Genome wide association studies (GWAS) on residual feed intake (RFI) and its component traits including daily dry matter intake (DMI), average daily gain (ADG), and metabolic body weight (MWT) were ...conducted in a population of 7573 animals from multiple beef cattle breeds based on 7,853,211 imputed whole genome sequence variants. The GWAS results were used to elucidate genetic architectures of the feed efficiency related traits in beef cattle.
The DNA variant allele substitution effects approximated a bell-shaped distribution for all the traits while the distribution of additive genetic variances explained by single DNA variants followed a scaled inverse chi-squared distribution to a greater extent. With a threshold of P-value < 1.00E-05, 16, 72, 88, and 116 lead DNA variants on multiple chromosomes were significantly associated with RFI, DMI, ADG, and MWT, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on DMI, ADG, and MWT were found on chromosomes 6, 14 and 20. On average, missense, 3'UTR, 5'UTR, and other regulatory region variants exhibited larger allele substitution effects in comparison to other functional classes. Intergenic and intron variants captured smaller proportions of additive genetic variance per DNA variant. Instead 3'UTR and synonymous variants explained a greater amount of genetic variance per DNA variant for all the traits examined while missense, 5'UTR and other regulatory region variants accounted for relatively more additive genetic variance per sequence variant for RFI and ADG, respectively. In total, 25 to 27 enriched cellular and molecular functions were identified with lipid metabolism and carbohydrate metabolism being the most significant for the feed efficiency traits.
RFI is controlled by many DNA variants with relatively small effects whereas DMI, ADG, and MWT are influenced by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory region and synonymous functional classes play a more important role per sequence variant in determining variation of the feed efficiency traits. The genetic architecture as revealed by the GWAS of the imputed 7,853,211 DNA variants will improve our understanding on the genetic control of feed efficiency traits in beef cattle.
Linkage of rumen microbial structure to host phenotypical traits may enhance the understanding of host-microbial interactions in livestock species. This study used culture-independent PCR-denaturing ...gradient gel electrophoresis (PCR-DGGE) to investigate the microbial profiles in the rumen of cattle differing in feed efficiency. The analysis of detectable bacterial PCR-DGGE profiles showed that the profiles generated from efficient steers clustered together and were clearly separated from those obtained from inefficient steers, indicating that specific bacterial groups may only inhabit in efficient steers. In addition, the bacterial profiles were more likely clustered within a certain breed, suggesting that host genetics may play an important role in rumen microbial structure. The correlations between the concentrations of volatile fatty acids and feed efficiency traits were also observed. Significantly higher concentrations of butyrate (P<0.001) and valerate (P=0.006) were detected in the efficient steers. Our results revealed potential associations between the detectable rumen microbiota and its fermentation parameters with the feed efficiency of cattle.
Genome wide association studies (GWAS) were conducted on 7,853,211 imputed whole genome sequence variants in a population of 3354 to 3984 animals from multiple beef cattle breeds for five ...carcass merit traits including hot carcass weight (HCW), average backfat thickness (AFAT), rib eye area (REA), lean meat yield (LMY) and carcass marbling score (CMAR). Based on the GWAS results, genetic architectures of the carcass merit traits in beef cattle were elucidated.
The distributions of DNA variant allele substitution effects approximated a bell-shaped distribution for all the traits while the distribution of additive genetic variances explained by single DNA variants conformed to a scaled inverse chi-squared distribution to a greater extent. At a threshold of P-value < 10
, 51, 33, 46, 40, and 38 lead DNA variants on multiple chromosomes were significantly associated with HCW, AFAT, REA, LMY, and CMAR, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on HCW, AFAT, REA, and LMY were found on chromosome 6. On average, missense variants, 3'UTR variants, 5'UTR variants, and other regulatory region variants exhibited larger allele substitution effects on the traits in comparison to other functional classes. The amounts of additive genetic variance explained per DNA variant were smaller for intergenic and intron variants on all the traits whereas synonymous variants, missense variants, 3'UTR variants, 5'UTR variants, downstream and upstream gene variants, and other regulatory region variants captured a greater amount of additive genetic variance per sequence variant for one or more carcass merit traits investigated. In total, 26 enriched cellular and molecular functions were identified with lipid metabolisms, small molecular biochemistry, and carbohydrate metabolism being the most significant for the carcass merit traits.
The GWAS results have shown that the carcass merit traits are controlled by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory, synonymous, and missense functional classes have relatively larger impacts per sequence variant on the variation of carcass merit traits. The genetic architecture as revealed by the GWAS will improve our understanding on genetic controls of carcass merit traits in beef cattle.
Heterosis has been suggested to be caused by dominance effects. We performed a joint genome-wide association analysis (GWAS) using data from multi-breed and crossbred beef cattle to identify single ...nucleotide polymorphisms (SNPs) with significant dominance effects associated with variation in growth and carcass traits and to understand the mode of action of these associations.
Illumina BovineSNP50 genotypes and phenotypes for 11 growth and carcass traits were available for 6796 multi-breed and crossbred beef cattle. After performing quality control, 42,610 SNPs and 6794 animals were used for further analyses. A single-SNP GWAS for the joint association of additive and dominance effects was conducted in purebred, crossbred, and combined datasets using the ASReml software. Genomic breed composition predicted from admixture analyses was included in the mixed effect model to account for possible population stratification and breed effects. A threshold of 10% genome-wide false discovery rate was applied to declare associations as significant. The significant SNPs with dominance association were mapped to their corresponding genes at 100 kb.
Seven SNPs with significant dominance associations were detected for birth weight, weaning weight, pre-weaning daily gain, yearling weight and marbling score across the three datasets at a false discovery rate of 10%. These SNPs were located on bovine chromosomes 1, 3, 4, 6 and 21 and mapped to six putative candidate genes: U6atac, AGBL4, bta-mir-2888-1, REPIN1, ICA1 and NXPH1. These genes have interesting biological functions related to the regulation of gene expression, glucose and lipid metabolism and body fat mass. For most of the identified loci, we observed over-dominance association with the studied traits, such that the heterozygous individuals at any of these loci had greater genotypic values for the trait than either of the homozygous individuals.
Our results revealed very few regions with significant dominance genetic effects across all the traits studied in the three datasets used. Regarding the SNPs that were detected with dominance associations, further investigation is needed to determine their relevance in crossbreeding programs assuming that dominance effects are the main cause of (or contribute usefully to) heterosis.
Genetic parameters were estimated for objective and subjective traits assessed after 3 and 29 days aging in meat samples of 1154 commercial beef cattle. Meat attributes Warner-Bratzler shear force ...(WBSF), intramuscular fat (IMF), and pH and sensory traits flavor intensity (FI), off-flavor (OF), connective tissue (CT), overall tenderness (OT), sustained juiciness (SJ), and overall palatability (OP) were available. The animal mixed model used included additive genetic and residual effects as random effects, contemporary group as fixed effect and genomic breed composition and slaughter age as covariates. Genetic parameters were estimated using airemlf90 software and single-step genomic BLUP. Heritability estimates for OT (3 and 29 d), OP (3 d) and OF (29 d) were of moderate magnitude ranging from 0.18 ± 0.07 to 0.31 ± 0.07. Heritabilities were negligible or of low magnitude for all other sensory traits with values ranging from 0.03 ± 0.05 to 0.14 ± 0.07. Among objectively measured traits, the estimate of heritability for meat pH was moderate at day 3 (0.20 ± 0.08) and negligible at 29 (0.00 ± 0.05). For IMF and WBSF the heritability estimates were 0.43 ± 0.09 and 0.54 ± 0.09, and 0.22 ± 0.07 and 0.19 ± 0.07 for day 3 and 29, respectively. Genetic correlations between days for each sensory trait tended to be of high and positive magnitude ranging from 0.54 ± 0.60 to 0.99 ± 0.28. Genetic and phenotypic correlations of subjectively assessed traits were consistent in direction and magnitude with WBSF (negative) and IMF (positive) suggesting that genetic selection based on objectively measured traits can be used for meat quality improvement and to increase consumer satisfaction. In addition, selection can be implemented using sensory traits collected after 3 days of aging.
Agricultural soils in Canada have been observed to emit a large pulse of nitrous oxide (N2O) gas during the spring thaw, representing a large percentage of the annual emissions. We report on three ...years of spring thaw N2O flux measurements taken at three Alberta agricultural sites: a crop production site (Crop), cattle winter-feeding site (WF), and a cattle winter-grazing site (WG). Soil fluxes were calculated with a micrometeorological technique based on the vertical gradient in N2O concentration above each site measured with an open-path (line-averaging) FTIR gas detector. The Crop and WG sites showed a clear N2O emission pulse lasting 10 to 25 days after thawing began. During this pulse there was a strong diurnal cycle in emissions that paralleled the cycle in near-surface soil temperature. The emission pulse was less pronounced at the WF site. The average spring thaw losses (over 25 to 31 days) were 5.3 (Crop), 7.0 (WF), and 8.0 (WG) kg N2O-N ha−1, representing 1 to 3.5% of the annual nitrogen input to the sites. These large losses are higher than found in most previous western Canadian studies, and generally higher than the annual losses estimated from the Intergovernmental Panel on Climate Change and Canadian National Inventory Report calculations. The high N2O losses may be explained by high soil nitrate levels which promoted rapid denitrification during thawing. The application of a high resolution (temporal) micrometeorological technique was critical to revealing these losses.
Objectives were to quantify the phenotypic (rp) and genetic (rg) correlations between early‐life feeding behaviours, dry matter intake, and feed efficiency and measures of cow performance and ...lifetime productivity traits. Traits were measured on 1,145 crossbred replacement beef heifers and then on cows over parities one to four. Feeding event duration (FD) was phenotypically correlated with cow prebreeding body weight (PBWT; rp 0.29–0.45), cow prebreeding back fat thickness (PBBF; rp 0.35–0.49), progeny weaning weight (WW; rp 0.09–0.31) and progeny birthweight (BW; rp −0.06 to 0.17). Feeding event frequency (FF) was phenotypically correlated with PBBF (rp 0.16–0.30). Dry matter intake (DMI) was phenotypically correlated with PBWT (rp 0.16–0.20) and PBBF (rp −0.22 to −0.05). Feeding event duration was genetically correlated with PBWT (rg 0.38–0.41). Feeding event frequency was genetically correlated with PBWT (rg −0.43 to −0.39). Dry matter intake was genetically correlated with PBWT (rg −0.27 to 0.14). Days in herd (DIH) was phenotypically correlated with FD and DMI (rp = 0.12, 0.20, respectively). Lifetime productivity was phenotypically correlated with FD and FF (rg = 0.25, 0.22, respectively). Calving interval was phenotypically correlated with FD and FF (rp = −0.12, −0.14, respectively) and genetically correlated with FF (rg = −0.41). Due to moderate positive correlations with cow weight, caution would be required in selection to prevent an increase in mature cow size. Use of FF, FD, DMI and a measure of feed efficiency such as residual feed intake adjusted for back fat (RFIFAT) in a balanced selection index is recommended.
•To predict the most and the least feed-efficient beef cattle with the optimum subset of DNA markers.•To identify the most and the least feed-efficient beef cattle using machine learning ...algorithms.•To identify the most and the least feed-efficient beef cattle without monitoring their daily feed intake and performance measures.•Machine learning algorithm is able to select a subset of markers (∼500 SNPs) and predict feed efficiency group of animals as accurate as a model with all 50k SNPs.
The present study evaluated three strategies to find the optimum subset of DNA markers from the 50 K Illumina Bovine panel to classify beef cattle into the most and the least feed-efficient groups without using individual feed intake and performance measures. Residual feed intake (RFI) and 50 K single nucleotide polymorphisms (SNPs) genotype data of 4,057 beef animals from research and commercial herds were included. Initially, all cattle were ranked based on their phenotypic RFI values. Then different datasets were created by selecting animals from the 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, and 45% range of top and bottom of the ranked RFI values. SNP subsets were selected based on the top-ranked SNPs contributing to the variance of RFI (first strategy), selecting SNPs from the SNP subsets created in the first strategy (strategy 2), and extracting SNPs from 50k SNPs (strategy 3). Then eleven ML algorithms were employed to classify the most and the least feed-efficient groups using 260 datasets generated by combinations of ten RFI phenotype percentage groups and 6, 18, and 2 SNP subsets in the first, second and third strategies, respectively. There was a high degree of accuracy (>69%) for classifying animals in the range of 1% for all ML algorithms under the three strategies and different SNP subsets. Implementing the linear Support Vector Machine algorithm for 15 K SNPs obtained in the first strategy predicted the 1% of the most and the least feed-efficient animals with an accuracy of 84%. In the second strategy, selecting 524 SNPs from the 15 K SNPs subset outperformed the other strategies with an accuracy of 81% for 1% of the population using the Naive Bayes algorithm. It was concluded that a smaller number of SNPs (524) could be used to predict the most and the least feed-efficient animals with an acceptable accuracy to reduce the cost of selection for RFI using genomic information.
MicroRNAs (miRNAs), a family of small non-coding RNA molecules, appear to regulate animal lipid metabolism and preadipocyte conversion to form lipid-assimilating adipocytes (i.e. adipogenesis). ...However, no miRNA to date has been reported to modulate adipogenesis and lipid deposition in beef cattle.
The expression patterns of 89 miRNAs including four bovine specific miRNAs in subcutaneous adipose tissues from three groups of crossbred steers differing in backfat thickness were compared using qRT-PCR analysis. Eighty-six miRNAs were detectable in all samples, with 42 miRNAs differing among crossbreds (P < 0.05) and 15 miRNAs differentially expressed between tissues with high and low backfat thickness (P < 0.05). The expression levels of 18 miRNAs were correlated with backfat thickness (P < 0.05). The miRNA most differentially expressed and the most strongly associated with backfat thickness was miR-378, with a 1.99-fold increase in high backfat thickness tissues (r = 0.72).
MiRNA expression patterns differed significantly in response to host genetic components. Approximately 20% of the miRNAs in this study were identified as being correlated with backfat thickness. This result suggests that miRNAs may play a regulatory role in white adipose tissue development in beef animals.
Currently, knowledge regarding the ecology and function of bacteria attached to the epithelial tissue of the rumen wall is limited. In this study, the diversity of the bacterial community attached to ...the rumen epithelial tissue was compared to the rumen content bacterial community using 16S rRNA gene sequencing, PCR-DGGE, and qRT-PCR analysis. Sequence analysis of 2785 randomly selected clones from six 16S rDNA (∼1.4
kb) libraries showed that the community structures of three rumen content libraries clustered together and were separated from the rumen tissue libraries. The diversity index of each library revealed that ruminal content bacterial communities (4.12/4.42/4.88) were higher than ruminal tissue communities (2.90/2.73/3.23), based on 97% similarity. The phylum
Firmicutes was predominant in the ruminal tissue communities, while the phylum
Bacteroidetes was predominant in the ruminal content communities. The phyla
Fibrobacteres,
Planctomycetes, and
Verrucomicrobia were only detected in the ruminal content communities. PCR-DGGE analysis of the bacterial profiles of the rumen content and ruminal epithelial tissue samples from 22 steers further confirmed that there is a distinct bacterial community that inhibits the rumen epithelium. The distinctive epimural bacterial communities suggest that
Firmicutes, together with other epithelial-specific species, may have additional functions other than food digestion.
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