K. L. Weber

Hot topic: Performance of bovine high-density genotyping platforms in Holsteins and Jerseys

Two high-density single nucleotide polymorphism (SNP) genotyping arrays have recently become available for bovine genomic analyses, the Illumina High-Density Bovine BeadChip Array (777,962 SNP) and the Affymetrix Axiom Genome-Wide BOS 1 Array (648,874 SNP). These products each have unique design and chemistry attributes, and the extent of marker overlap and their potential utility for quantitative trait loci fine mapping, detection of copy number variation, and multibreed genomic selection are of significant interest to the cattle community. This is the first study to compare the performance of these 2 arrays. Deoxyribonucleic acid samples from 16 dairy cattle (10 Holstein, 6 Jersey) were used for the comparison. An independent set of DNA samples taken from 46 Jersey cattle and 18 Holstein cattle were used to ascertain the amount of SNP variation accounted by the 16 experimental samples. Data were analyzed with SVS7 software (Golden Helix Inc., Bozeman, MT) to remove SNP having a call rate less than 90%, and linkage disequilibrium pruning was used to remove linked SNP (r² ≥ 0.9). Maximum, average, and median gaps were calculated for each analysis based on genomic position of SNP on the bovine UMD3.1 genome assembly. All samples were successfully genotyped (≥ 98% SNP genotyped) with both platforms. The average number of genotyped SNP in the Illumina platform was 775,681 and 637,249 for the Affymetrix platform. Based on genomic position, a total of 107,896 SNP were shared between the 2 platforms; however, based on genotype concordance, only 96,031 SNP had complete concordance at these loci. Both Affymetrix BOS 1 and Illumina BovineHD genotyping platforms are well designed and provide high-quality genotypes and similar coverage of informative SNP. Despite fewer total SNP on BOS 1, 19% more SNP remained after linkage disequilibrium pruning, resulting in a smaller gap size (5.2 vs. 6.9 kb) in Holstein and Jersey samples relative to BovineHD. However, only 224,115 Illumina and 241,038 Affymetrix SNP remained following removal of SNP with a minor allele frequency of zero in Holstein and Jersey samples, resulting in an average gap size of 11,887 bp and 11,018 bp, respectively. Combining the 354,348 informative (r² ≥ 0.9), polymorphic (minor allele frequency ≥ 0), unique SNP data from both platforms decreased the average gap size to 7,560 bp. Genome-wide copy number variant analyses were performed using intensity files from both platforms. The BovineHD platform provided an advantage to the copy number variant data compared with the BOS 1 because of the larger number of SNP, higher intensity signals, and lower background effects. The combined use of both platforms significantly improved coverage over either platform alone and decreased the gap size between SNP, providing a valuable tool for fine mapping quantitative trait loci and multibreed animal evaluation.

Complex I-associated hydrogen peroxide production is decreased and electron transport chain enzyme activities are altered in n-3 enriched fat-1 mice.

The polyunsaturated nature of n-3 fatty acids makes them prone to oxidative damage. However, it is not clear if n-3 fatty acids are simply a passive site for oxidative attack or if they also modulate mitochondrial reactive oxygen species (ROS) production. The present study used fat-1 transgenic mice, that are capable of synthesizing n-3 fatty acids, to investigate the influence of increases in n-3 fatty acids and resultant decreases in the n-6∶n-3 ratio on liver mitochondrial H2O2 production and electron transport chain (ETC) activity. There was an increase in n-3 fatty acids and a decrease in the n-6∶n-3 ratio in liver mitochondria from the fat-1 compared to control mice. This change was largely due to alterations in the fatty acid composition of phosphatidylcholine and phosphatidylethanolamine, with only a small percentage of fatty acids in cardiolipin being altered in the fat-1 animals. The lipid changes in the fat-1 mice were associated with a decrease (p<0.05) in the activity of ETC complex I and increases (p<0.05) in the activities of complexes III and IV. Mitochondrial H2O2 production with either succinate or succinate/glutamate/malate substrates was also decreased (p<0.05) in the fat-1 mice. This change in H2O2 production was due to a decrease in ROS production from ETC complex I in the fat-1 animals. These results indicate that the fatty acid changes in fat-1 liver mitochondria may at least partially oppose oxidative stress by limiting ROS production from ETC complex I.

Accuracy of genomic breeding values in multibreed beef cattle populations derived from deregressed breeding values and phenotypes.

Genomic selection involves the assessment of genetic merit through prediction equations that allocate genetic variation with dense marker genotypes. It has the potential to provide accurate breeding values for selection candidates at an early age and facilitate selection for expensive or difficult to measure traits. Accurate across-breed prediction would allow genomic selection to be applied on a larger scale in the beef industry, but the limited availability of large populations for the development of prediction equations has delayed researchers from providing genomic predictions that are accurate across multiple beef breeds. In this study, the accuracy of genomic predictions for 6 growth and carcass traits were derived and evaluated using 2 multibreed beef cattle populations: 3,358 crossbred cattle of the U.S. Meat Animal Research Center Germplasm Evaluation Program (USMARC_GPE) and 1,834 high accuracy bull sires of the 2,000 Bull Project (2000_BULL) representing influential breeds in the U.S. beef cattle industry. The 2000_BULL EPD were deregressed, scaled, and weighted to adjust for between- and within-breed heterogeneous variance before use in training and validation. Molecular breeding values (MBV) trained in each multibreed population and in Angus and Hereford purebred sires of 2000_BULL were derived using the GenSel BayesCπ function (Fernando and Garrick, 2009) and cross-validated. Less than 10% of large effect loci were shared between prediction equations trained on (USMARC_GPE) relative to 2000_BULL although locus effects were moderately to highly correlated for most traits and the traits themselves were highly correlated between populations. Prediction of MBV accuracy was low and variable between populations. For growth traits, MBV accounted for up to 18% of genetic variation in a pooled, multibreed analysis and up to 28% in single breeds. For carcass traits, MBV explained up to 8% of genetic variation in a pooled, multibreed analysis and up to 42% in single breeds. Prediction equations trained in multibreed populations were more accurate for Angus and Hereford subpopulations because those were the breeds most highly represented in the training populations. Accuracies were less for prediction equations trained in a single breed due to the smaller number of records derived from a single breed in the training populations.

Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq.

Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for feed efficiency affects many underlying molecular networks and physiological traits. This study describes the differences between steer progeny of two influential Angus bulls with divergent genomic predictions for residual feed intake (RFI). Eight steer progeny of each sire were phenotyped for growth and feed intake from 8 mo. of age (average BW 254 kg, with a mean difference between sire groups of 4.8 kg) until slaughter at 14–16 mo. of age (average BW 534 kg, sire group difference of 28.8 kg). Terminal samples from pituitary gland, skeletal muscle, liver, adipose, and duodenum were collected from each steer for transcriptome sequencing. Gene expression networks were derived using partial correlation and information theory (PCIT), including differentially expressed (DE) genes, tissue specific (TS) genes, transcription factors (TF), and genes associated with RFI from a genome-wide association study (GWAS). Relative to progeny of the high RFI sire, progeny of the low RFI sire had -0.56 kg/d finishing period RFI (P = 0.05), -1.08 finishing period feed conversion ratio (P = 0.01), +3.3 kg^0.75 finishing period metabolic mid-weight (MMW; P = 0.04), +28.8 kg final body weight (P = 0.01), -12.9 feed bunk visits per day (P = 0.02) with +0.60 min/visit duration (P = 0.01), and +0.0045 carcass specific gravity (weight in air/weight in air—weight in water, a predictor of carcass fat content; P = 0.03). RNA-seq identified 633 DE genes between sire groups among 17,016 expressed genes. PCIT analysis identified >115,000 significant co-expression correlations between genes and 25 TF hubs, i.e. controllers of clusters of DE, TS, and GWAS SNP genes. Pathway analysis suggests low RFI bull progeny possess heightened gut inflammation and reduced fat deposition. This multi-omics analysis shows how differences in RFI genomic breeding values can impact other traits and gene co-expression networks.

The accuracies of DNA-based estimates of genetic merit derived from Angus or multibreed beef cattle training populations 1,2,3

Several organizations have developed prediction models for molecular breeding values (MBV) for quantitative growth and carcass traits in beef cattle using Bovine SNP50 genotypes and phenotypic or EBV data. Molecular breeding values for Angus cattle have been developed by IGENITY, Pfizer Animal Genetics, and a collaboration between researchers from Iowa State University and the University of Missouri-Columbia (ISU/UMC). The U.S. Meat Animal Research Center (USMARC; Clay Center, NE) has also developed MBV for 16 cattle breeds using 2 multibreed populations, the Germplasm Evaluation (GPE) Program and the 2,000 Bull Project (2K(ALL)), and 2 single breed subpopulations of the 2,000 Bull Project, Angus (2K(AN)) and Hereford (2K(HH)). In this study, these MBV were assessed relative to commercial ranch EBV estimated from the progeny phenotypes of Angus bulls naturally mated in multisire breeding pastures to commercial cows: 121 for USMARC MBV, 99 for ISU/UMC MBV, and 29 for IGENITY and Pfizer MBV (selected based on number of progeny carcass records). Five traits were analyzed: weaning weight (WW), HCW, marbling score (MS), rib-eye muscle area (RE), and, for IGENITY and Pfizer only, feedlot ADG. The average accuracies of MBV across traits were 0.38 ± 0.05 for IGENITY, 0.61 ± 0.12 for Pfizer, 0.46 ± 0.12 for ISU/UMC, 0.16 ± 0.04 for GPE, 0.26 ± 0.05 for 2K(ALL), 0.24 ± 0.04 for 2K(AN), and 0.02 ± 0.12 for 2K(HH). Angus-based MBV (IGENITY, Pfizer, ISU/UMC, and 2K(AN)) explained larger proportions of genetic variance in this population than GPE, 2K(ALL), or 2K(HH) MBV for the same traits. In this data set, IGENITY, Pfizer, and ISU/UMC MBV were predictive of realized performance of progeny, and incorporation of that information into national genetic evaluations would be expected to improve EPD accuracy, particularly for young animals.

Evaluation of bull prolificacy on commercial beef cattle ranches using DNA paternity analysis

SNP-based DNA testing was used to assign paternity to 5,052 calves conceived in natural service multisire breeding pastures from 3 commercial ranches in northern California representing 15 calf crops over 3 yr. Bulls present for 60 to 120 d at a 25:1 cow to bull ratio in both fall and spring breeding seasons in ∼40 ha or smaller fenced breeding pastures sired a highly variable (P < 0.001) number of calves (Ncalf), ranging from 0 (4.4% of bulls present in any given breeding season) to 64 calves per bull per breeding season, with an average of 18.9 ± 13.1. There was little variation in Ncalf among ranches (P = 0.90), years (P = 0.96), and seasons (P = 0.94). Bulls varied widely (P < 0.01) in the average individual 205-d adjusted weaning weight (I205) of progeny, and I205 varied between years (P < 0.01) and seasons (P < 0.01) but not ranches (P = 0.29). The pattern for cumulative total 205-d adjusted weaning weight of all progeny sired by a bull (T205) was highly correlated to Ncalf, with small differences between ranches (P = 0.35), years (P = 0.66), and seasons (P = 0.20) but large differences (P < 0.01) between bulls, ranging from an average of 676 to 8,838 kg per bull per calf crop. The peak Ncalf occurred at about 5 yr of age for bulls ranging from 2 to 11 yr of age. Weekly conception rates as assessed by date of calving varied significantly and peaked at wk 3 of the calving season. The distribution of calves born early in the calving season was disproportionately skewed toward the highly prolific bulls. The DNA paternity testing of the subset of those calves born in wk 3 of the calving season was highly predictive of overall bull prolificacy and may offer a reduced-cost DNA-based option for assessing prolificacy. Prolificacy of young bulls in their first breeding season was positively linearly related (P < 0.05) to subsequent breeding seasons, explaining about 20% of the subsequent variation. Prolificacy was also positively linearly related (P < 0.05) to scrotal circumference (SC) EPD for Angus bulls that had SC EPD Beef Improvement Federation accuracies greater than 0.05. Varying prolificacy of herd bulls has implications for the genetic composition of replacement heifers, with the genetics of those bulls siring an increased number of calves being disproportionately represented in the early-born replacement heifer pool.