Concurrently mapping quantitative trait loci associations from multiple subspecies within hybrid populations.

Many of the world's agriculturally important plant and animal populations consist of hybrids of subspecies. Cattle in tropical and sub-tropical regions for example, originate from two subspecies, Bos taurus indicus (Bos indicus) and Bos taurus taurus (Bos taurus). Methods to derive the underlying genetic architecture for these two subspecies are essential to develop accurate genomic predictions in these hybrid populations. We propose a novel method to achieve this. First, we use haplotypes to assign SNP alleles to ancestral subspecies of origin in a multi-breed and multi-subspecies population. Then we use a BayesR framework to allow SNP alleles originating from the different subspecies differing effects. Applying this method in a composite population of B. indicus and B. taurus hybrids, our results show that there are underlying genomic differences between the two subspecies, and these effects are not identified in multi-breed genomic evaluations that do not account for subspecies of origin effects. The method slightly improved the accuracy of genomic prediction. More significantly, by allocating SNP alleles to ancestral subspecies of origin, we were able to identify four SNP with high posterior probabilities of inclusion that have not been previously associated with cattle fertility and were close to genes associated with fertility in other species. These results show that haplotypes can be used to trace subspecies of origin through the genome of this hybrid population and, in conjunction with our novel Bayesian analysis, subspecies SNP allele allocation can be used to increase the accuracy of QTL association mapping in genetically diverse populations.

Use of whole-genome sequence data and novel genomic selection strategies to improve selection for age at puberty in tropically-adapted beef heifers.

BACKGROUND: In tropically-adapted beef heifers, application of genomic prediction for age at puberty has been limited due to low prediction accuracies. Our aim was to investigate novel methods of pre-selecting whole-genome sequence (WGS) variants and alternative analysis methodologies; including genomic best linear unbiased prediction (GBLUP) with multiple genomic relationship matrices (MGRM) and Bayesian (BayesR) analyses, to determine if prediction accuracy for age at puberty can be improved. METHODS: Genotypes and phenotypes were obtained from two research herds. In total, 868 Brahman and 960 Tropical Composite heifers were recorded in the first population and 3695 Brahman, Santa Gertrudis and Droughtmaster heifers were recorded in the second population. Genotypes were imputed to 23 million whole-genome sequence variants. Eight strategies were used to pre-select variants from genome-wide association study (GWAS) results using conditional or joint (COJO) analyses. Pre-selected variants were included in three models, GBLUP with a single genomic relationship matrix (SGRM), GBLUP MGRM and BayesR. Five-way cross-validation was used to test the effect of marker panel density (6 K, 50 K and 800 K), analysis model, and inclusion of pre-selected WGS variants on prediction accuracy. RESULTS: In all tested scenarios, prediction accuracies for age at puberty were highest in BayesR analyses. The addition of pre-selected WGS variants had little effect on the accuracy of prediction when BayesR was used. The inclusion of WGS variants that were pre-selected using a meta-analysis with COJO analyses by chromosome, fitted in a MGRM model, had the highest prediction accuracies in the GBLUP analyses, regardless of marker density. When the low-density (6 K) panel was used, the prediction accuracy of GBLUP was equal (0.42) to that with the high-density panel when only six additional sequence variants (identified using meta-analysis COJO by chromosome) were included. CONCLUSIONS: While BayesR consistently outperforms other methods in terms of prediction accuracies, reasonable improvements in accuracy can be achieved when using GBLUP and low-density panels with the inclusion of a relatively small number of highly relevant WGS variants.

Optimized Genetic Testing for Polledness in Multiple Breeds of Cattle.

Many breeds of modern cattle are naturally horned, and for sound husbandry management reasons the calves frequently undergo procedures to physically remove the horns by disbudding or dehorning. These procedures are however a welfare concern. Selective breeding for polledness - absence of horns - has been effective in some cattle breeds but not in others (Bos indicus genotypes) due in part to the complex genetics of horn phenotype. To address this problem different approaches to genetic testing which provide accurate early-in-life prediction of horn phenotype have been evaluated, initially using microsatellites (MSAT) and more recently single nucleotide polymorphism (SNP). A direct gene test is not effective given the genetic heterogeneity and large-sized sequence variants associated with polledness in different breeds. The current study investigated 39,943 animals of multiple breeds to assess the accuracy of available poll testing assays. While the standard SNP-based test was an improvement on the earlier MSAT haplotyping method, 1999 (9.69%) out of 20,636 animals tested with this SNP-based assay did not predict a genotype, most commonly associated with the Indicus-influenced breeds. The current study has developed an optimized poll gene test that resolved the vast majority of these 1999 unresolved animals, while the predicted genotypes of those previously resolved remained unchanged. Hence the optimized poll test successfully predicted a genotype in 99.96% of samples assessed. We demonstrated that a robust set of 5 SNPs can effectively determine PC and PF alleles and eliminate the ambiguous and undetermined results of poll gene testing previously identified as an issue in cattle.

Multivariate genomic predictions for age at puberty in tropically adapted beef heifers.

Heifers that have an earlier age at puberty often have greater lifetime productivity. Age at puberty is moderately heritable so selection should effectively reduce the number of days to puberty, and improve heifer productivity and profitability as a result. However, recording age at puberty is intensive, requiring repeat ovarian scanning to determine age at first corpus luteum (AGECL). Genomic selection has been proposed as a strategy to select for earlier age at puberty; however, large reference populations of cows with AGECL records and genotypes would be required to generate accurate GEBV for this trait. Reproductive maturity score (RMS) is a proxy trait for age at puberty for implementation in northern Australia beef herds, where large scale recording of AGECL is not feasible. RMS assigns a score of 0 to 5 from a single ovarian scan to describe ovarian maturity at ~600 d. Here we use multivariate genomic prediction to evaluate the value of a large RMS data set to improve accuracy of GEBV for age at puberty (AGECL). There were 882 Brahman and 990 Tropical Composite heifers with AGECL phenotypes, and an independent set of 974 Brahman, 1,798 Santa Gertrudis, and 910 Droughtmaster heifers with RMS phenotypes. All animals had 728,785 real or imputed SNP genotypes. The correlation of AGECL and RMS (h2 = 0.23) was estimated as -0.83 using the genomic information. This result also demonstrates that using genomic information it is possible to estimate genetic correlations between traits collected on different animals in different herds, with minimal or unknown pedigree linkage between them. Inclusion of heifers with RMS in the multi-trait model improved the accuracy of genomic evaluations for AGECL. Accuracy of RMS GEBV generally did not improve by adding heifers with AGECL phenotypes into the reference population. These results suggest that RMS and AGECL may be used together in a multi-trait prediction model to increase the accuracy of prediction for age at puberty in tropically adapted beef cattle.

Towards multi-breed genomic evaluations for female fertility of tropical beef cattle.

Developing accurate genomic evaluations of fertility for tropical beef cattle must deal with at least two major challenges (i) recording cow fertility traits in extensive production systems on large numbers of cows and (ii) the genomic evaluations should work across the breeds, crossbreds, and composites used in tropical beef production. Here, we assess accuracy of genomic evaluations for a trait which can be collected on a large scale in extensive conditions, corpus luteum score (CLscore), which is 1 if ovarian scanning indicates a heifer has cycled by 600 d and 0 if not, in a multi-breed population. A total of 3,696 heifers, including 979 Brahmans, 914 Droughtmasters, and 1,803 Santa Gertrudis in seven herds across 3-yr cohorts with CLscores, were genotyped for 24,211 SNPs. Genotypes were imputed to 728,785 SNPs. GBLUP and BayesR were used to predict GEBV. Accuracy of GEBV was evaluated with two validation strategies. In the first strategy, the last year cohort of heifers from each herd was used for validation, such that every herd had heifers in both reference and validation populations. In the second validation strategy, each herd in turn was removed in its entirety from the reference population, and was used for validation. For both validation strategies, accuracy of GEBV for single breed and multi-breed reference populations was assessed. For the first validation strategy, accuracy of GEBV ranged from 0.2 for Brahmans to 0.4 for Droughtmasters. Increasing marker density from 24K SNPs to 728K SNPs resulted in a small increase in accuracy, and including multiple-breeds in the reference did not help improve accuracy. These results suggest that provided a herd has animals in the reference population, the accuracy of the GEBV is largely determined by within herd (linkage) information. The situation was very different when entire herds were predicted in the second validation. In this case accuracy of GEBV using only 24K SNPs and only a within breed reference was close to zero for all breeds. Accuracy increased substantially when 728K SNPs, BayesR, and a multi-breed reference were used, from 0.15 for Brahmans to 0.35 for Santa Gertrudis. Given the second validation strategy is more likely to reflect the situation for many herds in tropical beef production (no animals in the reference), genomic evaluations for fertility in tropical beef cattle should be based on high-density markers (728K SNPs) and should be multi-breed.

Ultrasonographic measurements in first trimester concepti identify predictors of birth weight and postnatal development in cattle.

The placenta is a major driver of prenatal growth and involved in programming of postnatal performance. We therefore determined placental and embryo-fetal ultrasonographic parameters in early pregnancy and their relationships with birth weight and postnatal weights in a Bos indicus-Bos taurus composite beef cattle population. Pregnancies were generated in 2-yr-old Droughtmaster heifers by artificial insemination after estrus synchronization in 2 consecutive years (2009, n = 36 and 2010, n = 57), with a subset of 2010 heifers used again as lactating 3-yr-old cows in 2011 (n = 24). Each cohort was managed as 1 contemporary group for measurements of Corpus luteum diameter, amnion length and width, placentome width and thickness, and embryo-fetal crown-rump length, at 7 and 8 wk of gestation. This was followed by recordings of birth weight, branding weight at 5 to 6 mo of age and weaning weight 2 mo later. At a significance threshold of P < 0.05, placentome thickness at week 7 was negatively correlated with weights at birth (r = -0.23), branding (r = -0.25), and weaning (r = -0.35), whereas placentome width at week 7 (r = 0.24) and thickness at week 8 (r = 0.29) were positively correlated with birth weight. Thicker placentomes in males at week 7 (7%) difference mirrored sex differences in weights at birth (7%), branding (10%), and weaning (6%). The sex difference trend for birth weight was not consistent across sire-year combinations, ranging from -3.2 to +4.7 kg (birth weight of males - females per sire). These results support the hypothesis that placental parameters at the transition from embryo to fetal stage are major predictors of fetal and postnatal growth, albeit with significant environmentally induced plasticity, in stabilized B. indicus-B. taurus composite populations, and suggest that elements of B. indicus-B. taurus reciprocal differences in birth weight persist in composite populations.

Atlas of tissue- and developmental stage specific gene expression for the bovine insulin-like growth factor (IGF) system.

The insulin-like growth factor (IGF) axis is fundamental for mammalian growth and development. However, no comprehensive reference data on gene expression across tissues and pre- and postnatal developmental stages are available for any given species. Here we provide systematic promoter- and splice variant specific information on expression of IGF system components in embryonic (Day 48), fetal (Day 153), term (Day 277, placenta) and juvenile (Day 365-396) tissues of domestic cow, a major agricultural species and biomedical model. Analysis of spatiotemporal changes in expression of IGF1, IGF2, IGF1R, IGF2R, IGFBP1-8 and IR genes, as well as lncRNAs H19 and AIRN, by qPCR, indicated an overall increase in expression from embryo to fetal stage, and decrease in expression from fetal to juvenile stage. The stronger decrease in expression of lncRNAs (average -16-fold) and ligands (average -12.1-fold) compared to receptors (average -5.7-fold) and binding proteins (average -4.3-fold) is consistent with known functions of IGF peptides and supports important roles of lncRNAs in prenatal development. Pronounced overall reduction in postnatal expression of IGF system components in lung (-12.9-fold) and kidney (-13.2-fold) are signatures of major changes in organ function while more similar hepatic expression levels (-2.2-fold) are evidence of the endocrine rather than autocrine/paracrine role of IGFs in postnatal growth regulation. Despite its rapid growth, placenta displayed a more stable expression pattern than other organs during prenatal development. Quantitative analyses of contributions of promoters P0-P4 to global IGF2 transcript in fetal tissues revealed that P4 accounted for the bulk of transcript in all tissues but skeletal muscle. Demonstration of IGF2 expression in fetal muscle and postnatal liver from a promoter orthologous to mouse and human promoter P0 provides further evidence for an evolutionary and developmental shift from placenta-specific P0-expression in rodents and suggests that some aspects of bovine IGF expression may be closer to human than mouse.

Scrotal circumference of Australian beef bulls.

Normal range for scrotal circumference in Australian beef bulls was established using more than 300,000 measurements of breed, management group, age, liveweight, and scrotal circumference. The data used were derived from Australian bull breeders and two large research projects in northern Australia. Most bulls were within 250 to 750 kg liveweight and 300 to 750 days of age. The differences between breeds and variances within breeds were higher when scrotal circumference was predicted from age rather than liveweight, because of variance in growth rates. The average standard deviation for predicted scrotal circumference from liveweight and age was 25 and 30 mm, respectively. Scrotal circumference by liveweight relationships have a similar pattern across all breeds, except in Waygu, with a 50 to 70 mm range in average scrotal circumference at liveweights between 250 and 750 kg. Temperate breed bulls tended to have higher scrotal circumference at the same liveweight than tropically adapted breeds. Five groupings of common beef breeds in Australian were identified, within which there were similar predictions of scrotal circumference from liveweight. It was concluded that liveweight and breed are required to identify whether scrotal circumference is within normal range for Australian beef bulls that experience a wide range of nutritional conditions.

Widespread differential maternal and paternal genome effects on fetal bone phenotype at mid-gestation.

Parent-of-origin-dependent (epi)genetic factors are important determinants of prenatal development that program adult phenotype. However, data on magnitude and specificity of maternal and paternal genome effects on fetal bone are lacking. We used an outbred bovine model to dissect and quantify effects of parental genomes, fetal sex, and nongenetic maternal effects on the fetal skeleton and analyzed phenotypic and molecular relationships between fetal muscle and bone. Analysis of 51 bone morphometric and weight parameters from 72 fetuses recovered at day 153 gestation (54% term) identified six principal components (PC1-6) that explained 80% of the variation in skeletal parameters. Parental genomes accounted for most of the variation in bone wet weight (PC1, 72.1%), limb ossification (PC2, 99.8%), flat bone size (PC4, 99.7%), and axial skeletal growth (PC5, 96.9%). Limb length showed lesser effects of parental genomes (PC3, 40.8%) and a significant nongenetic maternal effect (gestational weight gain, 29%). Fetal sex affected bone wet weight (PC1, p < 0.0001) and limb length (PC3, p < 0.05). Partitioning of variation explained by parental genomes revealed strong maternal genome effects on bone wet weight (74.1%, p < 0.0001) and axial skeletal growth (93.5%, p < 0.001), whereas paternal genome controlled limb ossification (95.1%, p < 0.0001). Histomorphometric data revealed strong maternal genome effects on growth plate height (98.6%, p < 0.0001) and trabecular thickness (85.5%, p < 0.0001) in distal femur. Parental genome effects on fetal bone were mirrored by maternal genome effects on fetal serum 25-hydroxyvitamin D (96.9%, p < 0.001) and paternal genome effects on alkaline phosphatase (90.0%, p < 0.001) and their correlations with maternally controlled bone wet weight and paternally controlled limb ossification, respectively. Bone wet weight and flat bone size correlated positively with muscle weight (r = 0.84 and 0.77, p < 0.0001) and negatively with muscle H19 expression (r = -0.34 and -0.31, p < 0.01). Because imprinted maternally expressed H19 regulates growth factors by miRNA interference, this suggests muscle-bone interaction via epigenetic factors.

Genomic regions associated with fertility traits in male and female cattle: advances from microsatellites to high-density chips and beyond.

A current challenge in genetic improvement of cattle is to identify genomic selection strategies that could work across breeds. Breed differences, scarcity of data, and lack of quantitative trait loci (QTL) validation contribute to this challenge. We conducted a review of the literature to identify QTL, markers, and candidate genes that are associated with fertility across breeds to arrive at an integrated view of bovine fertility genomics and to guide the direction of future studies. This review considers both male and female fertility traits as these are economically relevant for all breeds and production systems. Regions associated with fertility traits were found in each of the 30 bovine chromosomes, confirming the complexity of these polygenic traits. Across breeds, regions on chromosomes 1, 5, 14, and 16 were associated with female reproductive traits. The X chromosome was associated with male reproductive traits in both dairy and beef bulls. It has recently been proposed that a Y chromosome anomaly may be involved in infertility in cows. Knowledge of these QTL may assist discovery of causative mutations and has the potential to improve the accuracy of genomic selection, especially across breeds of cattle.

Maternal and paternal genomes differentially affect myofibre characteristics and muscle weights of bovine fetuses at midgestation.

Postnatal myofibre characteristics and muscle mass are largely determined during fetal development and may be significantly affected by epigenetic parent-of-origin effects. However, data on such effects in prenatal muscle development that could help understand unexplained variation in postnatal muscle traits are lacking. In a bovine model we studied effects of distinct maternal and paternal genomes, fetal sex, and non-genetic maternal effects on fetal myofibre characteristics and muscle mass. Data from 73 fetuses (Day153, 54% term) of four genetic groups with purebred and reciprocal cross Angus and Brahman genetics were analyzed using general linear models. Parental genomes explained the greatest proportion of variation in myofibre size of Musculus semitendinosus (80-96%) and in absolute and relative weights of M. supraspinatus, M. longissimus dorsi, M. quadriceps femoris and M. semimembranosus (82-89% and 56-93%, respectively). Paternal genome in interaction with maternal genome (P<0.05) explained most genetic variation in cross sectional area (CSA) of fast myotubes (68%), while maternal genome alone explained most genetic variation in CSA of fast myofibres (93%, P<0.01). Furthermore, maternal genome independently (M. semimembranosus, 88%, P<0.0001) or in combination (M. supraspinatus, 82%; M. longissimus dorsi, 93%; M. quadriceps femoris, 86%) with nested maternal weight effect (5-6%, P<0.05), was the predominant source of variation for absolute muscle weights. Effects of paternal genome on muscle mass decreased from thoracic to pelvic limb and accounted for all (M. supraspinatus, 97%, P<0.0001) or most (M. longissimus dorsi, 69%, P<0.0001; M. quadriceps femoris, 54%, P<0.001) genetic variation in relative weights. An interaction between maternal and paternal genomes (P<0.01) and effects of maternal weight (P<0.05) on expression of H19, a master regulator of an imprinted gene network, and negative correlations between H19 expression and fetal muscle mass (P<0.001), suggested imprinted genes and miRNA interference as mechanisms for differential effects of maternal and paternal genomes on fetal muscle.