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Many traits affecting profitability and sustainability of meat, milk, and fiber production are polygenic, with no single gene having an overwhelming influence on observed variation. No knowledge of the specific genes controlling these traits has been needed to make substantial improvement through selection. Significant gains have been made through phenotypic selection enhanced by pedigree relationships and continually improving statistical methodology. Genomic selection, recently enabled by assays for dense SNP located throughout the genome, promises to increase selection accuracy and accelerate genetic improvement by emphasizing the SNP most strongly correlated to phenotype although the genes and sequence variants affecting phenotype remain largely unknown. These genomic predictions theoretically rely on linkage disequilibrium (LD) between genotyped SNP and unknown functional variants, but familial linkage may increase effectiveness when predicting individuals related to those in the training data. Genomic selection with functional SNP genotypes should be less reliant on LD patterns shared by training and target populations, possibly allowing robust prediction across unrelated populations. Although the specific variants causing polygenic variation may never be known with certainty, a number of tools and resources can be used to identify those most likely to affect phenotype. Associations of dense SNP genotypes with phenotype provide a 1-dimensional approach for identifying genes affecting specific traits; in contrast, associations with multiple traits allow defining networks of genes interacting to affect correlated traits. Such networks are especially compelling when corroborated by existing functional annotation and established molecular pathways. The SNP occurring within network genes, obtained from public databases or derived from genome and transcriptome sequences, may be classified according to expected effects on gene products. As illustrated by functionally informed genomic predictions being more accurate than naive whole-genome predictions of beef tenderness, coupling evidence from livestock genotypes, phenotypes, gene expression, and genomic variants with existing knowledge of gene functions and interactions may provide greater insight into the genes and genomic mechanisms affecting polygenic traits and facilitate functional genomic selection for economically important traits. [ABSTRACT FROM AUTHOR]

Several organizations have developed prediction models for molecular breeding values (MBV) for quantitative growth and carcass traits in beef cattle using Bovine SNP50 genotypes and phenotypic or EBV data. Molecular breeding values for Angus cattle have been developed by IGENITY, Pfizer Animal Genetics, and a collaboration between researchers from Iowa State University and the University of Missouri-Columbia (ISU/UMC). The U.S. Meat Animal Research Center (USMARC; Clay Center, NE) has also developed MBV for 16 cattle breeds using 2 multibreed populations, the Germplasm Evaluation (GPE) Program and the 2,000 Bull Project (2KALL), and 2 single breed subpopulations of the 2,000 Bull Project, Angus (2KAN) and Hereford (2KHH). In this study, these MBV were assessed relative to commercial ranch EBV estimated from the progeny phenotypes of Angus bulls naturally mated in multisire 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), HCW, marbling score (MS), rib-eye muscle area (RE), and, for IGENITY and Pfizer only, feedlot ADG. The average accuracies of MBV across traits were 0.38 ± 0.05 for IGENITY, 0.61 ± 0.12 for Pfizer, 0.46 ± 0.12 for ISU/UMC, 0.16 ± 0.04 for GPE, 0.26 ± 0.05 for 2KALL, 0.24 ± 0.04 for 2KAN, and 0.02 ± 0.12 for 2KHH. Angus-based MBV (IGENITY, Pfizer, ISU/UMC, and 2KAN) explained larger proportions of genetic variance in this population than GPE, 2KALL, or 2KHH 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. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate alternative methods of designing and using reduced SNP panels for imputing SNP genotypes. Two purebred Hereford populations, an experimental population known as Line 1 Hereford (LI, n = 240) and registered Hereford with American Hereford Association (AHA, n = 311), were used. Using different reference samples of 62 to 311 animals with 39,497 SNP on 29 autosomes and study samples of 57 or 62 animals for which genotypes were available for ~2,600 SNP (reduced panels), imputations were performed to predict the other ~36,900 loci that had been masked. An imputation package, including LinkPHASE and DAGPHASE, was used for imputation. Four reduced panels differing in minor allele frequency (MAF) and marker spacing were evaluated. Reduced panels included every 15th SNP across the genome (SNP_space), commercial Illumina Bovine3K Beadchip (SNP_3K), SNP with the highest MAF (SNP_MAF), and SNP with high MAF that were also evenly spaced across the genome (SNP_MS). Imputation accuracy was defined as the correlation of imputed genotypes and real genotypes. Reference samples were either from LI or AHA. Among animals with genotypes, genetic relationships were estimated based on molecular marker genotypes or pedigree. Reduced panel design, number of animals in the reference sample, reference origin and genetic relationship between animals in the reference, and study samples all affected imputation accuracy (P < 0.001). Across genotyping schemes, imputed genotypes from SNP_MS had the greatest accuracy. A 0.1 increase in average pedigree relationship or average molecular relationship between reference and study samples increased imputation accuracy 10 to 20%. Using reference samples from the LI population resulted in lower imputation accuracy than using reference samples from the admixed population AHA (P < 0.001). Increasing the number of animals in the reference panel by 100 individuals increased imputation accuracy by 8% when pedigree relationship was used as a covariate and 6% when molecular relationship was used as a covariate. We concluded that imputation accuracy would be increased through optimization of reduced panel design and genotyping strategy. [ABSTRACT FROM AUTHOR]

Summary Feed cost for beef cattle is the largest expense incurred by cattle producers. The development of genetic markers to enhance selection of more efficient animals that require less feed while still achieving acceptable levels of production has the potential to substantially reduce production costs. A genome-wide marker association approach based on the Illumina BovineSNP50 BeadChip™ was used to identify genomic regions affecting average daily feed intake (ADFI), average daily gain (ADG) and residual feed intake traits in a population of 1159 crossbred steers. This approach identified a region on BTA14 from 22.02 to 23.92 Mb containing several single-nucleotide polymorphisms (SNPs) that have significant association with at least one of the traits. Two genes in this region, lysophospholipase 1 (LYPLA1) and transmembrane protein 68 ( TMEM68), appeared to be logical positional and functional candidate genes. LYPLA1 deacylates ghrelin, a hormone involved in the regulation of appetite in the rat stomach, while TMEM68 is expressed in bovine rumen, abomasum, intestine and adipose tissue in cattle, and likely affects lipid biosynthetic processes. SNPs lying in or near these two genes were identified by sequencing a subset of animals with extreme phenotypes. A total of 55 SNPs were genotyped and tested for association with the same population of steers. After correction for multiple testing, five markers within 22.79-22.84 Mb, located downstream of TMEM68, and between TMEM68 and the neighbouring gene XKR4, were significant for both ADFI and ADG. Genetic markers predictive of feed intake and weight gain phenotypes in this population of cattle may be useful for the identification and selection of animals that consume less feed, although further evaluation of these markers for effects on other production traits and validation in additional populations will be required. [ABSTRACT FROM AUTHOR]

Growth, feed intake, and temperament indicator data, collected over 5 yr on a total of 1,141 to 1,183 mixed-breed steers, were used to estimate genetic and phenotypic parameters. All steers had a portion of either Hereford or Angus or both plus varying percentages also of Simmental, Charolais, Limousin, Gelbvieh, Red Angus and MARC III composite. Because the steers were slaughtered on various dates each year and thus the animals varied in days on feed, weight and feed data were adjusted to a 140-d feeding period basis. Adjustment of measures of feed efficiency (gain:feed, G:F or residual feed intake, RFI, intake adjusted for metabolic body size and gain) for body fatness recorded at harvest had little effect on results of analyses. Average daily gain was less heritable (0.26) than mid-test body weight (MBW; 0.35). Measures of feed intake had greater estimates of heritability with 140-d dry matter intake (DMI) at 0.40 and RFI at 0.52; heritability estimate for G:F was 0.27. Flight speed (FS), as an indicator of temperament, had an estimated heritability of 0.34 and repeatability of 0.63. As expected, strong genetic (0.86) correlation was estimated between ADG and MBW; genetic correlations were less strong between DMI and ADG or MBW (0.56 and 0.71). Residual feed intake and DMI had a genetic correlation of 0.66. Indexes for phenotypic RFI and genotypically restricted RFI (no correlation with gain) were compared to simple economic indexes incorporating feed intake and growth to elucidate expected selection responses under different criteria. In general, few breed differences were detected across the various measurements. Heterosis contributed to greater DMI, RFI, and MBW, but it did not significantly affect ADG, G:F or FS. Balancing output (growth) with input costs (feed) is needed in practicing selection, and FS would not be recommended as an indicator trait for selection to change feed efficiency. An index including gain and RFI produced the best economic outcome. [ABSTRACT FROM AUTHOR]

A whole-genome scan was conducted on 328 F2 progeny in a Wagyu × Limousin cross to identify quantitative trait loci (QTL) affecting palatability and fatty acid composition of beef at an age-constant endpoint. We have identified seven QTL on five chromosomes involved in lipid metabolism and tenderness. None of the genes encoding major enzymes involved in fatty acid metabolism, such as fatty acid synthase ( FASN), acetyl-CoA carboxylase alpha ( ACACA), solute carrier family 2 (facilitated glucose transporter) member 4 ( SLC2A4), stearoyl-CoA desaturase ( SCD) and genes encoding the subunits of fatty acid elongase, was located in these QTL regions. The present study may lead to a better-tasting and healthier product for consumers through improved selection for palatability and lipid content of beef. [ABSTRACT FROM AUTHOR]

We report the identification and fine mapping of QTL for birth weight (BWT), preweaning ADG (PWADG), and postweaning ADG on feed (ADGF) in a commercial line of Bos taurus using an identical-by-descent haplotype sharing method. One hundred seventy-six calves of 12 bulls (9 to 30 male calves from each sire) of the Beefbooster, Inc., M1 line were typed using 71 genetic markers from bovine chromosomes (BTA) 2, 6, 14, 19, 21, and 23 (8 to 16 markers from each chromosome). Sixteen haplotypes were found to have significant (P < 0.05) associations with BWT at the comparison-wise threshold. The 16 haplotypes span 13 chromosomal regions, two on BTA 2 (9.1 to 22.5 cM and 95.0 to 100.3 cM), three on BTA 6 (8.2 to 11.8 cM, 35.5 to 49.7 cM, and 83.0 to 86.2 cM), three on BTA 14 (26.0 to 26.7 cM, 36.2 to 46.2 cM, and 52.0 to 67.7 cM), one on BTA 19 (52.0 to 52.7 cM), two on BTA 21 (9.9 to 20.4 cM and 28.2 to 46.1 cM), and two on BTA 23 (23.9 to 36.0 cM and 45.1 to 50.9 cM). Thirteen haplotypes spanning seven chromosomal regions significantly affected (P < 0.05) PWADG at the comparison-wise threshold. The seven chromosomal regions include two regions on BTA 6 (11.8 to 44.2 cM and 83.0 to 86.2 cM), one on BTA 14 (26.7 to 50.8 cM), one on BTA 19 (4.8 to 15.9 cM), one on BTA 21 (9.9 to 20.4 cM), and two on BTA 23 (17.3 to 36.0 cM and 45.1 to 50.9 cM). For ADGF, 11 haplotypes were identified to have significant associations (P < 0.05) at the comparison-wise threshold. The 11 haplotypes represented eight chromosomal regions, one on BTA 2 (9.1 to 22.5 cM), two on BTA 6 (49.7 to 50.1 cM and 59.6 to 63.6 cM), two on BTA 14 (17.0 to 24.0 cM and 36.2 to 46.2 cM), two on BTA 19 (52.0 to 52.7 cM and 65.1 to 65.7 cM), and one on BTA 21 (46.1 to 53.1 cM). The QTL regions identified and fine mapped in this study will provide a reference for future positional candidate gene research and marker-assisted selection of various growth traits. [ABSTRACT FROM AUTHOR]

Summary Feed cost for beef cattle is the largest expense incurred by cattle producers. The development of genetic markers to enhance selection of more efficient animals that require less feed while still achieving acceptable levels of production has the potential to substantially reduce production costs. A genome-wide marker association approach based on the Illumina BovineSNP50 BeadChip™ was used to identify genomic regions affecting average daily feed intake (ADFI), average daily gain (ADG) and residual feed intake traits in a population of 1159 crossbred steers. This approach identified a region on BTA14 from 22.02 to 23.92 Mb containing several single-nucleotide polymorphisms (SNPs) that have significant association with at least one of the traits. Two genes in this region, lysophospholipase 1 (LYPLA1) and transmembrane protein 68 ( TMEM68), appeared to be logical positional and functional candidate genes. LYPLA1 deacylates ghrelin, a hormone involved in the regulation of appetite in the rat stomach, while TMEM68 is expressed in bovine rumen, abomasum, intestine and adipose tissue in cattle, and likely affects lipid biosynthetic processes. SNPs lying in or near these two genes were identified by sequencing a subset of animals with extreme phenotypes. A total of 55 SNPs were genotyped and tested for association with the same population of steers. After correction for multiple testing, five markers within 22.79-22.84 Mb, located downstream of TMEM68, and between TMEM68 and the neighbouring gene XKR4, were significant for both ADFI and ADG. Genetic markers predictive of feed intake and weight gain phenotypes in this population of cattle may be useful for the identification and selection of animals that consume less feed, although further evaluation of these markers for effects on other production traits and validation in additional populations will be required. [ABSTRACT FROM AUTHOR]

The objective of this study was to search for quantitative trait loci (QTL) that segregate between Japanese Black and Limousin cattle breeds and affect relative amounts of saturated (SFA), mono-unsaturated (MUFA) and poly-unsaturated (PUFA) fatty acids. Six F1 Japanese Black-Limousin cross bulls were joined with 121 F1 females over a three-year period to produce 328 F2 progeny. Calves, aged from 450 to 641 d (average 561 d), were harvested using standard industry procedures. After aging, 2.54 cm thick steaks were cut from the posterior end of the wholesale rib, frozen at -20 °C, and held for determination of fatty acid composition. Percentages of the individual fatty acids were classified into percentages of SFA, MUFA and PUFA. Two hundred seventeen microsatellite markers covering the 29 bovine autosomes were assayed and QTL were identified by least squares regression. Genome-wise significant QTL with additive effects on SFA (-0.61 ± 0.19%), MUFA (0.93 ± 0.19%) and PUFA (-0.52 ± 0.11%) were observed near the centromere of BTA2. Also observed were five QTL indicative of dominance effects on: MUFA (BTA9, 119 cM, -1.87 ± 0.72%; BTA22, 47 cM, 1.85 ± 0.60%) and PUFA (BTA9, 54 cM, -1.49 ± 0.42%; BTA10, 38 cM, 1.20 ± 0.35%; and BTA15, 14 cM, 1.11 ± 0.36%). Based on these results, we conclude that it may be possible to improve the healthfulness of beef by manipulating fatty acid composition using genetic markers and appropriate crossbreeding systems. [ABSTRACT FROM AUTHOR]