L. A. Kuehn

Genome-wide association study of growth in crossbred beef cattle

Chromosomal regions harboring variation affecting cattle birth weight and BW gain to 1 yr of age were identified by marker association using the highly parallel BovineSNP50 BeadChip (50K) assay composed of 54,001 individual SNP. Genotypes were obtained from progeny (F(1); 590 steers) and 2-, 3-, and 4-breed cross grandprogeny (F(1)(2) = F(1) x F(1); 1,306 steers and 707 females) of 150 AI sires representing 7 breeds (22 sires per breed; Angus, Charolais, Gelbvieh, Hereford, Limousin, Red Angus, and Simmental). Genotypes and birth, weaning, and yearling BW records were used in whole-genome association analyses to estimate effects of individual SNP on growth. Traits analyzed included growth component traits: birth weight (BWT), 205-d adjusted birth to weaning BW gain (WG), 160-d adjusted postweaning BW gain (PWG); cumulative traits: 205-d adjusted weaning weight (WW = BWT + WG) and 365-d adjusted yearling weight (YW = BWT + WG + PWG); and indexes of relative differences between postnatal growth and birth weight. Modeled fixed effects included additive effects of calf and dam SNP genotype, year-sex-management contemporary groups, and covariates for calf and dam breed composition and heterosis. Direct and maternal additive polygenic effects and maternal permanent environment effects were random. Missing genotypes, including 50K genotypes of most dams, were approximated with a single-locus BLUP procedure from pedigree relationships and known 50K genotypes. Various association criteria were applied: stringent tests to account for multiple testing but with limited power to detect associations with small effects, and relaxed nominal P that may detect SNP associated with small effects but include excessive false positive associations. Genomic locations of the 231 SNP meeting stringent criteria generally coincided with described previously QTL affecting growth traits. The 12,425 SNP satisfying relaxed tests were located throughout the genome. Most SNP associated with BWT and postnatal growth affected components in the same direction, although detection of SNP associated with one component independent of others presents a possible opportunity for SNP-assisted selection to increase postnatal growth relative to BWT.

Evaluation of antral follicle count and ovarian morphology in crossbred beef cows: investigation of influence of stage of the estrous cycle, age, and birth weight.

Depletion of the ovarian reserve is associated with reproductive senescence in mammalian females, and there is a positive relationship between the size of the ovarian reserve and the number of antral follicles on the surface of the ovary. Therefore, we conducted a series of experiments to investigate the influence of stage of the estrous cycle, age, and birth weight on antral follicle counts (AFC) in beef cows and heifers. Pairs of ovaries were collected from crossbred beef cows at slaughter (n = 72) or at necropsy (n = 333; 0 to 11 yr of age); all visible antral follicles were counted, the ovaries were weighed, and stage of the estrous cycle was estimated based on ovarian morphology. There was no influence of estimated stage of the estrous cycle on AFC (P = 0.36). There was a small but positive effect of birth weight on AFC [AFC = -1.7 + 0.31(birth weight); P = 0.007, r(2) = 0.05]. When antral follicle counts were regressed on age, there was a quadratic effect of age such that AFC increased until 5 yr of age and decreased thereafter [AFC = 12.9 + 9.0(yr) - 0.86(yr(2)); P < 0.001, r(2) = 0.22]. In a third experiment, crossbred beef heifers (n = 406; 353 to 463 d of age) at 3 locations were subjected to ovarian ultrasonography on unknown day of the estrous cycle. Heifers were classified as low AFC (<15 follicle, n = 84) or high AFC (>24 follicles, n = 178). Whereas estimated stage of the estrous cycle did not influence AFC (P = 0.62), heifers classified as low AFC had smaller ovaries (P = 0.001), decreased birth weight (P = 0.003), and a decreased heifer pregnancy rate (P = 0.05) compared with heifers in the high AFC group. From these results, we conclude that AFC in beef cows and heifers is influenced by birth weight and age but not by stage of the estrous cycle. In beef cows, the number of antral follicles increases to 5 yr of age and then begins to decline. This may indicate that a decrease in fertility due to decline of the ovarian reserve may begin earlier than previously thought in beef cows.

Rumen Microbiome from Steers Differing in Feed Efficiency

The cattle rumen has a diverse microbial ecosystem that is essential for the host to digest plant material. Extremes in body weight (BW) gain in mice and humans have been associated with different intestinal microbial populations. The objective of this study was to characterize the microbiome of the cattle rumen among steers differing in feed efficiency. Two contemporary groups of steers (n=148 and n=197) were fed a ration (dry matter basis) of 57.35% dry-rolled corn, 30% wet distillers grain with solubles, 8% alfalfa hay, 4.25% supplement, and 0.4% urea for 63 days. Individual feed intake (FI) and BW gain were determined. Within contemporary group, the four steers within each Cartesian quadrant were sampled (n=16/group) from the bivariate distribution of average daily BW gain and average daily FI. Bacterial 16S rRNA gene amplicons were sequenced from the harvested bovine rumen fluid samples using next-generation sequencing technology. No significant changes in diversity or richness were indicated, and UniFrac principal coordinate analysis did not show any separation of microbial communities within the rumen. However, the abundances of relative microbial populations and operational taxonomic units did reveal significant differences with reference to feed efficiency groups. Bacteroidetes and Firmicutes were the dominant phyla in all ruminal groups, with significant population shifts in relevant ruminal taxa, including phyla Firmicutes and Lentisphaerae, as well as genera Succiniclasticum, Lactobacillus, Ruminococcus, and Prevotella. This study suggests the involvement of the rumen microbiome as a component influencing the efficiency of weight gain at the 16S level, which can be utilized to better understand variations in microbial ecology as well as host factors that will improve feed efficiency.

Association, effects and validation of polymorphisms within the NCAPG - LCORL locus located on BTA6 with feed intake, gain, meat and carcass traits in beef cattle

BackgroundIn a previously reported genome-wide association study based on a high-density bovine SNP genotyping array, 8 SNP were nominally associated (P ≤ 0.003) with average daily gain (ADG) and 3 of these were also associated (P ≤ 0.002) with average daily feed intake (ADFI) in a population of crossbred beef cattle. The SNP were clustered in a 570 kb region around 38 Mb on the draft sequence of bovine chromosome 6 (BTA6), an interval containing several positional and functional candidate genes including the bovine LAP3, NCAPG, and LCORL genes. The goal of the present study was to develop and examine additional markers in this region to optimize the ability to distinguish favorable alleles, with potential to identify functional variation.ResultsAnimals from the original study were genotyped for 47 SNP within or near the gene boundaries of the three candidate genes. Sixteen markers in the NCAPG-LCORL locus displayed significant association with both ADFI and ADG even after stringent correction for multiple testing (P ≤ 005). These markers were evaluated for their effects on meat and carcass traits. The alleles associated with higher ADFI and ADG were also associated with higher hot carcass weight (HCW) and ribeye area (REA), and lower adjusted fat thickness (AFT). A reduced set of markers was genotyped on a separate, crossbred population including genetic contributions from 14 beef cattle breeds. Two of the markers located within the LCORL gene locus remained significant for ADG (P ≤ 0.04).ConclusionsSeveral markers within the NCAPG-LCORL locus were significantly associated with feed intake and body weight gain phenotypes. These markers were also associated with HCW, REA and AFT suggesting that they are involved with lean growth and reduced fat deposition. Additionally, the two markers significant for ADG in the validation population of animals may be more robust for the prediction of ADG and possibly the correlated trait ADFI, across multiple breeds and populations of cattle.

Partial-genome evaluation of postweaning feed intake and efficiency of crossbred beef cattle

The effects of individual SNP and the variation explained by sets of SNP associated with DMI, metabolic midtest BW, BW gain, and feed efficiency, expressed as phenotypic and genetic residual feed intake, were estimated from BW and the individual feed intake of 1,159 steers on dry lot offered a 3.0 Mcal/kg ration for at least 119 d before slaughter. Parents of these F(1) × F(1) (F(1)(2)) steers were AI-sired F(1) progeny of Angus, Charolais, Gelbvieh, Hereford, Limousin, Red Angus, and Simmental bulls mated to US Meat Animal Research Center Angus, Hereford, and MARC III composite females. Steers were genotyped with the BovineSNP50 BeadChip assay (Illumina Inc., San Diego, CA). Effects of 44,163 SNP having minor allele frequencies >0.05 in the F(1)(2) generation were estimated with a mixed model that included genotype, breed composition, heterosis, age of dam, and slaughter date contemporary groups as fixed effects, and a random additive genetic effect with recorded pedigree relationships among animals. Variance in this population attributable to sets of SNP was estimated with models that partitioned the additive genetic effect into a polygenic component attributable to pedigree relationships and a genotypic component attributable to genotypic relationships. The sets of SNP evaluated were the full set of 44,163 SNP and subsets containing 6 to 40,000 SNP selected according to association with phenotype. Ninety SNP were strongly associated (P < 0.0001) with at least 1 efficiency or component trait; these 90 accounted for 28 to 46% of the total additive genetic variance of each trait. Trait-specific sets containing 96 SNP having the strongest associations with each trait explained 50 to 87% of additive variance for that trait. Expected accuracy of steer breeding values predicted with pedigree and genotypic relationships exceeded the accuracy of their sires predicted without genotypic information, although gains in accuracy were not sufficient to encourage that performance testing be replaced by genotyping and genomic evaluations.

Investigation of bacterial diversity in the feces of cattle fed different diets.

The objective of this study is to investigate individual animal variation of bovine fecal microbiota including as affected by diets. Fecal samples were collected from 426 cattle fed 1 of 3 diets typically fed to feedlot cattle: 1) 143 steers fed finishing diet (83% dry-rolled corn, 13% corn silage, and 4% supplement), 2) 147 steers fed late growing diet (66% dry-rolled corn, 26% corn silage, and 8% supplement), and 3) 136 heifers fed early growing diet (70% corn silage and 30% alfalfa haylage). Bacterial 16S rRNA gene amplicons were determined from individual fecal samples using next-generation pyrosequencing technology. A total of 2,149,008 16S rRNA gene sequences from 333 cattle with at least 2,000 sequences were analyzed. Firmicutes and Bacteroidetes were dominant phyla in all fecal samples. At the genus level, Oscillibacter, Turicibacter, Roseburia, Fecalibacterium, Coprococcus, Clostridium, Prevotella, and Succinivibrio were represented by more than 1% of total sequences. However, numerous sequences could not be assigned to a known genus. Dominant unclassified groups were unclassified Ruminococcaceae and unclassified Lachnospiraceae that could be classified to a family but not to a genus. These dominant genera and unclassified groups differed (P < 0.001) with diets. A total of 176,692 operational taxonomic units (OTU) were identified in combination across all the 333 cattle. Only 2,359 OTU were shared across 3 diet groups. UniFrac analysis showed that bacterial communities in cattle feces were greatly affected by dietary differences. This study indicates that the community structure of fecal microbiota in cattle is greatly affected by diet, particularly between forage- and concentrate-based diets.

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.

Contribution of genetic influences to animal-to-animal variation in myoglobin content and beef lean color stability.

Longissimus thoracis steaks from steers (n = 464) with 0 to 50% inheritance of Angus, Charolais, Gelbvieh, Hereford, Limousin, Red Angus, and Simmental were evaluated during 6 d of display to assess genetic contributions to color stability. Color space values [CIE L* (lightness), a* (redness), b* (yellowness)], chroma, color change (DeltaE), and surface metmyoglobin (K/S 572/525) were determined on d 0 and 6 of display. Myoglobin concentration was highly heritable (0.85), but ultimate pH was weakly heritable (0.06). Day 0 L* values were moderately heritable (0.24). Variation in metmyoglobin, L*, and DeltaE on d 6 was moderately explained by genetic factors (41, 40, and 29%, respectively). Change during display was moderately heritable for a* (0.31), b* (0.23), chroma (0.35), and surface metmyoglobin (0.29). At the start of display, Angus steaks had greater (P < 0.05) L* values than those from all breeds except Charolais. On d 6, Angus steaks had greater (P < 0.05) L* (50.0) values than Gelbvieh, Hereford, and Simmental steaks (46.1, 44.0, and 44.5, respectively). Day 0 values for a*, b*, chroma, and DeltaE were not affected by breed (P > 0.05). On d 6, a* values were greater (P < 0.05) for Charolais and Limousin steaks (31.1 and 30.5) than Angus, Hereford, and Red Angus steaks (27.4, 27.7, and 26.3, respectively). Thus, a* changed less (P < 0.05) in Charolais and Limousin steaks (1.8 and 2.6, respectively) vs. steaks from other breeds. Day 6 b* values were greater (P < 0.05) in Charolais (24.5) and Limousin steaks (24.0) vs. Gelbvieh (22.2), Hereford (21.9), and Red Angus steaks (21.4). Thus, b* values changed less (P < 0.05) in Charolais and Limousin steaks (1.5 and 1.7, respectively) than in Angus, Gelbvieh, Hereford, and Red Angus steaks (4.3, 3.8, 4.4, and 5.1, respectively). After 6 d of display, Charolais and Limousin steaks had greater chroma (P < 0.05; 39.5 and 38.8, respectively) compared with Angus, Hereford, and Red Angus steaks (35.4, 35.3, and 33.9, respectively). Less (P < 0.05) change in chroma occurred for Charolais and Limousin (2.1 and 2.8, respectively) than in Angus, Gelbvieh, Hereford, and Red Angus steaks (7.1, 6.6, 7.4, and 9.0, respectively). Myoglobin concentration was less for Charolais and Limousin (P < 0.05; 2.77 and 2.72, respectively) compared with Gelbvieh, Red Angus, and Simmental steaks (3.62, 3.43, and 3.71, respectively). Breeds did not differ in pH (P > 0.05). These data suggest Charolais- and Limousin-carcasses produced steaks with greater lean color stability than Angus, Hereford, and Red Angus carcasses. Furthermore, these findings suggest that genetics contribute substantially to animal-to-animal variation in lean color, particularly in maintaining color.

Predicting breed composition using breed frequencies of 50,000 markers from the US Meat Animal Research Center 2,000 Bull Project

Knowledge of breed composition can be useful in multiple aspects of cattle production, and can be critical for analyzing the results of whole genome-wide association studies currently being conducted around the world. We examine the feasibility and accuracy of using genotype data from the most prevalent bovine genome-wide association studies platform, the Illumina BovineSNP50 array (Illumina Inc., San Diego, CA), to estimate breed composition for individual breeds of cattle. First, allele frequencies (of Illumina-defined allele B) of SNP on the array for each of 16 beef cattle breeds were defined by genotyping a large set of more than 2,000 bulls selected in cooperation with the respective breed associations to be representative of their breed. With these breed-specific allele frequencies, the breed compositions of approximately 2,000 two-, three-, and four-way cross (of 8 breeds) cattle produced at the US Meat Animal Research Center were predicted by using a simple multiple regression technique or Mendel (http://www.genetics.ucla.edu/software/mendel) and their genotypes from the Illumina BovineSNP50 array, and were then compared with pedigree-based estimates of breed composition. The accuracy of marker-based breed composition estimates was 89% when using either estimation method for all breeds except Angus and Red Angus (averaged 79%), based on comparing estimates with pedigree-based average breed composition. Accuracy increased to approximately 88% when these 2 breeds were combined into an aggregate Angus group. Additionally, we used a subset of these markers, approximately 3,000 that populate the Illumina Bovine3K (Illumina Inc.), to see whether breed composition could be estimated with similar accuracy when using this reduced panel of SNP makers. When breed composition was estimated using only SNP in common with the Bovine 3K array, accuracy was slightly reduced to 83%. These results suggest that SNP data from these arrays could be used to estimate breed composition in most US beef cattle in situations where pedigree is not known (e.g., multiple-sire natural service matings, non-source-verified animals in feedlots or at slaughter). This approach can aid analyses that depend on knowledge of breed composition, including identification and adjustment of breed-based population stratification, when performing genome-wide association studies on populations with incomplete pedigrees. In addition, SNP-based breed composition estimates may facilitate fitting cow germplasm to the environment, managing cattle in the feedlot, and tracing disease cases back to the geographic region or farm of origin.

Physiology and Endocrinology Symposium: How single nucleotide polymorphism chips will advance our knowledge of factors controlling puberty and aid in selecting replacement beef females.

The promise of genomic selection is accurate prediction of the genetic potential of animals from their genotypes. Simple DNA tests might replace low-accuracy predictions for expensive or lowly heritable measures of puberty and fertility based on performance and pedigree. Knowing with some certainty which DNA variants (e.g., SNP) affect puberty and fertility is the best way to fulfill the promise. Several SNP from the BovineSNP50 assay have tentatively been associated with reproductive traits including age at puberty, antral follicle count, and pregnancy observed on different sets of heifers. However, sample sizes are too small and SNP density is too sparse to definitively determine genomic regions harboring causal variants affecting reproductive success. Additionally, associations between individual SNP and similar phenotypes are inconsistent across data sets, and genomic predictions do not appear to be globally applicable to cattle of different breeds. Discrepancies may be a result of different QTL segregating in the sampled populations, differences in linkage disequilibrium (LD) patterns such that the same SNP are not correlated with the same QTL, and spurious correlations with phenotype. Several approaches can be used independently or in combination to improve detection of genomic factors affecting heifer puberty and fertility. Larger samples and denser SNP will increase power to detect real associations with SNP having more consistent LD with underlying QTL. Meta-analysis combining results from different studies can also be used to effectively increase sample size. High-density genotyping with heifers pooled by pregnancy status or early and late puberty can be a cost-effective means to sample large numbers. Networks of genes, implicated by associations with multiple traits correlated with puberty and fertility, could provide insight into the complex nature of these traits, especially if corroborated by functional annotation, established gene interaction pathways, and transcript expression. Example analyses are provided to demonstrate how integrating information about gene function and regulation with statistical associations from whole-genome SNP genotyping assays might enhance knowledge of genomic mechanisms affecting puberty and fertility, enabling reliable DNA tests to guide heifer selection decisions.