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.

Snelling WM ，Allan MF ，Keele JW ，Kuehn LA ，Thallman RM ，Bennett GL ，Ferrell CL ，Jenkins TG ，Freetly HC ，Nielsen MK ，Rolfe KM ... -  《-》

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.

Snelling WM ，Allan MF ，Keele JW ，Kuehn LA ，McDaneld T ，Smith TP ，Sonstegard TS ，Thallman RM ，Bennett GL ... -  《-》

Genetic and phenotypic parameter estimates for feed intake and other traits in growing beef cattle, and opportunities for selection.

Growth, feed intake, and temperament indicator data, collected over 5 yr on a total of 1,141 to 1,183 mixed-breed steers, were used to estimate genetic and phenotypic parameters. All steers had a portion of Hereford, Angus, or both as well as varying percentages of Simmental, Charolais, Limousin, Gelbvieh, Red Angus, and MARC III composite. Because the steers were slaughtered on various dates each year and the animals thus varied in days on feed, BW and feed data were adjusted to a 140-d feeding period basis. Adjustment of measures of feed efficiency [G:F or residual feed intake (RFI), intake adjusted for metabolic body size, and BW gain] for body fatness recorded at slaughter had little effect on the results of analyses. Average daily gain was less heritable (0.26) than was midtest BW (MBW; 0.35). Measures of feed intake had greater estimates of heritability, with 140-d DMI at 0.40 and RFI at 0.52; the heritability estimate for G:F was 0.27. Flight speed (FS), as an indicator of temperament, had an estimated heritability of 0.34 and a repeatability of 0.63. As expected, a strong genetic (0.86) correlation was estimated between ADG and MBW; genetic correlations were less strong between DMI and ADG or MBW (0.56 and 0.71). Residual feed intake and DMI had a genetic correlation of 0.66. Indexes for phenotypic RFI and genotypically restricted RFI (no correlation with BW gain) were compared with simple economic indexes incorporating feed intake and growth to elucidate expected selection responses under different criteria. In general, few breed differences were detected across the various measurements. Heterosis contributed to greater DMI, RFI, and MBW, but it did not significantly affect ADG, G:F, or FS. Balancing output (growth) with input costs (feed) is needed in practicing selection, and FS would not be recommended as an indicator trait for selection to change feed efficiency. An index including BW gain and RFI produced the best economic outcome.

Rolfe KM ，Snelling WM ，Nielsen MK ，Freetly HC ，Ferrell CL ，Jenkins TG ... -  《-》

Primary genome scan to identify putative quantitative trait loci for feedlot growth rate, feed intake, and feed efficiency of beef cattle.

Feed intake and feed efficiency of beef cattle are economically relevant traits. The study was conducted to identify QTL for feed intake and feed efficiency of beef cattle by using genotype information from 100 microsatellite markers and 355 SNP genotyped across 400 progeny of 20 Angus, Charolais, or Alberta Hybrid bulls. Traits analyzed include feedlot ADG, daily DMI, feed-to-gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F)], and residual feed intake (RFI). A mixed model with sire as random and QTL effects as fixed was used to generate an F-statistic profile across and within families for each trait along each chromosome, followed by empirical permutation tests to determine significance thresholds for QTL detection. Putative QTL for ADG (chromosome-wise P < 0.05) were detected across families on chromosomes 5 (130 cM), 6 (42 cM), 7 (84 cM), 11 (20 cM), 14 (74 cM), 16 (22 cM), 17 (9 cM), 18 (46 cM), 19 (53 cM), and 28 (23 cM). For DMI, putative QTL that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (93 cM), 3 (123 cM), 15 (31 cM), 17 (81 cM), 18 (49 cM), 20 (56 cM), and 26 (69 cM) in the across-family analyses. Putative across-family QTL influencing F:G that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 3 (62 cM), 5 (129 cM), 7 (27 cM), 11 (16 cM), 16 (30 cM), 17 (81 cM), 22 (72 cM), 24 (55 cM), and 28 (24 cM). Putative QTL influencing RFI that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (90 cM), 5 (129 cM), 7 (22 cM), 8 (80 cM), 12 (89 cM), 16 (41 cM), 17 (19 cM), and 26 (48 cM) in the across-family analyses. In addition, a total of 4, 6, 1, and 8 chromosomes showed suggestive evidence (chromosome-wise, P < 0.10) for putative ADG, DMI, F:G, and RFI QTL, respectively. Most of the QTL detected across families were also detected within families, although the locations across families were not necessarily the locations within families, which is likely because of differences among families in marker informativeness for the different linkage groups. The locations and direction of some of the QTL effects reported in this study suggest potentially favorable pleiotropic effects for the underlying genes. Further studies will be required to confirm these QTL in other populations so that they can be fine-mapped for potential applications in marker-assisted selection and management of beef cattle.

Nkrumah JD ，Sherman EL ，Li C ，Marques E ，Crews DH Jr ，Bartusiak R ，Murdoch B ，Wang Z ，Basarab JA ，Moore SS ... -  《-》

Associations of marker panel scores with feed intake and efficiency traits in beef cattle using preselected single nucleotide polymorphisms.

Because of the moderate heritability and the expense associated with collecting feed intake data, effective selection for residual feed intake would be enhanced if marker-assisted evaluation were used for accurate estimation of genetic merit. In this study, a suite of genetic markers predictive of residual feed intake, DMI, and ADG were preselected using single-marker regression analysis, and the top 100 SNP were analyzed further to provide prediction equations for the traits. The data used consisted of 728 spring-born beef steers, offspring of a cross between a composite dam line and Angus, Charolais, or University of Alberta hybrid bulls. Feed intake data were collected over a 5-yr period, with 2 groups (fall-winter and winter-spring) tested every year. Training and validation data sets were obtained by splitting the data into 2 distinct sets, by randomly splitting the data into training and testing sets based on sire family (split 1) in 5 replicates or by retaining all animals with no known pedigree relationships as the validation set (split 2). A total of 37,959 SNP were analyzed by single-marker regression, of which only the top 100 that corresponded to a P-value <0.002 were retained. The 100 SNP were then analyzed using random regression BLUP, and only SNP that were jointly significant (P < 0.05) were included in the final marker panels. The marker effects from the selected panels were used to derive the molecular breeding values, which were calculated as a weighted sum of the number of copies of the more frequent allele at each SNP locus, with the weights being the allele substitution effects. The correlation between molecular breeding value and phenotype represented the accuracy of prediction. For all traits evaluated, accuracy across breeds was low, ranging between 0.007 and 0.414. Accuracy was least in data split 2, where the validation individuals had no pedigree relationship with animals in the training data. Given the low predictive ability observed, a large number of individuals may be needed for prediction when using such an admixed population. Further, these results suggest that breed composition of the target population in which the marker panels are likely to be used should be an important consideration when developing prediction equations across breeds, especially where an admixed population is used as the training data set.

Mujibi FD ，Nkrumah JD ，Durunna ON ，Grant JR ，Mah J ，Wang Z ，Basarab J ，Plastow G ，Crews DH Jr ，Moore SS ... -  《-》