Mammalian genomic regulatory regions predicted by utilizing human genomics, transcriptomics, and epigenetics data

Genome sequences for hundreds of mammalian species are available, but an understanding of their genomic regulatory regions, which control gene expression, is only beginning. A comprehensive prediction of potential active regulatory regions is necessary to functionally study the roles of the majority of genomic variants in evolution, domestication, and animal production. We developed a computational method to predict regulatory DNA sequences (promoters, enhancers, and transcription factor binding sites) in production animals (cows and pigs) and extended its broad applicability to other mammals. The method utilizes human regulatory features identified from thousands of tissues, cell lines, and experimental assays to find homologous regions that are conserved in sequences and genome organization and are enriched for regulatory elements in the genome sequences of other mammalian species. Importantly, we developed a filtering strategy, including a machine learning classification method, to utilize a very small number of species-specific experimental datasets available to select for the likely active regulatory regions. The method finds the optimal combination of sensitivity and accuracy to unbiasedly predict regulatory regions in mammalian species. Furthermore, we demonstrated the utility of the predicted regulatory datasets in cattle for prioritizing variants associated with multiple production and climate change adaptation traits and identifying potential genome editing targets.

Convergent Evolution of Slick Coat in Cattle through Truncation Mutations in the Prolactin Receptor

Evolutionary adaptations are occasionally convergent solutions to the same problem. A mutation contributing to a heat tolerance adaptation in Senepol cattle, a New World breed of mostly European descent, results in the distinct phenotype known as slick, where an animal has shorter hair and lower follicle density across its coat than wild type animals. The causal variant, located in the 11^th exon of prolactin receptor, produces a frameshift that results in a truncated protein. However, this mutation does not explain all cases of slick coats found in criollo breeds. Here, we obtained genome sequences from slick cattle of a geographically distinct criollo breed, namely Limonero, whose ancestors were originally brought to the Americas by the Spanish. These data were used to identify new causal alleles in the 11^th exon of the prolactin receptor, two of which also encode shortened proteins that remove a highly conserved tyrosine residue. These new mutations explained almost 90% of investigated cases of animals that had slick coats, but which also did not carry the Senepol slick allele. These results demonstrate convergent evolution at the molecular level in a trait important to the adaptation of an animal to its environment.

Climate Adaptation of Tropical Cattle

There is sustained growth in the number of tropical cattle, which represent more than half of all cattle worldwide. By and large, most research in tropical areas is still focused on breeds of cattle, their particular advantages or disadvantages in tropical areas, and the tropical forages or feeds that could be usefully fed to them. A consistent issue for adaptation to climate is the heat of tropical environments. Changing the external characteristics of the animal, such as color and coat characteristics, is one way to adapt, and there are several major genes for these traits. However, further improvement in heat tolerance and other adaptation traits will need to use the entire genome and all physical and physiological systems. Apart from the response to heat, climate forcing through methane emission identifies dry season weight loss as an important if somewhat neglected trait in climate adaptation of cattle. The use of genome-estimated breeding values in tropical areas is in its infancy and will be difficult to implement, but will be essential for rapid, coordinated genetic improvement. The difficulty of implementation cannot be exaggerated and may require major improvements in methodology.

Non-additive genetic variation in growth, carcass and fertility traits of beef cattle

Background

A better understanding of non-additive variance could lead to increased knowledge on the genetic control and physiology of quantitative traits, and to improved prediction of the genetic value and phenotype of individuals. Genome-wide panels of single nucleotide polymorphisms (SNPs) have been mainly used to map additive effects for quantitative traits, but they can also be used to investigate non-additive effects. We estimated dominance and epistatic effects of SNPs on various traits in beef cattle and the variance explained by dominance, and quantified the increase in accuracy of phenotype prediction by including dominance deviations in its estimation.

Methods

Genotype data (729 068 real or imputed SNPs) and phenotypes on up to 16 traits of 10 191 individuals from Bos taurus, Bos indicus and composite breeds were used. A genome-wide association study was performed by fitting the additive and dominance effects of single SNPs. The dominance variance was estimated by fitting a dominance relationship matrix constructed from the 729 068 SNPs. The accuracy of predicted phenotypic values was evaluated by best linear unbiased prediction using the additive and dominance relationship matrices. Epistatic interactions (additive × additive) were tested between each of the 28 SNPs that are known to have additive effects on multiple traits, and each of the other remaining 729 067 SNPs.

Results

The number of significant dominance effects was greater than expected by chance and most of them were in the direction that is presumed to increase fitness and in the opposite direction to inbreeding depression. Estimates of dominance variance explained by SNPs varied widely between traits, but had large standard errors. The median dominance variance across the 16 traits was equal to 5% of the phenotypic variance. Including a dominance deviation in the prediction did not significantly increase its accuracy for any of the phenotypes. The number of additive × additive epistatic effects that were statistically significant was greater than expected by chance.

Conclusions

Significant dominance and epistatic effects occur for growth, carcass and fertility traits in beef cattle but they are difficult to estimate precisely and including them in phenotype prediction does not increase its accuracy.

The genetic architecture of climatic adaptation of tropical cattle

Adaptation of global food systems to climate change is essential to feed the world. Tropical cattle production, a mainstay of profitability for farmers in the developing world, is dominated by heat, lack of water, poor quality feedstuffs, parasites, and tropical diseases. In these systems European cattle suffer significant stock loss, and the cross breeding of taurine x indicine cattle is unpredictable due to the dilution of adaptation to heat and tropical diseases. We explored the genetic architecture of ten traits of tropical cattle production using genome wide association studies of 4,662 animals varying from 0% to 100% indicine. We show that nine of the ten have genetic architectures that include genes of major effect, and in one case, a single location that accounted for more than 71% of the genetic variation. One genetic region in particular had effects on parasite resistance, yearling weight, body condition score, coat colour and penile sheath score. This region, extending 20 Mb on BTA5, appeared to be under genetic selection possibly through maintenance of haplotypes by breeders. We found that the amount of genetic variation and the genetic correlations between traits did not depend upon the degree of indicine content in the animals. Climate change is expected to expand some conditions of the tropics to more temperate environments, which may impact negatively on global livestock health and production. Our results point to several important genes that have large effects on adaptation that could be introduced into more temperate cattle without detrimental effects on productivity.

SNP discovery in nonmodel organisms: strand bias and base-substitution errors reduce conversion rates

Single nucleotide polymorphisms (SNPs) have become the marker of choice for genetic studies in organisms of conservation, commercial or biological interest. Most SNP discovery projects in nonmodel organisms apply a strategy for identifying putative SNPs based on filtering rules that account for random sequencing errors. Here, we analyse data used to develop 4723 novel SNPs for the commercially important deep-sea fish, orange roughy (Hoplostethus atlanticus), to assess the impact of not accounting for systematic sequencing errors when filtering identified polymorphisms when discovering SNPs. We used SAMtools to identify polymorphisms in a velvet assembly of genomic DNA sequence data from seven individuals. The resulting set of polymorphisms were filtered to minimize 'bycatch'-polymorphisms caused by sequencing or assembly error. An Illumina Infinium SNP chip was used to genotype a final set of 7714 polymorphisms across 1734 individuals. Five predictors were examined for their effect on the probability of obtaining an assayable SNP: depth of coverage, number of reads that support a variant, polymorphism type (e.g. A/C), strand-bias and Illumina SNP probe design score. Our results indicate that filtering out systematic sequencing errors could substantially improve the efficiency of SNP discovery. We show that BLASTX can be used as an efficient tool to identify single-copy genomic regions in the absence of a reference genome. The results have implications for research aiming to identify assayable SNPs and build SNP genotyping assays for nonmodel organisms.

A marker-derived gene network reveals the regulatory role of PPARGC1A, HNF4G, and FOXP3 in intramuscular fat deposition of beef cattle

High intramuscular fat (IMF) awards price premiums to beef producers and is associated with meat quality and flavor. Studying gene interactions and pathways that affect IMF might unveil causative physiological mechanisms and inform genomic selection, leading to increased accuracy of predictions of breeding value. To study gene interactions and pathways, a gene network was derived from genetic markers associated with direct measures of IMF, other fat phenotypes, feedlot performance, and a number of meat quality traits relating to body conformation, development, and metabolism that might be plausibly expected to interact with IMF biology. Marker associations were inferred from genomewide association studies (GWAS) based on high density genotypes and 29 traits measured on 10,181 beef cattle animals from 3 breed types. For the network inference, SNP pairs were assessed according to the strength of the correlation between their additive association effects across the 29 traits. The co-association inferred network was formed by 2,434 genes connected by 28,283 edges. Topological network parameters suggested a highly cohesive network, in which the genes are strongly functionally interconnected. Pathway and network analyses pointed towards a trio of transcription factors (TF) as key regulators of carcass IMF: PPARGC1A, HNF4G, and FOXP3. Importantly, none of these genes would have been deemed as significantly associated with IMF from the GWAS. Instead, a total of 313 network genes show significant co-association with the 3 TF. These genes belong to a wide variety of biological functions, canonical pathways, and genetic networks linked to IMF-related phenotypes. In summary, our GWAS and network predictions are supported by the current literature and suggest a cooperative role for the 3 TF and other interacting genes including CAPN6, STC2, MAP2K4, EYA1, COPS5, XKR4, NR2E1, TOX, ATF1, ASPH, TGS1, and TTPA as modulators of carcass and meat quality traits in beef cattle.

A multi-trait, meta-analysis for detecting pleiotropic polymorphisms for stature, fatness and reproduction in beef cattle

Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The meta-analysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t'V⁻¹t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups.

We describe novel methods for finding significant associations between a genome wide panel of SNPs and multiple complex traits, and further for distinguishing between genes with effects on multiple traits and multiple linked genes affecting different traits. The method uses a meta-analysis based on estimates of SNP effects from independent single trait genome wide association studies (GWAS). The method could therefore be widely used to combine already published GWAS results. The method was applied to 32 traits that describe growth, body composition, feed intake and reproduction in 10,191 beef cattle genotyped for approximately 700,000 SNP. The genes found to be associated with these traits can be arranged into 4 groups that differ in their pattern of effects and hence presumably in their physiological mechanism of action. For instance, one group of genes affects weight and fatness in the opposite direction and can be described as a group of genes affecting mature size, while another group affects weight and fatness in the same direction.

Evidence for positive selection of taurine genes within a QTL region on chromosome X associated with testicular size in Australian Brahman cattle

Background

Previous genome-wide association studies have identified significant regions of the X chromosome associated with reproductive traits in two Bos indicus-influenced breeds: Brahman cattle and Tropical Composites. Two QTL regions on this chromosome were identified in both breeds as strongly associated with scrotal circumference measurements, a reproductive trait previously shown to be useful for selection of young bulls. Scrotal circumference is genetically correlated with early age at puberty in both male and female offspring. These QTL were located at positions 69–77 and 81–92 Mb respectively, large areas each to which a significant number of potential candidate genes were mapped.

Results

To further characterise these regions, a bioinformatic approach was undertaken to identify novel non-synonymous SNP within the QTL regions of interest in Brahman cattle. After SNP discovery, we used conventional molecular assay technologies to perform studies of two candidate genes in both breeds. Non-synonymous SNP mapped to Testis-expressed gene 11 (Tex11) were associated (P < 0.001) with scrotal circumference in both breeds, and associations with percentage of normal sperm cells were also observed (P < 0.05). Evidence for recent selection was found as Tex11 SNP form a haplotype segment of Bos taurus origin that is retained within Brahman and Tropical Composite cattle with greatest reproductive potential.

Conclusions

Association of non-synonymous SNP presented here are a first step to functional genetic studies. Bovine species may serve as a model for studying the role of Tex11 in male fertility, warranting further in-depth molecular characterisation.

Should animal fats be back on the table? A critical review of the human health effects of animal fat

Humans hunt or raise a wide variety of animals for meat, which vary from free-range to intensively reared. These animals form a valuable part of human nutrition. Their tissues, including the fat, contain vitamin and other essential nutrients necessary for health. However, animal fat from ruminants and other land mammals is usually regarded as saturated. The purpose of this review is partly to examine the basis for the saturated fat hypothesis of cardiovascular disease given more recent research, to examine the human health effects of animal fats, and partly to draw into one place the diverse knowledge about animal fat and the effects of fat on metabolism. Mechanistic understanding of the initiation of the fatty streak and atherosclerosis calls into question the avoidance of ruminant or porcine fat. Due to high levels of oleic acid, a low n-6 : n-3 fatty acid ratio in some groups, and the presence of specific micronutrients including vitamins and essential fatty acids, animal fats are of benefit in human nutrition. Animal fats can be obtained in minimally processed form making them a convenient source of energy and micronutrients.

Detection of quantitative trait loci in Bos indicus and Bos taurus cattle using genome-wide association studies

BACKGROUND

The apparent effect of a single nucleotide polymorphism (SNP) on phenotype depends on the linkage disequilibrium (LD) between the SNP and a quantitative trait locus (QTL). However, the phase of LD between a SNP and a QTL may differ between Bos indicus and Bos taurus because they diverged at least one hundred thousand years ago. Here, we test the hypothesis that the apparent effect of a SNP on a quantitative trait depends on whether the SNP allele is inherited from a Bos taurus or Bos indicus ancestor.

METHODS

Phenotype data on one or more traits and SNP genotype data for 10 181 cattle from Bos taurus, Bos indicus and composite breeds were used. All animals had genotypes for 729 068 SNPs (real or imputed). Chromosome segments were classified as originating from B. indicus or B. taurus on the basis of the haplotype of SNP alleles they contained. Consequently, SNP alleles were classified according to their sub-species origin. Three models were used for the association study: (1) conventional GWAS (genome-wide association study), fitting a single SNP effect regardless of subspecies origin, (2) interaction GWAS, fitting an interaction between SNP and subspecies-origin, and (3) best variable GWAS, fitting the most significant combination of SNP and sub-species origin.

RESULTS

Fitting an interaction between SNP and subspecies origin resulted in more significant SNPs (i.e. more power) than a conventional GWAS. Thus, the effect of a SNP depends on the subspecies that the allele originates from. Also, most QTL segregated in only one subspecies, suggesting that many mutations that affect the traits studied occurred after divergence of the subspecies or the mutation became fixed or was lost in one of the subspecies.

CONCLUSIONS

The results imply that GWAS and genomic selection could gain power by distinguishing SNP alleles based on their subspecies origin, and that only few QTL segregate in both B. indicus and B. taurus cattle. Thus, the QTL that segregate in current populations likely resulted from mutations that occurred in one of the subspecies and can have both positive and negative effects on the traits. There was no evidence that selection has increased the frequency of alleles that increase body weight.

Evidence for pleiotropism and recent selection in the PLAG1 region in Australian Beef cattle

A putative functional mutation (rs109231213) near PLAG1 (BTA14) associated with stature was studied in beef cattle. Data from 8199 Bos taurus, Bos indicus and Tropical Composite cattle were used to test the associations between rs109231213 and various phenotypes. Further, 23 496 SNPs located on BTA14 were tested for association with these phenotypes, both independently and fitted together with rs109231213. The C allele of rs109231213 significantly increased hip height, weight, net food intake, age at puberty in males and females and decreased IGF-I concentration in blood and fat depth. When rs109231213 was fitted as a fixed effect in the model, there was an overall reduction in associations between other SNPs and these traits but some SNPs remained associated (P < 10(-4) ). Frequency of the mutant C allele of rs109231213 differed among B. indicus (0.52), B. taurus (0.96) and Tropical Composite (0.68). Most chromosomes carrying the C allele had the same surrounding 10 SNP haplotype, probably because the C allele was introgressed into Brahman from B. taurus cattle. A region of reduced heterozygosity surrounds the C allele; this is small in B. taurus but 20 Mb long in Brahmans, indicating recent and strong selection for the mutant allele. Thus, the C allele appears to mark a mutation that has been selected almost to fixation in the B. taurus breeds studied here and introduced into Brahman cattle during grading up and selected to a frequency of 0.52 despite its negative effects on fertility.

Accuracy of prediction of genomic breeding values for residual feed intake and carcass and meat quality traits in Bos taurus, Bos indicus, and composite beef cattle

The aim of this study was to assess the accuracy of genomic predictions for 19 traits including feed efficiency, growth, and carcass and meat quality traits in beef cattle. The 10,181 cattle in our study had real or imputed genotypes for 729,068 SNP although not all cattle were measured for all traits. Animals included Bos taurus, Brahman, composite, and crossbred animals. Genomic EBV (GEBV) were calculated using 2 methods of genomic prediction [BayesR and genomic BLUP (GBLUP)] either using a common training dataset for all breeds or using a training dataset comprising only animals of the same breed. Accuracies of GEBV were assessed using 5-fold cross-validation. The accuracy of genomic prediction varied by trait and by method. Traits with a large number of recorded and genotyped animals and with high heritability gave the greatest accuracy of GEBV. Using GBLUP, the average accuracy was 0.27 across traits and breeds, but the accuracies between breeds and between traits varied widely. When the training population was restricted to animals from the same breed as the validation population, GBLUP accuracies declined by an average of 0.04. The greatest decline in accuracy was found for the 4 composite breeds. The BayesR accuracies were greater by an average of 0.03 than GBLUP accuracies, particularly for traits with known genes of moderate to large effect mutations segregating. The accuracies of 0.43 to 0.48 for IGF-I traits were among the greatest in the study. Although accuracies are low compared with those observed in dairy cattle, genomic selection would still be beneficial for traits that are hard to improve by conventional selection, such as tenderness and residual feed intake. BayesR identified many of the same quantitative trait loci as a genomewide association study but appeared to map them more precisely. All traits appear to be highly polygenic with thousands of SNP independently associated with each trait.

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.

Variation in the XKR4 gene was significantly associated with subcutaneous rump fat thickness in indicine and composite cattle

Variation in the XK, Kell blood group complex subunit-related family, member 4 (XKR4) gene on BTA14 was associated with rump fat thickness in a recent genome-wide association study. This region is also of interest because it is known to show evidence of a signature of population genetic selection. In this study, additional variation in this gene was genotyped in a sample of a total of 1283 animals of the Belmont Red (BEL) and Santa Gertrudis (SGT) breeds. The SNP rs41724387 was significantly (P < 0.001) associated with rump fat thickness and explained 5.9% of the genetic variance for the trait in this sample. Using the 4466 genotypes for the SNP rs42646708 from several data sets to estimate effects in seven breeds, this relatively large quantitative trait locus effect appears to be a result of the variation in indicine and taurine-indicine composite cattle. However, the only DNA variant found in Brahman cattle that altered the predicted amino acid sequence of XKR4 was not associated with rump fat thickness. This suggests that causative mutations lie outside the coding sequence of this gene.

Genome-wide analysis of the world's sheep breeds reveals high levels of historic mixture and strong recent selection

Genomic structure in a global collection of domesticated sheep reveals a history of artificial selection for horn loss and traits relating to pigmentation, reproduction, and body size.

Through their domestication and subsequent selection, sheep have been adapted to thrive in a diverse range of environments. To characterise the genetic consequence of both domestication and selection, we genotyped 49,034 SNP in 2,819 animals from a diverse collection of 74 sheep breeds. We find the majority of sheep populations contain high SNP diversity and have retained an effective population size much higher than most cattle or dog breeds, suggesting domestication occurred from a broad genetic base. Extensive haplotype sharing and generally low divergence time between breeds reveal frequent genetic exchange has occurred during the development of modern breeds. A scan of the genome for selection signals revealed 31 regions containing genes for coat pigmentation, skeletal morphology, body size, growth, and reproduction. We demonstrate the strongest selection signal has occurred in response to breeding for the absence of horns. The high density map of genetic variability provides an in-depth view of the genetic history for this important livestock species.

During the process of domestication, mankind recruited animals from the wild into a captive environment, changing their morphology, behaviour, and genetics. In the case of sheep, domestication and subsequent selection by their animal handlers over thousands of years has produced a spectrum of breeds specialised for the production of wool, milk, and meat. We sought to use this population history to search for the genes that directly underpin phenotypic variation. We collected DNA from 2,819 sheep, belonging to 74 breeds sampled from around the world, and assessed the genotype of each animal at nearly 50,000 locations across the genome. Our results show that sheep breeds have maintained high levels of genetic diversity, in contrast to other domestic animals such as dogs. We also show that particular regions of the genome contain strong evidence for accelerated change in response to artificial selection. The most prominent example was identified in response to breeding for the absence of horns, a trait now common across many modern breeds. Furthermore, we demonstrate that other genomic regions under selection in sheep contain genes controlling pigmentation, reproduction, and body size.

Next generation sequencing of African and Indicine cattle to identify single nucleotide polymorphisms

We sequenced the genomes of a Brahman, an Africander and a Tuli bull because tropically adapted breeds of cattle have so far not been well characterised at the level of DNA variation. In excess of 16 Gb of Illumina GA-II sequence was obtained for each animal in the form of 75-bp paired-end reads, generating more than 6× coverage of each genome, and between 86.7 and 88.8% of the bases of each genome sequence was covered by one or more sequence reads. A total of 6.35 million single nucleotide polymorphisms (SNP) were discovered in the three animals, adding 3.56 million new SNP to dbSNP. The Brahman animal had nearly twice as many SNP as either the Tuli or the Africander. Comparing genome sequence to genotypic array data, genotype accuracy from sequencing was more than 98% for homozygotes that had at least six high quality sequence reads and for heterozygotes that had at least two high quality reads containing the alternative allele. Intergenic and intronic SNP were found at higher densities closer to coding sequences, and there was a reduction in numbers of SNP within 5 bp of a splice site, features consistent with genetic selection. On average, slightly more SNP per Mb, and slightly higher average reads per SNP per Mb, were found towards the ends of chromosomes, especially towards the telomeric end of the chromosome. At least one autosome in each animal showed a large stretch of homozygosity, the largest was 58 Mb long in the Tuli, although the animals are not known to have recent inbreeding.

The structure of a cattle stud determined using a medium density single nucleotide polymorphism array

Genetic progress depends on accurate knowledge of the genetic composition of a population or herd including level of inbreeding and parentage. However, in many circumstances, such as at an individual property level, the relationships between animals may be unknown, or at best, only partly known. In this study, we used DNA from 938 animals and genotypes from ~54 000 single nucleotide polymorphisms (SNP) to determine the genetic structure of a stud from Central Queensland. Animals on the study were bred using multi-sire mating in mobs of composite tropically adapted cattle of the Senepol, Belmont and Bonsmara breeds. Following genotyping using an array of 54 000 SNP, we were able to separate animals into breed groups using principal components and show that ~400 SNP were sufficient to separate animals into stable groups if the sample was genetically diverse. However, precise principal component values were only achieved when a few thousand SNP were used. We characterised the pedigree relationships between individuals using a genome relationship matrix. At least 3000 SNP were required to calculate accurate relationship coefficients between individuals. Around 19% of paired comparisons between animals showed similarity equivalent to sharing a great-grandparent or 1/64 shared ancestry. Approximately 8% of the individuals showed more than 10% inbreeding. To demonstrate the utility of calculating the relationship coefficients, we counted the tick burden on each animal at more than one time and then calculated the heritability of tick burden of h2 = 0.46 (±0.08). There was no significant genetic difference in tick burden between Belmont and Bonsmara cattle compared with Senepol on this property once a genetic relationship matrix was included to account for co-ancestry of individuals.

Haplotype analysis improved evidence for candidate genes for intramuscular fat percentage from a genome wide association study of cattle

In genome wide association studies (GWAS), haplotype analyses of SNP data are neglected in favour of single point analysis of associations. In a recent GWAS, we found that none of the known candidate genes for intramuscular fat (IMF) had been identified. In this study, data from the GWAS for these candidate genes were re-analysed as haplotypes. First, we confirmed that the methodology would find evidence for association between haplotypes in candidate genes of the calpain-calpastatin complex and musculus longissimus lumborum peak force (LLPF), because these genes had been confirmed through single point analysis in the GWAS. Then, for intramuscular fat percent (IMF), we found significant partial haplotype substitution effects for the genes ADIPOQ and CXCR4, as well as suggestive associations to the genes CEBPA, FASN, and CAPN1. Haplotypes for these genes explained 80% more of the phenotypic variance compared to the best single SNP. For some genes the analyses suggested that there was more than one causative mutation in some genes, or confirmed that some causative mutations are limited to particular subgroups of a species. Fitting the SNPs and their interactions simultaneously explained a similar amount of the phenotypic variance compared to haplotype analyses. Haplotype analysis is a neglected part of the suite of tools used to analyse GWAS data, would be a useful method to extract more information from these data sets, and may contribute to reducing the missing heritability problem.

Genome-wide association studies of female reproduction in tropically adapted beef cattle

The genetics of reproduction is poorly understood because the heritabilities of traits currently recorded are low. To elucidate the genetics underlying reproduction in beef cattle, we performed a genome-wide association study using the bovine SNP50 chip in 2 tropically adapted beef cattle breeds, Brahman and Tropical Composite. Here we present the results for 3 female reproduction traits: 1) age at puberty, defined as age in days at first observed corpus luteum (CL) after frequent ovarian ultrasound scans (AGECL); 2) the postpartum anestrous interval, measured as the number of days from calving to first ovulation postpartum (first rebreeding interval, PPAI); and 3) the occurrence of the first postpartum ovulation before weaning in the first rebreeding period (PW), defined from PPAI. In addition, correlated traits such as BW, height, serum IGF1 concentration, condition score, and fatness were also examined. In the Brahman and Tropical Composite cattle, 169 [false positive rate (FPR) = 0.262] and 84 (FPR = 0.581) SNP, respectively, were significant (P < 0.001) for AGECL. In Brahman, 41% of these significant markers mapped to a single chromosomal region on BTA14. In Tropical Composites, 16% of these significant markers were located on BTA5. For PPAI, 66 (FPR = 0.67) and 113 (FPR = 0.432) SNP were significant (P < 0.001) in Brahman and Tropical Composite, respectively, whereas for PW, 68 (FPR = 0.64) and 113 (FPR = 0.432) SNP were significant (P < 0.01). In Tropical Composites, the largest concentration of PPAI markers were located on BTA5 [19% (PPAI) and 23% (PW)], and BTA16 [17% (PPAI) and 18% (PW)]. In Brahman cattle, the largest concentration of markers for postpartum anestrus was located on BTA3 (14% for PPAI and PW) and BTA14 (17% PPAI). Very few of the significant markers for female reproduction traits for the Brahman and Tropical Composite breeds were located in the same chromosomal regions. However, fatness and BW traits as well as serum IGF1 concentration were found to be associated with similar genome regions within and between breeds. Clusters of SNP associated with multiple traits were located on BTA14 in Brahman and BTA5 in Tropical Composites.