Publications by authors named "G S Plastow"

183 Publications

Multiple Country Approach to Improve the Test-Day Prediction of Dairy Cows' Dry Matter Intake.

Animals (Basel) 2021 May 4;11(5). Epub 2021 May 4.

AGROBIOCHEM Department, Research and Teaching Centre (TERRA), Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium.

We predicted dry matter intake of dairy cows using parity, week of lactation, milk yield, milk mid-infrared (MIR) spectrum, and MIR-based predictions of bodyweight, fat, protein, lactose, and fatty acids content in milk. The dataset comprised 10,711 samples of 534 dairy cows with a geographical diversity (Australia, Canada, Denmark, and Ireland). We set up partial least square (PLS) regressions with different constructs and a one-hidden-layer artificial neural network (ANN) using the highest contribution variables. In the ANN, we replaced the spectra with their projections to the 25 first PLS factors explaining 99% of the spectral variability to reduce the model complexity. Cow-independent 10 × 10-fold cross-validation (CV) achieved the best performance with root mean square errors (RMSE) of 3.27 ± 0.08 kg for the PLS regression and 3.25 ± 0.13 kg for ANN. Although the available data were significantly different, we also performed a country-independent validation (CIV) to measure the models' performance fairly. We found RMSE varying from 3.73 to 6.03 kg for PLS and 3.69 to 5.08 kg for ANN. Ultimately, based on the country-independent validation, we discussed the developed models' performance with those achieved by the National Research Council's equation.
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http://dx.doi.org/10.3390/ani11051316DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8147833PMC
May 2021

Validation of Dairy Cow Bodyweight Prediction Using Traits Easily Recorded by Dairy Herd Improvement Organizations and Its Potential Improvement Using Feature Selection Algorithms.

Animals (Basel) 2021 Apr 30;11(5). Epub 2021 Apr 30.

AGROBIOCHEM Department, Research and Teaching Centre (TERRA), Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium.

Knowing the body weight (BW) of a cow at a specific moment or measuring its changes through time is of interest for management purposes. The current work aimed to validate the feasibility of predicting BW using the day in milk, parity, milk yield, and milk mid-infrared (MIR) spectrum from a multiple-country dataset and reduce the number of predictors to limit the risk of over-fitting and potentially improve its accuracy. The BW modeling procedure involved feature selections and herd-independent validation in identifying the most interesting subsets of predictors and then external validation of the models. From 1849 records collected in 9 herds from 360 Holstein cows, the best performing models achieved a root mean square error (RMSE) for the herd-independent validation between 52 ± 2.34 kg to 56 ± 3.16 kg, including from 5 to 62 predictors. Among these models, three performed remarkably well in external validation using an independent dataset (N = 4067), resulting in RMSE ranging from 52 to 56 kg. The results suggest that multiple optimal BW predictive models coexist due to the high correlations between adjacent spectral points.
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http://dx.doi.org/10.3390/ani11051288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145206PMC
April 2021

Proliferation of Peripheral Blood Mononuclear Cells From Healthy Piglets After Mitogen Stimulation As Indicators of Disease Resilience.

J Anim Sci 2021 May 4. Epub 2021 May 4.

Department of Large Animal Clinical Sciences, University of Saskatchewan, Saskatoon, SK, Canada.

Disease resilience refers to productivity of an animal under disease. Given the high biosecurity of pig nucleus herds, traits that can be measured on healthy pigs and that are genetically correlated with disease resilience, i.e. genetic indicator traits, offer a strategy to select for disease resilience. Our objective was to evaluate mitogen stimulation assays on peripheral blood mononuclear cells from young healthy pigs as genetic indicators for disease resilience. Data were from a natural disease challenge in which batches of 60 or 75 naïve Yorkshire x Landrace piglets were introduced every three weeks into a continuous flow barn that was seeded with multiple diseases. In this environment, disease resilience traits, including growth, treatment, and mortality rates, were recorded on 3136 pigs that were genotyped with a high-density marker panel. Peripheral blood mononuclear cells from 882 of these pigs from 19 batches were isolated from whole blood collected prior to the disease challenge and stimulated with five mitogens: concanavalin A (ConA), phytohemagglutinin (PHA), pokeweed mitogen (PWM), lipopolysaccharide (LPS), and phorbol myristate acetate (PMA). Proliferation of cells was evaluated at 48, 72, and 96 hrs and compared to unstimulated samples (rest count). Heritabilities of cell proliferation were estimated using a model with batch as a fixed effect, covariates of entry age, rest count, and complete blood count proportions of lymphocytes, monocytes, eosinophils, and basophils, and pen, litter, and animal genetics as random effects. Heritability estimates were highest for response to ConA (0.30+0.09, 0.28+0.10, 0.17+0.10, and 0.25+0.10 at 48, 72, and 96 hrs after stimulation and for area under the curve across the three time points, respectively). Estimates were in a similar range for response to PHA and PMA, but low for PWM and LPS. Responses to ConA, PHA, and PMA were moderately genetically correlated with several disease resilience traits and in the expected direction but individual estimates were not significantly different from zero due to large standard errors. In conclusion, although validation is needed, mitogen stimulation assays, in particular based on ConA, show promise as genetic indicator traits for disease resilience.
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http://dx.doi.org/10.1093/jas/skab084DOI Listing
May 2021

Abundance and Expression of Shiga Toxin Genes in at the Recto-Anal Junction Relates to Host Immune Genes.

Front Cell Infect Microbiol 2021 17;11:633573. Epub 2021 Mar 17.

Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.

Shiga toxin (Stx) is the main virulence factor of Shiga toxin-producing  (STEC), and ruminants are the main reservoir of STEC. This study assessed the abundance and expression of genes and the expression of host immune genes, aiming to determine factors affecting these measures and potential gene markers to differentiate gene expression in the recto-anal junction of feedlot beef cattle. Rectal tissue and content samples were collected from 143 feedlot steers of three breeds (Angus, Charolais, and Kinsella Composite) over 2 consecutive years 2014 (n=71) and 2015 (n=72). The abundance and expression of  and  were quantified using qPCR and reverse-transcription-qPCR (RT-qPCR), respectively. Four immune genes (, and ), previously reported to be down-regulated in super-shedder cattle (i.e., > 10 CFU g) were selected, and their expression was evaluated using RT-qPCR. The gene abundance was only detected in tissue samples collected in year 2 and did not differ among breeds. The gene was detected in STEC from all samples collected in both years and did not vary among breeds. The abundance of and  differed (P < 0.001) in content samples collected across breeds (:AN>CH>KC, : AN=CH>KC) in year 1, but not in year 2. Expression of was detected in 13 RAJ tissue samples (2014: n=6, 2015: n=7), while expression of was not detected. Correlation analysis showed that the expression of was negatively correlated with the expression of  (R=-0.56, P=0.05) and positively correlated with the expression of (R=0.60, P=0.05). The random forest model and Boruta method revealed that expression of selected immune genes could be predictive indicators of expression with prediction accuracy of  > > >. Our results indicate that the abundance of could be affected by cattle breed and sampling year, suggesting that host genetics and environment may influence STEC colonization of the recto-anal junction of feedlot cattle. Additionally, the identified relationship between expressions of host immune genes and suggests that the host animal may regulate expression in colonizing STEC through immune functions.
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http://dx.doi.org/10.3389/fcimb.2021.633573DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010187PMC
March 2021

Whole-Blood Transcriptome Analysis of Feedlot Cattle With and Without Bovine Respiratory Disease.

Front Genet 2021 8;12:627623. Epub 2021 Mar 8.

Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton, AB, Canada.

Bovine respiratory disease (BRD) is one of the main factors leading to morbidity and mortality in feedlot operations in North America. A complex of viral and bacterial pathogens can individually or collectively establish BRD in cattle, and to date, most disease characterization studies using transcriptomic techniques examine bronchoalveolar and transtracheal fluids, lymph node, and lung tissue as well as nasopharyngeal swabs, with limited studies investigating the whole-blood transcriptome. Here, we aimed to identify differentially expressed (DE) genes involved in the host immune response to BRD using whole blood and RNA sequencing. Samples were collected from heifers (average arrival weight = 215.0 ± 5.3 kg) with ( = 25) and without ( = 18) BRD at a commercial feedlot in Western Canada. RNAseq analysis showed a distinct whole-blood transcriptome profile between BRD and non-BRD heifers. Further examination of the DE genes revealed that those involved in the host inflammatory response and infectious disease pathways were enriched in the BRD animals, while gene networks associated with metabolism and cell growth and maintenance were downregulated. Overall, the transcriptome profile derived from whole blood provided evidence that a distinct antimicrobial peptide-driven host immune response was occurring in the animals with BRD. The blood transcriptome of the BRD animals shows similarities to the transcriptome profiles obtained from lung and bronchial lymph nodes in other studies. This suggests that the blood transcriptome is a potential diagnostic tool for the identification of biomarkers of BRD infection and can be measured in live animals and used to further understand infection and disease in cattle. It may also provide a useful tool to increase the understanding of the genes involved in establishing BRD in beef cattle and be used to investigate potential therapeutic applications.
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http://dx.doi.org/10.3389/fgene.2021.627623DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7982659PMC
March 2021