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Background:The Boran (Bos indicus), indigenous Zebu cattle breed from subSaharan Africa, is remarkably well adapted to harsh tropical environments. Due to financial constraints and low-quality forage, African livestock are rarely fed at 100% maintenance energy requirements (MER) and the effect of sub-optimal restricted feeding on the rumen microbiome of African Zebu cattle remains largely unexplored. We collected 24 rumen fluid samples from six Boran cattle fed at suboptimal and optimal MER levels and characterised their rumen microbial composition by performing shotgun metagenomics and de novo assembly of metagenome-assembled genomes (MAGs). These MAGs were used as reference database to investigate the effect of diet restriction on the composition and functional potential of the rumen microbiome of African cattle.

Results: We report 1200 newly discovered MAGs from the rumen of Boran cattle. A total of 850 were dereplicated, and their uniqueness confirmed with pairwise comparisons (based on Mash distances) between African MAGs and other publicly available genomes from the rumen. A genome-centric investigation into sub-optimal diets highlighted a statistically significant effect on rumen microbial abundance profiles and a previously unobserved relationship between whole microbiome shifts in functional potential and taxon-level associations in metabolic pathways.

Conclusions: This study is the first to identify 1200 high-quality African rumen specific MAGs and provides further insight into the rumen function in harsh environments with food scarcity. The genomic information from the rumen microbiome of an indigenous African cattle breed sheds light on the microbiome contribution to rumen functionality and constitutes a vital resource in addressing food security in developing countries.

Korean 'Hanwoo' cattle are prized for their high marbling ability and meat quality. Classically, these cattle possess a homogeneous yellow coat colouring, with farmers believing that 'Hanwoo' with white spotted coats are crossbred and therefore unacceptable for breeding purposes. In this study we first attempted to determine if the coat spots were due to a non-'Hanwoo' genetic background or, alternatively, if the trait is intrinsic to the breed. By genotyping 232 (136 spotted) animals from half-sib families on the Illumina Bovine 50K SNP array, we compared the genotyped Hanwoo to other unrelated 'Hanwoo' and European taurine breeds using principal component analysis. Results showed no evidence of crossbreeding in the spotted animals. A differential evolution algorithm was then used to evolve a classifier for the trait which selected 12 SNP with an accuracy of ~82% in separating individuals; further investigation using only haplotypes inherited from the sires resulted in a marked improvement to ~92% accuracy for these 12 SNP. This research highlights the potential for using these SNP as genetic markers to either entirely remove the trait from the population in the long term or manage matings so that the trait is not expressed in the offspring.

The wild water buffalo (Asian buffalo, wild Asian buffalo) 'Bubalus arnee' (Kerr 1792) - is one of a number of 'Bubalus' species which were widely distributed in Europe and southern Asia in the Pleistocene, but later was restricted to the Indian subcontinent and Southeast Asia (Mason 1974). Two species, 'B. teilhardi' and 'B.youngi', which were morphologically identified from bone remains in the Wei River valley (Shaanxi Province, China) apparently became extinct during the Pleistocene (Yang et al. 2008). A third species in China, 'B. mephistopheles' (Hopwood, 1925) also found in the Wei River valley and the lower Yangzi River region, survived to the Neolithic and Bronze Age in the Holocene (Liu et al. 2004; Yang et al. 2008). Extant 'Bubalus' species include 'B. mindorensis' (Heude 1888) or tamaraw from Mindoro Island, the Philippines, which is critically endangered (Hedges et al. 2008a), and two species of anoa from Sulawesi, Indonesia: 'B. depressicornis' (C. H. Smith 1827) or lowland anoa and 'B. quarlesi' (Ouwens 1910) or mountain anoa. There is still debate about whether these two are distinct species (Burton et al. 2005), but both are endangered (Semiadi et al. 2008a, 2008b). In historical times, the wild Asian buffalo ranged across South and Southeast Asia from Mesopotamia to Indo-China (Epstein 1971; Mason 1974; Cockrill 1984). It is currently listed as Endangered (Hedges et al. 2008b), with a world population of fewer than 4000, potentially fewer than 200, and it is even possible that no purebred wild animals exist.

Emissions of 710 ewes at pasture were measured for 1 h (between 09:00-16:30 h) in batches of 15 sheep in portable accumulation chambers (PAC) after an overnight fast continuing until 2 h before measurement, when the sheep had access to baled hay for 1 h. The test was used to identify a group of 104 low emitters (I-Low) and a group of 103 high emitters (I-Hi) for methane emissions adjusted for liveweight (CH4awt). The 207 ewes selected at the initial study were remeasured in 5 repeat tests from 2009 through 2014 at another location. The first repeat used the original measurement protocol. Two modified protocols, each used in 2 yr, drafted unfasted sheep on the morning of the test into a yard or holding paddock until measurement. Emissions of the I-Hi sheep were higher (102-112%) than I-Low sheep in all subsequent PAC tests, with statistical significance (P < 0.05) in 3 tests. Tests without overnight fasting were simpler to conduct and had repeatabilities of 51 to 60% compared with 31 and 43% for the initial and first repeat tests, respectively. After habituation to a diet fed at 20 g/kg liveweight, 160 of the 207 sheep were measured in respiration chambers (RC); 10 high (Hi-10) and 10 low (Low-10) sheep were chosen, representing extremes (top and bottom 6.25%) for methane yield (MY; g CH4/kg DMI). The Hi-10 group emitted 14% more methane (adjusted for feed intake) in a follow-up RC test, but Low-10 and Hi-10 sheep differed in only 1 of the 5 PAC tests, when Hi-10 sheep emitted less CH4awt than Low-10 sheep (P = 0.002) and tended to eat less in the feeding opportunity (P = 0.085). Compared with their weight on good pasture, Low-10 sheep were proportionately lighter than Hi-10 sheep in the relatively poor pasture conditions of the initial test. Sheep identified as low emitters by PAC tests using the initial protocol did not produce less CH4 (mg/min) when fed a fixed level of intake in RC. Correlations between estimates of an animal's CH4awt measured in PAC and CH4 adjusted for feed intake in RC were quite low (r = 0-19%) and significant (P < 0.05) in only 1 test of unfasted sheep. With moderate repeatability over the 5 yr, PAC tests of CH4awt could be a viable way to select for reduced emissions of grazing sheep. As well as exploiting any variation in MY, selecting for reduced CH4awt in PAC could result in lower feed intake than expected for the animals' liveweight and might affect the diurnal feeding pattern. Further work is required on these issues.

Wheat is a common raw material in Australian broiler diets because of its high starch and protein content. However, the main concern with wheat is the presence of soluble non starch polysaccharides (NSPs), especially arabinoxylans. Arabinoxylans may account for up to 61 g/kg of wheat dry matter (Choct and Annison, 1990). These NSPs are difficult to digest and may cause digesta to become viscous thereby reducing nutrient digestion and absorption. Many NSP degrading enzyme products are commercially available and are used in the poultry feed industry. This study was undertaken to compare the effect of different enzymes preparations on in vitro viscosity of different wheat varieties.

A trial was conducted to test the following hypothesis; broiler exposure to coarse insoluble fibre in the diet or litter will result in enhanced gizzard function and performance, improved adaptability to an intermittent feeding program and an increase in the occurrence of reverse peristalsis. Ross 308 broiler chickens were either intermittent or ad libitum fed a basal diet, a basal diet diluted with 15 % coarse hulls (barley and oats) or a basal diet diluted with 15 % finely ground hulls in a 2x3-factorial experiment (n = 17 birds/treatment). From 18 days of age, the birds were transferred to individual cages. Birds on intermittent feeding had restricted access to feed from 11 days of age. From 18 days of age, the restrictive feeding program consisted of four one-hour meals and one two-hour meal per day. AME value and faecal starch digestibility were determined by quantitative collection of excreta. At 31 and 32 days of age, birds were inoculated with CrEDTA via the cloaca. Weights were recorded and digesta samples collected from the gizzard, duodenum, jejunum, and ileum. There was no interaction between diet and feeding regime for any of the parameters measured. The addition of coarse oat and barley hulls resulted in birds with fuller, heavier gizzards (p < 0.001). Intermittently fed birds raised on the coarse hull diet exhibited an improved starch digestibility compared to birds not exposed to hulls (p < 0.001). The presence of chromium in all intestinal tract sections of birds from the six treatment groups, confirms that reflux occurs along the entire length of the gastro intestinal tract, irrespective of insoluble fiber content of the feed or feeding regime.

The aim of the present studywas to determine the direct cause of the mutation-induced, increased ovulation rate in Booroola Merino (BB) sheep. Granulosa cells were removed from antral follicles before ovulation and post-ovulation from BB (nZ5) and WT (nZ12) Merino ewes. Direct immunofluorescence measurement of mature cell surface receptors using flow cytometry demonstrated a significant up-regulation of FSH receptor (FSHR), transforming growth factor beta type 1, bone morphogenetic protein receptor (BMPR1B), and LH receptor (LHR) in BB sheep. The increased density of FSHR and LHR provide novel evidence of a mechanism for increasing the number of follicles that are recruited during dominant follicle selection. The compounding increase in receptors with increasing follicle size maintained the multiple follicles and reduced the apoptosis, which contributed to a high ovulation rate in BB sheep. In addition, we report a mutation-independent mechanism of down-regulation to reduce receptor density of the leading dominant follicle in sheep. The suppression of receptor density coincides with the cessation of mitogenic growth and steroidogenic differentiation as part of the luteinization of the follicle. The BB mutation-induced attenuation of BMPR1B signaling led to an increased density of the FSHR and LHR and a concurrent reduction in apoptosis to increase the ovulation rate. The role of BMPs in receptor modulation is implicated in the development of multiple ovulations.

Body weight (BW) is an important trait for meat production in sheep. In order to clarify genes and chromosomal regions that might be associated with body weight in sheep, a genome-wide association study using Illumina 50K Ovine SNP chip on a population of 1,743 Australian Merino sheep was carried out. A total of 39 SNPs were found to be associated with BW at Bonferroni-corrected genome-wide significance of 1%. One region on OAR6, between 40.3 Mb and 42.9 Mb, included 13 significant SNPs that were identified as being associated with the trait. The most significant SNP (OAR6_41936490.1) has 2.11 kg of allele substitution effect, while the second most significant SNP (s17946.1) has 2.13 kg of effect on body weight. These correspond to 24.33% and 24.57%, respectively, of the phenotypic standard deviations for BW in Australian Merino sheep.

Background: In many traits, not only individual trait levels are under genetic control, but also the variation around that level. In other words, genotypes do not only differ in mean, but also in (residual) variation around the genotypic mean. New statistical methods facilitate gaining knowledge on the genetic architecture of complex traits such as phenotypic variability. Here we study litter size (total number born) and its variation in a Large White pig population using a Double Hierarchical Generalized Linear model, and perform a genome-wide association study using a Bayesian method. Results: In total, 10 significant single nucleotide polymorphisms (SNPs) were detected for total number born (TNB) and 9 SNPs for variability of TNB (varTNB). Those SNPs explained 0.83% of genetic variance in TNB and 1.44% in varTNB. The most significant SNP for TNB was detected on 'Sus scrofa' chromosome (SSC) 11. A possible candidate gene for TNB is 'ENOX1', which is involved in cell growth and survival. On SSC7, two possible candidate genes for varTNB are located. The first gene is coding a swine heat shock protein 90 ('HSPCB = Hsp90'), which is a well-studied gene stabilizing morphological traits in 'Drosophila' and 'Arabidopsis'. The second gene is 'VEGFA', which is activated in angiogenesis and vasculogenesis in the fetus. Furthermore, the genetic correlation between additive genetic effects on TNB and on its variation was 0.49. This indicates that the current selection to increase TNB will also increase the varTNB. Conclusions: To the best of our knowledge, this is the first study reporting SNPs associated with variation of a trait in pigs. Detected genomic regions associated with varTNB can be used in genomic selection to decrease varTNB, which is highly desirable to avoid very small or very large litters in pigs. However, the percentage of variance explained by those regions was small. The SNPs detected in this study can be used as indication for regions in the 'Sus scrofa' genome involved in maintaining low variability of litter size, but further studies are needed to identify the causative loci.

'Background': Knowledge of the genetic structure and overall diversity of livestock species is important to maximise the potential of genome-wide association studies and genomic prediction. Commonly used measures such as linkage disequilibrium (LD), effective population size ('N'ₑ), heterozygosity, fixation index ('F'ST) and runs of homozygosity (ROH) are widely used and help to improve our knowledge about genetic diversity in animal populations. The development of high-density single nucleotide polymorphism (SNP) arrays and the subsequent genotyping of large numbers of animals have greatly increased the accuracy of these population-based estimates. 'Methods': In this study, we used the Illumina OvineSNP50 BeadChip array to estimate and compare LD (measured by r² and D¹), Ne, heterozygosity, FST and ROH in five Australian sheep populations: three pure breeds, i.e., Merino (MER), Border Leicester (BL), Poll Dorset (PD) and two crossbred populations i.e. F1 crosses of Merino and Border Leicester (MxB) and MxB crossed to Poll Dorset (MxBxP). 'Results': Compared to other livestock species, the sheep populations that were analysed in this study had low levels of LD and high levels of genetic diversity. The rate of LD decay was greater in Merino than in the other pure breeds. Over short distances (<10 kb), the levels of LD were higher in BL and PD than in MER. Similarly, BL and PD had comparatively smaller Nₑthan MER. Observed heterozygosity in the pure breeds ranged from 0.3 in BL to 0.38 in MER. Genetic distances between breeds were modest compared to other livestock species (highest 'F'ST = 0.063) but the genetic diversity within breeds was high. Based on ROH, two chromosomal regions showed evidence of strong recent selection. 'Conclusions': This study shows that there is a large range of genome diversity in Australian sheep breeds, especially in Merino sheep. The observed range of diversity will influence the design of genome-wide association studies and the results that can be obtained from them. This knowledge will also be useful to design reference populations for genomic prediction of breeding values in sheep.

The independent domestication of local wild boar populations in Asia and Europe about 10,000 years ago led to distinct European and Asian pig breeds, each with very different phenotypic characteristics. During the Industrial Revolution, Chinese breeds were imported to Europe to improve commercial traits in European breeds. Here we demonstrate the presence of introgressed Asian haplotypes in European domestic pigs and selection signatures on some loci in these regions, using whole genome sequence data. The introgression signatures are widespread and the Asian haplotypes are rarely fixed. The Asian introgressed haplotypes are associated with regions harbouring genes involved in meat quality, development and fertility. We identify Asian-derived non-synonymous mutations in the AHR gene that associate with increased litter size in multiple European commercial lines. These findings demonstrate that increased fertility was an important breeding goal for early nineteenth century pig farmers, and that Asian variants of genes related to this trait were preferentially selected during the development of modern European pig breeds.

In this paper we proposed a method to improve the accuracy of prediction of genomic best linear unbiased prediction (GBLUP). In GBLUP a genomic relationship matrix (GRM) is used to define the variance-covariance relationship between individuals and is calculated from all available genotyped markers. Instead of using all markers to build the GRM, which is then used for trait prediction, we used an evolutionary algorithm (differential evolution - DE) to subset the marker set and identify the markers that best capture the variance-covariance structure between individuals for specific traits. This subset of markers was then used to build a trait relationship matrix (TRM) that replaces the GRM in GBLUP (herein referred to as TBLUP). The predictive ability of TBLUP was compared against GBLUP and a Bayesian method (Bayesian LASSO) using simulated and real data. We found that TBLUP has better predictive ability than GBLUP and Bayesian LASSO in almost all scenarios.

Background: Selection pressure on the number of teats has been applied to be able to provide enough teats for the increase in litter size in pigs. Although many QTL were reported, they cover large chromosomal regions and the functional mutations and their underlying biological mechanisms have not yet been identified. To gain a better insight in the genetic architecture of the trait number of teats, we performed a genome-wide association study by genotyping 936 Large White pigs using the Illumina PorcineSNP60 Beadchip. The analysis is based on deregressed breeding values to account for the dense family structure and a Bayesian approach for estimation of the SNP effects. Results: The genome-wide association study resulted in 212 significant SNPs. In total, 39 QTL regions were defined including 170 SNPs on 13 'Sus scrofa' chromosomes (SSC) of which 5 regions on SSC7, 9, 10, 12 and 14 were highly significant. All significantly associated regions together explain 9.5% of the genetic variance where a QTL on SSC7 explains the most genetic variance (2.5%). For the five highly significant QTL regions, a search for candidate genes was performed. The most convincing candidate genes were VRTN and Prox2 on SSC7, MPP7, ARMC4, and MKX on SSC10, and vertebrae δ-EF1 on SSC12. All three QTL contain candidate genes which are known to be associated with vertebral development. In the new QTL regions on SSC9 and SSC14, no obvious candidate genes were identified. Conclusions: Five major QTL were found at high resolution on SSC7, 9, 10, 12, and 14 of which the QTL on SSC9 and SSC14 are the first ones to be reported on these chromosomes. The significant SNPs found in this study could be used in selection to increase number of teats in pigs, so that the increasing number of live-born piglets can be nursed by the sow. This study points to common genetic mechanisms regulating number of vertebrae and number of teats.

Background: Traditional breeding programs consider an average pairwise kinship between sibs. Based on pedigree information, the relationship matrix is used for genetic evaluations disregarding variation due to Mendelian sampling. Therefore, inbreeding and kinship coefficients are either over or underestimated resulting in reduction of accuracy of genetic evaluations and genetic progress. Single nucleotide polymorphism (SNPs) can be used to estimate pairwise kinship and individual inbreeding more accurately. The aim of this study was to optimize the selection of markers and determine the required number of SNPs for estimation of kinship and inbreeding. Results: A total of 1,565 animals from three commercial pig populations were analyzed for 28,740 SNPs from the PorcineSNP60 Beadchip. Mean genomic inbreeding was higher than pedigree-based estimates in lines 2 and 3, but lower in line 1. As expected, a larger variation of genomic kinship estimates was observed for half and full sibs than for pedigree-based kinship reflecting Mendelian sampling. Genomic kinship between father-offspring pairs was lower (0.23) than the estimate based on pedigree (0.26). Bootstrap analyses using six reduced SNP panels (n = 500, 1000, 1500, 2000, 2500 and 3000) showed that 2,000 SNPs were able to reproduce the results very close to those obtained using the full set of unlinked markers (n = 7,984-10,235) with high correlations (inbreeding r > 0.82 and kinship r > 0.96) and low variation between different sets with the same number of SNPs. Conclusions: Variation of kinship between sibs due to Mendelian sampling is better captured using genomic information than the pedigree-based method. Therefore, the reduced sets of SNPs could generate more accurate kinship coefficients between sibs than the pedigree-based method. Variation of genomic kinship of father-offspring pairs is recommended as a parameter to determine accuracy of the method rather than correlation with pedigree-based estimates. Inbreeding and kinship coefficients can be estimated with high accuracy using ≥2,000 unlinked SNPs within all three commercial pig lines evaluated. However, a larger number of SNPs might be necessary in other populations or across lines.

The Poll DNA marker test is used to determine the poll genetics of an animal, given the alleles observed within the poll locus. This paper describes improvements made to the commercially available Poll DNA marker test, to capture more variability, enable predictions that are more accurate and clarify uncertainty of polled probabilities.

Cattle were first introduced to Australia with European settlement in 1788. Growth in the Australian beef herd was initially slow, but expanded in the late 19th century with the discovery of gold and the advent of refrigerated transport. By 1900, the Australian beef herd was estimated at 8.6 million head (ABS 2005) and extended to most regions of Australia, including very large pastoral holdings in central and northern Australia. The subsequent impact of two world wars and the Depression saw numbers remain comparatively stable for the next 50 years. In 1950, the Australian beef cattle herd was 9.7 million head (ABS 2005). During the first half of the 20th century, beef production in northern Australia was limited by a lack of effective inland transport systems, a strong (alternative) wool industry in some areas of northern Australia and the poor adaptation of 'Bos taurus' breeds of cattle to the stressors of the tropical environments (McDonald 1988). This changed dramatically over the 1950s to 1970s with the emergence of export markets in the UK and the development of major export markets to the USA and Japan when the trade to Great Britain abruptly ended with its entrance to the European Union. After the beef slump of the mid 1970s and the successful eradication of brucellosis and tuberculosis, there has been an extraordinary expansion of Brahman and Brahman-derived cattle in northern Australia since the 1980s (Bindon and Jones 2001).

The relationship between rumen microbial ecology and the host is regulated by multiple factors including diet, the microbial inoculum entering the gut, and host genetics. Two hypotheses associated with this statement were developed and tested during this project. The first focused on the relationship between diet, early life microbial inoculum and rumen microbiota and the second concentrated on the association between host genetics and gut microbial ecology. Hypothesis one was that the rumen microbiome of lambs could be altered by post-natal diet and by early-life microbial intervention, to achieve differences in rumen fermentation, development and animal performance that persist beyond weaning. Secondly, it was hypothesized that sheep with different genetic merit for wool growth harbour differences in their rumen microbiome that are associated with differences in gut morphology, physiology, digesta retention time and microbial protein outflow which underpin their wool phenotypes.

This thesis explores various methods to optimise breeding programs that use female reproductive technologies and genomic selection. Simulation studies have shown that female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro embryo production and transfer (JIVET) can increase rates of genetic gain through increased female selection intensity and decreased generation interval. Furthermore the use of genomic selection has facilitated better selection decisions to be made on younger selection candidates that may not have phenotypic measurements. When combining genomic selection with reproductive technologies the rate of genetic gain could be further accelerated. However intensive use of the best females in breeding programs can also increase the rate of inbreeding to unsustainable levels. This thesis aimed to stochastically simulate breeding programs where reproductive and genomic technologies are optimally implemented while maintaining a sustainable increase of inbreeding. The impacts of using reproductive technologies and/or genomic selection were evaluated for breeding programs across species. Furthermore, the thesis investigated a cost-benefit analysis of using reproductive technologies which led to a further study that optimized the use of reproductive technologies that considered their costs as well as future co-ancestry during selection.

Noug ('Guizotia abyssinica') is a semidomesticated oil-seed crop, which is primarily cultivated in Ethiopia. Unlike its closest crop relative, sunflower, noug has small seeds, small flowering heads, many branches, many flowering heads, and indeterminate flowering, and it shatters in the field. Here, we conducted common garden studies and microsatellite analyses of genetic variation to test whether high levels of crop-wild gene flow and/or unfavorable phenotypic correlations have hindered noug domestication. With the exception of one population, analyses of microsatellite variation failed to detect substantial recent admixture between noug and its wild progenitor. Likewise, only very weak correlations were found between seed mass and the number or size of flowering heads. Thus, noug's 'atypical' domestication syndrome does not seem to be a consequence of recent introgression or unfavorable phenotypic correlations. Nonetheless, our data do reveal evidence of local adaptation of noug cultivars to different precipitation regimes, as well as high levels of phenotypic plasticity, which may permit reasonable yields under diverse environmental conditions. Why noug has not been fully domesticated remains a mystery, but perhaps early farmers selected for resilience to episodic drought or untended environments rather than larger seeds. Domestication may also have been slowed by noug's outcrossing mating system.

When making the decision about whether or not to breed a given cow, knowledge about the expected outcome would have an economic impact on profitability of the breeding program and net income of the farm. The outcome of each breeding can be affected by many management and physiological features that vary between farms and interact with each other. Hence, the ability of machine learning algorithms to accommodate complex relationships in the data and missing values for explanatory variables makes these algorithms well suited for investigation of reproduction performance in dairy cattle. The objective of this study was to develop a user-friendly and intuitive on-farm tool to help farmers make reproduction management decisions. Several different machine learning algorithms were applied to predict the insemination outcomes of individual cows based on phenotypic and genotypic data. Data from 26 dairy farms in the Alta Genetics (Watertown, WI) Advantage Progeny Testing Program were used, representing a 10-yr period from 2000 to 2010. Health, reproduction, and production data were extracted from on-farm dairy management software, and estimated breeding values were downloaded from the US Department of Agriculture Agricultural Research Service Animal Improvement Programs Laboratory (Beltsville, MD) database. The edited data set consisted of 129,245 breeding records from primiparous Holstein cows and 195,128 breeding records from multiparous Holstein cows. Each data point in the final data set included 23 and 25 explanatory variables and 1 binary outcome for of 0.756 ± 0.005 and 0.736 ± 0.005 for primiparous and multiparous cows, respectively. The naïve Bayes algorithm, Bayesian network, and decision tree algorithms showed somewhat poorer classification performance. An information-based variable selection procedure identified herd average conception rate, incidence of ketosis, number of previous (failed) inseminations, days in milk at breeding, and mastitis as the most effective explanatory variables in predicting pregnancy outcome.

Social interactions between individuals living in a group can have both positive and negative effects on welfare, productivity, and health of these individuals. Negative effects of social interactions in livestock are easier to observe than positive effects. For example, laying hens may develop feather pecking, which can cause mortality due to cannibalism, and pigs may develop tail biting or excessive aggression. Several studies have shown that social interactions affect the genetic variation in a trait. Genetic improvement of socially-affected traits, however, has proven to be difficult until relatively recently. The use of classical selection methods, like individual selection, may result in selection responses opposite to expected, because these methods neglect the effect of an individual on its group mates (social genetic effects). It has become clear that improvement of socially-affected traits requires selection methods that take into account not only the direct effect of an individual on its own phenotype but also the social genetic effects, also known as indirect genetic effects, of an individual on the phenotypes of its group mates. Here, we review the theoretical and empirical work on social genetic effects, with a focus on livestock. First, we present the theory of social genetic effects. Subsequently, we evaluate the evidence for social genetic effects in livestock and other species, by reviewing estimates of genetic parameters for direct and social genetic effects. Then we describe the results of different selection experiments. Finally, we discuss issues concerning the implementation of social genetic effects in livestock breeding programs. This review demonstrates that selection for socially-affected traits, using methods that target both the direct and social genetic effects, is a promising, but sometimes difficult to use in practice, tool to simultaneously improve production and welfare in livestock.

This paper reviews the literature to determine the extent of genetic variation for resistance to stressors of tropical environments in beef and dairy cattle and goats and sheep. It also investigates the existence of genetic antagonisms that would preclude simultaneous improvement of productive and adaptive traits. Most adaptive traits are at least moderately heritable, meaning breeding to improve adaptation is feasible. It also appears that in cattle, goats and sheep which are well-adapted to the tropics, there are very few antagonistic correlations that would preclude simultaneous genetic improvement of both productive and adaptive traits to maximise herd profitability. The major constraint to genetic improvement of adaptation in tropical environments is the ability to accurately and cost-effectively record the fixed effects and phenotypes required for selection programs. Options to overcome this constraint are examined.

The successful breeding of ewes before the age of 12 months presents an opportunity to improve flock reproduction efficiency and increase returns for sheep producers. However, uptake of this practice is currently low in Australia and New Zealand. A contributing factor to this is that reproductive performance at 1 year of age is lower and more variable than in older ewes; between flocks and also from year to year. Whilst previous research has explored what factors contribute to successful reproduction at 1 year of age, there is no universally accepted measure of puberty and sexual maturity in sheep nor is there an accurate phenotypic predictor of yearling reproductive success. Although established genetic correlations between reproduction and production traits exist, reproduction has previously been analysed as a repeated records trait across parities, rather than treating first parity as a separate trait. Model studies show that genomic information offers the opportunity to select animals more accurately at younger ages. However the implications of a lower and more variable fertility rate of ewes mated prior to 1 year of age has been largely ignored. The aim of this thesis was to evaluate the impact of mating ewes prior to 1 year of age on flock genetic progress and to quantify the relationship between potential pubertal traits, yearling reproduction traits, reproduction traits at later parities and other key production traits.

Gene discovery, estimation of heritability captured by SNP arrays, inference on genetic architecture and prediction analyses of complex traits are usually performed using different statistical models and methods, leading to inefficiency and loss of power. Here we use a Bayesian mixture model that simultaneously allows variant discovery, estimation of genetic variance explained by all variants and prediction of unobserved phenotypes in new samples. We apply the method to simulated data of quantitative traits and Welcome Trust Case Control Consortium (WTCCC) data on disease and show that it provides accurate estimates of SNP-based heritability, produces unbiased estimators of risk in new samples, and that it can estimate genetic architecture by partitioning variation across hundreds to thousands of SNPs. We estimated that, depending on the trait, 2,633 to 9,411 SNPs explain all of the SNP-based heritability in the WTCCC diseases. The majority of those SNPs (>96%) had small effects, confirming a substantial polygenic component to common diseases. The proportion of the SNP-based variance explained by large effects (each SNP explaining 1% of the variance) varied markedly between diseases, ranging from almost zero for bipolar disorder to 72% for type 1 diabetes. Prediction analyses demonstrate that for diseases with major loci, such as type 1 diabetes and rheumatoid arthritis, Bayesian methods outperform profile scoring or mixed model approaches.

Asian wild water buffalo ('Bubalus arnee') are large ungulates, and the progenitors of all domestic water buffalo ('Bubalus bubalis'). There are two domestic types: the river buffalo of the Indian sub-continent and further west to the Balkans and Italy (Figure 24.1), and the swamp buffalo of Assam in the west, through Southeast Asia to the Yangtze Valley of China (Figure 24.2). All populations of 'Bubalus arnee' are considered Endangered (IUCN 2013), but in Nepal this species is protected by the National Parks and Wildlife Conservation Act (His Majesty's Government Ministry of Law and Justice 1977). There is evidence of buffaloes in the Indus Valley at least 5000 years ago (Nowak 1999; Lenstra & Bradley 1999). Although the historic range is uncertain, the species may have occurred from Mesopotamia to Indochina (Sinclair 1977). River and swamp buffalo were domesticated independently from different wild stocks that diverged anywhere from 10 000-15 000 (Barker et al. 1997) to over one million years ago (Amano 'et al'. 1994), but probably around 128 000-280 000 years ago (Kumar 'et al'. 2007a). River buffalo were domesticated around 6300 BP in the western region of the Indian subcontinent (Kumar 'et a'l. 2007b). Microsatellite and mtDNA diversity analyses (Yindee 2010; Zhang 'et al'. 2011) combined with archaeological evidence (Higham 2002) indicate domestication of the swamp buffalo in southern China/northern Indo-China about 2000 BC.

The objective of this study was to explore the relationship between SNP and haplotype variation on gene expression traits. The data used included expression levels from 24,128 probe sets of 'logissimus lumborum' muscle from 38 half-sib Poll Dorset sheep from six families and genotypes from 49,034 SNPs collected from the same animals. The analytical approaches used sought to analyse the effects of family and haplotype blocks on conservation of gene expression traits in this sheep population. Our study indicated that there is a genetic component in gene expression traits and hence gene expression is heritable to non-negligible extent. On average, our estimated heritability for gene expression obtained from skeletal muscle samples of sheep is 0.27 and 0.29 based on two different approaches. These preliminary results are consistent with previous heritability estimates.

Individual or combined effects of xylanase and protease on nutritive value of diets containing sorghum distillers dried grains with solubles (sDDGS) and fed to broiler chickens were investigated. A total of 480 day-old male broiler chickens were assessed in a 3 x 2 x 2 (0, 150 or 300 g sDDGS/kg diet, with or without xylanase, and with or without protease) factorial design. Each of the 12 treatments was replicated 5 times accommodating 8 birds per replicate. Feed intake (FI) and body weight gain (BWG) of the birds were increased by inclusion of sDDGS to the diets independent of enzyme supplementation. Feed conversion ratio (FCR) deteriorated as sDDGS was incorporated into the diets at both levels. Regardless of sDDGS and protease, xylanase significantly improved FCR. Digestibility of protein and most amino acids were adversely affected by inclusion of 150 and 300 g/kg sDDGS. While protease, individually, improved amino acid digestibility in birds offered diets containing the highest amount of sDDGS (300 g/kg), an admixture of xylanase and protease did not result in further improvement in amino acid digestibility. Addition of xylanase reduced the concentration of insoluble non-starch polysaccharides (NSP) in the ileum. Noticeably, the response of birds to xylanase supplementation on the concentrations of arabinose, xylose and total insoluble NSP was compromised when xylanase and protease were added to the diet simultaneously. To conclude, xylanase and protease in combination were effective for the growth performance of the birds on sDDGS, in particular improving FCR.

The aim of the present thesis was to identify genomic regions associated with parasite resistance in sheep and to evaluate the potential improvements in genomic prediction accuracies when incorporating genomic information in estimating breeding values. Data were derived from a large reference population of sheep developed in Australia, based on the CRC Information Nucleus Flock (INF). Worm egg counts (WEC) were collected from animals that were naturally infected in the field with mixed gastrointestinal worm species. Egg counts determined the presence of three predominant strongyle species; Teladorsagia circumcincta, Haemonchus contortus, and Trichostrongylus colubriformis. Heritability estimate for WEC based on pedigree relationships (0.20±0.03) was similar to those obtained from genomic relationships calculated from 50k and 600k genotypes. In a genome partitioning analysis, the genetic variance explained by each chromosome was proportional to the chromosomal length, providing strong evidence that parasite resistance is a polygenic trait with a large number of loci underlying the mechanism of resistance.
Genome wide association studies (GWAS) and regional heritability mapping (RHM) identified a significant region on OAR2 associated with parasite resistance. Haplotype analysis confirmed a haplotype block within this region on OAR2, which overlaps with GALNTL6 (Polypeptide N-Acetylgalactosaminyltransferase Like 6) gene, responsible for mucus production. Fine-mapping RHM analysis with smaller window sizes identified more significant regions on OAR6, OAR18, OAR24 as well as OAR20 within the major histocompatibility complex (MHC). Each region explained only a small proportion of WEC heritability, ranging from 2% to 5%. Pathway analyses revealed key genes involved in innate and acquired immune system pathways as well as cytokine signalling pathways. Mucus production and haemostasis are also relevant in protecting the host from parasite infections.
The accuracy of genomic predictions was evaluated for different groups of animals that had varying degree of relationships to their respective training populations. A closer relationship between the training and validation groups led to a higher accuracy of genomic prediction for WEC. GBLUP predicted breeding values more accurately than pedigree-based BLUP, especially when the relationship between training and validation groups was distant. These results highlight the importance of the relationships between animals in training and validation sets as a key factor in determining prediction accuracies.
The increased availability of whole-genome sequence (WGS) data, combined with a larger number of genotyped animals, made it possible to split datasets into QTL discovery and training/validation subsets and evaluate the prediction accuracy across the three marker densities. The performance of genomic prediction was evaluated using cross-validation design across sire families. Prediction accuracy of WEC improved slightly from 0.16±0.02 using 50k genotypes to 0.18±0.01 and 0.19±0.01 when using HD and WGS data, respectively. Variants selected from WGS data using GWAS and RHM methods improved the prediction accuracy substantially, when fitted alongside 50k genotypes, compared to when the 50k genotypes were fitted alone. However, when variant selection was based only on GWAS, the prediction accuracy increased by 5%, whereas when selection was limited to variants with the lowest GWAS p-values in windows identified by RHM, the prediction accuracy increased by 9%. These findings offer potentially important implications for future genomic prediction studies for parasite resistance.

The Australian beef (and meat sheep) industries face a significant strategic challenge around optimizing the joint improvement of qualities demanded by the consumer and production attributes affecting on- and off-farm enterprise profitability. A very simple example based on beef cattle value chains is used to show that this joint optimization may not be trivial. Possible responses to this challenge are discussed, with an emphasis on the need for coordination across the sectors involve in the value chain.