Response to Oxidative Burst-Induced Hypoxia Is Associated With Macrophage Inflammatory Profiles as Revealed by Cellular Genome-Wide Association

BackgroundIn mammalian species, hypoxia is a prominent feature of inflammation. The role of hypoxia in regulating macrophage responses via alteration in metabolic pathways is well established. Recently, oxidative burst-induced hypoxia has been shown in murine macrophages after phagocytosis. Despite the available detailed information on the regulation of macrophage function at transcriptomic and epigenomic levels, the association of genetic polymorphism and macrophage function has been less explored. Previously, we have shown that host genetics controls approximately 80% of the variation in an oxidative burst as measured by nitric oxide (NO-). Further studies revealed two clusters of transcription factors (hypoxia-related and inflammatory-related) are under the genetic control that shapes macrophages’ pro-inflammatory characteristics.Material and MethodsIn the current study, the association between 43,066 autosomal Single Nucleic Polymorphism (SNPs) and the ability of MDMs in production of NO- in response to E. coli was evaluated in 58 Holstein cows. The positional candidate genes near significant SNPs were selected to perform functional analysis. In addition, the interaction between the positional candidate genes and differentially expressed genes from our previous study was investigated.ResultsSixty SNPs on 22 chromosomes of the bovine genome were found to be significantly associated with NO- production of macrophages. The functional genomic analysis showed a significant interaction between positional candidate genes and mitochondria-related differentially expressed genes from the previous study. Further examination showed 7 SNPs located in the vicinity of genes with roles in response to hypoxia, shaping approximately 73% of the observed individual variation in NO- production by MDM. Regarding the normoxic condition of macrophage culture in this study, it was hypothesized that oxidative burst is responsible for causing hypoxia at the cellular level.ConclusionThe results suggest that the genetic polymorphism via regulation of response to hypoxia is a candidate step that perhaps shapes macrophage functional characteristics in the pathway of phagocytosis leading to oxidative burst, hypoxia, cellular response to hypoxia and finally the pro-inflammatory responses. Since all cells in one individual carry the same alleles, the effect of genetic predisposition of sensitivity to hypoxia will likely be notable on the clinical outcome to a broad range of host-pathogen interactions

Characteristics of linkage disequilibrium in North American Holsteins

<p>Abstract</p> <p>Background</p> <p>Effectiveness of genomic selection and fine mapping is determined by the level of linkage disequilibrium (LD) across the genome. Knowledge of the range of genome-wide LD, defined as a non-random association of alleles at different loci, can provide an insight into the optimal density and location of single-nucleotide polymorphisms (SNPs) for genome-wide association studies and can be a keystone for interpretation of results from QTL mapping.</p> <p>Results</p> <p>Linkage disequilibrium was measured by |D'| and r²between 38,590 SNPs (spaced across 29 bovine autosomes and the X chromosome) using genotypes of 887 Holstein bulls. The average level of |D'| and r²for markers 40-60 kb apart was 0.72 and 0.20, respectively in Holstein cattle. However, a high degree of heterogeneity of LD was observed across the genome. The sample size and minor allele frequency had an effect on |D'| estimates, however, r²was not noticeably affected by these two factors. Syntenic LD was shown to be useful for verifying the physical location of SNPs. No differences in the extent of LD and decline of LD with distance were found between the intragenic and intergenic regions.</p> <p>Conclusions</p> <p>A minimal sample size of 444 and 55 animals is required for an accurate estimation of LD by |D'| and r², respectively. The use of only maternally inherited haplotypes is recommended for analyses of LD in populations consisting of large paternal half-sib families. Large heterogeneity in the pattern and the extent of LD in Holstein cattle was observed on both autosomes and the X chromosome. The extent of LD was higher on the X chromosome compared to the autosomes.</p

Efficient computation of the inverse of gametic relationship matrix for a marked QTL

Best linear unbiased prediction of genetic merits for a marked quantitative trait locus (QTL) using mixed model methodology includes the inverse of conditional gametic relationship matrix (G-1) for a marked QTL. When accounting for inbreeding, the conditional gametic relationships between two parents of individuals for a marked QTL are necessary to build G-1 directly. Up to now, the tabular method and its adaptations have been used to compute these relationships. In the present paper, an indirect method was implemented at the gametic level to compute these few relationships. Simulation results showed that the indirect method can perform faster with significantly less storage requirements than adaptation of the tabular method. The efficiency of the indirect method was mainly due to the use of the sparseness of G-1. The indirect method can also be applied to construct an approximate G-1 for populations with incomplete marker data, providing approximate probabilities of descent for QTL alleles for individuals with incomplete marker data

Imputation of ungenotyped parental genotypes in dairy and beef cattle from progeny genotypes

peer-reviewedThe objective of this study was to quantify the accuracy of imputing the genotype of parents using information on the genotype of their progeny and a family-based and population-based imputation algorithm. Two separate data sets were used, one containing both dairy and beef animals (n = 3122) with high-density genotypes (735 151 single nucleotide polymorphisms (SNPs)) and the other containing just dairy animals (n = 5489) with medium-density genotypes (51 602 SNPs). Imputation accuracy of three different genotype density panels were evaluated representing low (i.e. 6501 SNPs), medium and high density. The full genotypes of sires with genotyped half-sib progeny were masked and subsequently imputed. Genotyped half-sib progeny group sizes were altered from 4 up to 12 and the impact on imputation accuracy was quantified. Up to 157 and 258 sires were used to test the accuracy of imputation in the dairy plus beef data set and the dairy-only data set, respectively. The efficiency and accuracy of imputation was quantified as the proportion of genotypes that could not be imputed, and as both the genotype concordance rate and allele concordance rate. The median proportion of genotypes per animal that could not be imputed in the imputation process decreased as the number of genotyped half-sib progeny increased; values for the medium-density panel ranged from a median of 0.015 with a half-sib progeny group size of 4 to a median of 0.0014 to 0.0015 with a half-sib progeny group size of 8. The accuracy of imputation across different paternal half-sib progeny group sizes was similar in both data sets. Concordance rates increased considerably as the number of genotyped half-sib progeny increased from four (mean animal allele concordance rate of 0.94 in both data sets for the medium-density genotype panel) to five (mean animal allele concordance rate of 0.96 in both data sets for the medium-density genotype panel) after which it was relatively stable up to a half-sib progeny group size of eight. In the data set with dairy-only animals, sufficient sires with paternal half-sib progeny groups up to 12 were available and the withinanimal mean genotype concordance rates continued to increase up to this group size. The accuracy of imputation was worst for the low-density genotypes, especially with smaller half-sib progeny group sizes but the difference in imputation accuracy between density panels diminished as progeny group size increased; the difference between high and medium-density genotype panels was relatively small across all half-sib progeny group sizes. Where biological material or genotypes are not available on individual animals, at least five progeny can be genotyped (on either a medium or high-density genotyping platform) and the parental alleles imputed with, on average, ⩾96% accuracy

Accuracy of genomic selection in simulated populations mimicking the extent of linkage disequilibrium in beef cattle

<p>Abstract</p> <p>Background</p> <p>The success of genomic selection depends mainly on the extent of linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), the number of animals in the training set (TS) and the heritability (h²) of the trait. The extent of LD depends on the genetic structure of the population and the density of markers. The aim of this study was to calculate accuracy of direct genomic estimated breeding values (DGEBV) using best linear unbiased genomic prediction (GBLUP) for different marker densities, heritabilities and sizes of the TS in simulated populations that mimicked previously reported extent and pattern of LD in beef cattle.</p> <p>Results</p> <p>The accuracy of DGEBV increased significantly (p < 0.05) with the increase in the number of bulls in the TS (480, 960 or 1920), trait h²(0.10, 0.25 or 0.40) and marker densities (40 k or 800 k). Increasing the number of animals in the TS by 4-fold and using their phenotypes to estimate marker effects was not sufficient to maintain or increase the accuracy of DGEBV obtained using estimated breeding values (EBVs) when the trait h²was lower than 0.40 for both marker densities. Comparing to expected accuracies of parent average (PA), the gains by using DGEBV would be of 27%, 13% and 10% for trait h²equal to 0.10, 0.25 and 0.40, respectively, considering the scenario with 40 k markers and 1920 bulls in TS.</p> <p>Conclusions</p> <p>As reported in dairy cattle, the size of the TS and the extent of LD have major impact on the accuracy of DGEBV. Based on the findings of this simulation study, large TS, as well as dense marker panels, aiming to increase the level of LD between markers and QTL, will likely be needed in beef cattle for successful implementation of genomic selection.</p

Short communication: Uncovering quantitative trait loci associated with resistance to Mycobacterium avium ssp. paratuberculosis infection in Holstein cattle using a high-density single nucleotide polymorphism panel

peer-reviewedMycobacterium avium ssp. paratuberculosis (MAP) is the etiological agent of Johne's disease in cattle. Johne's disease is a disease of significant economic, animal welfare, and public health concern around the globe. Therefore, understanding the genetic architecture of resistance to MAP infection has great relevance to advance genetic selection methods to breed more resistant animals. The objectives of this study were to perform a genome-wide association study of previously analyzed 50K genotypes now imputed to a high-density single nucleotide polymorphism panel (777K), aiming to validate previously reported associations and potentially identify additional single nucleotide polymorphisms associated with antibody response to MAP infection. A principal component regression-based genome-wide association study revealed 15 putative quantitative trait loci (QTL) associated with the MAP infection phenotype (serum or milk ELISA tests) on 9 different chromosomes (Bos taurus autosomes 5, 6, 7, 10, 14, 15, 16, 20, and 21). These results validated previous findings and identified new QTL on Bos taurus autosomes 15, 16, 20, and 21. The positional candidate genes NLRP3, IFi47, TRIM41, TNFRSF18, and TNFRSF4 lying within these QTL were identified. Further functional validation of these genes is now warranted to investigate their roles in regulating the immune response and, consequently, cattle resistance to MAP infection

Optimizing Selection of the Reference Population for Genotype Imputation From Array to Sequence Variants

Imputation of high-density genotypes to whole-genome sequences (WGS) is a cost-effective method to increase the density of available markers within a population. Imputed genotypes have been successfully used for genomic selection and discovery of variants associated with traits of interest for the population. To allow for the use of imputed genotypes for genomic analyses, accuracy of imputation must be high. Accuracy of imputation is influenced by multiple factors, such as size and composition of the reference group, and the allele frequency of variants included. Understanding the use of imputed WGSs prior to the generation of the reference population is important, as accurate imputation might be more focused, for instance, on common or on rare variants. The aim of this study was to present and evaluate new methods to select animals for sequencing relying on a previously genotyped population. The Genetic Diversity Index method optimizes the number of unique haplotypes in the future reference population, while the Highly Segregating Haplotype selection method targets haplotype alleles found throughout the majority of the population of interest. First the WGSs of a dairy cattle population were simulated. The simulated sequences mimicked the linkage disequilibrium level and the variants’ frequency distribution observed in currently available Holstein sequences. Then, reference populations of different sizes, in which animals were selected using both novel methods proposed here as well as two other methods presented in previous studies, were created. Finally, accuracies of imputation obtained with different reference populations were compared against each other. The novel methods were found to have overall accuracies of imputation of more than 0.85. Accuracies of imputation of rare variants reached values above 0.50. In conclusion, if imputed sequences are to be used for discovery of novel associations between variants and traits of interest in the population, animals carrying novel information should be selected and, consequently, the Genetic Diversity Index method proposed here may be used. If sequences are to be used to impute the overall genotyped population, a reference population consisting of common haplotypes carriers selected using the proposed Highly Segregating Haplotype method is recommended

The genetic architecture of milk ELISA scores as an indicator of Johne's disease (paratuberculosis) in dairy cattle

peer-reviewedJohne's disease (or paratuberculosis), caused by Mycobacterium avium ssp. paratuberculosis (MAP) infection, is a globally prevalent disease with severe economic and welfare implications. With no effective treatment available, understanding the role of genetics influencing host infection status is essential to develop selection strategies to breed for increased resistance to MAP infection. The main objectives of this study were to estimate genetic parameters for the MAP-specific antibody response using milk ELISA scores in Canadian Holstein cattle as an indicator of resistance to Johne's disease, and to unravel genomic regions and candidate genes significantly associated with MAP infection. After data editing, 168,987 milk ELISA records from 2,306 herds, obtained from CanWest Dairy Herd Improvement, were used for further analyses. Variance and heritability estimates for MAP infection status were determined using univariate linear animal models under 3 scenarios: (a) SCEN1: the complete data set (all herds); (b) SCEN2: herds with at least one suspect or test-positive animal (ELISA optical density ≥0.07); and (c) SCEN3: herds with at least one test-positive animal (ELISA optical density ≥0.11). Heritability estimates were calculated as 0.066, 0.064, and 0.063 for SCEN1, SCEN2, and SCEN3, respectively. The correlations between estimated breeding values for resistance to MAP infection and other economically important traits, when significant, were favorable and of low magnitude. Genome-wide association analyses identified important genomic regions on Bos taurus autosome (BTA)1, BTA7, BTA9, BTA14, BTA15, BTA17, BTA19, and BTA25 showing significant association with MAP infection status. These regions included 2 single nucleotide polymorphisms located 2 kb upstream of positional candidate genes CD86 and WNT9B, which play key roles in host immune response and tissue homeostasis. This study revealed the genetic architecture of MAP infection in Canadian Holstein cattle as measured by milk ELISA scores by estimating genetic parameters along with the identification of genomic regions potentially influencing MAP infection status. These findings will be of significant value toward implementing genetic and genomic evaluations for resistance to MAP infection in Holstein cattle