Linkage disequilibrium among commonly genotyped SNP variants detected from bull sequence.

Genomic prediction utilizing causal variants could increase selection accuracy above that achieved with SNPs genotyped by currently available arrays used for genomic selection. A number of variants detected from sequencing influential sires are likely to be causal, but noticeable improvements in prediction accuracy using imputed sequence variant genotypes have not been reported. Improvement in accuracy of predicted breeding values may be limited by the accuracy of imputed sequence variants. Using genotypes of SNPs on a high-density array and non-synonymous SNPs detected in sequence from influential sires of a multibreed population, results of this examination suggest that linkage disequilibrium between non-synonymous and array SNPs may be insufficient for accurate imputation from the array to sequence. In contrast to 75% of array SNPs being strongly correlated to another SNP on the array, less than 25% of the non-synonymous SNPs were strongly correlated to an array SNP. When correlations between non-synonymous and array SNPs were strong, distances between the SNPs were greater than separation that might be expected based on linkage disequilibrium decay. Consistently near-perfect whole-genome linkage disequilibrium between the full array and each non-synonymous SNP within the sequenced bulls suggests that whole-genome approaches to infer sequence variants might be more accurate than imputation based on local haplotypes. Opportunity for strong linkage disequilibrium between sequence and array SNPs may be limited by discrepancies in allele frequency distributions, so investigating alternate genotyping approaches and panels providing greater chances of frequency-matched SNPs strongly correlated to sequence variants is also warranted. Genotypes used for this study are available from https://www.animalgenome.org/repository/pub/;USDA2017.0519/.

Genetic variance and covariance and breed differences for feed intake and average daily gain to improve feed efficiency in growing cattle.

Feed costs are a major economic expense in finishing and developing cattle; however, collection of feed intake data is costly. Examining relationships among measures of growth and intake, including breed differences, could facilitate selection for efficient cattle. Objectives of this study were to estimate genetic parameters for growth and intake traits and compare indices for feed efficiency to accelerate selection response. On-test ADFI and on-test ADG (TESTADG) and postweaning ADG (PWADG) records for 5,606 finishing steers and growing heifers were collected at the U.S. Meat Animal Research Center in Clay Center, NE. On-test ADFI and ADG data were recorded over testing periods that ranged from 62 to 148 d. Individual quadratic regressions were fitted for BW on time, and TESTADG was predicted from the resulting equations. We included PWADG in the model to improve estimates of growth and intake parameters; PWADG was derived by dividing gain from weaning weight to yearling weight by the number of days between the weights. Genetic parameters were estimated using multiple-trait REML animal models with TESTADG, ADFI, and PWADG for both sexes as dependent variables. Fixed contemporary groups were cohorts of calves simultaneously tested, and covariates included age on test, age of dam, direct and maternal heterosis, and breed composition. Genetic correlations (SE) between steer TESTADG and ADFI, PWADG and ADFI, and TESTADG and PWADG were 0.33 (0.10), 0.59 (0.06), and 0.50 (0.09), respectively, and corresponding estimates for heifers were 0.66 (0.073), 0.77 (0.05), and 0.88 (0.05), respectively. Indices combining EBV for ADFI with EBV for ADG were developed and evaluated. Greater improvement in feed efficiency can be expected using an unrestricted index versus a restricted index. Heterosis significantly affected each trait contributing to greater ADFI and TESTADG. Breed additive effects were estimated for ADFI, TESTADG, and the efficiency indices.

Ruminal expression of the NQO1, RGS5, and ACAT1 genes may be indicators of feed efficiency in beef steers.

Ruminal genes differentially expressed in crossbred beef steers from USMARC with variation in gain and feed intake were identified in a previous study. Several of the genes identified with expression patterns differing between animals with high gain-low feed intake and low gain-high feed intake were evaluated in a separate, unrelated population of Angus × Hereford beef steers from the University of Wyoming that was classified to differ in residual feed intake (RFI). Of the 17 genes tested, two were differentially expressed by RFI class in the Angus × Hereford animals. These genes included NAD(P)H dehydrogenase, quinone 1 (NQO1; P = 0.0009) and regulator of G-protein signaling 5 (RGS5; P = 0.01). A third gene, acetyl-CoA acetyltransferase 1 (ACAT1; P = 0.06), displayed a trend toward association with RFI. These data suggest that some of the genes identified in a previous rumen transcriptome discovery study may have utility for identifying or selecting for animals with superior feed efficiency phenotypes across cattle breeds and populations.

Genome-wide copy number variation in the bovine genome detected using low coverage sequence of popular beef breeds.

Copy number variations (CNVs) are large insertions, deletions or duplications in the genome that vary between members of a species and are known to affect a wide variety of phenotypic traits. In this study, we identified CNVs in a population of bulls using low coverage next-generation sequence data. First, in order to determine a suitable strategy for CNV detection in our data, we compared the performance of three distinct CNV detection algorithms on benchmark CNV datasets and concluded that using the multiple sample read depth approach was the best method for identifying CNVs in our sequences. Using this technique, we identified a total of 1341 copy number variable regions (CNVRs) from genome sequences of 154 purebred sires used in Cycle VII of the USMARC Germplasm Evaluation Project. These bulls represented the seven most popular beef breeds in the United States: Hereford, Charolais, Angus, Red Angus, Simmental, Gelbvieh and Limousin. The CNVRs covered 6.7% of the bovine genome and spanned 2465 protein-coding genes and many known quantitative trait loci (QTL). Genes harbored in the CNVRs were further analyzed to determine their function as well as to find any breed-specific differences that may shed light on breed differences in adaptation, health and production.

Breed effects and genetic parameter estimates for calving difficulty and birth weight in a multibreed population.

Birth weight (BWT) and calving difficulty (CD) were recorded on 4,579 first-parity females from the Germplasm Evaluation Program at the U.S. Meat Animal Research Center (USMARC). Both traits were analyzed using a bivariate animal model with direct and maternal effects. Calving difficulty was transformed from the USMARC scores to corresponding -scores from the standard normal distribution based on the incidence rate of the USMARC scores. Breed fraction covariates were included to estimate breed differences. Heritability estimates (SE) for BWT direct, CD direct, BWT maternal, and CD maternal were 0.34 (0.10), 0.29 (0.10), 0.15 (0.08), and 0.13 (0.08), respectively. Calving difficulty direct breed effects deviated from Angus ranged from -0.13 to 0.77 and maternal breed effects deviated from Angus ranged from -0.27 to 0.36. Hereford-, Angus-, Gelbvieh-, and Brangus-sired calves would be the least likely to require assistance at birth, whereas Chiangus-, Charolais-, and Limousin-sired calves would be the most likely to require assistance at birth. Maternal breed effects for CD were least for Simmental and Charolais and greatest for Red Angus and Chiangus. Results showed that the diverse biological types of cattle have different effects on both BWT and CD. Furthermore, results provide a mechanism whereby beef cattle producers can compare EBV for CD direct and maternal arising from disjoined and breed-specific genetic evaluations.

Genomewide association study of liver abscess in beef cattle.

Fourteen percent of U.S. cattle slaughtered in 2011 had liver abscesses, resulting in reduced carcass weight, quality, and value. Liver abscesses can result from a common bacterial cause, , which inhabits rumen lesions caused by acidosis and subsequently escapes into the blood stream, is filtered by the liver, and causes abscesses in the liver. Our aim was to identify SNP associated with liver abscesses in beef cattle. We used lung samples as a DNA source because they have low economic value, they have abundant DNA, and we had unrestricted access to sample them. We collected 2,304 lung samples from a beef processing plant: 1,152 from animals with liver abscess and 1,152 from animals without liver abscess. Lung tissue from pairs of animals, 1 with abscesses and another without, were collected from near one another on the viscera table to ensure that pairs of phenotypically extreme animals came from the same lot. Within each phenotype (abscess or no abscess), cattle were pooled by slaughter sequence into 12 pools of 96 cattle for each phenotype for a total of 24 pools. The pools were constructed by equal volume of frozen lung tissue from each animal. The DNA needed to allelotype each pool was then extracted from pooled lung tissue and the BovineHD Bead Array (777,962 SNP) was run on all 24 pools. Total intensity (TI), an indicator of copy number variants, was the sum of intensities from red and green dyes. Pooling allele frequency (PAF) was red dye intensity divided TI. Total intensity and PAF were weighted by the inverse of their respective genomic covariance matrices computed over all SNP across the genome. A false discovery rate ≤ 5% was achieved for 15 SNP for PAF and 20 SNP for TI. Genes within 50 kbp from significant SNP were in diverse pathways including maintenance of pH homeostasis in the gastrointestinal tract, maintain immune defenses in the liver, migration of leukocytes from the blood into infected tissues, transport of glutamine into the kidney in response to acidosis to facilitate production of bicarbonate to increase pH, aggregate platelets to liver injury to facilitate liver repair, and facilitate axon guidance. Evidence from the 35 detected SNP associations combined with evidence of polygenic variation indicate that there is adequate genetic variation in incidence rate of liver abscesses, which could be exploited to select sires for reduced susceptibility to subacute acidosis and associated liver abscess.

A survey of polymorphisms detected from sequences of popular beef breeds.

The genome sequence was obtained from 270 sires used in the Germplasm Evaluation (GPE) project. These bulls included 154 purebred AI sires from GPE Cycle VII breeds (Hereford, Angus, Simmental, Limousin, Charolais, Gelbvieh, and Red Angus), 83 F crosses of those breeds, and 33 AI sires from 8 other breeds. The exome capture sequence targeting coding regions of the genome was obtained from 176 of these bulls. Sequence reads were mapped to the UMD 3.1 bovine genome assembly; a mean of 2.5-fold (x) coverage per bull was obtained from the genomic sequence, and the targeted exons were covered at a mean of 20.0x. Over 28.8 million biallelic sequence variants were detected where each allele was present in at least 3 different bulls. These included 22.0 million previously reported variants and 94.1% of the 774,660 autosomal and BTA X SNP on the BovineHD BeadChip assay (HD). More than 92% of the variants detected in targeted exons were also detected from the low-coverage genome sequence. Less than 1% of the variants detected from the combined genome and exome sequence occurred in annotated protein-coding sequences and 5' and 3' untranslated regions (UTR) surrounding the 19,994 annotated protein coding regions. Variation was detected in the coding sequence or UTR of 96.8% of the genes: loss-of-function variants were predicted for 3,298 genes, 14,973 contained nonsynonymous variants, 11,276 had variation in UTR, and 17,721 genes contained synonymous variants. Minor allele frequencies (MAF) were <0.05 for 47.8% of the coding sequence and UTR variants, and MAF distributions were skewed toward low MAF. In contrast, 11.1% of the HD SNP detected in these bulls had MAF < 0.05, and the distribution was skewed toward higher MAF. Genes involved in immune system processes and immune response were overrepresented among those genes containing high MAF loss-of-function and nonsynonymous polymorphisms. Detected variants were submitted to the National Center for Biotechnology Information genetic variation database (dbSNP) under the handle MARC, batch GPE_Bull_GenEx.

Differences in transcript abundance of genes on BTA15 located within a region associated with gain in beef steers.

Using results from a previous GWAS, we chose to evaluate seven genes located within a 229Kb region on BTA15 for variation in RNA transcript abundance in a library of tissue samples that included adipose, liver, rumen papillae, spleen, muscle, and small intestine epithelial layers from the duodenum, ileum and jejunum collected from steers (n = 14) with positive and negative residual GN near mean dry matter intake (DMI). The genes evaluated were two olfactory receptor-like genes (LOC525033 and LOC618173), RRM1, STIM1, RHOG, PGAP2, and NUP98. The rumen papillae transcript abundance of RHOG was positively correlated with residual GN (P = 0.02) and ruminal STIM1 exhibited a trend towards an association with residual GN (P = 0.08). The transcript abundance of one olfactory receptor (LOC618173) in the ileum was also positively associated with residual GN (P = 0.02) and PGAP2 and LOC525033 in the ileum displayed trends for association with GN (P ≤ 0.1). To further evaluate the differential expression detected in the ileum and rumen of these animals, the transcript abundance of STIM1 and RHOG in the rumen and of PGAP2 and the olfactory receptors in the ileum were assessed in an additional group of 32 animals with divergent average daily gain (ADG) and average daily feed intake (ADFI) collected over two groups. The olfactory receptor, LOC525033, was not expressed in the ileum for the majority of these animals. Only RHOG showed a slight, but non-significant trend towards greater expression in animals with greater gain. We have detected differences in the transcript abundance of genes within this region in the rumen and ileum of animals selected for greater and less residual gain; however, we were unable to validate the expression of these genes in the larger group of cattle possibly due to the differences in phenotype or contemporary group.

Evaluation of single nucleotide polymorphisms in chromosomal regions impacting pregnancy status in cattle.

Reproductive success is an important component of commercial beef cattle production, and identification of DNA markers with predictive merit for reproductive success would facilitate accurate prediction of mean daughter pregnancy rate, enabling effective selection of bulls to improve female fertility. A previous study identified SNP associated with beef cattle reproductive efficiency based on a genomewide association analysis approach using genotyping multiple-animal pools of DNA to increase the number of animals that could be genotyped with available resources. For the current study, we expand on this previous study by individually genotyping cattle from the pooling study for 89 SNP that were associated with female pregnancy rate. The aims of the study were to confirm the results of the pooling study and, more specifically, identify modes of gene action and DNA variations such as haplotypes that would not be possible with pooled genotyping. Eighty-nine SNP selected from the pooling study were evaluated using the Sequenom MassARRAY system to individually genotype animals from populations evaluated in the pooling study, including both and breeds. From this research, regions on chromosomes 5 (26.3-48.1 Mb; UMD3.1 assembly) and 9 (37,436,575 bp; UMD3.1 assembly), first identified in the previous pooling study, were shown through individual genotyping to harbor genetic variation ( < 0.05 genomewide significance) affecting reproductive efficiency in interspecific crosses ( and ) of cattle. Each of these markers exhibited additive (vs. dominant) gene action. Additionally, a haplotype block harboring an allele of origin with negative effects on reproduction was identified on chromosome 5 in interspecific composite breeds of × composites.

Genetic markers that influence feed efficiency phenotypes also affect cattle temperament as measured by flight speed.

Flight speed is a predictive indicator of cattle temperament and is associated with feed efficiency phenotypes. Genetic markers associated with both traits may assist with selection of calmer animals with improved economic value. A preliminary genome-wide association study determined chromosomal regions on BTA9, and 17 were associated with flight speed. The genes quaking (QKI), glutamate receptor, ionotropic, AMPA 2 (GRIA2) and glycine receptor ß (GLRB) were identified in these regions as potential functional candidates. Beef steers (n = 1057) were genotyped with SNPs located within and flanking these genes. One SNP located near QKI and one near GRIA2 were nominally associated with flight speed (P ≤ 0.05) although neither was significant after Bonferroni correction. Several studies have shown a correlation between flight speed and feed intake or gain; therefore, we also analyzed SNPs on BTA6:38-39 Mb known to be associated with average daily gain (ADG) and average daily feed intake (ADFI) for association with flight speed. Several SNPs on BTA6 were associated with flight speed (P ≤ 0.005), and three were significant after Bonferroni correction. These results suggest that the genes tested are unlikely to contribute to flight speed variation for our cattle population, but SNPs on BTA6 associated with ADG and ADFI may influence temperament. Use of these markers to select for economically important feed efficiency phenotypes may produce cattle with more desirable temperaments.

Genomewide association study of reproductive efficiency in female cattle.

Reproductive efficiency is of economic importance in commercial beef cattle production, as failure to achieve pregnancy reduces the number of calves marketed per cow exposed. Identification of genetic markers with predictive merit for reproductive success would facilitate early selection of sires with daughters having improved reproductive rate without increasing generation intervals. To identify regions of the genome harboring variation affecting reproductive success, we applied a genomewide association study (GWAS) approach based on the >700,000 SNP marker assay, using a procedure based on genotyping multianimal pools of DNA to increase the number of animals that could be genotyped with available resources. Cows from several populations were classified according to reproductive efficiency, and DNA was pooled within population and phenotype prior to genotyping. Populations evaluated included a research population at the U.S. Meat Animal Research Center, 2 large commercial ranch populations, and a number of smaller populations (<100 head) across the United States. We detected 2 SNP with significant genomewide association (P ≤ 1.49 × 10(-7)), on BTA21 and BTA29, 3 SNP with suggestive associations (P ≤ 2.91 × 10(-6)) on BTA5, and 1 SNP with suggestive association each on BTA1 and BTA25. In addition to our novel findings, we confirmed previously published associations for SNP on BTA-X and all autosomes except 3 (BTA21, BTA22, and BTA28) encompassing substantial breed diversity including Bos indicus and Bos taurus breeds. The study identified regions of the genome associated with reproductive efficiency, which are being targeted for further analysis to develop robust marker systems, and demonstrated that DNA pooling can be used to substantially reduce the cost of GWAS in cattle.

Genome-wide association of meat quality traits and tenderness in swine.

Pork quality has a large impact on consumer preference and perception of eating quality. A genome-wide association was performed for pork quality traits [intramuscular fat (IMF)], slice shear force (SSF), color attributes, purge, cooking loss, and pH] from 531 to 1,237 records on barrows and gilts of a Landrace-Duroc-Yorkshire population using the Illumina PorcineSNP60 BeadChip. Associations were detected using MTDFREML for all traits. Intramuscular fat had the greatest number of SNP associations, followed by pH, purge, cooking loss, shear force, and color. Two regions contained associations for multiple traits; one on SSC1 at 255 Mb near calcineurin subunit B (PPP3R2) was associated with SSF, moisture loss, and pH, and one on SSC6 from 28 to 29.5 Mb for purge and IMF containing the candidate genes glucose-6-phosphate isomerase (GPI) and KCTD15. Some of the other compelling candidate genes in regions associated with meat quality include CEBPA, SNAI1, and FAM132A for IMF, CAPN1 for SSF, GLUL for pH, and PRKAG3 and ITGB1 with cooking loss.

Breeding and Genetics Symposium: networks and pathways to guide genomic selection.

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.

Effects of reduced panel, reference origin, and genetic relationship on imputation of genotypes in Hereford cattle.

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 (L1, 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 L1 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 L1 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.

The accuracies of DNA-based estimates of genetic merit derived from Angus or multibreed beef cattle training populations.

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 (2K(ALL)), and 2 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 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 2K(ALL), 0.24 ± 0.04 for 2K(AN), and 0.02 ± 0.12 for 2K(HH). 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.

Accuracy of genomic breeding values in multibreed beef cattle populations derived from deregressed breeding values and phenotypes.

Genomic selection involves the assessment of genetic merit through prediction equations that allocate genetic variation with dense marker genotypes. It has the potential to provide accurate breeding values for selection candidates at an early age and facilitate selection for expensive or difficult to measure traits. Accurate across-breed prediction would allow genomic selection to be applied on a larger scale in the beef industry, but the limited availability of large populations for the development of prediction equations has delayed researchers from providing genomic predictions that are accurate across multiple beef breeds. In this study, the accuracy of genomic predictions for 6 growth and carcass traits were derived and evaluated using 2 multibreed beef cattle populations: 3,358 crossbred cattle of the U.S. Meat Animal Research Center Germplasm Evaluation Program (USMARC_GPE) and 1,834 high accuracy bull sires of the 2,000 Bull Project (2000_BULL) representing influential breeds in the U.S. beef cattle industry. The 2000_BULL EPD were deregressed, scaled, and weighted to adjust for between- and within-breed heterogeneous variance before use in training and validation. Molecular breeding values (MBV) trained in each multibreed population and in Angus and Hereford purebred sires of 2000_BULL were derived using the GenSel BayesCπ function (Fernando and Garrick, 2009) and cross-validated. Less than 10% of large effect loci were shared between prediction equations trained on (USMARC_GPE) relative to 2000_BULL although locus effects were moderately to highly correlated for most traits and the traits themselves were highly correlated between populations. Prediction of MBV accuracy was low and variable between populations. For growth traits, MBV accounted for up to 18% of genetic variation in a pooled, multibreed analysis and up to 28% in single breeds. For carcass traits, MBV explained up to 8% of genetic variation in a pooled, multibreed analysis and up to 42% in single breeds. Prediction equations trained in multibreed populations were more accurate for Angus and Hereford subpopulations because those were the breeds most highly represented in the training populations. Accuracies were less for prediction equations trained in a single breed due to the smaller number of records derived from a single breed in the training populations.

Gene network analyses of first service conception in Brangus heifers: use of genome and trait associations, hypothalamic-transcriptome information, and transcription factors.

Measures of heifer fertility are economically relevant traits for beef production systems and knowledge of candidate genes could be incorporated into future genomic selection strategies. Ten traits related to growth and fertility were measured in 890 Brangus heifers (3/8 Brahman × 5/8 Angus, from 67 sires). These traits were: BW and hip height adjusted to 205 and 365 d of age, postweaning ADG, yearling assessment of carcass traits (i.e., back fat thickness, intramuscular fat, and LM area), as well as heifer pregnancy and first service conception (FSC). These fertility traits were collected from controlled breeding seasons initiated with estrous synchronization and AI targeting heifers to calve by 24 mo of age. The BovineSNP50 BeadChip was used to ascertain 53,692 SNP genotypes for ∼802 heifers. Associations of genotypes and phenotypes were performed and SNP effects were estimated for each trait. Minimally associated SNP (P < 0.05) and their effects across the 10 traits formed the basis for an association weight matrix and its derived gene network related to FSC (57.3% success and heritability = 0.06 ± 0.05). These analyses yielded 1,555 important SNP, which inferred genes linked by 113,873 correlations within a network. Specifically, 1,386 SNP were nodes and the 5,132 strongest correlations (|r| ≥ 0.90) were edges. The network was filtered with genes queried from a transcriptome resource created from deep sequencing of RNA (i.e., RNA-Seq) from the hypothalamus of a prepubertal and a postpubertal Brangus heifer. The remaining hypothalamic-influenced network contained 978 genes connected by 2,560 edges or predicted gene interactions. This hypothalamic gene network was enriched with genes involved in axon guidance, which is a pathway known to influence pulsatile release of LHRH. There were 5 transcription factors with 21 or more connections: ZMAT3, STAT6, RFX4, PLAGL1, and NR6A1 for FSC. The SNP that identified these genes were intragenic and were on chromosomes 1, 5, 9, and 11. Chromosome 5 harbored both STAT6 and RFX4. The large number of interactions and genes observed with network analyses of multiple sources of genomic data (i.e., GWAS and RNA-Seq) support the concept of FSC being a polygenic trait.

Genome-wide association study of swine farrowing traits. Part II: Bayesian analysis of marker data.

Reproductive efficiency has a great impact on the economic success of pork (sus scrofa) production. Number born alive (NBA) and average piglet birth weight (ABW) contribute greatly to reproductive efficiency. To better understand the underlying genetics of birth traits, a genome-wide association study (GWAS) was undertaken. Samples of DNA were collected and tested using the Illumina PorcineSNP60 BeadChip from 1,152 first parity gilts. Traits included total number born (TNB), NBA, number born dead (NBD), number stillborn (NSB), number of mummies (MUM), total litter birth weight (LBW), and ABW. A total of 41,151 SNP were tested using a Bayesian approach. Beginning with the first 5 SNP on SSC1 and ending with the last 5 SNP on the SSCX, SNP were assigned to groups of 5 consecutive SNP by chromosome-position order and analyzed again using a Bayesian approach. From that analysis, 5-SNP groups were selected having no overlap with another 5-SNP groups and no overlap across chromosomes. These selected 5-SNP non-overlapping groups were defined as QTL. Of the available 8,814 QTL, 124 were found to be statistically significant (P < 0.01). Multiple testing was considered using the probability of false positives. Eleven QTL were found for TNB, 3 on SSC1, 3 on SSC4, 1 on SSC13, 1 on SSC14, 2 on SSC15, and 1 on SSC17. Statistical testing for NBA identified 14 QTL, 4 on SSC1, 1 on SSC4, 1 on SSC6, 1 on SSC10, 1on SSC13, 3 on SSC15, and 3 on SSC17. A single NBD QTL was found on SSC11. No QTL were identified for NSB or MUM. Thirty-three QTL were found for LBW, 3 on SSC1, 1 on SSC2, 1 on SSC3, 5 on SSC4, 2 on SSC5, 5 on SSC6, 3 on SSC7, 2 on SSC9, 1 on SSC10, 2 on SSC14, 6 on SSC15, and 2 on SSC17. A total of 65 QTL were found for ABW, 9 on SSC1, 3 on SSC2, 9 on SSC5, 5 on SSC6, 1 on SSC7, 2 on SSC8, 2 on SSC9, 3 on SSC10, 1 on SSC11, 3 on SSC12, 2 on SSC13, 8 on SSC14, 8 on SSC15, 1 on SSC17, and 8 on SSC18. Several candidate genes have been identified that overlap QTL locations among TNB, NBA, NBD, and ABW. These QTL when combined with information on genes found in the same regions should provide useful information that could be used for marker assisted selection, marker assisted management, or genomic selection applications in commercial pig populations.

Genetic markers on BTA14 predictive for residual feed intake in beef steers and their effects on carcass and meat quality traits.

With the high cost of feed for animal production, genetic selection for animals that metabolize feed more efficiently could result in substantial cost savings for cattle producers. The purpose of this study was to identify DNA markers predictive for differences among cattle for traits associated with feed efficiency. Crossbred steers were fed a high-corn diet for 140 days and average daily feed intake (ADFI), average daily gain (ADG), and residual feed intake (RFI) phenotypes were obtained. A region on chromosome 14 was previously associated with RFI in this population of animals. To develop markers with the highest utility for predicting an animal's genetic potential for RFI, we genotyped additional markers within this chromosomal region. These polymorphisms were genotyped on the same animals (n = 1066) and tested for association with ADFI, ADG and RFI. Six markers within this region were associated with RFI (P ≤ 0.05). After conservative correction for multiple testing, one marker at 25.09 Mb remained significant (P = 0.02) and is responsible for 3.6% of the RFI phenotypic variation in this population of animals. Several of these markers were also significant for ADG, although none were significant after correction. Marker alleles with positive effects on ADG corresponded to lower RFI, suggesting an effect increasing growth without increasing feed intake. All markers were also assessed for their effects on meat quality and carcass traits. All of the markers associated with RFI were associated with adjusted fat thickness (AFT, P ≤ 0.009) and three were also associated with hot carcass weight (HCW, P ≤ 0.003). Marker alleles associated with lower RFI were also associated with reduced AFT, and if they were associated for HCW, the effect was an increase in weight. These markers may be useful as prediction tools for animals that utilize feed more efficiently; however, validation with additional populations of cattle is required.

A region on BTA14 that includes the positional candidate genes LYPLA1, XKR4 and TMEM68 is associated with feed intake and growth phenotypes in cattle(1).

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.