Dataset Information

Association of genetic polymorphisms related to Johne's disease with estimated breeding values of Holstein sires for milk ELISA test scores.

ABSTRACT:

Background

Johne's disease (JD) is a chronic intestinal inflammatory disease caused by Mycobacterium avium subsp. paratuberculosis (MAP) infection in ruminants. Since there are currently no effective vaccine or treatment options available to control JD, genetic selection may be an alternative strategy to enhance JD resistance. Numerous Single Nucleotide Polymorphisms (SNPs) have been reported to be associated with MAP infection status based on published genome-wide association and candidate gene studies. The main objective of this study was to validate these SNPs that were previously identified to be associated with JD by testing their effect on Holstein bulls' estimated breeding values (EBVs) for milk ELISA test scores, an indirect indicator of MAP infection status in cattle.

Results

Three SNPs, rs41810662, rs41617133 and rs110225854, located on Bos taurus autosomes (BTA) 16, 23 and 26, respectively, were confirmed as significantly associated with Holstein bulls' EBVs for milk ELISA test score (FDR?ConclusionsThe findings of this study validate the association of SNPs with JD MAP infection status and highlight the need to further investigate the genomic regions harboring these SNPs.

SUBMITTER: Mallikarjunappa S

PROVIDER: S-EPMC7254716 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

Association of genetic polymorphisms related to Johne's disease with estimated breeding values of Holstein sires for milk ELISA test scores.

Mallikarjunappa Sanjay S Schenkel Flavio S FS Brito Luiz F LF Bissonnette Nathalie N Miglior Filippo F Chesnais Jacques J Lohuis Michael M Meade Kieran G KG Karrow Niel A NA

BMC veterinary research 20200527 1

<h4>Background</h4>Johne's disease (JD) is a chronic intestinal inflammatory disease caused by Mycobacterium avium subsp. paratuberculosis (MAP) infection in ruminants. Since there are currently no effective vaccine or treatment options available to control JD, genetic selection may be an alternative strategy to enhance JD resistance. Numerous Single Nucleotide Polymorphisms (SNPs) have been reported to be associated with MAP infection status based on published genome-wide association and candid ...[more]

PMID: 32460776

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Project description:Little is known about the correlations between the genetic susceptibility/resistance to Mycobacterium avium subsp. paratuberculosis (Map) infection and the estimated breeding values for type, production and functional traits. Previously, we identified 70 combinations of five single nucleotide polymorphisms (SNPs) in four bovine innate immune genes (SLC11A1, SP110, TLR2, CD209) that are associated with the genetic risk of paratuberculosis (PTB) or Johne's disease progression, which can be graded as low (LOWIN), latent (LATIN), or patent (PATIN) risk. Other possible combinations of these 5 SNPs were grouped in the average group (AVERIN). In the current study, differences in estimated breeding values (EBVs) for several traits were analyzed using linear models in a large cohort of Holstein cows (N = 15656) genotyped across Spain in 2016 or 2017. After the assignment of each genotyped cow to a risk group, cows within the PATIN risk group (N = 1448) had a superior combined genetic index (2797.57), type genetic index (524.62), milk yield (653.92 kg), protein yield (21.77 kg), fat yield (24.82 kg) and economic merit index (125 Euros) compared with the other three risk groups. Statistically significant differences in the longevity scores between the cows that were included in the PATIN risk group (108.85) and the LOWIN (107.82) and AVERIN (107.92) groups were also observed. The associations between the genetic risk groups and PTB diagnostic results were validated in a population of 99 cows from a Spanish farm with a high prevalence of PTB. Significant differences in ELISA readings between the PATIN (65.49 %) and the AVERIN (15.97 %), LATIN (2.11 %), and LOWIN (3.27 %) groups were observed. In addition, significant differences in Map DNA copies/gram of feces were observed between the PATIN and the other three risk groups. These results together with the substantial economic impact of PTB in dairy cattle support the selection of the animals with less susceptibility to PTB in the Spanish breeding program.

Project description:Two hip quality phenotypes-a hip-extended score assigned by a board certified radiologist and the PennHIP distraction index-were analyzed to estimate genetic parameters and to calculate estimated breeding values used for selecting replacement breeders. Radiographs obtained at 12-18 months of age were available on 5,201 German Shepherd Dogs, 4,987 Labrador Retrievers and 2,308 Golden Retrievers. Obtained by fitting a two-trait model using Bayesian techniques, estimates of heritability for the hip-extended score were 0.76, 0.72, and 0.41 in German Shepherd Dogs, Labrador Retrievers, and Golden Retrievers, respectively, while estimated heritabilities for distraction index were 0.60, 0.66 and 0.59, respectively. Genetic correlations between the two hip quality measures were -0.28 in German Shepherd Dogs, -0.21 in Labrador Retrievers, and -0.29 in Golden Retrievers. Genetic selection for improved hip quality based upon the hip extended score phenotype began in 1980. Among first generation puppies, 34% of 273 German Shepherd Dogs, 55% of 323 Labrador Retrievers, and 43% of 51 Golden Retrievers had an Excellent hip extended score. After 8 generations of selection, mostly based on estimated breeding values derived from the hip extended score, over 93% of 695 German Shepherd Dogs, 94% of 528 Labrador Retrievers, and 87% of 116 Golden Retrievers received an Excellent hip extended score. With respect to PennHIP distraction index values among these same dogs, median values were at or above 0.30 for all 3 breeds meaning that half or more of dogs possessing the Excellent hip-extended-score phenotype remained susceptible to developing the osteoarthritis of canine hip dysplasia. Genetic improvement of the hip-extended-view phenotype to its desired biological endpoint left a surprising proportion of dogs expressing sufficient joint laxity to place them in an osteoarthritis at-risk state as they age. Only by directly applying selection pressure to reduce distraction index was marked reduction in joint laxity noted.

Project description:BackgroundThe impact of additive-genetic relationships captured by single nucleotide polymorphisms (SNPs) on the accuracy of genomic breeding values (GEBVs) has been demonstrated, but recent studies on data obtained from Holstein populations have ignored this fact. However, this impact and the accuracy of GEBVs due to linkage disequilibrium (LD), which is fairly persistent over generations, must be known to implement future breeding programs.Materials and methodsThe data set used to investigate these questions consisted of 3,863 German Holstein bulls genotyped for 54,001 SNPs, their pedigree and daughter yield deviations for milk yield, fat yield, protein yield and somatic cell score. A cross-validation methodology was applied, where the maximum additive-genetic relationship (amax) between bulls in training and validation was controlled. GEBVs were estimated by a Bayesian model averaging approach (BayesB) and an animal model using the genomic relationship matrix (G-BLUP). The accuracy of GEBVs due to LD was estimated by a regression approach using accuracy of GEBVs and accuracy of pedigree-based BLUP-EBVs.ResultsAccuracy of GEBVs obtained by both BayesB and G-BLUP decreased with decreasing amax for all traits analyzed. The decay of accuracy tended to be larger for G-BLUP and with smaller training size. Differences between BayesB and G-BLUP became evident for the accuracy due to LD, where BayesB clearly outperformed G-BLUP with increasing training size.ConclusionsGEBV accuracy of current selection candidates varies due to different additive-genetic relationships relative to the training data. Accuracy of future candidates can be lower than reported in previous studies because information from close relatives will not be available when selection on GEBVs is applied. A Bayesian model averaging approach exploits LD information considerably better than G-BLUP and thus is the most promising method. Cross-validations should account for family structure in the data to allow for long-lasting genomic based breeding plans in animal and plant breeding.

Project description:This study investigated the main factors influencing the genetic variance and the variance of breeding values (EBV). The first is the variance of genetic values in the base population, and the latter is the variance of genetic values in the population under evaluation. These variances are important as improper variances can lead to systematic bias. The inverse of the genetic relationship matrix (K -1) and the phenotypic variance are the main factors influencing the genetic variance and heritability (h2). These factors and h2 are also the main factors influencing the variance of EBVs. Pedigree- and genomic-based relationship matrices (A and G as K) and phenotypes on 599 wheat lines were used. Also, data were simulated, and a hybrid (genomic-pedigree) relationship matrix (H as K) and phenotypes were used. First, matrix K underwent a transformation (K* = w K + α 11' + β I), and the responses in the mean and variation of diag(K -1) and offdiag(K -1) elements, and genetic variance in the form of h2 were recorded. Then, the original K was inverted, and matrix K -1 underwent the same transformations as K, and the responses in the h2 estimate and the variance of EBVs in the forms of correlation and regression coefficients with the EBVs estimated based on the original K -1 were recorded. In response to weighting K by w, the estimated genetic variance changed by 1/w. We found that μ(diag(K)) - μ(offdiag(K)) influences the genetic variance. As such, α did not change the genetic variance, and increasing β increased the estimated genetic variance. Weighting K -1 by w was equivalent to weighting K by 1/w. Using the weighted K -1 together with its corresponding h2, EBVs remained unchanged, which shows the importance of using variance components that are compatible with the K -1. Increasing β I added to K -1 increased the estimated genetic variance, and the effect of α 11' was minor. We found that larger variation of diag(K -1) and higher concentration of offdiag(K -1) around the mean (0) are responsible for lower h2 estimate and variance of EBVs.

Dataset Information

Association of genetic polymorphisms related to Johne's disease with estimated breeding values of Holstein sires for milk ELISA test scores.

Background

Results

Publications

Association of genetic polymorphisms related to Johne's disease with estimated breeding values of Holstein sires for milk ELISA test scores.

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