Genetic Difference of Five Beef Cattle Breeds Characterized by Genome-wide SNPs and Haplotypes

The objective of this study was to characterize breed differences using SNP available on commonly-used marker panels compared to using genome-wide SNP haplotypes derived from the same markers. The percentage of breed-specific segregating haplotypes was much higher than that of SNPs. Principal components of haplotypes characterized breed difference better than SNP genotypes. Results indicate that haplotypes characterize breed differences more adequately than SNP genotypes and hence offer promise to improve genomic prediction and fine mapping in multi breed population

Improved Accuracy of Across-breed Genomic Prediction Using Haplotypes in Beef Cattle Populations

Genomic prediction uses a reference population of animals with SNP genotypes and phenotypes to predict the merit of selection candidates that typically do not have observed phenotypes. Accuracy of genomic prediction from models that fitted 50K SNP genotypes was low when selection candidates were from a breed only distantly related with the breeds in the reference population. That accuracy was not improved by increasing SNP density from 50K to a ten-fold higher density using imputation. This indicates that the accuracy of genomic prediction mainly came from family-wise co-segregation information. In this study, a genomic prediction model that fitted genome-wide 100 kilo-bp (Kbp) haplotypes improved accuracy for breeds that were not in the reference population. The haplotype model is a more accurate alternative to the SNP model for genomic prediction when animals of the same breed as the prediction candidates are not available for the reference population

Estimation of Genetic Parameters for Carcass Traits and Their Corresponding Ultrasound Measurements in Crossbred Beef Cattle

Variance parameters including heritabilities, genetic and residual correlations are required for national cattle evaluation. There are huge amounts of data available for estimating such variance parameters for growth traits, but much less data is available for carcass traits. In this study, heritabilities and genetic correlations were estimated using restricted maximum likelihood on carcass weight (CWT), fat thickness (FAT), longissimus muscle area (LMA), marbling score (MRB), birth weight (BW), and ultrasound measurements of fat thickness (UFAT), longissimus muscle area (ULMA) and estimated percentage of intramuscular fat (UIMF) for crossbred cattle with carcass data recorded by the American Simmental Association. A multivariate animal model was fitted using ASREML4 software. The results demonstrate that UIMF measurements provide some useful information for carcass MRB (rg=0.73), but genetic correlations were only moderate between ULMA and LMA (0.56) and were weak between UFAT and FAT (0.38). The implications are that carcass measurements on progeny are the most reliable approach to evaluate carcass traits

Genome-wide Association Study of Birth and Weaning Weights in Brangus Beef Cattle

The objective of this study was to map quantitative trait loci (QTL) associated with birth weight and weaning weight in Brangus beef cattle. A total of 6 significant QTL over 4 chromosomes were identified. Two QTL were common to both traits. The genome-wide association study (GWAS) results could help us understand the biological process of growth in Brangus. Further analyses are needed to find and validate the casual mutations responsible for these QTL

Accuracy of Genomic Predictions for Birth, Weaning and Yearling Weights in US Simmental Beef Cattle

Direct genomic breeding values (DGV) based on actual or imputed GeneSeek Genomic Profiler HD (GGPHD) genotypes were obtained for birth, weaning and yearling weights using Bayesian regression on about 20,000 US Simmental pure- or cross-bred beef cattle. Accuracies of DGV were quantified using 4-fold cross validation. Accuracies expressed as genetic correlations between DGV and trait ranged from 0.61 to 0.65, and the regressions of phenotype on DGV ranged from 0.61 to 0.66. These results indicate good predictive ability of genomic prediction with GGPHD chips but DGV need to be adjusted for bias

Characterization of the F94L Double Muscling Mutation in Pure- and Crossbred Limousin Animals

The objective of this study was to investigate the nature of the effect of the F94L variant in the myostatin (MSTN) gene on economic traits in Limousin and Limousin-Angus crossbred animals in the context of genomic analyses using Illumina BovineSNP50 Bead chip genotypes

Characterization and Associations of Haplotypes Containing PLAG1 in Cattle

Genomic regions tend to be inherited in blocks known as haplotypes. The general region spanning PLAG1 shows association with various traits in beef cattle. There are few haplotypes spanning PLAG1, and these are common across breeds but do not capture the true effect. Higher density 770K genotyping demonstrates greater diversity of haplotypes in this region. The tag SNP in Holstein and Jersey dairy cattle segregates in Hereford cattle who show no effect in this region. Collectively, these results show the 50K SNP chip has inadequate coverage in this region of the genome

Characterizing Haplotype Diversity in Ten US Beef Cattle Breeds

The distributions of haplotype diversity across the whole genome among 10 US beef cattle breeds were constructed. In most chromosomes for all the breeds, consistent low haplotype diversity were observed in some specific regions, 55% of which was found to match the positions of reported gene duplications. Further work is required to determine whether the low haplotype diversity is real, or a result of problems in sequencing which have limited our ability to identify informative markers in those regions. Haplotype diversity will be the subject of ongoing work to identify haplotypes that are under-represented as homozygotes, to fine-map regions with major gene effects, and to fit haplotype rather than SNP models for genomic prediction

Genomic Prediction using Single or Multi-Breed Reference Populations in US Maine-Anjou Beef Cattle

The objective of this study was to estimate accuracies of genomic predictions based on 50K SNP genotypes for 8 nationally evaluated traits in US Maine-Anjou beef cattle using single or multi-breed reference populations. The accuracies of direct genomic values (DGV) ranged from 0.22 to 0.45 for 8 studied traits when the reference populations comprised only 573 Maine-Anjou animals. Accuracies were slightly reduced and ranged from 0.21 to 0.38 when the reference population included over 9,000 animals from many other breeds as well as Maine-Anjou. These results demonstrate that including data from other populations does not generally increase accuracy of prediction in one particular population. This means every breed association must develop its own reference population if it intends to offer genomic prediction

Kv7.4 Channel Contribute to Projection-Specific Auto-Inhibition of Dopamine Neurons in the Ventral Tegmental Area

Dopaminergic neurons in the ventral tegmental area (VTA) encode behavioral patterns important in reward and drug addiction as well as in emotional disorders. These functions of dopamine neurons are directly related to the release of dopamine in the targeted regions of the brain which are, thus, controlled by the excitability of dopamine neurons. One mechanism for modulation of dopamine neuronal excitability is mediated by the auto dopamine type 2 (D2) receptors, through activation of a Kir3/GIRK K+ channel which inhibits the firing of dopamine neurons. In this study, we provide evidence that Kv7.4, in addition to Kir3.2 channels, contributes to dopamine (DA)-mediated auto-inhibition of DA activity projecting to NAc and to basolateral amygdale (BLA). Furthermore, we demonstrate that D2 receptors enhance Kv7.4 currents through Gi/o protein and redox-dependent cellular pathway. Finally, we show this D2 mediated auto-inhibition is blunted in a social defeat mice model of depression, a phenomenon that may contribute to the altered excitability of VTA DA neurons in depressed animals. These results provide a new perspective for understanding the molecular mechanism of the excitability of VTA DA neurons and for potential new strategies against mental disorders involving altered excitability of DA neurons, such as major depression and drug addictions