Academic literature on the topic 'Multi-breed beef cattle'

Increased movement toward alliances and grid pricing in the U.S. has led to an increase interest in genetic values for carcass traits. The literature suggests that carcass genetic values are an effective tool to enhance selection for carcass traits, and that it is possible to select sires within a breed that can increase marbling score without adversely affecting external fat thickness or percent retail product relative to the breed mean. Ultrasound has been investigated as a cheaper means of collecting carcass information. The literature indicates that carcass traits measured via ultrasound on yearling seedstock will respond to selection. Although the literature is variable on the subject, there are reported genetic correlation (r g) estimates between live animal ultrasound and actual carcass attributes that are greater than .70 for all ultrasonically measured carcass traits. When r g between seedstock ultrasound and slaughter cattle carcass measures are > 0.70, similar or greater genetic progress in finished cattle carcass merit could be achieved by using ultrasound information entirely compared to using typical carcass progeny information; however, the maximum accuracy of prediction using ultrasound information in lieu of finished cattle carcass information would be r g. Therefore both actual and live animal, ultrasonically measured carcass traits should be included in genetic evaluation programs, which will allow for an increase in the accuracy of prediction of carcass genetic values on young seedstock animals due to the inclusion of ultrasound information, and will also allow for the possible production of high accuracy sires based on finished cattle progeny carcass information. Multi-breed models are being developed to allow for the prediction of genetic values for carcass traits in populations composed of animals of varying breed composition.

Phenotypic, environmental and genetic trends were estimated for birth weight, preweaning average daily gain (ADG) and weaning weight in males and females combined; postweaning ADG and yearling weight in males; and 18-mo weight in females in a purebred Hereford and a multi-breed Synthetic population of beef cattle, for the period 1966–1978, from The University of Alberta Ranch at Kinsella. Mean selection differential, heritability, expected genetic response and actual genetic response were estimated for each trait. Methods employed to estimate trends were: (1) deviation from a control population, and (2) best linear unbiased prediction estimates of sire breeding values. Heritabilities, selection differentials and expected gains were higher for traits in the Synthetics than in the Herefords except for the 18-mo weight in females. Realized gains in most of the traits were also higher in Synthetics than in Herefords. Genetic trends obtained by the two methods were variable and deviated from the expected gains. Positive genetic trends for growth traits indicated effectiveness of the selection program in both populations. Key words: Beef cattle, selection response, growth traits

Abstract Utilizing beef genetics in dairy herds to produce terminal beef x dairy (BXD) crosses is a growing trend in the U.S. dairy industry. It has been estimated that more than two million U.S. BXD calves were born in 2020, which is a practice that is expected to continue to grow throughout the foreseeable future. While not a new concept, the widespread adoption, scale, and strategies currently being used to produce BXD calves have recently received considerable industry attention. Although the increased duration of feeding exposes BXD feeders to increased price and production risks when compared to straightbred beef cattle, these risks are met with several potential benefits. A prime example of such benefits includes a consistent supply of uniform, traceable feeder cattle that are easily age and source verified, that also serve as ideal candidates for enrollment in or development of other value-added marketing programs. Current demand, as indicated by newborn calf prices, suggests that the industry perceives BXD calves to be superior when compared to their straightbred dairy breed contemporaries, and at times, suggests that they may be overvalued. Sustaining such demand will require BXD calves to meet or exceed the performance and profitability expectations of the various production sectors of the beef industry. Results of a multi-year analysis of the economics of BXD calves as compared to cattle of straightbred beef or dairy breed composition will be presented. Furthermore, specific factors expected to influence value throughout the production supply chain will be outlined and discussed. Calfhood management practices that promote calf health, paired with genetic selection strategies focused on complementary traits that minimize cost of gain and increase cutability, such as feed efficiency, carcass yield, and muscularity, will play key roles in sustaining the value of BXD calves to all aspects of the beef supply chain.

This study evaluated the accuracy of sequence imputation in Hanwoo beef cattle using different reference panels: a large multi-breed reference with no Hanwoo (n = 6269), a much smaller Hanwoo purebred reference (n = 88), and both datasets combined (n = 6357). The target animals were 136 cattle both sequenced and genotyped with the Illumina BovineSNP50 v2 (50K). The average imputation accuracy measured by the Pearson correlation (R) was 0.695 with the multi-breed reference, 0.876 with the purebred Hanwoo, and 0.887 with the combined data; the average concordance rates (CR) were 88.16%, 94.49%, and 94.84%, respectively. The accuracy gains from adding a large multi-breed reference of 6269 samples to only 88 Hanwoo was marginal; however, the concordance rate for the heterozygotes decreased from 85% to 82%, and the concordance rate for fixed SNPs in Hanwoo also decreased from 99.98% to 98.73%. Although the multi-breed panel was large, it was not sufficiently representative of the breed for accurate imputation without the Hanwoo animals. Additionally, we evaluated the value of high-density 700K genotypes (n = 991) as an intermediary step in the imputation process. The imputation accuracy differences were negligible between a single-step imputation strategy from 50K directly to sequence and a two-step imputation approach (50K-700K-sequence). We also observed that imputed sequence data can be used as a reference panel for imputation (mean R = 0.9650, mean CR = 98.35%). Finally, we identified 31 poorly imputed genomic regions in the Hanwoo genome and demonstrated that imputation accuracies were particularly lower at the chromosomal ends.

The type was evaluated in 5 424 young animals of twelve beef breeds. Ten type traits were evaluated: height at sacrum (HS), body length (BL), live weight (LW), front chest width (CW), chest depth (CD), pelvis (P), shoulder muscling (SM), back muscling (BM), rump muscling (RM) and production type (PT). The traits represent two groups: (1) traits scoring body measurements and body capacity (HS, BL, LW, CW, CD, P) and (2) traits scoring muscling (SM, BM, RM, PT). These fixed effects were included in the model: breed, sex, HYS, mother’s age, linear regression on age at evaluation and average gain from birth to evaluation. Fixed effects in the model explained 40% to 60% of variability. The highest values of heritability coefficient were estimated for HS (h² = 0.51) and LW (h² = 0.50). BL had the lowest values of heritability coefficient (h² = 0.25). The values h² = 0.25–0.32 were calculated for the traits scoring body capacity (CW, CD, P). The range of values for muscling traits was h² = 0.26–0.35. The coefficient of heritability for PT was h² = 0.34. All traits scoring muscling and PT showed high genetic correlations (r_g > 0.95). The traits scoring body capacity (P, CW, CD) were highly genetically correlated with muscling r_g > 0.83. Breeding values were determined by a multi-trait animal model. Standard deviations of breeding values were higher in HS (s_BV = 0.71) and LW (s_BV = 0.84), which was connected with a different method of evaluation of these traits. They were in the range of 0.19 (BL) to 0.30 (RM) in the other traits.  

In beef cattle, growth, reproductive, and carcass traits have been studied for improving productivity and quality of meat products. The aim of this study was to estimate genetic parameters for birth (BW), weaning (WW) and yearling (YW) weights, scrotal circumferences at weaning (SCW) and yearling (SCY), age at first calving (AFC), ribeye area (REA) and back fat thickness (BFT) in order to provide support for the evaluation program of the composite Canchim breed. Data on 12 967 (BW), 7481 (WW), 5131 (YW), 1447 (SCW), 1224 (SCY), 1400 (AFC), and 2082 (REA and BFT) animals were analysed using the Average Information Restricted Maximum Likelihood method under an animal model (single and multi-trait analyses). A substantial proportion of the variation in the bodyweights, scrotal circumferences and carcass traits was associated with the additive genetic term indicating that these traits may respond to the selection process. For AFC, a low heritability estimate was observed. Genetic correlations among bodyweights varied from 0.41 to 0.93. The genetic correlation among scrotal circumferences was 0.91. Important genetic correlations among YW, SCW, and SCY with AFC were observed (–0.48, –0.61, and –0.71, respectively), indicating that indirect responses to selection for these traits would be expected in the age of which the heifers calve. Furthermore, BFT presented an interesting result with calving performance due to the genetic correlation (–0.69) with AFC. Post-weaning weights showed moderate genetic correlations with REA. Many of the traits considered in the genetic evaluation of this breed are genetically correlated in a favourable manner. Genetic improvement through selection is expected for production, reproduction, and carcass traits in Canchim beef cattle.

Abstract Thermal stress in subtropical regions is a major limiting factor in beef cattle productions with around $370 million being lost annually due to reduced performance. About 45% of beef cattle in the United States are in the southern and southeastern states where tropical and subtropical climates are most prevalent. Cattle utilize sweating to dispense most of their excess heat allowing them to return to their thermoneutral zone. The objective of this study was to conduct a genome-wide association study on sweat gland area in the Multi-breed Angus-Brahman herd of the University of Florida. Skin samples were collected along the shoulder from 337 cows of varying Brahman and Angus percentages. Cows were genotyped with the Bovine GGP F250k array. The biopsies were processed into histology slides and then ImageJ software was used to measure sweat gland area. A general linear model was used to test the significance of breed composition and age group on sweat gland area. Breed composition and age group had a significant effect on sweat gland area (P < 0.0001 and P < 0.0001, respectively), with sweat gland area increasing with Brahman percentage. Quality control was conducted using BLUPF90 software including a call rate of 0.90 and a minor allele frequency of 0.01 which left 125,035 SNPs available for the single-step genome wide association analysis. BLUPF90 software was used to fit a single locus mixed model to test the effect of each marker. There were a significant SNPs located in the MINDY1 and PRUNE1 gene, which are involved in cell proliferation and induction of cell motility. These results show that with selection on these SNPs, can improve the ability of cattle to adapt to thermal stress.

Abstract Multi-breed evaluations have the advantage of increasing the size of the reference population for genomic evaluations and are quite simple; however, combining breeds usually have a negative impact on prediction accuracy. The aim of this study was to evaluate the use of a multi-breed genomic relationship matrix (G), where SNP for each breed are non-shared. The multi-breed G is set assuming known genotypes for one breed and missing genotypes for the remaining breeds. This setup may avoid spurious IBS relationships between breeds and considers breed-specific allele frequencies. This scenario was contrasted to multi-breed evaluations where all SNP are shared, i.e., the same SNP, and to single-breed evaluations. Different SNP densities, namely 9k and 45k, and different effective population sizes (Ne) were tested. Five breeds mimicking recent beef cattle populations that diverged from the same historical population were simulated using different selection criteria. It was assumed that QTL effects were the same over all breeds. For the recent population, generations 1 to 9 had approximately half of the animals genotyped, whereas all 1200 animals were genotyped in generation 10. Genotyped animals in generation 10 were set as validation; therefore, each breed had a validation set. Analysis were performed using single-step GBLUP (ssGBLUP). Prediction accuracy was calculated as correlation between true (T) and genomic estimated (GE) BV. Accuracies of GEBV were lower for the larger Ne and low SNP density. All three scenarios using 45K resulted in similar accuracies, suggesting that the marker density is high enough to account for relationships and linkage disequilibrium with QTL. A shared multi-breed evaluation using 9K resulted in a decrease of accuracy of 0.08 for a smaller Ne and 0.11 for a larger Ne. This loss was mostly avoided when markers were treated as non-shared within the same genomic relationship matrix.

Mate selection is an attractive breeding strategy for multi-breed beef cattle populations, as it allows selection and crossbreeding to be exploited simultaneously. Two components are required for mate selection; an objective function called a mate selection index (MSI) which describes economic gain as a function of selection and mate allocations (or 'mate selections'), and a mate selection algorithm which finds the mating set which maximises the MSI.

One concern with mate selection is that as breeding decisions are based on progeny merit only (the next generation), short term genetic merit may be maximised at the cost of longer term genetic merit. To address this concern, LAMS (Look Ahead Mate Selection) schemes have been proposed. In LAMS schemes, some weight is given in the MSI to the merit of predicted grand-progeny in mate selection decisions.

To date, there have been few studies predicting the benefits of mate selection in multi-breed beef cattle populations. The impact of mate selection, especially LAMS schemes, on population structure and longer term genetic gain is unknown. Further, the advantages of mate selection when the genetic model of multi-breed populations is extended beyond selection and heterosis to include within breed dominance variance is unknown.

This thesis was designed to investigate three issues:

1. What population structures will emerge when mate selection (including LAMS schemes) is applied in multi-breed populations?
2. What is the effect of longer term implementation of LAMS schemes on genetic merit of multi-breed populations
3. Does mate selection significantly improve the genetic value of a multi-breed population when individual dominance is included in the MSI (relative to other breeding strategies, such as selection followed by mate allocation)?

To investigate the first issue, a deterministic evaluation of mate selection was considered. Mate selection was at the level of genetic groups, where genetic groups were defined by breed composition and selection history. The initial population structure consisted of breeds A and B. Genetic merit of genetic group l was y_l =  µ_l + g^A_lm_A + g^B_lm_B + g^A_jd_ABg^B_k + g^B_jd_ABg^A_k, where g^A_l, the proportion of breed A in progeny genotype l, is calculated as g^A_l = 1/2(g^A_j + g^A_k), where g^A_j and g^A_k are proportions of breed A in parental genotypes j and k respectively. The proportion of breed B in progeny genotype l is calculated similarly. Parameter d_AB, is the F₁ heterosis when breeds A and B are crossed, and µ_l is the mean additive breeding value for progeny genotype l.

The aim of each breeding schemes was to create a new herd in the first generation by importing sires and dams of breeds A and B, and then breed a further generation of progeny in the home herd. The second generation of progeny could be created either by importing more sires and dams, or using sires and dams bred in the home herd in the previous generation. It was assumed no selection was occurring within the foreign populations. Breeding schemes were compared by using the sum of progeny merit over the two generations, for a range of heritabilities and heterosis values. Schemes evaluated were structured crossbreeding (F₁ and F₂ designs), progeny merit each generation as mate selection criteria (PROG_DET), or cumulative merit over two generations as mate selection criteria (CUMUL_DET). CUMUL_DET was a LAMS scheme, as merit of the generation beyond the progeny generation was considered in the mate selection decisions. At all parameter values, PROG_DET and CUMUL_DET gave better cumulative merit than structured crossbreeding designs. This was a result of selecting sires and dams from the whole population rather than within genotypes or genetic groups. The advantage of mate selection strategies over structured strategies was greatest when h²=0.6; up to 1.9% for cumulative merit from CUMUL_DET over the best F₁ cross.

CUMUL_DET gave slightly greater cumulative merit than PROG_DET in all scenarios, with the advantage increasing with greater heritability or greater selection intensities. The advantage of CUMUL_DET over PROG_DET was from allocation of a proportion of purebred matings in the first generation in the home herd in CUMUL_DET. In the second generation, purebred progeny from these selected purebred parents could be crossed to breed F₁ grandprogeny with maximum heterosis and cumulative additive merit from selection. The proportion of purebred matings in the home herd in the first generation increased with heritability (1% of all matings in the first generation when h²=0.1 and 11% when h²=0.6).

To investigate the second issue, response from implementation of tactical (at the individual animal level) LAMS schemes was investigated. The genetic model used included additive breed and maternal effects, and direct and maternal heterosis. For this model, progeny merit of an individual progeny from a mating was PM_i = 1/2(p^T_s + p^T_d)a + p^T_sDp_d + p^T_da_m + p^T_mgsD_mp_mgd where vector p represents the proportion of genes of each breed in sire (s) or dam (d), maternal grand sire (mgs) or maternal granddam (mgd), a is a vector of fixed breed effects (breed means for each breed), a_m is a vector of fixed maternal breed effects, D is a breed x breed matrix of direct heterosis effects, and Dm is a breed x breed matrix of maternal heterosis effects.

Schemes investigated included mate selection with progeny merit only in the MSI (PROG strategy) and mate selection with progeny merit and grandprogeny merit equally weighted in the MSI (LAMS strategy). An additional scheme, COMP, was evaluated which used the contribution of the mating set to progeny with an optimal composite genotype as the MSI. Schemes were assessed using simulation of a single trait (yearling weight) over six generations of a four breed population. It was assumed no selection was occurring in foreign populations. With LAMS, a proportion of matings each generation in all simulations were allocated to breed F1 dams, improving the merit of the next generation, as a three breed cross could be created. LAMS gave the highest cumulative progeny merit over six generations; 20kg greater than PROG, and almost 70kg greater than COMP.

COMP created a population of optimum composite animals after six generations of breeding, with no variation in breed composition among individuals in the population (all animals had the optimum composite genotype). This strategy would be useful for commercial beef producers aiming to produce uniform lines of turnoff progeny.

The performance of LAMS was also evaluated when the genetic model was extended to include individual additive breeding values...