Vitamin A and marbling attributes: Intramuscular fat hyperplasia effects in cattle

© 2017 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Twenty Angus steers were fed a diet low in β-carotene and vitamin A for 10 months. Ten steers were supplemented with vitamin A weekly, while the other ten steers did not receive any additional vitamin A. The results demonstrated that the restriction of vitamin A intake increased intramuscular fat (IMF) by 46%. This was a function of the total number of marbling flecks increasing by 22% and the average marbling fleck size increasing by 14%. Vitamin A restriction resulted in marbling flecks that were less branched (22%) and slightly more round (4%) with an increased minor axis length (7%). However, restricting vitamin A did not affect the size of the intramuscular or subcutaneous adipocyte cells or the subcutaneous fat depth. The results suggest that vitamin A affects the amount of marbling and other attributes of the marbling flecks due to hyperplasia rather than hypertrophy. This may explain why vitamin A restriction specifically affects IMF rather than subcutaneous fat deposition

Production efficiency

Livestock industries operate in an internationally competitive environment with changes in currency value and terms of trade affecting the competitiveness of industries in export-oriented countries. For example, Australia's share of the Japanese and South Korean beef markets has been under intense competition from the USA since 1986 (Bindon and Jones 2001; Chapters 4, 8, 11). Beef market share is impacted by prices of other meats, animal protein substitutes and changing consumer preferences. Input costs for intensive beef producers increase with any expansion of the crop-based biofuel sector. Traceability, food safety and animal welfare concerns add costs to the industry without necessarily bringing greater returns. For example, if exporting South American countries are free of foot and mouth disease they can compete more for Australian beef markets in Canada and Taiwan. These and other challenges are best met by production efficiency improvements to ensure the continuing economic viability of the beef industry. Increased productivity (a measure of the efficiency of the production process) reflects the ability to produce more goods and services (outputs) given available resources (inputs) (Chapter 20). Production efficiency gains are usually achieved through lowered costs and/or higher outputs, thus greater profit margins for the producer. Whether market or feed prices are high or low, production efficiency largely determines the magnitude of farm profit or loss (Chapter 20)

Genomic Analysis of Purebred and Crossbred Angus Cows Quantifies Heterozygosity, Breed, and Additive Effects on Components of Reproduction

Multiple studies have quantified the production differences of Hereford Angus crossbreds compared to purebred Angus for a range of traits including growth, carcass, and reproductive traits. This study aims to quantify breed and heterosis effects on maternal performance using genomics. Thirty Hereford and thirty Angus sires were mated to 1100 Angus heifers and cows in a large commercial herd run on pasture at Musselroe Bay, Tasmania, Australia. Approximately 1650 calves were born. Heifers were weaned, scanned for attainment of puberty prior to joining at approximately 15 months of age, joined, and then recorded for status of pregnancy, calving, lactating, 2nd pregnancy, and weaning of second calf. Heterozygosity effects were significant for heifer pre-joining weight and height as well as proportion pubertal. Breed differences were significant for the same traits plus pregnancy rate at second joining and proportion rearing two calves. Genetic parameters were reported for 13 traits. On average, higher genetic merit (Estimated Breeding Value, EBV percentile) Hereford bulls were used than Angus for growth and puberty, but they were similar for fat and reproduction. Days to calving BREEDPLAN EBVs of the sires were related to puberty and reproduction. Scrotal size BREEDPLAN EBVs of the sires were related to attainment of puberty genomic EBVs calculated. In summary, breed differences in growth and puberty were due to heterosis, but there was an advantage of Hereford genes for reproductive performance. Ongoing emphasis on selection for reduced days to calving and estimation of multi-breed EBVs is important

Genetic and Phenotypic Relationships between Kid Survival and Birth Weight in Australian Meat Goats

The Australian goat industry would like to improve reproductive rate by increasing kid survival. Parameter estimates for kid survival and correlated traits are yet to be reported. A preliminary analysis of birth weight and survival was conducted using 16,050 records from industry herds. The heritability for birth weight (0.32±0.029) was similar to previous reports, but the heritability for kid survival (0.29±0.024) was higher than expected in comparison to other breeds of goats and sheep. The phenotypic variance for birth weight is similar to those previously reported for Boer goats. For a binomial trait there was moderate variation in kid survival with a phenotypic deviation of 0.288, birth weight had a moderate amount of variation with a standard deviation of 0.599kg. The lowest kid survival rates occur in animals less than 2.5kg with survival rates between 67% and 85%, while animals over 2.5kg had survival rates between 92% and 98%, the overall mean for survival was 85%. The phenotypic correlation estimate of 0.16 is low but positive for birth weight and survival. The genetic correlation was also positive and high at 0.54±0.068. Improving survival could potentially be achieved either with direct selection or indirect selection with birth weight

Residual Variance–Covariance Modelling in Analysis of Multivariate Data from Variety Selection Trials

Field trials for variety selection often exhibit spatial correlation between plots. When multivariate data are analysed from these field trials, there is the added complication in having to simultaneously account for correlation between the traits at both the residual and genetic levels. This may be temporal correlation in the case of multi-harvest data from perennial crop field trials, or between-trait correlation in multi-trait data sets. Use of parsimonious yet plausible models for the variance–covariance structure of the residuals for such data is a key element to achieving an efficient and inferentially sound analysis. In this paper, a model is developed for the residual variance–covariance structure firstly by considering a multivariate autoregressive model in one spatial direction and then extending this to two spatial directions. Conditions for ensuring that the processes are directionally invariant are presented. Using a canonical decomposition, these directionally invariant processes can be transformed into a set of independent separable processes. This simplifies the estimation process. The new model allows for flexible modelling of the spatial and multivariate interaction and allows for different spatial correlation parameters for each harvest or trait. The methods are illustrated using data from lucerne breeding trials at several environments

Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data

Genetic Correlations between Days to Calving across Joinings and Lactation Status in a Tropically Adapted Composite Beef Herd

Female fertility is essential to any beef breeding program. However, little genetic gain has been made due to long generation intervals and low levels of phenotyping. Days to calving (DC) is a fertility trait that may provide genetic gain and lead to an increased weaning rate. Genetic parameters and correlations were estimated and compared for DC across multiple joinings (first, second and third+) and lactation status (lactating and non-lactating) for a tropical composite cattle population where cattle were first mated as yearlings. The genetic correlation between first joining DC and mature joining DC (third+) was moderate–high (0.55–0.83). DC was uncorrelated between multiparous lactating and non-lactating cows (rG = −0.10). Mature joining DC was more strongly correlated with second joining lactating DC (0.41–0.69) than with second joining non-lactating DC (−0.14 to −0.16). Thus, first joining DC, second joining DC and mature joining DC should be treated as different traits to maximise genetic gain. Further, for multi-parous cows, lactating and non-lactating DC should be treated as different traits. Three traits were developed to report back to the breeding programs to maximise genetic gain: the first joining days to calving, the second joining days to calving lactating and mature days to calving lactating

Comparison of Methods to Select Candidates for High-Density Genotyping; Practical Observations in a Cattle Breeding Program

Imputation can be used to obtain a large number of high-density genotypes at the cost of procuring low-density panels. Accurate imputation requires a well-formed reference population of high-density genotypes to enable statistical inference. Five methods were compared using commercial Wagyu genotype data to identify individuals to produce a “well-formed” reference population. Two methods utilised a relationship matrix (MCG and MCA), two of which utilised a haplotype block library (AHAP2 and IWS), and the last selected high influential sires with greater than 10 progeny (PROG). The efficacy of the methods was assessed based on the total proportion of genetic variance accounted for and the number of haplotypes captured, as well as practical considerations in implementing these methods. Concordance was high between the MCG and MCA and between AHAP2 and IWS but was low between these groupings. PROG-selected animals were most similar to MCA. MCG accounted for the greatest proportion of genetic variance in the population (35%, while the other methods accounted for approximately 30%) and the greatest number of unique haplotypes when a frequency threshold was applied. MCG was also relatively simple to implement, although modifications need to be made to account for DNA availability when running over a whole population. Of the methods compared, MCG is the recommended starting point for an ongoing sequencing project

Comparison of Methods to Select Candidates for High-Density Genotyping; Practical Observations in a Cattle Breeding Program

Imputation can be used to obtain a large number of high-density genotypes at the cost of procuring low-density panels. Accurate imputation requires a well-formed reference population of high-density genotypes to enable statistical inference. Five methods were compared using commercial Wagyu genotype data to identify individuals to produce a “well-formed” reference population. Two methods utilised a relationship matrix (MCG and MCA), two of which utilised a haplotype block library (AHAP2 and IWS), and the last selected high influential sires with greater than 10 progeny (PROG). The efficacy of the methods was assessed based on the total proportion of genetic variance accounted for and the number of haplotypes captured, as well as practical considerations in implementing these methods. Concordance was high between the MCG and MCA and between AHAP2 and IWS but was low between these groupings. PROG-selected animals were most similar to MCA. MCG accounted for the greatest proportion of genetic variance in the population (35%, while the other methods accounted for approximately 30%) and the greatest number of unique haplotypes when a frequency threshold was applied. MCG was also relatively simple to implement, although modifications need to be made to account for DNA availability when running over a whole population. Of the methods compared, MCG is the recommended starting point for an ongoing sequencing project