Weighted single‐step genome‐wide association study and pathway analyses for feed efficiency traits in Nellore cattle

The aim was to conduct a weighted single‐step genome‐wide association study to detect genomic regions and putative candidate genes related to residual feed intake, dry matter intake, feed efficiency (FE), feed conversion ratio, residual body weight gain, residual intake and weight gain in Nellore cattle. Several protein‐coding genes were identified within the genomic regions that explain more than 0.5% of the additive genetic variance for these traits. These genes were associated with insulin, leptin, glucose, protein and lipid metabolisms; energy balance; heat and oxidative stress; bile secretion; satiety; feed behaviour; salivation; digestion; and nutrient absorption. Enrichment analysis revealed functional pathways (p‐value < .05) such as neuropeptide signalling (GO:0007218), negative regulation of canonical Wingless/Int‐1 (Wnt) signalling (GO:0090090), bitter taste receptor activity (GO:0033038), neuropeptide hormone activity (GO:0005184), bile secretion (bta04976), taste transduction (bta0742) and glucagon signalling pathway (bta04922). The identification of these genes, pathways and their respective functions should contribute to a better understanding of the genetic and physiological mechanisms regulating Nellore FE‐related traits.     

A genomewide association mapping study using ultrasound‐scanned information identifies potential genomic regions and candidate genes affecting carcass traits in Nellore cattle

The aim of this study was to identify candidate genes and genomic regions associated with ultrasound‐derived measurements of the rib‐eye area (REA), backfat thickness (BFT) and rumpfat thickness (RFT) in Nellore cattle. Data from 640 Nellore steers and young bulls with genotypes for 290 863 single nucleotide polymorphisms (SNPs) were used for genomewide association mapping. Significant SNP associations were explored to find possible candidate genes related to physiological processes. Several of the significant markers detected were mapped onto functional candidate genes including ARFGAP3, CLSTN2 and DPYD for REA; OSBPL3 and SUDS3 for BFT; and RARRES1 and VEPH1 for RFT. The physiological pathway related to lipid metabolism (CLSTN2, OSBPL3, RARRES1 and VEPH1) was identified. The significant markers within previously reported QTLs reinforce the importance of the genomic regions, and the other loci offer candidate genes that have not been related to carcass traits in previous investigations.     

Identification of potential genomic regions for egg weight by a haplotype-based genome-wide association study using Bayesian methods

ABSTRACT

1. Theoretically, haplotype blocks might be a more suitable alternative to SNP genotypes as they are usually better at capturing multi-allelic QTL effects, compared to individual SNP genotypes in genome-wide association studies. The objectives of this study were to identify genomic regions related to egg weight traits by Bayesian methods (BayesA, BayesB, and BayesN) that fit fixed-length haplotypes using GenSel software.

2. Genotypes at 294,705 SNPs, that were common on a 600K Affymetrix chip, were phased for an egg-laying hen population of 1,063 birds. Recorded traits included first egg weight (FEW) and average egg weight at 28, 36, 56, 66, 72 and 80 weeks of age.

2. Fitting 1Mb haplotypes from BayesB resulted in the highest proportion of genetic variance explained for the egg weight traits. Based on the trait, the genetic variance explained by each marker ranged from 27% to 76%.

3. Different haplotype windows associated with egg weight traits only explained a small percentage of the genetic variance.

4. The top one 1-Mb window on GGA1 explained approximately 4.05% of total genetic variance for the FEW. Candidate genes, including PRKAR2B, HMGA2, LEMD3, GRIP1, EHBP1, MAP3K7, and MYH were identified for egg weight traits.

5. Several genomic regions, potentially associated with egg weight traits, were identified, some of which overlapped with known genes and previously reported QTL regions for egg production traits.     

Genomic imprinting variances of beef carcass traits and physiochemical characteristics in Japanese Black cattle

The objective of this study was to estimate variance components related to imprinting for carcass traits and physiochemical characteristics in Japanese Black cattle. The carcass records obtained from 4,220 Japanese Black feedlot cattle included carcass weight (CW), rib eye area (REA), rib thickness, subcutaneous fat thickness, and beef marbling score (BMS), and the physiochemical characteristics were fat, moisture, glycogen per proportion of moisture content, oleic acid, and monounsaturated fatty acids (MUFA). To detect gametic effects, an imprinting model was fitted. High additive heritabilities were estimated for all traits (from 0.516 for glycogen to 0.853 for fat) and were reduced in Mendelian heritability. The range of the differences was from 0.002 (CW) to 0.331 (fat and moisture), and the reductions were due to their imprinting variances. The ratio of the imprinting variance to the total additive genetic variance for REA (0.374), BMS (0.291), fat (0.387), moisture (0.388), and MUFA (0.337) were large (p < 0.05). These imprinting variances were due to the maternal contribution and suggested the existence of maternally expressed genomic imprinting effects on the traits in Japanese Black cattle. Therefore, maternal gametic effects should be considered in breeding programs for Japanese Black cattle.     

Genome‐wide association study for egg production and quality in layer chickens

Discovery of genes with large effects on economically important traits has for many years been of interest to breeders. The development of SNP panels which cover the whole genome with high density and, more importantly, that can be genotyped on large numbers of individuals at relatively low cost, has opened new opportunities for genome‐wide association studies (GWAS). The objective of this study was to find genomic regions associated with egg production and quality traits in layers using analysis methods developed for the purpose of whole genome prediction. Genotypes on over 4500 birds and phenotypes on over 13 000 hens from eight generations of a brown egg layer line were used. Birds were genotyped with a custom 42K Illumina SNP chip. Recorded traits included two egg production and 11 egg quality traits (puncture score, albumen height, yolk weight and shell colour) at early and late stages of production, as well as body weight and age at first egg. Egg weight was previously analysed by Wolc et al. ( 2012 ). The Bayesian whole genome prediction model – BayesB (Meuwissen et al. 2001 ) was used to locate 1 Mb regions that were most strongly associated with each trait. The posterior probability of a 1 Mb window contributing to genetic variation was used as the criterion for suggesting the presence of a quantitative trait locus (QTL) in that window. Depending upon the trait, from 1 to 7 significant (posterior probability >0.9) 1 Mb regions were found. The largest QTL, a region explaining 32% of genetic variance, was found on chr4 at 78 Mb for body weight but had pleiotropic effects on other traits. For the other traits, the largest effects were much smaller, explaining <7% of genetic variance, with regions on chromosomes 2, 12 and 17 explaining above 5% of genetic variance for albumen height, shell colour and egg production, respectively. In total, 45 of 1043 1 Mb windows were estimated to have a non‐zero effect with posterior probability > 0.9 for one or more traits.     

Genetic association between different criteria to define sexual precocious heifers with growth,carcass, reproductive and feed efficiency indicator traits in Nellore cattle using genomic information

The aim of this study was to estimate genetic parameters for different precocious calving criteria and their relationship with reproductive, growth, carcass and feed efficiency in Nellore cattle using the single‐step genomic BLUP. The reproductive traits used were probability of precocious calving (PPC) at 24 (PPC24), 26 (PPC26), 28 (PPC28) and 30 (PPC30) months of age, stayability (STAY) and scrotal circumference at 455 days of age (SC455). Growth traits such as weights at 240 (W240) and 455 (W455) days of age and adult weight (AW) were used. Rib eye area (REA), subcutaneous fat thickness (SFT), rump fat thickness (RFT) and residual feed intake (RFI) were included in the analyses. The estimation of genetic parameters was performed using a bi‐trait threshold model including genomic information in a single‐step approach. Heritability for PPC traits was moderate to high (0.29–0.56) with highest estimates for PPC24 (0.56) and PPC26 (0.50). Genetic correlation estimates between PPC and STAY weakened as a function of calving age. Correlation with SC455, growth and carcass traits were low (0.25–0.31; ?0.22 to 0.04; ?0.09 to 0.18, respectively), the same occurs with RFI (?0.09 to 0.08), this suggests independence between female sexual precocity and feed efficiency traits. The results of this study encourage the use of PPC traits in Nellore cattle because the selection for such trait would not have a negative impact on reproductive, growth, carcass and feed efficiency indicator traits. Stayability for sexual precocious heifers (PPC24 and PPC26) must be redefined to avoid incorrectly phenotype assignment.     

A genomewide association study in divergently selected lines in rabbits reveals novel genomic regions associated with litter size traits

Uterine capacity (UC), defined as the total number of kits from unilaterally ovariectomized does at birth, has a high genetic correlation with litter size. The aim of our research was to identify genomic regions associated with litter size traits through a genomewide association study using rabbits from a divergent selection experiment for UC. A high-density SNP array (200K) was used to genotype 181 does from a control population, high and low UC lines. Traits included total number born (TNB), number born alive (NBA), number born dead, ovulation rate (OR), implanted embryos (IE) and embryo, foetal and prenatal survivals at second parity. We implemented the Bayes B method and the associations were tested by Bayes factors and the percentage of genomic variance (GV) explained by windows. Different genomic regions associated with TNB, NBA, IE and OR were found. These regions explained 7.36%, 1.27%, 15.87% and 3.95% of GV, respectively. Two consecutive windows on chromosome 17 were associated with TNB, NBA and IE. This genomic region accounted for 6.32% of GV of TNB. In this region, we found the BMP4, PTDGR, PTGER2, STYX and CDKN3 candidate genes which presented functional annotations linked to some reproductive processes. Our findings suggest that a genomic region on chromosome 17 has an important effect on litter size traits. However, further analyses are needed to validate this region in other maternal rabbit lines.     

Estimation of additive and non-additive genetic effects for fertility and reproduction traits in North American Holstein cattle using genomic information

Non-additive genetic effects are usually ignored in animal breeding programs due to data structure (e.g., incomplete pedigree), computational limitations and over-parameterization of the models. However, non-additive genetic effects may play an important role in the expression of complex traits in livestock species, such as fertility and reproduction traits. In this study, components of genetic variance for additive and non-additive genetic effects were estimated for a variety of fertility and reproduction traits in Holstein cattle using pedigree and genomic relationship matrices. Four linear models were used: (a) an additive genetic model; (b) a model including both additive and epistatic (additive by additive) genetic effects; (c) a model including both additive and dominance effects; and (d) a full model including additive, epistatic and dominance genetic effects. Nine fertility and reproduction traits were analysed, and models were run separately for heifers (N = 5,825) and cows (N = 6,090). For some traits, a larger proportion of phenotypic variance was explained by non-additive genetic effects compared with additive effects, indicating that epistasis, dominance or a combination thereof is of great importance. Epistatic genetic effects contributed more to the total phenotypic variance than dominance genetic effects. Although these models varied considerably in the partitioning of the components of genetic variance, the models including a non-additive genetic effect did not show a clear advantage over the additive model based on the Akaike information criterion. The partitioning of variance components resulted in a re-ranking of cows based solely on the cows’ additive genetic effects between models, indicating that adjusting for non-additive genetic effects could affect selection decisions made in dairy cattle breeding programs. These results suggest that non-additive genetic effects play an important role in some fertility and reproduction traits in Holstein cattle.     

Use of robust multivariate linear mixed models for estimation of genetic parameters for carcass traits in beef cattle

Assumptions of normality of residuals for carcass evaluation may make inferences vulnerable to the presence of outliers, but heavy‐tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. We compare estimates of genetic parameters by fitting multivariate Normal (MN) or heavy‐tail distributions (multivariate Student's t and multivariate Slash, MSt and MS) for residuals in data of hot carcass weight (HCW), longissimus muscle area (REA) and 12th to 13th rib fat (FAT) traits in beef cattle using 2475 records from 2007 to 2008 from a large commercial operation in Nebraska. Model comparisons using deviance information criteria (DIC) favoured MSt over MS and MN models, respectively. The posterior means (and 95% posterior probability intervals, PPI) of v for the MSt and MS models were 5.89 ± 0.90 (4.35, 7.86) and 2.04 ± 0.18 (1.70, 2.41), respectively. Smaller values of posterior densities of v for MSt and MS models confirm that the assumption of normally distributed residuals is not adequate for the analysis of the data set. Posterior mean (PM) and posterior median (PD) estimates of direct genetic variances were variable with MSt having the highest mean value followed by MS and MN, respectively. Posterior inferences on genetic variance were, however, comparable among the models for FAT. Posterior inference on additive heritabilities for HCW, REA and FAT using MN, MSt and MS models indicated similar and moderate heritability comparable with the literature. Posterior means of genetic correlations for carcass traits were variable but positive except for between REA and FAT, which showed an antagonistic relationship. We have demonstrated that genetic evaluation and selection strategies will be sensitive to the assumed model for residuals.     

Genome‐wide association study for feedlot average daily gain in Nellore cattle (Bos indicus)

The genome‐wide association study (GWAS) results are presented for average daily gain (ADG) in Nellore cattle. Phenotype of 720 male Bos indicus animals with information of ADG in feedlots and 354 147 single‐nucleotide polymorphisms (SNPs) obtained from a database added by information from Illumina Bovine HD (777 962 SNPs) and Illumina BovineSNP50 (54 609) by imputation were used. After quality control and imputation, 290 620 SNPs remained in the association analysis, using R package Genome‐wide Rapid Association using Mixed Model and Regression method GRAMMAR‐Gamma. A genomic region with six significant SNPs, at Bonferroni‐corrected significance, was found on chromosome 3. The most significant SNP (rs42518459, BTA3: 85849977, p = 9.49 × 10^?8) explained 5.62% of the phenotypic variance and had the allele substitution effect of ?0.269 kg/day. Important genes such as PDE4B, LEPR, CYP2J2 and FGGY are located near this region, which is overlapped by 12 quantitative trait locus (QTLs) described for several production traits. Other regions with markers with suggestive effects were identified in BTA6 and BTA10. This study showed regions with major effects on ADG in Bos indicus in feedlots. This information may be useful to increase the efficiency of selecting this trait and to understand the physiological processes involved in its regulation.     

Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.     

Genetic and environmental factors affecting ultrasound measures of longissimus muscle area and backfat thickness in Nelore cattle

The aim of the present study was to evaluate the genetic and environmental factors affecting records of longissimus muscle area (LMA) and backfat thickness (BF) obtained between the 12th and 13th ribs, and rump fat thickness (RF) between the hook and pin bones, measured by real-time ultrasound in Nelore cattle. Also, weight records of 22,778 animals born from 1998 to 2003, in ten farms across six Brazilian states were used. Carcass traits as measured by ultrasound of the live animal were recorded from 2002 to 2004 in 2590 males and females with ages varying from 450 to 599 days. Fixed models including farm, year and season of birth, sex and type of feed effects, and the covariates age of dam (AOD) and age of animal at measurement were used to study the effect of environmental factors on these traits. The genetic parameters for LMA, BF and RF were estimated with two and three-trait animal models with 120-day weights using a restricted maximum likelihood method. All environmental effects significantly affected carcass traits, with the exception of year of birth for BF and RF and AOD for LMA. The heritability estimates for LMA, BF and RF were 0.35, 0.51 and 0.39, respectively. Standard errors obtained in one-trait analyses were from 0.07 to 0.09. Genetic correlation estimates between LMA and the two traits of subcutaneous fat were low (close to zero) and 0.74 between BF and RF, indicating that the selection for LMA should not cause antagonism in the genetic improvement of subcutaneous fat measured by real-time ultrasound.     

Evaluation of effects of multiple candidate genes (LEP,LEPR, MC4R,PIK3C3, and VRTN) on production traits in Duroc pigs

We evaluated multiple effects of genetic variations of five candidate loci (LEP, LEPR, MC4R, PIK3C3 and VRTN) on four production traits (average daily weight gain (ADG); backfat thickness (BFT); loin eye muscle area (EMA); and intramuscular fat content (IMF)) in a closed nucleus herd of pure Duroc pigs. Polymorphisms in LEPR, MC4R and PIK3C3 had significant single gene effects on ADG and BFT. The additive genetic variance in ADG and BFT (16.99% and 22.51%, respectively) was explained by genetic effects of these three loci. No correlations were observed between the LEP genotype and production traits in this study. Although we detected marginally epistatic interactions between LEPR and PIK3C3 on the eye muscle area, there were no significant epistatic effects on any traits among all loci pairs. These results suggest that LEPR, MC4R, PIK3C3 and VRTN may independently influence growth rate and fat deposition. Furthermore, the statistical models for predicting the breeding values of each trait had the lowest Akaike's information criterion values when considering the effect of the MC4R, LEPR, PIK3C3 and VRTN genotype simultaneously. These results suggest that LEPR, MC4R, PIK3C3 and VRTN are useful markers for accurately predicting breeding values in Duroc pigs.     

Allelic frequencies and association with carcass traits of six genes in local subpopulations of Japanese Black cattle

Marker‐assisted selection (MAS) is expected to accelerate the genetic improvement of Japanese Black cattle. However, verification of the effects of the genes for MAS in different subpopulations is required prior to the application of MAS. In this study, we investigated the allelic frequencies and genotypic effects for carcass traits of six genes, which can be used in MAS, in eight local subpopulations. These genes are SCD, FASN and SREBP1, which are associated with the fatty acid composition of meat, and NCAPG, MC1R and F11, which are associated with carcass weight, coat color and blood coagulation abnormality, respectively. The frequencies of desirable alleles of SCD and FASN were relatively high and that of NCAPG was relatively low, and NCAPG was significantly associated with several carcass traits, including carcass weight. The proportions of genotypic variance explained by NCAPG to phenotypic variance were 4.83 for carcass weight. We thus confirmed that NCAPG is a useful marker for selection of carcass traits in these subpopulations. In addition, we found that the desirable alleles of six genes showed no negative effects on carcass traits. Therefore, selection using these genes to improve target traits should not have negative impacts on carcass traits.     

Selection for feed efficiency does not change the selection for growth and carcass traits in Nellore cattle

The objectives were to conduct a genetic evaluation of residual feed intake (RFI) and residual feed intake adjusted for fat (RFIFat) and to analyse the effect of selection for these traits on growth, carcass and reproductive traits. Data from 945 Nellore bulls in seven feed efficiency tests in a feedlot were analysed. Genetic evaluation was performed using an animal model in which the feed efficiency test and age of the animal at the beginning of the test were considered as a systematic effect. Direct additive genetic and residual effects were considered as random effects. Correlations and genetic gains were estimated by two‐trait analysis between feed efficiency measures (RFI and RFIFat) and other traits. Feed conversion showed low heritability (0.06), but dry matter intake (DMI), average daily gain, RFI, RFIFat, metabolic body weight and scrotal circumference measured at 450 days of age (SC450) showed moderate to high heritability (0.49, 0.28, 0.33, 0.36, 0.38 and 0.80, respectively). Similarly, ribeye area, backfat thickness, rump cap fat thickness, marbling score and subcutaneous fat thickness also had high heritability values (0.46, 0.37, 0.57, 0.51 and 0.47, respectively). Genetic correlations between RFI and SC450 were null, and between RFIFat and SC450 were strongly positive. Genetic and phenotypic correlations of RFI and RFIFat with carcass traits were not different from zero, as correlated responses for carcass traits were also not different from zero. The Nellore selection for feed efficiency by RFI or RFIFat allows the recognition of feed efficient animals, with DMI reduction and without significant changes in growth and carcass traits. However, because of the observed results between RFIFat and SC450, selection of animals should be analysed with caution and a preselection for reproductive traits is necessary to avoid reproductive impairments in the herd.     

Leather quality of beefalo‐Nellore cattle in different production systems

The aim was to compare the effects of two production systems on performance, carcass traits and physical‐mechanical characteristics of leather from Beefalo‐Nellore steers and heifers and to determine if the response to the production system was similar for both genders. A total of 40 Beefalo‐Nellore cattle, 20 steers and 20 heifers, were evaluated. Animals were divided into two production systems: slaughtered at 15 (intensive system) or 26 (extensive system) months of age. In the intensive system, all animals received a ration containing 600 g/kg corn silage and 400 g/kg concentrate. In the extensive system, animals were kept on a pasture predominantly based on Brachiaria sp. and supplemented with 2 kg/day concentrate. In the intensive system, there was no difference in slaughter weight (470 kg body weight) between steers and heifers but steers in the extensive system had greater slaughter weight than heifers (463 and 428 kg body weight, respectively). Leather weight was higher for animals in the intensive than extensive system but there was no difference in leather weight once excess fat was removed. Leather quality from Beefalo‐Nellore cattle slaughtered at 15 or 26 months of age is similar although carcass yield is higher for cattle slaughtered at a younger age.     

Genetic parameters for growth traits in Mexican Nellore cattle

The aim of this study was to estimate genetic parameters for growth traits in Mexican Nellore cattle. A univariate animal model was used to estimate (co)variance components and genetic parameters. The traits evaluated were birth weight (BW), weaning weight (WW), and yearling weight (YW). Models used included the fixed effects of contemporary groups (herd, sex, year, and season of birth) and age of dam (linear and quadratic) as a covariate. They also included the animal, dam, and residual as random effects. Phenotypic means (SD) for BW, WW, and YW were 31.4 (1.6), 175 (32), and 333 (70) kg, respectively. Direct heritability, maternal heritability, and the genetic correlation between additive direct and maternal effects were 0.59, 0.17, and −0.90 for BW; 0.29, 0.17, and −0.90 for WW; and 0.24, 0.15, and −0.86 for YW, respectively. The results showed moderate direct and maternal heritabilities for the studied traits. The genetic correlations between direct and maternal effects were negative and high for all the traits indicating important tradeoffs between direct and maternal effects. There are significant possibilities for genetic progress for the growth traits studied if they are included in a breeding program considering these associations.     

Identification of genomic regions related to age at first calving and first calving interval in water buffalo using single-step GBLUP

In Brazil, water buffaloes have been used to produce milk for mozzarella cheese production. Consequently, the main selection criterion applied for the buffalo genetic improvement is the estimated mozzarella yield as a function of milk, fat and protein production. However, given the importance of reproductive traits in production systems, this study aimed to use techniques for identifying genomic regions that affect the age at first calving (AFC) and first calving interval (FCI) in buffalo cows and to select candidate genes for the identification of QTL and gene expression studies. The single-step GBLUP method was used for the identification of genomic regions. Windows of 1 Mb containing single-nucleotide polymorphisms were constructed and the 10 windows that explained the greatest proportion of genetic variance were considered candidate regions for each trait. Genes present into the selected windows were identified using the UOA_WB_1 assembly as the reference, and their ontology was defined with the Panther tool. Candidate regions for both traits were identified on BBU 3, 12, 21 and 22; for AFC, candidates were detected on BBU 6, 7, 8, 9 and 15 and for first calving interval on BBU 4, 14 and 19. This study identified regions with great contribution to the additive genetic variance of age at first calving and first calving interval in the population of buffalo cows studied. The ROCK2, PMVK, ADCY2, MAP2K6, BMP10 and GFPT1 genes are main candidates for reproductive traits in water dairy buffaloes, and these results may have future applications in animal breeding programs or in gene expression studies of the species.