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Avendano-Reyes L.,Mississippi State University | Avendano-Reyes L.,Autonomous University of Baja California | Fuquay J.W.,Mississippi State University | Moore R.B.,Mississippi State University | And 4 more authors.
Tropical Animal Health and Production | Year: 2010

To estimate the relationship between heat stress during the last 60 days prepartum, body condition score and certain reproductive traits in the subsequent lactation of Holstein cows, 564 multiparous cows and 290 primiparous cows from four dairy herds were used in a hot, humid region. Maximum prepartum degree days were estimated to quantify the degree of heat stress. Multiple regressions analyses and logistic regression analysis were performed to determine the effect of prepartum heat stress and body condition change on reproductive parameters, which were obtained from DHIA forms at the end of the lactation. Multiparous and primiparous cows which gained body condition score from calving to 60 d postpartum exhibited 28 and 27 fewer days open (P < 0.05), respectively, than cows not gaining. There was no effect (P > 0.05) of heat stress measurement on days open or services per conception in either multiparous or primiparous cows. During hotter months of calving, multiparous cows showed higher services per conception and primiparous cows showed higher days open and services per conception (P < 0.05). Maximum prepartum degree-days were positively associated (P < 0.05) with calving difficulty score. Multiparous cows with high body condition score at calving were 1.47 times more likely to present a very difficult calving than cows that calved in October (P < 0.05). Collectively, these results suggest that reproductive performance was not affected by cumulative prepartum heat stress although it was associated with very difficult calving score. © Springer Science+Business Media B.V. 2009.

Tiezzil F.,North Carolina State University | Parker-Gaddis K.L.,North Carolina State University | Parker-Gaddis K.L.,U.S. Department of Agriculture | Cole J.B.,U.S. Department of Agriculture | And 2 more authors.
PLoS ONE | Year: 2015

Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profitability and animal welfare. The objective of this study was to perform a genome-wide association study (GWAS) for CM in first-lactation Holstein. Producer-recorded mastitis event information for 103,585 first-lactation cows were used, together with genotype information on 1,361 bulls from the Illumina BovineSNP50 BeadChip. Single-step genomic-BLUP methodology was used to incorporate genomic data into a threshold-liability model. Association analysis confirmed that CM follows a highly polygenic mode of inheritance. However, 10-adjacent- SNP windows showed that regions on chromosomes 2, 14 and 20 have impacts on genetic variation for CM. Some of the genes located on chromosome 14 (LY6K, LY6D, LYNX1, LYPD2, SLURP1, PSCA) are part of the lymphocyte-antigen-6 complex (LY6) known for its neutrophil regulation function linked to the major histocompatibility complex. Other genes on chromosome 2 were also involved in regulating immune response (IFIH1, LY75, and DPP4), or are themselves regulated in the presence of specific pathogens (ITGB6, NR4A2). Other genes annotated on chromosome 20 are involved in mammary gland metabolism (GHR, OXCT1), antibody production and phagocytosis of bacterial cells (C6, C7, C9, C1QTNF3), tumor suppression (DAB2), involution of mammary epithelium (OSMR) and cytokine regulation (PRLR). DAVID enrichment analysis revealed 5 KEGG pathways. The JAK-STAT signaling pathway (cell proliferation and apoptosis) and the 'Cytokine-cytokine receptor interaction' (cytokine and interleukines response to infectious agents) are co-regulated and linked to the 'ABC transporters' pathway also found here. Gene network analysis performed using GeneMania revealed a co-expression network where 665 interactions existed among 145 of the genes reported above. Clinical mastitis is a complex trait and the different genes regulating immune response are known to be pathogen-specific. Despite the lack of information in this study, candidate QTL for CM were identified in the US Holstein population.

Parker Gaddis K.L.,University of Florida | Cole J.B.,U.S. Department of Agriculture | Clay J.S.,Dairy Records Management Systems | Maltecca C.,North Carolina State University
Journal of Dairy Science | Year: 2016

Genetic improvement of dairy cattle health through the use of producer-recorded data has been determined to be feasible. Low estimated heritabilities indicate that genetic progress will be slow. Variation observed in lowly heritable traits can largely be attributed to nongenetic factors, such as the environment. More rapid improvement of dairy cattle health may be attainable if herd health programs incorporate environmental and managerial aspects. More than 1,100 herd characteristics are regularly recorded on farm test-days. We combined these data with producer-recorded health event data, and parametric and nonparametric models were used to benchmark herd and cow health status. Health events were grouped into 3 categories for analyses: mastitis, reproductive, and metabolic. Both herd incidence and individual incidence were used as dependent variables. Models implemented included stepwise logistic regression, support vector machines, and random forests. At both the herd and individual levels, random forest models attained the highest accuracy for predicting health status in all health event categories when evaluated with 10-fold cross-validation. Accuracy (SD) ranged from 0.61 (0.04) to 0.63 (0.04) when using random forest models at the herd level. Accuracy of prediction (SD) at the individual cow level ranged from 0.87 (0.06) to 0.93 (0.001) with random forest models. Highly significant variables and key words from logistic regression and random forest models were also investigated. All models identified several of the same key factors for each health event category, including movement out of the herd, size of the herd, and weather-related variables. We concluded that benchmarking health status using routinely collected herd data is feasible. Nonparametric models were better suited to handle this complex data with numerous variables. These data mining techniques were able to perform prediction of health status and could add evidence to personal experience in herd management. © 2016 American Dairy Science Association.

Parker Gaddis K.L.,North Carolina State University | Cole J.B.,U.S. Department of Agriculture | Clay J.S.,Dairy Records Management Systems | Maltecca C.,North Carolina State University
Journal of Dairy Science | Year: 2014

Emphasizing increased profit through increased dairy cow production has revealed a negative relationship of production with fitness and health traits. Decreased cow health can affect herd profitability through increased rates of involuntary culling and decreased or lost milk sales. The development of genomic selection methodologies, with accompanying substantial gains in reliability for low-heritability traits, may dramatically improve the feasibility of genetic improvement of dairy cow health. Producer-recorded health information may provide a wealth of information for improvement of dairy cow health, thus improving profitability. The principal objective of this study was to use health data collected from on-farm computer systems in the United States to estimate variance components and heritability for health traits commonly experienced by dairy cows. A single-step analysis was conducted to estimate genomic variance components and heritabilities for health events, including cystic ovaries, displaced abomasum, ketosis, lameness, mastitis, metritis, and retained placenta. A blended H matrix was constructed for a threshold model with fixed effects of parity and year-season and random effects of herd-year and sire. The single-step genomic analysis produced heritability estimates that ranged from 0.02 (standard deviation = 0.005) for lameness to 0.36 (standard deviation = 0.08) for retained placenta. Significant genetic correlations were found between lameness and cystic ovaries, displaced abomasum and ketosis, displaced abomasum and metritis, and retained placenta and metritis. Sire reliabilities increased, on average, approximately 30% with the incorporation of genomic data. From the results of these analyses, it was concluded that genetic selection for health traits using producer-recorded data are feasible in the United States, and that the inclusion of genomic data substantially improves reliabilities for these traits. © 2014 American Dairy Science Association.

Dhakal K.,North Carolina State University | Tiezzi F.,North Carolina State University | Clay J.S.,Dairy Records Management Systems | Maltecca C.,North Carolina State University
Journal of Dairy Science | Year: 2015

Hoof lesions contributing to lameness are crucial economic factors that hinder the profitability of dairy enterprises. Producer-recorded hoof lesions data of US Holsteins were categorized into infectious (abscess, digital and interdigital dermatitis, heel erosion, and foot rot) and noninfectious (korn, corkscrew, sole and toe ulcer, sole hemorrhage, white line separation, fissures, thin soles, and upper leg lesions) categories of hoof lesions. Pedigree- and genomic-based univariate analyses were conducted to estimate the variance components and heritability of infectious and noninfectious hoof lesions. A threshold sire model was used with fixed effects of year-seasons and random effects of herd and sire. For genomic-based analysis, a single-step procedure was conducted, incorporating H matrix to estimate genomic variance components and heritability for hoof lesions. The pedigree-based analysis produced heritability estimates of 0.11 (±0.05) for infectious hoof lesions and 0.08 (±0.05) for noninfectious hoof lesions. The single-step genomic analysis produced heritability estimates of 0.14 (±0.06) for infectious hoof lesions and 0.12 (±0.08) for noninfectious hoof lesions. Approximated genetic correlations between hoof lesion traits and hoof type traits along with productive life and net merit were all low and ranged between -0.25 and 0.14. Sire reliabilities increased, on average, by 0.24 and 0.18 for infectious and noninfectious hoof lesions, respectively, with incorporation of genomic data. © 2015 American Dairy Science Association.

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