Genomic Prediction Accuracies for Growth and Carcass Traits in a Brangus Heifer Population

The predictive abilities and accuracies of genomic best linear unbiased prediction (GBLUP) and the Bayesian (BayesA, BayesB, BayesC and Lasso) genomic selection (GS) methods for economically important growth (birth, weaning, and yearling weights) and carcass (depth of rib fat, apercent intramuscular fat and longissimus muscle area) traits were characterized by estimating the linkage disequilibrium (LD) structure in Brangus heifers using single nucleotide polymorphisms (SNP) markers. Sharp declines in LD were observed as distance among SNP markers increased. The application of the GBLUP and the Bayesian methods to obtain the GEBV for growth and carcass traits within k-means and random clusters showed that k-means and random clustering had quite similar heritability estimates, but the Bayesian methods resulted in the lower estimates of heritability between 0.06 and 0.21 for growth and carcass traits compared with those between 0.21 and 0.35 from the GBLUP methodologies. Although the prediction ability of the GBLUP and the Bayesian methods were quite similar for growth and carcass traits, the Bayesian methods overestimated the accuracies of GEBV because of the lower estimates of heritability of growth and carcass traits. However, GBLUP resulted in accuracy of GEBV for growth and carcass traits that parallels previous reports.

A SNP within the PMCH gene as a molecular marker associated with fertility traits in Angus and Brangus beef heifers raised under a desert environment

Components of the GH/IGF1 endocrine axis regulate growth and reproductive traits in cattle. The pro-melanin-concentrating hormone (PMCH) gene located within chromosome 5 belongs to this axis. Objective herein was to evaluate PMCH single-nucleotide polymorphisms (SNPs) as molecular markers associated with age at first calving, calving interval, and age at second calving in Angus and Brangus beef heifers raised in desert conditions. Five SNPs within the PMCH gene were included in the study. Three of these SNPs had minor allele frequency > 10% and only one SNP did not deviate from Hardy-Weinberg equilibrium. A genotype to phenotype association analyses was performed using a mixed-effects model which included phenotype as the response variable, SNP genotype, breed, year of birth and age of dam as fixed terms, and sire as a random effect. Genotypes from the SNP rs135033882 were found to be associated (P < 0.05) with all evaluated fertility traits, and the term breed resulted as a significant source of variation only for age at second calving. The allele A was the favorable allele because it decreased the age at first calving 98.6 days, the calving interval 85.3 days, and the age at second calving 183.1 days, in Angus and Brangus heifers. In conclusion, we proposed a SNP within the PMCH gene as a potential candidate marker associated with reproductive performance in Angus and Brangus beef heifers raised in a desert climate.

Genomic analysis of stayability in Nellore cattle

Stayability, which can be defined as the probability of a cow calving at a certain age when given the opportunity, is an important reproductive trait in beef cattle because it is directly related to herd profitability. The objective of this study was to estimate genetic parameters and to identify possible genomic regions associated with the phenotypic expression of stayability in Nellore cows. The variance components were estimated by Bayesian inference using a threshold animal model that included the systematic effects of contemporary group and sexual precocity and the random effects of animal and residual. The SNP effects were estimated by the single-step genomic BLUP method using information of 2,838 animals (2,020 females and 930 sires) genotyped with the Illumina High-Density BeadChip Array (San Diego, CA, USA). The variance explained by windows formed by 200 consecutive SNPs was used to identify genomic regions of largest effect on the expression of stayability. The heritability was 0.11 ± 0.01 when A matrix (pedigree) was used and 0.14 ± 0.01 when H matrix (relationship matrix that combines pedigree information and SNP data) was used. A total of 147 candidate genes for stayability were identified on chromosomes 1, 2, 5, 6, 9 and 20 and on the X chromosome. New candidate regions for stayability were detected, most of them related to reproductive, immunological and central nervous system functions.

The effects of age, weight, and sire on pregnancy rate in cattle

The goal was to estimate the heritabilities and genetic variances for pregnancy rate (PR) and calving date (CD) in Angus cattle along with the effect of weight, age, and sire on PR and CD. The data consisted of 4,999 records on PR and CD. Statistical models included year as a fixed effect; premating/postmating weight and age as covariates; and sire of embryo, maternal grandsire (MGS), and permanent maternal environmental effects as random effects. The models also included the interactions between herd and weight (weight change). Direct and maternal effects on PR and CD were estimated using sire MGS and animal models in REML. Pregnancy rate increased from age 2 to 6 and decreased from age 7 to 11 (P < 0.01) and this effect was independent of the culling strategy. There was a quadratic effect of premating cow weight independent of age on PR, with lower PR for low weights (P < 0.01). Overall, cows with a premating weight of 550 kg had the greatest PR. Cows that lost weight during mating had lower PR (P < 0.01). The maternal additive heritability for PR was 0.001 ± 0.012 and the direct additive heritability was 0.024 ± 0.020. The ratio of permanent maternal environmental variance to phenotypic variance was significant (0.048 ± 0.017; P < 0.01). This demonstrates that permanent maternal environmental effects play a major role in the repeatability of PR (0.049 ± 0.015; P < 0.01). The maternal additive heritability for CD was 0.040 ± 0.022, and the direct additive heritability was 0.076 ± 0.045. The ratio of permanent maternal environmental variance to phenotypic variance was low (0.014 ± 0.017) and the repeatability for CD was significant (0.0544 ± 0.0180; P < 0.01). This suggests that maternal genetic effects are as important as direct genetic effects on CD. There was a positive quadratic relationship between premating cow weight and CD with delayed calving for low/high weights (P < 0.01). Cows that lost weight over mating also had a later CD (P < 0.01). Comparisons of a weight-selected herd to the control herd showed differences (P < 0.05) in the optimal premating weight for early calving (control, 480 kg, and weight selected, 615 kg). Calving date was also more sensitive to changes in weight over mating in the weight selection herd (P < 0.05). Therefore, the set point in the weight-fertility axis and the sensitivity of fertility to changes in weight both changed in the weight selection herd.

Growth performance of Brangus steers fed graded levels of sun-dried broiler litter as a substitute for cottonseed cake

An experiment was conducted to determine the optimum inclusion levels of dried broiler litter (DBL) as a substitute for cottonseed cake (CSC) in fattening diets for Brangus steers. Thirty Brangus steers were randomly allocated to five groups of six animals each. Each group was fed one of the experimental diets which had CSC substituted for DBL at levels of 0 (DBL0), 50 (DBL50), 100 (DBL100), 150 (DBL150) and 200 g/kg (DBL200). Average daily gain (ADG), dry matter intake and live weight gain (LWG) were measured over a period of 90 days, and the results were analysed using the MIXED procedures of SAS. Linear and quadratic effects of DBL inclusion on dry matter intake, LWG and ADG were also determined. Results showed interactions between diet and time that significantly affected ADG and LWG (p < 0.05). Both ADG and LWG decreased with increases in DBL inclusion with the depressed performance becoming more pronounced with time. Linear and non-linear decreases in LWG and ADG, respectively, were observed with increasing levels of DBL. The DBL50 diet resulted in performance that was similar to DBL50 and was 4% cheaper. Broiler litter can be used as a supplement for conventional protein sources, but at higher inclusion levels, it needs to be augmented by increased fermentable energy.

Multi-tissue omics analyses reveal molecular regulatory networks for puberty in composite beef cattle

Puberty is a complex physiological event by which animals mature into an adult capable of sexual reproduction. In order to enhance our understanding of the genes and regulatory pathways and networks involved in puberty, we characterized the transcriptome of five reproductive tissues (i.e. hypothalamus, pituitary gland, ovary, uterus, and endometrium) as well as tissues known to be relevant to growth and metabolism needed to achieve puberty (i.e., longissimus dorsi muscle, adipose, and liver). These tissues were collected from pre- and post-pubertal Brangus heifers (3/8 Brahman; Bos indicus x 5/8 Angus; Bos taurus) derived from a population of cattle used to identify quantitative trait loci associated with fertility traits (i.e., age of first observed corpus luteum (ACL), first service conception (FSC), and heifer pregnancy (HPG)). In order to exploit the power of complementary omics analyses, pre- and post-puberty co-expression gene networks were constructed by combining the results from genome-wide association studies (GWAS), RNA-Seq, and bovine transcription factors. Eight tissues among pre-pubertal and post-pubertal Brangus heifers revealed 1,515 differentially expressed and 943 tissue-specific genes within the 17,832 genes confirmed by RNA-Seq analysis. The hypothalamus experienced the most notable up-regulation of genes via puberty (i.e., 204 out of 275 genes). Combining the results of GWAS and RNA-Seq, we identified 25 loci containing a single nucleotide polymorphism (SNP) associated with ACL, FSC, and (or) HPG. Seventeen of these SNP were within a gene and 13 of the genes were expressed in uterus or endometrium. Multi-tissue omics analyses revealed 2,450 co-expressed genes relative to puberty. The pre-pubertal network had 372,861 connections whereas the post-pubertal network had 328,357 connections. A sub-network from this process revealed key transcriptional regulators (i.e., PITX2, FOXA1, DACH2, PROP1, SIX6, etc.). Results from these multi-tissue omics analyses improve understanding of the number of genes and their complex interactions for puberty in cattle.

Heritability and Bayesian genome-wide association study of first service conception and pregnancy in Brangus heifers

Brangus [3/8 Brahman (Bos indicus) × 5/8 Angus (Bos taurus); n ≈ 800] heifers from 67 sires were used to estimate heritability and conduct a genome-wide association study (GWAS) for 2 binary fertility traits: first service conception (FSC) and heifer pregnancy (HPG). Genotypes were from 53,692 loci on the BovineSNP50 (Infinium Bead Chips, Illumina, San Diego, CA). Yearling heifers were estrous synchronized, bred by AI, and then exposed to natural service breeding. Reproductive ultrasound and DNA-based parentage testing were used to determine if the heifer conceived by AI or natural service, and code for FSC and HPG traits. Success rates for FSC and HPG were 53.3% and 78.0% ± 0.01%, and corresponding heritability estimates were 0.18 ± 0.07 and 0.10 ± 0.06, respectively. The models used in obtaining these heritability estimates and GWAS included fixed effects of year (i.e., 2005 to 2007), birth location, calving season, age of dam, and contemporary group. In GWAS, simultaneous associations of 1 Mb SNP windows with phenotype were undertaken with Bayes C analyses using GenSel software. The 1 Mb windows contained 21.3 ± 1.1 SNP. Analyses fitted a mixture model that treated SNP effects as random, with an assumed fraction pi = 0.9995 having no effect on phenotype. The windows that accounted for 1.0% of genetic variance were considered as QTL associated with FSC or HPG. Eighteen QTL existed on 15 chromosomes for the 2 traits. On average, each QTL accounted for 2.43% ± 0.2% of the genetic variance. Chromosome 8 harbored 2 QTL for FSC and 1 for HPG; however, these regions did not overlap. Chromosomes 3, 15, 16, 19, 24, 26, 27, 29, and X included QTL only for FSC, whereas chromosomes 2, 4, 10, 13, and 20 contained QTL only for HPG. The multitude of QTL detected for FSC and HPG in this GWAS involving Brangus heifers exemplifies the complex regulation of variation in heifer fertility traits of low heritability.

Gene network analyses of first service conception in Brangus heifers: use of genome and trait associations, hypothalamic-transcriptome information, and transcription factors

Measures of heifer fertility are economically relevant traits for beef production systems and knowledge of candidate genes could be incorporated into future genomic selection strategies. Ten traits related to growth and fertility were measured in 890 Brangus heifers (3/8 Brahman × 5/8 Angus, from 67 sires). These traits were: BW and hip height adjusted to 205 and 365 d of age, postweaning ADG, yearling assessment of carcass traits (i.e., back fat thickness, intramuscular fat, and LM area), as well as heifer pregnancy and first service conception (FSC). These fertility traits were collected from controlled breeding seasons initiated with estrous synchronization and AI targeting heifers to calve by 24 mo of age. The BovineSNP50 BeadChip was used to ascertain 53,692 SNP genotypes for ∼802 heifers. Associations of genotypes and phenotypes were performed and SNP effects were estimated for each trait. Minimally associated SNP (P < 0.05) and their effects across the 10 traits formed the basis for an association weight matrix and its derived gene network related to FSC (57.3% success and heritability = 0.06 ± 0.05). These analyses yielded 1,555 important SNP, which inferred genes linked by 113,873 correlations within a network. Specifically, 1,386 SNP were nodes and the 5,132 strongest correlations (|r| ≥ 0.90) were edges. The network was filtered with genes queried from a transcriptome resource created from deep sequencing of RNA (i.e., RNA-Seq) from the hypothalamus of a prepubertal and a postpubertal Brangus heifer. The remaining hypothalamic-influenced network contained 978 genes connected by 2,560 edges or predicted gene interactions. This hypothalamic gene network was enriched with genes involved in axon guidance, which is a pathway known to influence pulsatile release of LHRH. There were 5 transcription factors with 21 or more connections: ZMAT3, STAT6, RFX4, PLAGL1, and NR6A1 for FSC. The SNP that identified these genes were intragenic and were on chromosomes 1, 5, 9, and 11. Chromosome 5 harbored both STAT6 and RFX4. The large number of interactions and genes observed with network analyses of multiple sources of genomic data (i.e., GWAS and RNA-Seq) support the concept of FSC being a polygenic trait.

A single nucleotide polymorphism-derived regulatory gene network underlying puberty in 2 tropical breeds of beef cattle

Harsh tropical environments impose serious challenges on poorly adapted species. In beef cattle, tropical adaptation in the form of temperature and disease resistance, coupled with acclimatization to seasonal and limited forage, comes at a cost to production efficiency. Prominent among these costs is delayed onset of puberty, a challenging phenotype to manipulate through traditional breeding mechanisms. Recently, system biology approaches, including gene networks, have been applied to the genetic dissection of complex phenotypes. We aimed at developing and studying gene networks underlying cattle puberty. Our starting material comprises the association results of ~50,000 SNP on 22 traits, including age at puberty, and 2 cattle breed populations: Brahman (n = 843) and Tropical Composite (n = 866). We defined age at puberty as the age at first corpus luteum (AGECL). By capturing the genes harboring mutations minimally associated (P < 0.05) to AGECL or to a set of traits related with AGECL, we derived a gene network for each breed separately and a third network for the combined data set. At the intersection of the 3 networks, we identified candidate genes and pathways that were common to both breeds. Resulting from these analyses, we identified an enrichment of genes involved in axon guidance, cell adhesion, ErbB signaling, and glutamate activity, pathways that are known to affect pulsatile release of GnRH, which is necessary for the onset of puberty. Furthermore, we employed network connectivity and centrality parameters along with a regulatory impact factor metric to identify the key transcription factors (TF) responsible for the molecular regulation of puberty. As a novel finding, we report 5 TF (HIVEP3, TOX, EYA1, NCOA2, and ZFHX4) located in the network intersecting both breeds and interacting with other TF, forming a regulatory network that harmonizes with the recent literature of puberty. Finally, we support our network predictions with evidence derived from gene expression in hypothalamic tissue of adult cows.