Imputation of missing milk Fourier transform mid-infrared spectra using existing milk spectral databases: A strategy to improve the reliability of breeding values and predictive models.

The use of milk Fourier transform mid-infrared (FT-MIR) spectrometry to develop management and breeding tools for dairy farmers and industry is growing and supported by the availability of numerous new predicted phenotypes to assess the nutritional quality of milk and its technological properties, but also the animal health and welfare status and its environmental fingerprint. For genetic evaluations, having a long-term and representative spectral dairy herd improvement (DHI) database improves the reliabilities of estimated breeding values (EBV) from these phenotypes. Unfortunately, most of the time, the raw spectral data used to generate these estimations are not stored. Moreover, many reference measurements of those phenotypes, needed during the FT-MIR calibration step, are available from past research activities but lack spectra records. So, it is impossible to use them to improve the FT-MIR models. Consequently, there is a strong interest in imputing those missing spectra. The innovative objective of this study was to use the existing large spectral DHI database to estimate missing spectra by selecting probable spectra using, as the match criteria, common dairy traits recorded for a long time by DHI organizations. We tested 4 match criteria combinations. Combination 1 required to have equal fat and protein contents between the sample for which a spectrum was to be estimated and the reference samples in the DHI database. Combination 2 also required an equal urea content. Combination 3 requested equal fat, protein, and lactose contents. Finally, combination 4 included all criteria. When more than one spectrum was found during the search, their average was the estimated spectrum for the query sample. Concretely, this study estimated missing spectra for 1,700 samples using 2,000,000 spectral DHI records. For assessing the effect of this spectral estimation on the prediction quality, FT-MIR equations were used to predict 11 phenotypes, selected as their quantification used different FT-MIR regions. They were related to the milk fat and mineral composition, lactoferrin content, quantity of eructed methane, body weight (BW), and dry matter intake. The accuracy between predictions obtained from actual and estimated spectra was evaluated by calculating the mean absolute error (MAE). The criteria in the fourth and second combinations were too strict to estimate a spectrum for most samples. Indeed, for many samples, no spectra with the same values for those matching criteria was found. The third match criteria combination had a poorer prediction performance for all studied traits and spectral absorptions than the first combination due to fewer matched samples available to compute the missing spectrum. By allowing a range for matching lactose content (±0.1 g/dL milk), we showed that this new combination increased the number of selected samples to compute missing spectra and predict better the infrared absorption at different wavenumbers, especially those related to the lactose quantification. The prediction performance was further improved by performing queries on the entire Walloon DHI spectral database (6,625,570 spectra), and it varied among the studied phenotypes. Without considering the traits used for the matching, the best predictions were obtained for the content of saturated fatty acids (MAE = 0.15 g/dL milk) and BW (MAE = 12.80 kg). Yet, the predictions for the unsaturated fatty acids were less accurate (MAE = 0.13 and 0.018 g/dL milk for monounsaturated and polyunsaturated fatty acids), likely because of the poorer predictions of spectral regions related to long-chain fatty acids. Similarly, poorer predictions were observed for the amount of methane eructed by dairy cows (MAE = 47.02 g/d), likely because it is not directly related to fat content or composition. Prediction accuracies for the remaining traits were also low. In conclusion, we observed that increasing the number of relevant matching criteria helps improve the quality of FT-MIR predicted phenotypes and the number of spectra used during the search. So, it would be of great interest to test in the future the suitability of the developed methodology with large-scale international spectral databases to improve the reliability of EBV from these FT-MIR-based phenotypes and the robustness of FT-MIR predictive models.

Predicting milk mid-infrared spectra from first-parity Holstein cows using a test-day mixed model with the perspective of herd management.

The use of test-day models to model milk mid-infrared (MIR) spectra for genetic purposes has already been explored; however, little attention has been given to their use to predict milk MIR spectra for management purposes. The aim of this paper was to study the ability of a test-day mixed model to predict milk MIR spectra for management purposes. A data set containing 467,496 test-day observations from 53,781 Holstein dairy cows in first lactation was used for model building. Principal component analysis was implemented on the selected 311 MIR spectral wavenumbers to reduce the number of traits for modeling; 12 principal components (PC) were retained, explaining approximately 96% of the total spectral variation. Each of the retained PC was modeled using a single trait test-day mixed model. The model solutions were used to compute the predicted scores of each PC, followed by a back-transformation to obtain the 311 predicted MIR spectral wavenumbers. Four new data sets, containing altogether 122,032 records, were used to test the ability of the model to predict milk MIR spectra in 4 distinct scenarios with different levels of information about the cows. The average correlation between observed and predicted values of each spectral wavenumber was 0.85 for the modeling data set and ranged from 0.36 to 0.62 for the scenarios. Correlations between milk fat, protein, and lactose contents predicted from the observed spectra and from the modeled spectra ranged from 0.83 to 0.89 for the modeling set and from 0.32 to 0.73 for the scenarios. Our results demonstrated a moderate but promising ability to predict milk MIR spectra using a test-day mixed model. Current and future MIR traits prediction equations could be applied on the modeled spectra to predict all MIR traits in different situations instead of developing one test-day model separately for each trait. Modeling MIR spectra would benefit farmers for cow and herd management, for instance through prediction of future records or comparison between observed and expected wavenumbers or MIR traits for the detection of health and management problems. Potential resulting tools could be incorporated into milk recording systems.

Integration of external estimated breeding values and associated reliabilities using correlations among traits and effects.

Based on a Bayesian view of linear mixed models, several studies showed the possibilities to integrate estimated breeding values (EBV) and associated reliabilities (REL) provided by genetic evaluations performed outside a given evaluation system into this genetic evaluation. Hereafter, the term "internal" refers to this given genetic evaluation system, and the term "external" refers to all other genetic evaluations performed outside the internal evaluation system. Bayesian approaches integrate external information (i.e., external EBV and associated REL) by altering both the mean and (co)variance of the prior distributions of the additive genetic effects based on the knowledge of this external information. Extensions of the Bayesian approaches to multivariate settings are interesting because external information expressed on other scales, measurement units, or trait definitions, or associated with different heritabilities and genetic parameters than the internal traits, could be integrated into a multivariate genetic evaluation without the need to convert external information to the internal traits. Therefore, the aim of this study was to test the integration of external EBV and associated REL, expressed on a 305-d basis and genetically correlated with a trait of interest, into a multivariate genetic evaluation using a random regression test-day model for the trait of interest. The approach we used was a multivariate Bayesian approach. Results showed that the integration of external information led to a genetic evaluation for the trait of interest for, at least, animals associated with external information, as accurate as a bivariate evaluation including all available phenotypic information. In conclusion, the multivariate Bayesian approaches have the potential to integrate external information correlated with the internal phenotypic traits, and potentially to the different random regressions, into a multivariate genetic evaluation. This allows the use of different scales, heritabilities, variance components, measurement units, or trait definitions for external and internal traits. However, one possible issue for implementing multivariate Bayesian approaches could be the availability or estimation of genetic correlations between external and internal traits.

Genetic diversity and population structure of Synthesium pontoporiae (Digenea, Brachycladiidae) linked to its definitive host stocks, the endangered Franciscana dolphin, Pontoporia blainvillei (Pontoporiidae) off the coast of Brazil and Argentina.

Pontoporia blainvillei (Gervais and d'Orbigny, 1844) is an endangered small cetacean endemic to South America with four Franciscana Management Areas (FMA) recognized as different population stocks. The role of the intestinal parasite Synthesium pontoporiae (Digenea: Brachycladiidae) as a possible biological marker to differentiate P. blainvillei stocks was evaluated using nuclear and mitochondrial DNA markers. Internal transcribed sequence 1 and 2 (ITS1 and ITS2) regions of S. pontoporiae did not show intraspecific variability. The mitochondrial NADH dehydrogenase subunit 3 (ND3) and cytochrome oxidase subunit I (COI) gene sequences suggested lack of population structure in S. pontoporiae and population expansion. The apparent panmixia of S. pontoporiae may be due to the high mobility of one or more of its intermediary hosts. Alternatively, it may be due to the small sample size. This result is incongruent with the previously proposed FMA.

PAHs in franciscana dolphins from the Southwestern Atlantic Ocean: Concentration and maternal transfer assessments.

Polycyclic aromatic hydrocarbons (PAHs) are organic compounds ubiquitous in the environment and known for their toxic, mutagenic, and carcinogenic effects. These compounds can bioaccumulate in the biota and be transferred through trophic webs. The franciscana dolphin (Pontoporia blainvillei), as top predators, can be an environmental sentinels. Thus, this study aimed to provide data about PAHs concentration in their hepatic tissue collected on the coast of Espírito Santo (Franciscana Management Area, FMA Ia), Rio de Janeiro (FMA IIa), and São Paulo states (FMA IIb), in Southeastern Brazil. PAHs were detected in 86 % of franciscana dolphins (n = 50). The highest ∑PAHsTotal median concentration was reported in FMA Ia followed by FMA IIb and FMA IIa (1055.6; 523.9, and 72.1 ng.g-1 lipid weight, respectively). Phenanthrene was detected in one fetus and two neonates, showing maternal transfer of PAHs in these dolphins. Evaluating PAHs with potential toxic effects is of utmost importance for the conservation of a threatened species.

Survey of selected viral agents (herpesvirus, adenovirus and hepatitis E virus) in liver and lung samples of cetaceans, Brazil.

Hepatic and pulmonary lesions are common in cetaceans, despite their poorly understood viral etiology. Herpesviruses (HV), adenoviruses (AdV) and hepatitis E virus (HEV) are emerging agents in cetaceans, associated with liver and/or pulmonary damage in mammals. We isolated and molecularly tested DNA for HV and AdV (n = 218 individuals; 187 liver and 108 lung samples) and RNA for HEV (n = 147 animals; 147 liver samples) from six cetacean families. All animals stranded or were bycaught in Brazil between 2001 and 2021. Positive-animals were analyzed by histopathology. Statistical analyses assessed if the prevalence of viral infection could be associated with the variables: species, family, habitat, region, sex, and age group. All samples were negative for AdV and HEV. Overall, 8.7% (19/218) of the cetaceans were HV-positive (4.8% [9/187] liver and 11.1% [12/108] lung), without HV-associated lesions. HV-prevalence was statistically significant higher in Pontoporiidae (19.2%, 10/52) when compared to Delphinidae (4.1%, 5/121), and in southeastern (17.1%, 13/76)-the most industrialized Brazilian region-when compared to the northeastern region (2.4%, 3/126). This study broadens the herpesvirus host range in cetaceans, including its description in pygmy sperm whales (Kogia breviceps) and humpback whales (Megaptera novaeangliae). Further studies must elucidate herpesvirus drivers in cetaceans.

Dechlorane-related compounds in franciscana dolphin (Pontoporia blainvillei) from southeastern and southern coast of Brazil.

Concentrations of Dechlorane (Dec) 603 (0.75 ng/g lipid weight (lw); mean) and Dec 602 (0.38 ng/g lw; mean) were quantified in more than 95% of the franciscana (Pontoporia blainvillei) dolphin samples, whereas the frequency of detection decreased to 75% for Dechlorane Plus (DP) (1.53 ng/g lw, mean). The presence of Chlordene Plus (CP) was also observed (0.13 ng/g lw, mean) in half of the samples. On the contrary, Dec 604, decachloropentacyclooctadecadiene (aCl(10)DP), and undecachloropentacyclooctadecadiene (aCl(11)DP) concentrations were below the limit of quantifications in all cases. To the best of our knowledge, this is the first article reporting the presence of Dec 603, Dec 602, and CP in mammals. For comparative purposes, levels of Mirex, polybrominated diphenyl ethers (PBDEs), and decabromodiphenylethane (DBDPE) are also reported. Considering geographic distribution evaluation together with the strong positive correlations found between DP and PBDEs (r(s) = 0.63; p < 0.01), highly anthropogenic areas were identified as potential sources of these chemicals in this dolphin species. However, local sources for Dec 602, 603, Mirex, CP, and DBDPE were not found indicating that in this case historical use and/or atmospheric transport and deposition may play an important role in their fate.

Spatial trends of trace elements bioaccumulation in the most endangered dolphin from the Southwestern Atlantic Ocean: The franciscana (Pontoporia blainvillei).

Trace elements bioaccumulation patterns can be an important tool to assess differences among cetaceans' populations. In this work, their use as potential chemical markers to differentiate franciscanas (Pontoporia blainvillei) populations was evaluated. Franciscanas were collected from three states in southeastern Brazil, which comprise three different Franciscana Management Areas (FMAs): Espírito Santo (FMA Ia), southern Rio de Janeiro (FMA IIa), and central São Paulo (FMA IIb). The concentrations of As, Cd, Cu, Fe, Hg, Mn and Zn were determined in the muscle, liver and kidney of the animals. Cadmium was the most valuable chemical marker to differentiate stocks, separating at least FMA IIa from the others. The higher Cd levels in FMA IIa, along with dietary information, indicate that the predominant consumption of cephalopods by this population is the main reason for the differences found. Additionally, environmental characteristics of the areas should also be considered as divergent sources of trace elements. Our findings suggest that non-essential trace elements, such as Cd, can be successful markers to differentiate populations. The Mn concentrations in FMA Ia raised concern and must be carefully monitored, as well as other elements that compose the iron ore tailings that have impacted the Espírito Santo coastal area. Additionally, this is the first study to report trace element concentration in the franciscanas from FMA IIa (southern Rio de Janeiro). Trace element concentrations found in franciscanas may represent different contamination levels in their preys and environments, which might pose specific threats to distinct populations. Therefore, our findings are important to characterize and differentiate franciscana populations and to guide precise management and conservation actions for the distinct stocks of this endangered species.

The selectins and their ligands.

The selectins are a family of carbohydrate-binding proteins, or lectins, that have stimulated tremendous interest because of their involvement in a wide array of interactions between leukocytes and endothelial cells. Highlights of recent progress include an extension of the list of instances of selectin participation in inflammatory diseases, further definition of selectin carbohydrate specificities, and identification of their carbohydrate-based ligands.

Cell surface engineering by a modified Staudinger reaction.

Selective chemical reactions enacted within a cellular environment can be powerful tools for elucidating biological processes or engineering novel interactions. A chemical transformation that permits the selective formation of covalent adducts among richly functionalized biopolymers within a cellular context is presented. A ligation modeled after the Staudinger reaction forms an amide bond by coupling of an azide and a specifically engineered triarylphosphine. Both reactive partners are abiotic and chemically orthogonal to native cellular components. Azides installed within cell surface glycoconjugates by metabolism of a synthetic azidosugar were reacted with a biotinylated triarylphosphine to produce stable cell-surface adducts. The tremendous selectivity of the transformation should permit its execution within a cell's interior, offering new possibilities for probing intracellular interactions.

Chemical glycobiology.

Chemical tools have proven indispensable for studies in glycobiology. Synthetic oligosaccharides and glycoconjugates provide materials for correlating structure with function. Synthetic mimics of the complex assemblies found on cell surfaces can modulate cellular interactions and are under development as therapeutic agents. Small molecule inhibitors of carbohydrate biosynthetic and processing enzymes can block the assembly of specific oligosaccharide structures. Inhibitors of carbohydrate recognition and biosynthesis can reveal the biological functions of the carbohydrate epitope and its cognate receptors. Carbohydrate biosynthetic pathways are often amenable to interception with synthetic unnatural substrates. Such metabolic interference can block the expression of oligosaccharides or alter the structures of the sugars presented on cells. Collectively, these chemical approaches are contributing great insight into the myriad biological functions of oligosaccharides.

Engineering chemical reactivity on cell surfaces through oligosaccharide biosynthesis.

Cell surface oligosaccharides can be engineered to display unusual functional groups for the selective chemical remodeling of cell surfaces. An unnatural derivative of N-acetyl-mannosamine, which has a ketone group, was converted to the corresponding sialic acid and incorporated into cell surface oligosaccharides metabolically, resulting in the cell surface display of ketone groups. The ketone group on the cell surface can then be covalently ligated under physiological conditions with molecules carrying a complementary reactive functional group such as the hydrazide. Cell surface reactions of this kind should prove useful in the introduction of new recognition epitopes, such as peptides, oligosaccharides, or small organic molecules, onto cell surfaces and in the subsequent modulation of cell-cell or cell-small molecule binding events. The versatility of this technology was demonstrated by an example of selective drug delivery. Cells were decorated with biotin through selective conjugation to ketone groups, and selectively killed in the presence of a ricin A chain-avidin conjugate.

A small-molecule modulator of poly-alpha 2,8-sialic acid expression on cultured neurons and tumor cells.

Poly-alpha2,8-sialic acid (PSA) has been implicated in numerous normal and pathological processes, including development, neuronal plasticity, and tumor metastasis. We report that cell surface PSA expression can be reversibly inhibited by a small molecule, N-butanoylmannosamine (ManBut). Inhibition occurs through a metabolic mechanism in which ManBut is converted to unnatural sialic acid derivatives that effectively act as chain terminators during cellular PSA biosynthesis. N-Propanoylmannosamine (ManProp), which differs from ManBut by a single methylene group, did not inhibit PSA biosynthesis. Modulation of PSA expression by chemical means has a role complementary to genetic and biochemical approaches in the study of complex PSA-mediated events.

Genetic analysis of lactoferrin content in bovine milk.

Bovine lactoferrin (LF) is mainly present in milk and shows important physiological and biological functions. The aim of this study was to estimate the heritability and correlation values of LF content in bovine milk with different economic traits as milk yield (MY), fat and protein percentages, and somatic cell score (SCS). Variance components of the studied traits were estimated by REML using a multiple-trait mixed model. The obtained heritability (0.22) for LF content predicted using mid-infrared spectrometry (pLF) suggested the possibility of animal selection based on the increase of LF content in milk. The phenotypic and genetic correlation values calculated between pLF and SCS were moderate (0.31 and 0.24, respectively). Furthermore, a preliminary study of bovine LF gene polymorphism effects was performed on the same production traits. By PCR, all exons of the LF gene were amplified and then sequenced. Three new polymorphisms were detected in exon 2, exon 11, and intron 8. We examined the effects of LF gene polymorphisms of exons 2, 4, 9, 11, and 15, and intron 8 on pLF, MY, fat and protein percentages, and SCS. The different observed effects did not reach a significant level probably because of the characteristics of the studied population. However, the results were promising, and LF may be a potential indicator of mastitis. Further studies are necessary to evaluate the effect of genetic selection based on LF content on the improvement of mastitis resistance.

Potential estimation of major mineral contents in cow milk using mid-infrared spectrometry.

Milk and dairy products are a major source of minerals, particularly calcium, involved in several metabolic functions in humans. Currently, several dairy products are enriched with calcium to prevent osteoporosis. The development of an inexpensive and fast quantitative analysis for minerals is required to offer dairy farmers an opportunity to improve the added value of the produced milk. The aim of this study was to develop 5 equations to measure Ca, K, Mg, Na, and P contents directly in bovine milk using mid-infrared (MIR) spectrometry. A total of 1,543 milk samples were collected between March 2005 and May 2006 from 478 cows during the Walloon milk recording and analyzed by MIR spectrometry. Using a principal component approach, 62 milk samples were selected by their spectral variability and separated in 2 calibration sets. Five outliers were detected and deleted. The mineral contents of the selected samples were measured by inductively coupled plasma atomic emission spectrometry. Using partial least squares combined with a repeatability file, 5 calibration equations were built to estimate the contents of Ca, K, Mg, Na, and P in milk. To assess the accuracy of the developed equations, a full cross-validation and an external validation were performed. The cross-validation coefficients of determination (R(2)cv) were 0.80, 0.70, and 0.79 for Ca, Na, and P, respectively (n = 57), and 0.23 and 0.50 for K and Mg, respectively (n = 31). Only Ca, Na, and P equations showed sufficient R(2)cv for a potential application. These equations were validated using 30 new milk samples. The validation coefficients of determination were 0.97, 0.14, and 0.88 for Ca, Na, and P, respectively, suggesting the potential to use the Ca and P calibration equations. The last 30 samples were added to the initial milk samples and the calibration equations were rebuilt. The R(2)cv for Ca, K, Mg, Na, and P were 0.87, 0.36, 0.65, 0.65, and 0.85, respectively, confirming the potential utilization of the Ca and P equations. Even if new samples should be added in the calibration set, the first results of this study showed the feasibility to quantify the calcium and phosphorus directly in bovine milk using MIR spectrometry.

Modeling milk urea of Walloon dairy cows in management perspectives.

The aim of this study was to develop an adapted random regression test-day model for milk urea (MU) and to study the possibility of using predictions and solutions given by the model for management purposes. Data included 607,416 MU test-day records of first-lactation cows from 632 dairy herds in the Walloon Region of Belgium. Several advanced features were used. First, to detect the herd influence, the classical herd x test-day effect was split into 3 new effects: a fixed herd x year effect, a fixed herd x month-period effect, and a random herd test-day effect. A fixed time period regression was added in the model to take into account the yearly oscillations of MU on a population scale. Moreover, first autoregressive processes were introduced and allowed us to consider the link between successive test-day records. The variance component estimation indicated that large variance was associated with the random herd x test-day effect (48% of the total variance), suggesting the strong influence of herd management on the MU level. The heritability estimate was 0.13. By comparing observed and predicted MU levels at both the individual and herd levels, target ranges for MU concentrations were defined to take into account features of each cow and each herd. At the cow level, an MU record was considered as deviant if it was <200 or >400 mg/L (target range used in the field) and if the prediction error was >50 mg/L (indicating a significant deviation from the expected level). Approximately 7.5% of the MU records collected between June 2007 and May 2008 were beyond these thresholds. This combination allowed for the detection of potentially suspicious cows. At the herd level, the expected MU level was considered as the sum of the solutions for specific herd effects. A herd was considered as deviant from its target range when the prediction error was greater than the standard deviation of MU averaged by herd test day. Results showed that 6.7% of the herd test-day MU levels between June 2007 and May 2008 were considered deviant. These deviations seemed to occur more often during the grazing period. Although theoretical considerations developed in this study should be validated in the field, this research showed the potential use of a test-day model for analyzing functional traits to advise dairy farmers.

Variation of Delta 9-desaturase activity in dairy cattle.

The endogenous production of unsaturated fatty acids (FA), particularly some monounsaturated FA (%MONO) and nearly all conjugated linoleic acids, is regulated by the Delta(9)-desaturase activity. The aims of this study were to assess the variation of this enzymatic activity within lactation, across dairy breeds, and to estimate its genetic parameters. The ratios of C14:1 cis-9 to C14:0, C16:1 cis-9 to C16:0, and C18:1 cis to C18:0 were calculated from FA contents predicted by mid-infrared spectrometry. Variance components and standard errors were estimated using average information REML. The multitrait mixed model included as fixed effects herd x test date x class of lactation number, class of days in milk x class of lactation number, class of age x class of lactation number, and regressions on breed composition. Four random effects were also included: animal genetic effect, 2 permanent environments (within and across lactations), and residual effect. Under the assumption that the calculated ratios are an approximate measurement of Delta(9)-desaturase activity, this study showed different sources of variation for this enzymatic activity. A slight difference was observed within lactation. The ratios of C14:1 cis-9 to C14:0 and C16:1 cis-9 to C16:0 increased as a function of days in milk. Differences across 7 dairy breeds were observed. The values of Delta(9)-desaturase indices observed for Jersey and Brown-Swiss cows were lower compared with Holstein. The opposite was observed for dual-purpose Belgian Blue cows. Values of heritability for the ratios of C14:1 cis-9 to C14:0, C16:1 cis-9 to C16:0, and C18:1 cis to C18:0 were 20, 20, and 3%, respectively. Negative genetic correlations observed between fat or protein contents and the 3 indices suggested that an increased activity of Delta(9)-desaturase could inhibit the synthesis of fat and protein in bovine milk. Negative correlations were also observed between fat or protein contents and the contents of 3 studied unsaturated FA in milk fat (C14:1 cis-9, C16:1 cis-9, and C18:1 cis). The positive genetic correlations observed between %MONO and the ratios of C14:1 cis-9 to C14:0 (0.72), C16:1 cis-9 to C16:0 (0.62), and C18:1 cis to C18:0 (0.97) showed that %MONO is linked to the Delta(9)-desaturase activity.

Bayesian single-step genomic evaluations combining local and foreign information in Walloon Holsteins.

Most dairy cattle populations found in different countries around the world are small to medium sized and use many artificial insemination bulls imported from different foreign countries. The Walloon population in the southern part of Belgium is a good example for such a small-scale population. Wallonia has also a very active community of Holstein breeders requesting high level genetic evaluation services. Single-step Genomic BLUP (ssGBLUP) methods allow the simultaneous use of genomic, pedigree and phenotypic information and could reduce potential biases in the estimation of genomically enhanced breeding values (GEBV). Therefore, in the context of implementing a Walloon genomic evaluation system for Holsteins, it was considered as the best option. However, in contrast to multi-step genomic predictions, natively ssGBLUP will only use local phenotypic information and is unable to use directly important other sources of information coming from abroad, for example Multiple Across Country Evaluation (MACE) results as provided by the Interbull Center (Uppsala, Sweden). Therefore, we developed and implemented single-step Genomic Bayesian Prediction (ssGBayes), as an alternative method for the Walloon genomic evaluations. The ssGBayes method approximated the correct system of equations directly using estimated breeding values (EBV) and associated reliabilities (REL) without any explicit deregression step. In the Walloon genomic evaluation, local information refers to Walloon EBV and REL and foreign information refers to MACE EBV and associated REL. Combining simultaneously all available genotypes, pedigree, local and foreign information in an evaluation can be achieved but adding contributions to left-hand and right-hand sides subtracting double-counted contributions. Correct propagation of external information avoiding double counting of contributions due to relationships and due to records can be achieved. This ssGBayes method computed more accurate predictions for all types of animals. For example, for genotyped animals with low Walloon REL (<0.25) without MACE results but sired by genotyped bulls with MACE results, the average increase of REL for the studied traits was 0.38 points of which 0.08 points could be traced to the inclusion of MACE information. For other categories of genotyped animals, the contribution by MACE information was also high. The Walloon genomic evaluation system passed for the first time the Interbull GEBV tests for several traits in July 2013. Recent experiences reported here refer to its use in April 2016 for the routine genomic evaluations of milk production, udder health and type traits. Results showed that the proposed methodology should also be of interest for other, similar, populations.

Two selectins converge on sulphate. Leukocyte adhesion.

Selectins mediate the attachment of leukocytes to endothelial cells and to platelets under conditions of blood flow. Sulphation of the ligands for two of the selectins is required for optimal cell-cell interactions.

Metabolic selection of glycosylation defects in human cells.

Changes in glycosylation are often associated with disease progression, but the genetic and metabolic basis of these events is rarely understood in detail at a molecular level. We describe a metabolism-based approach to the selection of mutants in glycoconjugate biosynthesis that provides insight into regulatory mechanisms for oligosaccharide expression and metabolic flux. Unnatural intermediates are used to challenge a specific pathway, and cell surface expression of their metabolic products provides a readout of flux in that pathway and a basis for selecting genetic mutants. The approach was applied to the sialic acid metabolic pathway in human cells, yielding novel mutants with phenotypes related to the inborn metabolic defect sialuria and metastatic tumor cells.