Perspectives on Future Protein Production.

An increasing world population, rising affluence, urbanization, and changing eating habits are all contributing to the diversification of protein production. Protein is a building block of life and is an essential part of a healthy diet, providing amino acids for growth and repair. The challenges and opportunities for production of protein-rich foods from animals (meat, dairy, and aquaculture), plant-based sources (pulses), and emerging protein sources (insects, yeast, and microalgae) are discussed against the backdrop of palatability, nutrition, and sustainability.

ImmuneDEX: a strategy for the genetic improvement of immune competence in Australian Angus cattle.

In animal breeding and genetics, the ability to cope with disease, here defined as immune competence (IC), with minimal detriment to growth and fertility is a desired objective which addresses both animal production and welfare considerations. However, defining and objectively measuring IC phenotypes using testing methods which are practical to apply on-farm has been challenging. Based on previously described protocols, we measured both cell-mediated immune response (Cell-IR) and antibody-mediated immune response (Ab-IR) and combined these measures to determine an animal's IC. Using a population of 2,853 Australian Angus steers and heifers, we compared 2 alternative methods to combine both metrics into a single phenotype to be used as a tool for the genetic improvement of IC. The first method, named ZMEAN, is obtained by taking the average of the individual metrics after subjecting each to a Z-score standardization. The second, ImmuneDEX (IDEX), is a weighted average that considers the correlation between Cell-IR and Ab-IR, as well as the difference in ranking of individuals by each metric, and uses these as weights in the averaging. Both simulation and real data were used to understand the behavior of ZMEAN and IDEX. To further ascertain the relationship between IDEX and other traits of economic importance, we evaluated a range of traits related to growth, feedlot performance, and carcass characteristics. We report estimates of heritability of 0.31 ± 0.06 for Cell-IR, 0.42 ± 0.06 for Ab-IR, 0.42 ± 0.06 for ZMEAN and 0.370 ± 0.06 for IDEX, as well as a unity genetic correlation (rg) between ZMEAN and IDEX. While a moderately positive rg was estimated between Cell-IR and Ab-IR (rg = 0.33 ± 0.12), strongly positive estimates were obtained between IDEX and Cell-IR (rg = 0.80 ± 0.05) and between IDEX and Ab-IR (rg = 0.85 ± 0.04). We obtained a moderately negative rg between IC traits and growth including an rg = -0.38 ± 0.14 between IDEX and weaning weight, and negligible with carcass fat measurements, including an rg = -0.03 ± 0.12 between IDEX and marbling. Given that breeding with a sole focus on production might inadvertently increase susceptibility to disease and associated antibiotic use, our analyses suggest that ImmuneDEX will provide a basis to breed animals that are both highly productive and with an enhanced ability to resist disease.

Associations between immune competence phenotype and feedlot health and productivity in Angus cattle.

Genetic strategies aimed at improving general immune competence (IC) have the potential to reduce the incidence and severity of disease in beef production systems, with resulting benefits of improved animal health and welfare and reduced reliance on antibiotics to prevent and treat disease. Implementation of such strategies first requires that methodologies be developed to phenotype animals for IC and demonstration that these phenotypes are associated with health outcomes. We have developed a methodology to identify IC phenotypes in beef steers during the yard weaning period, which is both practical to apply on-farm and does not restrict the future sale of tested animals. In the current study, a total of 838 Angus steers, previously IC phenotyped at weaning, were categorized as low (n = 98), average (n = 653), or high (n = 88) for the IC phenotype. Detailed health and productivity data were collected on all steers during feedlot finishing, and associations between IC phenotype, health outcomes, and productivity were investigated. A favorable association between IC phenotype and number of mortalities during feedlot finishing was observed with higher mortalities recorded in low IC steers (6.1%) as compared with average (1.2%, P < 0.001) or high (0%, P = 0.018) IC steers. Disease incidence was numerically highest in low IC steers (15.3 cases/100 animals) and similar in average IC steers (10.1 cases/100 animals) and high IC steers (10.2 cases/100 animals); however, differences between groups were not significant. No significant influence of IC phenotype on average daily gain was observed, suggesting that selection for improved IC is unlikely to incur a significant penalty to production. The potential economic benefits of selecting for IC in the feedlot production environment were calculated. Health-associated costs were calculated as the sum of lost production costs, lost capital investment costs, and disease treatment costs. Based on these calculations, health-associated costs were estimated at AUS$103/head in low IC steers, AUS$25/head in average IC steers, and AUS$4/head in high IC steers, respectively. These findings suggest that selection for IC has the potential to reduce mortalities during feedlot finishing and, as a consequence, improve the health and welfare of cattle in the feedlot production environment and reduce health-associated costs incurred by feedlot operators.

A low-density SNP genotyping panel for the accurate prediction of cattle breeds.

Genomic tools to better define breed composition in agriculturally important species have sparked scientific and commercial industry interest. Knowledge of breed composition can inform multiple scientifically important decisions of industry application including DNA marker-assisted selection, identification of signatures of selection, and inference of product provenance to improve supply chain integrity. Genomic tools are expensive but can be economized by deploying a relatively small number of highly informative single-nucleotide polymorphisms (SNP) scattered evenly across the genome. Using resources from the 1000 Bull Genomes Project we established calibration (more stringent quality criteria; N = 1,243 cattle) and validation (less stringent; N = 864) data sets representing 17 breeds derived from both taurine and indicine bovine subspecies. Fifteen successively smaller panels (from 500,000 to 50 SNP) were built from those SNP in the calibration data that increasingly satisfied 2 criteria, high differential allele frequencies across the breeds as measured by average Euclidean distance (AED) and high uniformity (even spacing) across the physical genome. Those SNP awarded the highest AED were in or near genes previously identified as important signatures of selection in cattle such as LCORL, NCAPG, KITLG, and PLAG1. For each panel, the genomic breed composition (GBC) of each animal in the validation dataset was estimated using a linear regression model. A systematic exploration of the predictive accuracy of the various sized panels was then undertaken on the validation population using 3 benchmarking approaches: (1) % error (expressed relative to the estimated GBC made from over 1 million SNP), (2) % breed misassignment (expressed relative to each individual's breed recorded), and (3) Shannon's entropy of estimated GBC across the 17 target breeds. Our analyses suggest that a panel of just 250 SNP represents an adequate balance between accuracy and cost-only modest gains in accuracy are made as one increases panel density beyond this point.

In silico validation of pooled genotyping strategies for genomic evaluation in Angus cattle.

In this study, we aimed to assess the value of genotyping DNA pools as a strategy to generate accurate and cost-effective genomic estimated breeding values (GEBV) of sires in multi-sire mating systems. In order to do that, we used phenotypic records of 2,436 Australian Angus cattle from 174 sires, including yearling weight (YWT; N = 1,589 records), coat score (COAT; N = 2,026 records), and Meat Standards Australia marbling score (MARB; N = 1,304 records). Phenotypes were adjusted for fixed effects and age at measurement and pools of 2, 5, 10, 15, 20, and 25 animals were explored. Pools were created either by phenotype or at random. When pools were created at random, 10 replicates were examined to provide a measure of sampling variation. The relative accuracy of each pooling strategy was measured by the Pearson correlation coefficient between the sire's GEBV with pooled progeny and the GEBV using individually genotyped progeny. Random pools allow the computation of sire GEBV that are, on average, moderately correlated (i.e., r > 0.5 at pool sizes [PS] ≤ 10) with those obtained without pooling. However, for pools assigned at random, the difference between the best and the worst relative accuracy obtained out of the 10 replicates was as high as 0.41 for YWT, 0.36 for COAT, and 0.61 for MARB. This uncertainty associated with the relative accuracy of GEBV makes randomly assigning animals to pools an unreliable approach. In contrast, pooling by phenotype allowed the estimation of sires' GEBV with a relative accuracy ≥ 0.9 at PS < 10 for all three phenotypes. Moreover, even with larger PS, the lowest relative accuracy obtained was 0.88 (YWT, PS = 20). In agreement with results using simulated data, we conclude that pooling by phenotype is a robust approach to implementing genomic evaluation using commercial herd data, and PS larger than 10 individuals can be considered.

Immune competence traits assessed during the stress of weaning are heritable and favorably genetically correlated with temperament traits in Angus cattle1.

Selection for production traits with little or no emphasis on health-related traits has the potential to increase susceptibility to disease in food-producing animals. A possible genetic strategy to mitigate such effects is to include both production and health traits in the breeding objective when selecting animals. For this to occur, reliable methodologies are required to assess beneficial health traits, such as the immune capacity of animals. We describe here a methodology to assess the immune competence of beef cattle which is both practical to apply on farm and does not restrict the future sale of tested animals. The methodology also accommodates variation in prior vaccination history of cohorts of animals being tested. In the present study, the immune competence phenotype of 1,100 Angus calves was assessed during yard weaning. Genetic parameters associated with immune competence traits were estimated and associations between immune competence, temperament, and stress-coping ability traits were investigated. Results suggested that immune competence traits, related to an animal's ability to mount both antibody and cell-mediated immune responses, are moderately heritable (h2 = 0.32 ± 0.09 and 0.27 ± 0.08, respectively) and favorably genetically correlated with the temperament trait, flight time (r = 0.63 ± 0.31 and 0.60 ± 0.29 with antibody and cell-mediated immune responses, respectively). Development of methodologies to assess the immune competence phenotype of beef cattle is a critical first step in the establishment of genetic selection strategies aimed at improving the general disease resistance of beef herds. Strategies aimed at reducing the incidence of disease in beef cattle are expected to significantly improve animal health and welfare, reduce reliance on the use of antibiotics to treat disease, and reduce disease-associated costs incurred by producers.

Quantification of differences in resistance to gastrointestinal nematode infections in sheep using a multivariate blood parameter.

Breeding for resistance to gastrointestinal nematodes (GIN) in sheep relies largely on the use of worm egg counts (WEC) to identify animals that are able to resist infection. As an alternative to such measures of parasite load we aimed to develop a method to identify animals showing resistance to GIN infection based on the impact of the infection on blood parameters. We hypothesized that blood parameters may provide a measure of infection level with a blood-feeding parasite through perturbation of red blood cell parameters due to feeding behaviour of the parasite, and white blood cell parameters through the mounting of an immune response in the host animal. We measured a set of blood parameters in 390 sheep that had been exposed to an artificial regime of repeated challenges with Trichostrongylus colubriformis followed by Haemonchus contortus. A simple analysis revealed strong relationships between single blood parameters and WECs with correlation coefficients -0.54 to -0.60. We then used more complex multi-variate methods based on supervised classifier models (including Bayesian Network) as well as regression models (Lasso and Elastic Net) to study the relationships between WECs and blood parameters, and derived algorithms describing the relationships. The ability of these algorithms to classify sheep GIN resistance status was tested using the WEC and blood parameters collected from a different group of 418 sheep that had acquired natural infections of H. contortus from pasture. We identified the most resistant and most susceptible animals (10% percentiles) of this group based on WECs, and then compared the identities of these animals to the identities of animals that were predicted to be most resistant and most susceptible by our algorithms. The models showed varying abilities to predict susceptible and resistant sheep, with up to 65% of the most susceptible animals and 30% of the most resistant animals identified by the Elastic Net model algorithms. The prediction algorithms derived from female sheep data performed better than those for male sheep in some cases, with the predicted animals accounting for up to 50-60% of the actual resistant and susceptible female animals. Heritability values were calculated for blood parameters and the aggregate trait descriptions defined by the novel prediction algorithms. The aggregate trait descriptions were moderately heritable and may therefore be suitable for use in genetic selection strategies. The present study indicates that multivariate models based on blood parameter data showed some ability to predict the resistance status of sheep to infection with H. contortus.

Estimating the genetic merit of sires by using pooled DNA from progeny of undetermined pedigree.

BACKGROUND: DNA-based predictions for hard-to-measure production traits hold great promise for selective breeding programs. DNA pooling might provide a cheap genomic approach to use phenotype data from commercial flocks which are commonly group-mated with parentage unknown. This study on sheep explores if genomic breeding values for stud sires can be estimated from genomic relationships that were obtained from pooled DNA in combination with phenotypes from commercial progeny. METHODS: Phenotypes used in this study were categorical data. Blood was pooled strategically aiming at even pool sizes and within sex and phenotype category. A hybrid genomic relationship matrix was constructed relating pools to sires. This matrix was used to determine the contribution of sires to each of the pools and therefore phenotype category by using a simple regression approach. Genomic breeding values were also estimated using the hybrid genomic relationship matrix. RESULTS: We demonstrated that, using pooled DNA, the genetic performance of sires can be illustrated as their contribution to phenotype categories and can be expressed as a regression coefficient. Genomic estimated breeding values for sires were equivalent to the regression coefficients and are a commonly used industry tool. CONCLUSIONS: Genotyping of DNA from pooled biological samples offers a cheap method to link phenotypic information from commercial production animals to the breeding population and can be turned into information on the genetic value of stud sires for traits that cannot be measured in the stud environment.

Linkage disequilibrium over short physical distances measured in sheep using a high-density SNP chip.

The extent of linkage disequilibrium (LD) between genetic loci has implications for both association studies and the accuracy of genomic prediction. To characterise the persistence of LD in diverse sheep breeds, two SNP genotyping platforms were used. First, existing SNP genotypes from 63 breeds obtained using the ovine SNP50 BeadChip (49,034 loci) were used to estimate LD decay in populations with contrasting levels of genetic diversity. Given the paucity of marker pairs separated by short physical distances on the SNP50 BeadChip, genotyping was subsequently performed for four breeds using the recently developed ovine HD BeadChip that assays approximately 600,000 SNPs with an average genomic spacing of 5 kb. This facilitated a highly accurate estimate of LD over short genomic distances (<30 kb) and revealed LD varies considerably between sheep breeds. Further, sheep appear to contain generally lower levels of LD than do other domestic species, likely a reflection of aspects of their past population history.

Descriptive statistics of data: understanding the data set and phenotypes of interest.

A good understanding of the design of an experiment and the observational data that have been collected as part of the experiment is a key pre-requisite for correct and meaningful preparation of field data for further analysis. In this chapter, I provide a guideline of how an understanding of the field data can be gained, preparation steps that arise as a consequence of the experimental or data structure, and how to fit a linear model to extract data for further analysis.

Chromosomal differences between European and North American Atlantic salmon discovered by linkage mapping and supported by fluorescence in situ hybridization analysis.

BACKGROUND: Geographical isolation has generated a distinct difference between Atlantic salmon of European and North American Atlantic origin. The European Atlantic salmon generally has 29 pairs of chromosomes and 74 chromosome arms whereas it has been reported that the North American Atlantic salmon has 27 chromosome pairs and an NF of 72. In order to predict the major chromosomal rearrangements causing these differences, we constructed a dense linkage map for Atlantic salmon of North American origin and compared it with the well-developed map for European Atlantic salmon. RESULTS: The presented male and female genetic maps for the North American subspecies of Atlantic salmon, contains 3,662 SNPs located on 27 linkage groups. The total lengths of the female and male linkage maps were 2,153 cM and 968 cM respectively, with males characteristically showing recombination only at the telomeres. We compared these maps with recently published SNP maps from European Atlantic salmon, and predicted three chromosomal reorganization events that we then tested using fluorescence in situ hybridization (FISH) analysis. The proposed rearrangements, which define the differences in the karyotypes of the North American Atlantic salmon relative to the European Atlantic salmon, include the translocation of the p arm of ssa01 to ssa23 and polymorphic fusions: ssa26 with ssa28, and ssa08 with ssa29. CONCLUSIONS: This study identified major chromosomal differences between European and North American Atlantic salmon. However, while gross structural differences were significant, the order of genetic markers at the fine-resolution scale was remarkably conserved. This is a good indication that information from the International Cooperation to Sequence the Atlantic salmon Genome, which is sequencing a European Atlantic salmon, can be transferred to Atlantic salmon from North America.

Estimating the effect of SNP genotype on quantitative traits from pooled DNA samples.

BACKGROUND: Studies to detect associations between DNA markers and traits of interest in humans and livestock benefit from increasing the number of individuals genotyped. Performing association studies on pooled DNA samples can provide greater power for a given cost. For quantitative traits, the effect of an SNP is measured in the units of the trait and here we propose and demonstrate a method to estimate SNP effects on quantitative traits from pooled DNA data. METHODS: To obtain estimates of SNP effects from pooled DNA samples, we used logistic regression of estimated allele frequencies in pools on phenotype. The method was tested on a simulated dataset, and a beef cattle dataset using a model that included principal components from a genomic correlation matrix derived from the allele frequencies estimated from the pooled samples. The performance of the obtained estimates was evaluated by comparison with estimates obtained using regression of phenotype on genotype from individual samples of DNA. RESULTS: For the simulated data, the estimates of SNP effects from pooled DNA are similar but asymptotically different to those from individual DNA data. Error in estimating allele frequencies had a large effect on the accuracy of estimated SNP effects. For the beef cattle dataset, the principal components of the genomic correlation matrix from pooled DNA were consistent with known breed groups, and could be used to account for population stratification. Correctly modeling the contemporary group structure was essential to achieve estimates similar to those from individual DNA data, and pooling DNA from individuals within groups was superior to pooling DNA across groups. For a fixed number of assays, pooled DNA samples produced results that were more correlated with results from individual genotyping data than were results from one random individual assayed from each pool. CONCLUSIONS: Use of logistic regression of allele frequency on phenotype makes it possible to estimate SNP effects on quantitative traits from pooled DNA samples. With pooled DNA samples, genotyping costs are reduced, and in cases where trait records are abundant this approach is promising to obtain SNP associations for marker-assisted selection.

The distribution of SNP marker effects for faecal worm egg count in sheep, and the feasibility of using these markers to predict genetic merit for resistance to worm infections.

SummaryGenetic resistance to gastrointestinal worms is a complex trait of great importance in both livestock and humans. In order to gain insights into the genetic architecture of this trait, a mixed breed population of sheep was artificially infected with Trichostrongylus colubriformis (n=3326) and then Haemonchus contortus (n=2669) to measure faecal worm egg count (WEC). The population was genotyped with the Illumina OvineSNP50 BeadChip and 48 640 single nucleotide polymorphism (SNP) markers passed the quality controls. An independent population of 316 sires of mixed breeds with accurate estimated breeding values for WEC were genotyped for the same SNP to assess the results obtained from the first population. We used principal components from the genomic relationship matrix among genotyped individuals to account for population stratification, and a novel approach to directly account for the sampling error associated with each SNP marker regression. The largest marker effects were estimated to explain an average of 0·48% (T. colubriformis) or 0·08% (H. contortus) of the phenotypic variance in WEC. These effects are small but consistent with results from other complex traits. We also demonstrated that methods which use all markers simultaneously can successfully predict genetic merit for resistance to worms, despite the small effects of individual markers. Correlations of genomic predictions with breeding values of the industry sires reached a maximum of 0·32. We estimate that effective across-breed predictions of genetic merit with multi-breed populations will require an average marker spacing of approximately 10 kbp.

Factors influencing the efficiency of a marker-assisted introgression programme in Merino sheep.

This study investigated a marker-assisted introgression programme in Australian Merino sheep. The goal was to introgress an allele with a large negative effect on fibre diameter into a Merino flock possessing medium average fibre diameter. The influence of two factors was explored: the strategy used to select animals from the purebred and backcross line for backcrossing purposes and the use of selection on background markers to accelerate the return to the purebred line's genome. The results were compared to introgression based on EBVs only. Introgression using EBVs only produced almost the same response in the dollar index as marker-based introgression methods. However, this study did not account for some of the costs associated with implementing the programmes, including the costs of phenotyping and genotyping. Given that the cost of measuring fibre diameter is low, it was concluded that introgression on EBVs only would be the preferred method since the marginal profit of marker-assisted introgression would not be large enough to cover the additional cost of genotyping. In marker-assisted introgression, reciprocal crossing of male and female selection candidates from the backcross and the purebred line was the most advantageous strategy from a practical and profit point of view. Selection for background markers was less profitable in this study than recovering the donor genome by selection on phenotype.

Quantitative trait loci for internal nematode resistance in sheep: a review.

Internal nematode resistance in sheep has a large impact on the economy of sheep industries. Selection for nematode resistance in sheep breeding schemes would help to reduce the direct and indirect cost of parasitism to these industries. However, this is not widely practiced because of the difficulty of measuring parasite resistance or correlated indirect selection criteria. The identification of genes or linked markers that have a significant association with the variance of indicator traits of internal nematode resistance in sheep would facilitate the inclusion of nematode resistance in sheep breeding operations. This review summarises findings reported in the literature of quantitative trait loci for internal nematode resistance in sheep. Issues relating to the analytical and phenotypic complexity of nematode resistance are discussed in the context of the findings of quantitative trait loci for nematode resistance published to date.