[show abstract][hide abstract] ABSTRACT: The domestication and development of cattle has considerably impacted human
societies, but the histories of cattle breeds have been poorly understood
especially for African, Asian, and American breeds. Using genotypes from 43,043
autosomal single nucleotide polymorphism markers scored in 1,543 animals, we
evaluate the population structure of 134 domesticated bovid breeds. Regardless
of the analytical method or sample subset, the three major groups of Asian
indicine, Eurasian taurine, and African taurine were consistently observed.
Patterns of geographic dispersal resulting from co-migration with humans and
exportation are recognizable in phylogenetic networks. All analytical methods
reveal patterns of hybridization which occurred after divergence. Using 19
breeds, we map the cline of indicine introgression into Africa. We infer that
African taurine possess a large portion of wild African auroch ancestry,
causing their divergence from Eurasian taurine. We detect exportation patterns
in Asia and identify a cline of Eurasian taurine/indicine hybridization in
Asia. We also identify the influence of species other than Bos taurus in the
formation of Asian breeds. We detect the pronounced influence of Shorthorn
cattle in the formation of European breeds. Iberian and Italian cattle possess
introgression from African taurine. American Criollo cattle are shown to be of
Iberian, and not African, decent. Indicine introgression into American cattle
occurred in the Americas, and not Europe. We argue that cattle migration,
movement and trading followed by admixture have been important forces in
shaping modern bovine genomic variation.
[show abstract][hide abstract] ABSTRACT: Artificial neural networks (ANN) mimic the function of the human brain and are capable of performing massively parallel computations for data processing and knowledge representation. ANN can capture nonlinear relationships between predictors and responses and can adaptively learn complex functional forms, in particular, for situations where conventional regression models are ineffective. In a previous study, ANN with Bayesian regularization outperformed a benchmark linear model when predicting milk yield in dairy cattle or grain yield of wheat. Although breeding values rely on the assumption of additive inheritance, the predictive capabilities of ANN are of interest from the perspective of their potential to increase the accuracy of prediction of molecular breeding values used for genomic selection. This motivated the present study, in which the aim was to investigate the accuracy of ANN when predicting the expected progeny difference (EPD) of marbling score in Angus cattle. Various ANN architectures were explored, which involved two training algorithms, two types of activation functions, and from 1 to 4 neurons in hidden layers. For comparison, BayesCpi models were used to select a subset of optimal markers (referred to as feature selection), under the assumption of additive inheritance, and then the marker effects were estimated using BayesCpi with pi set equal to zero. This procedure is referred to as BayesCpC and was implemented on a high-throughput computing cluster.
The ANN with Bayesian regularization method performed equally well for prediction of EPD as BayesCpC, based on prediction accuracy and sum of squared errors. With the 3K-SNP panel, for example, prediction accuracy was 0.776 using BayesCpC, and ranged from 0.776 to 0.807 using BRANN. With the selected 700-SNP panel, prediction accuracy was 0.863 for BayesCpC and ranged from 0.842 to 0.858 for BRANN. However, prediction accuracy for the ANN with scaled conjugate gradient back-propagation was lower, ranging from 0.653 to 0.689 with the 3K-SNP panel, and from 0.743 to 0.793 with the selected 700-SNP panel.
ANN with Bayesian regularization performed as well as linear Bayesian regression models in predicting additive genetic values, supporting the idea that ANN are useful as universal approximators of functions of interest in breeding contexts.
[show abstract][hide abstract] ABSTRACT: Meat quality traits are economically important because they impact consumers' acceptance which, in turn, influences the demand for beef. However, selection to improve meat quality is limited by the small numbers of animals on which meat tenderness can be evaluated due to the cost of performing shear force analysis and the resultant damage to the carcass. Genome wide-association studies (GWAS) for Warner-Bratzler shear force (WBSF) measured at different times of meat aging, backfat thickness (BFT), ribeye muscle area (REA), scanning parameters (Lightness (L*), redness (a*) and yellowness (b*) to ascertain color characteristics of meat and fat, water-holding capacity (WHC), cooking loss (CL) and muscle pH, were conducted using genotype data from the Illumina BovineHD BeadChip array to identify quantitative trait loci (QTL) in all phenotyped Nelore cattle. Phenotype count for these animals ranged from 430 to 536 across traits. Meat quality traits in Nelore are controlled by numerous QTL of small effect, except for a small number of large-effect QTL identified for a*fat, CL and pH. Genomic regions harboring these QTL and the pathways in which the genes from these regions act appear to differ from those identified in taurine cattle for meat quality traits. These results will guide future QTL mapping studies and the development of models for the prediction of genetic merit to implement genomic selection for meat quality in Nelore cattle.
[show abstract][hide abstract] ABSTRACT: Although the efficacy of genomic predictors based on within-breed training looks promising, it is necessary to develop and evaluate across-breed predictors for the technology to be fully applied in the beef industry. The efficacies of genomic predictors trained in one breed and utilized to predict genetic merit in differing breeds based on simulation studies have been reported, as have the efficacies of predictors trained using data from multiple breeds to predict the genetic merit of purebreds. However, comparable studies using beef cattle field data have not been reported.
Molecular breeding values for weaning and yearling weight were derived and evaluated using a database containing BovineSNP50 genotypes for 7294 animals from 13 breeds in the training set and 2277 animals from seven breeds (Angus, Red Angus, Hereford, Charolais, Gelbvieh, Limousin, and Simmental) in the evaluation set. Six single-breed and four across-breed genomic predictors were trained using pooled data from purebred animals. Molecular breeding values were evaluated using field data, including genotypes for 2227 animals and phenotypic records of animals born in 2008 or later. Accuracies of molecular breeding values were estimated based on the genetic correlation between the molecular breeding value and trait phenotype.
With one exception, the estimated genetic correlations of within-breed molecular breeding values with trait phenotype were greater than 0.28 when evaluated in the breed used for training. Most estimated genetic correlations for the across-breed trained molecular breeding values were moderate (> 0.30). When molecular breeding values were evaluated in breeds that were not in the training set, estimated genetic correlations clustered around zero.
Even for closely related breeds, within- or across-breed trained molecular breeding values have limited prediction accuracy for breeds that were not in the training set. For breeds in the training set, across- and within-breed trained molecular breeding values had similar accuracies. The benefit of adding data from other breeds to a within-breed training population is the ability to produce molecular breeding values that are more robust across breeds and these can be utilized until enough training data has been accumulated to allow for a within-breed training set.
[show abstract][hide abstract] ABSTRACT: Previous archeological and genetic research has shown that modern cattle breeds are descended from multiple independent domestication events of the wild aurochs (Bos primigenius) ∼10,000 y ago. Two primary areas of domestication in the Middle East/Europe and the Indian subcontinent resulted in taurine and indicine lines of cattle, respectively. American descendants of cattle brought by European explorers to the New World beginning in 1493 generally have been considered to belong to the taurine lineage. Our analyses of 47,506 single nucleotide polymorphisms show that these New World cattle breeds, as well as many related breeds of cattle in southern Europe, actually exhibit ancestry from both the taurine and indicine lineages. In this study, we show that, although European cattle are largely descended from the taurine lineage, gene flow from African cattle (partially of indicine origin) contributed substantial genomic components to both southern European cattle breeds and their New World descendants. New World cattle breeds, such as Texas Longhorns, provide an opportunity to study global population structure and domestication in cattle. Following their introduction into the Americas in the late 1400s, semiferal herds of cattle underwent between 80 and 200 generations of predominantly natural selection, as opposed to the human-mediated artificial selection of Old World breeding programs. Our analyses of global cattle breed population history show that the hybrid ancestry of New World breeds contributed genetic variation that likely facilitated the adaptation of these breeds to a novel environment.
Proceedings of the National Academy of Sciences 03/2013; · 9.74 Impact Factor
[show abstract][hide abstract] ABSTRACT: Gene regulation and transcriptome studies have been enabled by the development of RNA-Seq applications for high-throughput sequencing platforms. Next generation sequencing is remarkably efficient at data generation and avoids many issues inherent in hybridization-based microarray methodologies including the exon-specific dependence of probe design. Biologically relevant transcripts including messenger and regulatory RNAs may now be quantified and annotated regardless of whether they have previously been observed. We used RNA-Seq to investigate global patterns of gene expression in early developing rat liver. Liver samples of two littermates from timed-pregnant Lewis rats were collected at six fetal and neonatal stages (E14, E16, E18, E20, P1, P7), and transcripts were sequenced using an Illumina HiSeq 2000. Data analysis was performed using the Tuxedo software suite by aligning reads to the rat reference genome assembly using Bowtie and Tophat, assembling a parsimonious transcript set, and testing transcripts for differential abundance between adjacent developmental time-points using Cufflinks. Genes and isoforms differing in abundance were queried for enrichment within functionally-related gene groups using the Functional Annotation Tool of the DAVID Bioinformatics Database. We observed a substantial enrichment in Gene Ontology terms for genes involved in GTP and transcription factor binding for which alternate isoforms differed in abundance during liver development. These Gene Ontology terms differed significantly from those for genes which differed in abundance, which accurately recapitulated the biology of perinatal liver development. Finally, a bioinformatic approach was used to annotate 1,307 novel liver transcripts assembled from sequences that aligned to intergenic regions of the rat genome.
[show abstract][hide abstract] ABSTRACT: To assist cattle producers transition from microsatellite (MS) to single nucleotide polymorphism (SNP) genotyping for parental verification we previously devised an effective and inexpensive method to impute MS alleles from SNP haplotypes. While the reported method was verified with only a limited data set (N = 479) from Brown Swiss, Guernsey, Holstein, and Jersey cattle, some of the MS-SNP haplotype associations were concordant across these phylogenetically diverse breeds. This implied that some haplotypes predate modern breed formation and remain in strong linkage disequilibrium. To expand the utility of MS allele imputation across breeds, MS and SNP data from more than 8000 animals representing 39 breeds (Bos taurus and B. indicus) were used to predict 9410 SNP haplotypes, incorporating an average of 73 SNPs per haplotype, for which alleles from 12 MS markers could be accurately be imputed. Approximately 25% of the MS-SNP haplotypes were present in multiple breeds (N = 2 to 36 breeds). These shared haplotypes allowed for MS imputation in breeds that were not represented in the reference population with only a small increase in Mendelian inheritance inconsistancies. Our reported reference haplotypes can be used for any cattle breed and the reported methods can be applied to any species to aid the transition from MS to SNP genetic markers. While ~91% of the animals with imputed alleles for 12 MS markers had ≤1 Mendelian inheritance conflicts with their parents' reported MS genotypes, this figure was 96% for our reference animals, indicating potential errors in the reported MS genotypes. The workflow we suggest autocorrects for genotyping errors and rare haplotypes, by MS genotyping animals whose imputed MS alleles fail parentage verification, and then incorporating those animals into the reference dataset.
[show abstract][hide abstract] ABSTRACT: The domestication and subsequent selection by humans to create breeds and biological types of cattle undoubtedly altered the patterning of variation within their genomes. Strong selection to fix advantageous large-effect mutations underlying domesticability, breed characteristics or productivity created selective sweeps in which variation was lost in the chromosomal region flanking the selected allele. Selective sweeps have now been identified in the genomes of many animal species including humans, dogs, horses, and chickens. Here, we attempt to identify and characterise regions of the bovine genome that have been subjected to selective sweeps.
Two datasets were used for the discovery and validation of selective sweeps via the fixation of alleles at a series of contiguous SNP loci. BovineSNP50 data were used to identify 28 putative sweep regions among 14 diverse cattle breeds. Affymetrix BOS 1 prescreening assay data for five breeds were used to identify 85 regions and validate 5 regions identified using the BovineSNP50 data. Many genes are located within these regions and the lack of sequence data for the analysed breeds precludes the nomination of selected genes or variants and limits the prediction of the selected phenotypes. However, phenotypes that we predict to have historically been under strong selection include horned-polled, coat colour, stature, ear morphology, and behaviour.
The bias towards common SNPs in the design of the BovineSNP50 assay led to the identification of recent selective sweeps associated with breed formation and common to only a small number of breeds rather than ancient events associated with domestication which could potentially be common to all European taurines. The limited SNP density, or marker resolution, of the BovineSNP50 assay significantly impacted the rate of false discovery of selective sweeps, however, we found sweeps in common between breeds which were confirmed using an ultra-high-density assay scored in a small number of animals from a subset of the breeds. No sweep regions were shared between indicine and taurine breeds reflecting their divergent selection histories and the very different environmental habitats to which these sub-species have adapted.
[show abstract][hide abstract] ABSTRACT: BACKGROUND: In national evaluations, direct genomic breeding values can be considered as correlated traits to those for which phenotypes are available for traditional estimation of breeding values. For this purpose, estimates of the accuracy of direct genomic breeding values expressed as genetic correlations between traits and their respective direct genomic breeding values are required. METHODS: We derived direct genomic breeding values for 2239 registered Limousin and 2703 registered Simmental beef cattle genotyped with either the Illumina BovineSNP50 BeadChip or the Illumina BovineHD BeadChip. For the 264 Simmental animals that were genotyped with the BovineHD BeadChip, genotypes for markers present on the BovineSNP50 BeadChip were extracted. Deregressed estimated breeding values were used as observations in weighted analyses that estimated marker effects to derive direct genomic breeding values for each breed. For each breed, genotyped individuals were clustered into five groups using K-means clustering, with the aim of increasing within-group and decreasing between-group pedigree relationships. Cross-validation was performed five times for each breed, using four groups for training and the fifth group for validation. For each trait, we then applied a weighted bivariate analysis of the direct genomic breeding values of genotyped animals from all five validation sets and their corresponding deregressed estimated breeding values to estimate variance and covariance components. RESULTS: After minimizing relationships between training and validation groups, estimated genetic correlations between each trait and its direct genomic breeding values ranged from 0.39 to 0.76 in Limousin and from 0.29 to 0.65 in Simmental. The efficiency of selection based on direct genomic breeding values relative to selection based on parent average information ranged from 0.68 to 1.28 in genotyped Limousin and from 0.51 to 1.44 in genotyped Simmental animals. The efficiencies were higher for 323 non-genotyped young Simmental animals, born after January 2012, and ranged from 0.60 to 2.04. CONCLUSIONS: Direct genomic breeding values show promise for routine use by Limousin and Simmental breeders to improve the accuracy of predicted genetic merit of their animals at a young age and increase response to selection. Benefits from selecting on direct genomic breeding values are greater for breeders who use natural mating sires in their herds than for those who use artificial insemination sires. Producers with unregistered commercial Limousin and Simmental cattle could also benefit from being able to identify genetically superior animals in their herds, an opportunity that has in the past been limited to seed stock animals.
[show abstract][hide abstract] ABSTRACT: BACKGROUND: Several methods have recently been developed to identify regions of the genome that have been exposed to strong selection. However, recent theoretical and empirical work suggests that polygenic models are required to identify the genomic regions that are more moderately responding to ongoing selection on complex traits. We examine the effects of multi-trait selection on the genome of a population of US registered Angus beef cattle born over a 50-year period representing approximately 10 generations of selection. We present results from the application of a quantitative genetic model, called Birth Date Selection Mapping, to identify signatures of recent ongoing selection. RESULTS: We show that US Angus cattle have been systematically selected to alter their mean additive genetic merit for most of the 16 production traits routinely recorded by breeders. Using Birth Date Selection Mapping, we estimate the time-dependency of allele frequency for 44,817 SNP loci using genomic best linear unbiased prediction, generalized least squares, and BayesCpi analyses. Finally, we reconstruct the primary phenotypes that have historically been exposed to selection from a genome-wide analysis of the 16 production traits and gene ontology enrichment analysis. CONCLUSIONS: We demonstrate that Birth Date Selection Mapping utilizing mixed models corrects for time-dependent pedigree sampling effects that lead to spurious SNP associations and reveals genomic signatures of ongoing selection on complex traits. Because multiple traits have historically been selected in concert and most quantitative trait loci have small effects, selection has incrementally altered allele frequencies throughout the genome. Two quantitative trait loci of large effect were not the most strongly selected of the loci due to their antagonistic pleiotropic effects on strongly selected phenotypes. Birth Date Selection Mapping may readily be extended to temporally-stratified human or model organism populations.
[show abstract][hide abstract] ABSTRACT: Several organizations have developed prediction models for molecular breeding values (MBV) for quantitative growth and carcass traits in beef cattle using BovineSNP50 genotypes and phenotypic or EBV data. MBV for Angus cattle have been developed by IGENITY, Pfizer Animal Genetics, and a collaboration between researchers from Iowa State University (ISU) and the University of Missouri-Columbia (UMC). The U.S. Meat Animal Research Center (USMARC; Clay Center, NE) has also developed MBV for 16 cattle breeds using two multi-breed populations, the GermPlasm Evaluation program (GPE) and the 2,000 Bull Project (2K(ALL)), and two single breed subpopulations of the 2,000 Bull Project, Angus (2K(AN)) and Hereford (2K(HH)). In this study, these MBV were assessed relative to commercial ranch EBV estimated from the progeny phenotypes of Angus bulls naturally mated in multi-sire breeding pastures to commercial cows: 121 for USMARC MBV, 99 for ISU/UMC MBV, and 29 for IGENITY and Pfizer MBV (selected based on number of progeny carcass records). Five traits were analyzed: weaning weight (WW), hot carcass weight (CW), marbling score (MS), rib-eye muscle area (RE), and, for IGENITY and Pfizer only, feedlot average daily gain (ADG). The average accuracies of MBV across traits were: IGENITY 0.38±0.05, Pfizer 0.61±0.12, ISU/UMC 0.46±0.12, GPE 0.16±0.04, 2K(ALL) 0.26±0.05, 2K(AN) 0.24±0.04, and 2K(HH) 0.02±0.12. Angus-based MBV (IGENITY, Pfizer, ISU/UMC, and 2K(AN)) explained larger proportions of genetic variance in this population than GPE, 2K(ALL), or 2K(HH) MBV for the same traits. In this data set, IGENITY, Pfizer, and ISU/UMC MBV were predictive of realized performance of progeny, and incorporation of that information into national genetic evaluations would be expected to improve EPD accuracy, particularly for young animals.
Journal of Animal Science 08/2012; 90:4191-4202. · 2.09 Impact Factor
[show abstract][hide abstract] ABSTRACT: Summary Imputation of moderate-density genotypes from low-density panels is of increasing interest in genomic selection, because it can dramatically reduce genotyping costs. Several imputation software packages have been developed, but they vary in imputation accuracy, and imputed genotypes may be inconsistent among methods. An AdaBoost-like approach is proposed to combine imputation results from several independent software packages, i.e. Beagle(v3.3), IMPUTE(v2.0), fastPHASE(v1.4), AlphaImpute, findhap(v2) and Fimpute(v2), with each package serving as a basic classifier in an ensemble-based system. The ensemble-based method computes weights sequentially for all classifiers, and combines results from component methods via weighted majority 'voting' to determine unknown genotypes. The data included 3078 registered Angus cattle, each genotyped with the Illumina BovineSNP50 BeadChip. SNP genotypes on three chromosomes (BTA1, BTA16 and BTA28) were used to compare imputation accuracy among methods, and the application involved the imputation of 50K genotypes covering 29 chromosomes based on a set of 5K genotypes. Beagle and Fimpute had the greatest accuracy among the six imputation packages, which ranged from 0·8677 to 0·9858. The proposed ensemble method was better than any of these packages, but the sequence of independent classifiers in the voting scheme affected imputation accuracy. The ensemble systems yielding the best imputation accuracies were those that had Beagle as first classifier, followed by one or two methods that utilized pedigree information. A salient feature of the proposed ensemble method is that it can solve imputation inconsistencies among different imputation methods, hence leading to a more reliable system for imputing genotypes relative to independent methods.
Genetics Research 07/2012; 94(3):133-50. · 2.00 Impact Factor
[show abstract][hide abstract] ABSTRACT: We report a systematic study of gene expression during myogenesis and transdifferentiation in four bovine muscle tissues and of adipogenesis in three bovine fat tissues using DNA microarray analysis. One hundred hybridizations were performed and 7245 genes of known and unknown function were identified as being differentially expressed. Supervised hierarchical cluster analysis of gene expression patterns revealed the tissue specificity of genes. A close relationship in global gene expression observed for adipocyte-like cells derived from muscle and adipocytes derived from intramuscular fat suggests a common origin for these cells. The role of transthyretin in myogenesis is a novel finding. Different genes were highly induced during the transdifferentiation of myogenic satellite cells and in the adipogenesis of preadipocytes, indicating the involvement of different molecular mechanisms in these processes. Induction of CD36 and FABP4 expression in adipocyte-like cells and adipocytes may share a common pathway.
[show abstract][hide abstract] ABSTRACT: Copy number variations (CNVs) affect a wide range of phenotypic traits; however, CNVs in or near segmental duplication regions are often intractable. Using a read depth approach based on next-generation sequencing, we examined genome-wide copy number differences among five taurine (three Angus, one Holstein, and one Hereford) and one indicine (Nelore) cattle. Within mapped chromosomal sequence, we identified 1265 CNV regions comprising ~55.6-Mbp sequence--476 of which (~38%) have not previously been reported. We validated this sequence-based CNV call set with array comparative genomic hybridization (aCGH), quantitative PCR (qPCR), and fluorescent in situ hybridization (FISH), achieving a validation rate of 82% and a false positive rate of 8%. We further estimated absolute copy numbers for genomic segments and annotated genes in each individual. Surveys of the top 25 most variable genes revealed that the Nelore individual had the lowest copy numbers in 13 cases (~52%, χ(2) test; P-value <0.05). In contrast, genes related to pathogen- and parasite-resistance, such as CATHL4 and ULBP17, were highly duplicated in the Nelore individual relative to the taurine cattle, while genes involved in lipid transport and metabolism, including APOL3 and FABP2, were highly duplicated in the beef breeds. These CNV regions also harbor genes like BPIFA2A (BSP30A) and WC1, suggesting that some CNVs may be associated with breed-specific differences in adaptation, health, and production traits. By providing the first individualized cattle CNV and segmental duplication maps and genome-wide gene copy number estimates, we enable future CNV studies into highly duplicated regions in the cattle genome.
Genome Research 02/2012; 22(4):778-90. · 14.40 Impact Factor
[show abstract][hide abstract] ABSTRACT: We performed a genome-wide association study for Warner-Bratzler shear force (WBSF), a measure of meat tenderness, by genotyping 3360 animals from five breeds with 54 790 BovineSNP50 and 96 putative single-nucleotide polymorphisms (SNPs) within μ-calpain [HUGO nomenclature calpain 1, (mu/I) large subunit; CAPN1] and calpastatin (CAST). Within- and across-breed analyses estimated SNP allele substitution effects (ASEs) by genomic best linear unbiased prediction (GBLUP) and variance components by restricted maximum likelihood under an animal model incorporating a genomic relationship matrix. GBLUP estimates of ASEs from the across-breed analysis were moderately correlated (0.31-0.66) with those from the individual within-breed analyses, indicating that prediction equations for molecular estimates of breeding value developed from across-breed analyses should be effective for genomic selection within breeds. We identified 79 genomic regions associated with WBSF in at least three breeds, but only eight were detected in all five breeds, suggesting that the within-breed analyses were underpowered, that different quantitative trait loci (QTL) underlie variation between breeds or that the BovineSNP50 SNP density is insufficient to detect common QTL among breeds. In the across-breed analysis, CAPN1 was followed by CAST as the most strongly associated WBSF QTL genome-wide, and associations with both were detected in all five breeds. We show that none of the four commercialized CAST and CAPN1 SNP diagnostics are causal for associations with WBSF, and we putatively fine-map the CAPN1 causal mutation to a 4581-bp region. We estimate that variation in CAST and CAPN1 explains 1.02 and 1.85% of the phenotypic variation in WBSF respectively.
[show abstract][hide abstract] ABSTRACT: We performed a genome-wide association study for Warner–Bratzler shear force (WBSF), a measure of meat tenderness, by genotyping 3360 animals from five breeds with 54 790 BovineSNP50 and 96 putative single-nucleotide polymorphisms (SNPs) within l-calpain [HUGO nomenclature calpain 1, (mu/I) large subunit; CAPN1] and calpastatin (CAST). Within-and across-breed analyses estimated SNP allele substitution effects (ASEs) by genomic best linear unbiased prediction (GBLUP) and variance components by restricted maximum likelihood under an animal model incorporating a genomic relation-ship matrix. GBLUP estimates of ASEs from the across-breed analysis were moderately correlated (0.31–0.66) with those from the individual within-breed analyses, indicating that prediction equations for molecular estimates of breeding value developed from across-breed analyses should be effective for genomic selection within breeds. We identi-fied 79 genomic regions associated with WBSF in at least three breeds, but only eight were detected in all five breeds, suggesting that the within-breed analyses were under-powered, that different quantitative trait loci (QTL) underlie variation between breeds or that the BovineSNP50 SNP density is insufficient to detect common QTL among breeds. In the across-breed analysis, CAPN1 was followed by CAST as the most strongly associ-ated WBSF QTL genome-wide, and associations with both were detected in all five breeds. We show that none of the four commercialized CAST and CAPN1 SNP diagnostics are causal for associations with WBSF, and we putatively fine-map the CAPN1 causal muta-tion to a 4581-bp region. We estimate that variation in CAST and CAPN1 explains 1.02 and 1.85% of the phenotypic variation in WBSF respectively. Keywords beef, Bos taurus taurus, calpain 1, (mu/I) large subunit, calpastatin, genome-wide association, haplotype, meat tenderness, quantitative trait loci, single-nucleotide polymorphisms, Warner–Bratzler shear force.
[show abstract][hide abstract] ABSTRACT: The molecular mechanisms underlying myogenic satellite cells (MSCs) differentiation into myotube-formed cells (MFCs) and transdifferentiation into adipocyte-like cells (ALCs) are un-clear. As a step towards understanding the molecular mecha-nisms underlying MSC differentiation and transdifferentiation, we attempted to identify the genes differentially expressed dur-ing differentiation and transdifferentiation using gene micro-array analysis (GMA). Thirty oligonucleotide arrays were used with two technical replicates and nine and six biological repli-cates for MFCs vs. MSCs and ALCs vs. MSCs, respectively, to contrast expression profile differences. GMA identified 1,224 differentially expressed genes by at least 2-fold during differentiation and transdifferentiation of MSCs. To select the highly expressed genes for future functional study, genes with a 4-fold expression difference were selected for validation by real time RT-PCR and approximately 96.9% of the genes were validated. (MYL2, MYH3) and adipogenesis (PPARγ, and FABP4) was observed during the differentiation and transdifferentiation of MSCs into MFCs and ALCs, respectively. KOG analysis re-vealed that the most of the genes up-regulated during differ-entiation and transdifferentiation of MSCs were related to sig-nal transduction. Again the exact location of 109 differentially expressed genes by 4-fold were analyzed by chromosome mapping. Among those, co-localization of 29 genes up-regu-lated during transdifferentiation with QTL for marbling score and intramuscular fat percentage supports the involvement of these genes in cellular transdifferentiation. Interestingly, some genes with unknown function were also identified during the process. Functional studies on these genes may unfold the mo-lecular mechanisms controlling MSC differentiation and transdifferentiation.
[show abstract][hide abstract] ABSTRACT: Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction.
Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values.
Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied.
These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.
[show abstract][hide abstract] ABSTRACT: Estimated breeding values for average daily feed intake (AFI; kg/day), residual feed intake (RFI; kg/day) and average daily gain (ADG; kg/day) were generated using a mixed linear model incorporating genomic relationships for 698 Angus steers genotyped with the Illumina BovineSNP50 assay. Association analyses of estimated breeding values (EBVs) were performed for 41,028 single nucleotide polymorphisms (SNPs), and permutation analysis was used to empirically establish the genome-wide significance threshold (P < 0.05) for each trait. SNPs significantly associated with each trait were used in a forward selection algorithm to identify genomic regions putatively harbouring genes with effects on each trait. A total of 53, 66 and 68 SNPs explained 54.12% (24.10%), 62.69% (29.85%) and 55.13% (26.54%) of the additive genetic variation (when accounting for the genomic relationships) in steer breeding values for AFI, RFI and ADG, respectively, within this population. Evaluation by pathway analysis revealed that many of these SNPs are in genomic regions that harbour genes with metabolic functions. The presence of genetic correlations between traits resulted in 13.2% of SNPs selected for AFI and 4.5% of SNPs selected for RFI also being selected for ADG in the analysis of breeding values. While our study identifies panels of SNPs significant for efficiency traits in our population, validation of all SNPs in independent populations will be necessary before commercialization.