers divergently selected for primary antibody response to SRBC. A negative phenotypic correlation between levels of antibody titers and BW, was reported earlier within founder lines. The entire experimental population was genotyped with 174 microsatellite markers equally distributed over the genome. Two genetic models were applied in the QTL analysis: a half-sib model and a line-cross model, both using the regression interval method. In the half-sib model, 3 QTL for BW at 4 wk of age on chromosomes GGA2, GGA3, and GGA9 were detected. For BW at 6 wk of age, 3 QTL were detected on GGA2, GGA3, and GGA6. For BW at 8 wk of age, a QTL was detected on GGA7, and for BW at 12 and 18 wk of age, a QTL was detected on GGAZ. With the line-cross analysis model, one QTL on GGA7 for BW at 4 wk of age was detected. Two QTL were detected on GGA3 and GGA7 for BW at 6 wk of age, and one on GGA3 was detected for BW for 8 and 12 wk of age. For BW at 18 wk of age, there were no QTL under the line-cross analysis model. The present data suggest that 1) a different set of genes affects the early and the late growth, and 2) genes selected to humoral immune responsiveness are different from genes underlying growth.

Line differences for open-field behavior in chickens have been observed, and it has been shown that this behavior has a genetic component. The aim of this study was to detect quantitative trait loci (QTL) involved in open-field behavior. For this purpose, open-field behavior was studied at 5 and 29 weeks of age in F(2) hens coming from an intercross between two commercial White Leghorn laying lines selected for egg production traits. Latencies, durations, and frequencies of general activity (sitting, standing, walking, and stepping), defecation, and vocalizations were recorded individually for each bird, and a factor score was calculated. All animals (F(0), F(1), and F(2)) were screened with 180 microsatellite markers. Regression interval mapping was applied using both a paternal half-sib analysis and a line-cross analysis method. For general activity at 5 weeks of age, a significant QTL was detected on GGA4 and a suggestive QTL on GGA2 under the line-cross model. For general activity at 29 weeks of age, a significant QTL was detected on GGA4 and two suggestive QTLs were detected on GGA1 and on GGA10, respectively, also using the line-cross analysis. The QTL on GGA4 at 5 weeks of age did not overlap with the QTL on GGA4 at 29 weeks of age. The current study indicated that open-field behavior in young chickens was regulated by QTL that differ from the QTL for open-field behavior in adult chickens.

Quantitative trait loci involved in the primary antibody response to keyhole lympet hemocyanin (KLH) and Mycobacterium butyricum were detected in two independent populations of laying hens. The first population was an F2 cross (H/L) of lines divergently selected for either high or low primary antibody responses to SRBC, and the second population was an F2 cross between 2 commercial layer lines displaying differences in feather pecking behavior (FP). Both populations were typed with microsatellite markers widely distributed over the genome with similar intervals between markers. Titers of antibodies binding KLH and M. butyricum were measured for all individuals by ELISA. Two genetic models were applied to detect QTL involved in the humoral immune response: a half-sib model and a line-cross model, both using the regression interval method. In the half-sib analysis, 2 QTL (on GGA14 and GGA27) were detected for the antibody response to KLH for the H/L population, and 2 QTL (on GGA14 and GGA18) were detected for the FP population. Only 1 QTL was detected for M. butyricum on GGA14 in the FP population using the half-sib analysis model. Two QTL were detected for the FP population on GGA2 and GGA3 using the line-cross analysis model. A QTL for the primary antibody response to KLH detected on GGA14 was validated in both populations under the half-sib analysis model. The present data suggest differences in the genetic regulation of antibody responses to two different T-cell dependent antigens.

The aim of this study is to detect quantitative trait loci (QTL) involved in the regulation of the primary and the secondary immune response to sheep red blood cells (SRBC) in a resource population using microsatellite DNA markers. The F2 resource population originates from a cross of two divergently selected lines for either high (H line) or low (L line) primary antibody response to SRBC. The F2 population consisted of six half-sib families, three families per each of reciprocal crosses. Total antibody titres to SRBC were determined by agglutination in serum from all birds. F2, F1 and F0 generations were genotyped for 170 microsatellite markers, using a whole-genome scan approach. The half-sib and the line-cross analyses were performed to determine QTL regions associated with regulation of the immune response. In the half-sib analysis, four QTL for SRBC primary response have been identified: on GGA3, GGA5, GGA16 and GGA23. No QTL was identified for SRBC secondary response under the half-sib model. In the line-cross analysis, three QTL were identified on GGA10, GGA16 and GGA27 for SRBC primary response and five QTL were identified on GGA6, GGA9, GGA15, GGA16 and GGA27 for SRBC secondary response. Subsequently, the family contribution of individual families to the QTL was analysed. The family with the largest contribution was genotyped with additional microsatellite markers in the QTL region on GGA5. The extended half-sib analysis with additional genotype information results in narrowing down the QTL region on GGA5.

Feather pecking (FP) is a major problem in cage and free-range housing systems. In free-range systems, FP is more difficult to control. It is not known why a victim is being pecked. It could be that a bird is genetically predisposed to be pecked. To study the genetics of FP behavior, a large F2 population of 630 hens was generated from a cross between two commercial laying lines differing in their propensity to feather peck. The traits measured at 6 and 30 wk of age were receiving gentle FP, receiving severe FP, and receiving aggressive pecking. In addition, receiving toe pecking (TP) was also measured at 30 wk of age. For receiving gentle FP at 6 wk of age, a significant QTL on GGA1 and three different suggestive QTL were identified on GGA2, GGA6, and GGA7, respectively. For receiving gentle FP at 30 wk of age, a suggestive QTL on GGA5 was detected. For receiving aggressive pecking, a suggestive QTL was detected on GGA3. For receiving TP, three suggestive QTL were detected on GGA1, GGA5, and GGA23, respectively. The different QTL detected for receiving gentle FP at different ages indicate that this trait is regulated by different genes in young and adult hens.

In the European Union, legislation concerning animal housing is becoming stricter because of animal welfare concerns. Feather pecking (FP) in large group housing systems is a major problem. It has been suggested that corticosterone (CORT) response to manual restraint as a measure for stress is associated with FP behavior. The aim of the current study was to identify QTL involved in FP behavior and stress response in laying hens. An F2 population of 630 hens was established from a cross between two commercial lines of laying hens differing in their propensity to feather peck. The behavioral traits, measured at 6 and 30 wk of age, were gentle FP, severe FP, and aggressive pecking. Toe pecking was measured at 30 wk of age and CORT response to manual restraint was measured at 32 wk. All animals were genotyped for 180 microsatellite markers. A QTL analysis was performed using a regression interval mapping method. At 6 wk of age, a suggestive QTL on GGA10 was detected for gentle FP. At 30 wk of age, suggestive QTL were detected on GGA1 and GGA2 for gentle FP. A significant QTL was detected on GGA2 for severe FP. At 32 wk of age, a suggestive QTL was detected on GGA18 for CORT response to manual restraint. In addition, a suggestive QTL was detected on GGA5 with possible maternal parent-of-origin effect for CORT response.

The objective of the current study was to estimate heritabilities (h2) of feather pecking and open-field response of laying hens at two different ages. An F2 cross, originating from a high and a low feather pecking line of laying hens, was used for the experiment. Each of the 630 birds of the F2 cross was subjected to an open-field test (individual, 10 min) at 5 and 29 wk of age and to a social feather pecking test (groups of five birds on wood shavings, 30 min) at 6 and 30 wk of age. Both tests were performed in a square open field (1.25 x 1.25 m). Behavior was recorded directly from a monitor. Heritabilities of feather pecking and open-field behaviors were calculated. In the open-field test at 5 wk of age, high h2 were found for most traits, ranging from 0.20 for the frequency of flying to 0.49 for number of steps. In the social test at 6 wk, gentle feather pecking (0.12) and ground pecking (0.13) were found to be heritable. When both tests were repeated at 29 and 30 wk of age, h2 estimates were lower for the open-field test, ranging from 0.10 for duration of sitting to 0.20 for latency to first step. In the social test, however, higher h2 estimates of 0.15 for gentle feather pecking and 0.30 for ground pecking were found compared with 6 wk of age. In conclusion, gentle feather pecking and open-field behaviors may be used in selection against feather pecking.

A comparative map was made of chicken chromosome 13 (GGA13) with a part of human chromosome 5 (HSA5). Microsatellite markers specific for GGA13 were used to screen the Wageningen chicken bacterial artificial chromosome (BAC) library. Selected BAC clones were end sequenced and 57 sequence tag site (STS) markers were designed for contig building. In total, 204 BAC clones were identified which resulted in a coverage of about 20% of GGA13. Identification of genes was performed by a bi-directional approach. The first approach starting with sequencing mapped chicken BAC subclones, where sequences were used to identify orthologous genes in human and mouse by a basic local alignment search tool (BLAST) database search. The second approach started with the identification of chicken orthologues of human genes in the HSA5q23-35 region. The chicken orthologous genes were subsequently mapped by fluorescent in situ hybridisation (FISH) and/or single neucleotide polymorphism typing. The total number of genes mapped on GGA13 is increased from 14 to a total of 20 genes. Genes mapped on GGA13 have their orthologues on HSA5q23-5q35 in human and on Mmu11, Mmu13 and Mmu18 in mouse.

An F2 population was produced from mating G0 highly inbred (>99%) males of two MHC-congenic Fayoumi lines with G-B1 Leghorn hens. The F2 population was essentially a full-sibship with the F1 sire line reflecting MHC effect. Adult F2 hens (n = 158) were injected twice with SRBC and whole fixed Brucella abortus (BA). Agglutinating antibody titer at 7 d after primary immunization and mean titer of the final three samples (Days 18, 32, and 63 after the second immunization) were used as parameters for primary and equilibrium phases, respectively. Secondary phase parameters of minimum (Ymin), maximum titers (Ymax) and time needed to achieve minimum (Tmin) and maximum (Tmax) titers were estimated from seven postsecondary titers with a nonlinear regression model. Three candidate genes, interferon-gamma (IFN-gamma), interleukin-2 (IL-2), and immunoglobulin G light chain (IgL) were studied. Primers for the promoter regions were designed from EMBL chicken genomic sequences. Polymorphisms between parental lines were detected by direct sequencing. Polymerase chain reaction-restriction fragment length polymorphism methods were then developed to directly detect the polymorphism. There were significant main effects (P < 0.05, general linear model analysis) of IFN-gamma polymorphism on Ymax of BA antibody and interaction of IFN-gamma by IgL on primary antibody response to SRBC and BA, and on Tmin and Ymin of antibody response to SRBC in F2 offspring of M5.1 grandsires. There were significant main effects of IFN-gamma polymorphism on Tmax of BA and interaction of IFN-gamma by IL-2 on Ymin to SRBC in F2 offspring of M15.2 grandsires. The results suggest that IFN-gamma genes play an important role in chicken primary and secondary antibody response to SRBC and BA antigens, and there exists interaction among genes for antibody production.