T. G. McDaneld

Genome-wide association study of growth in crossbred beef cattle

Chromosomal regions harboring variation affecting cattle birth weight and BW gain to 1 yr of age were identified by marker association using the highly parallel BovineSNP50 BeadChip (50K) assay composed of 54,001 individual SNP. Genotypes were obtained from progeny (F(1); 590 steers) and 2-, 3-, and 4-breed cross grandprogeny (F(1)(2) = F(1) x F(1); 1,306 steers and 707 females) of 150 AI sires representing 7 breeds (22 sires per breed; Angus, Charolais, Gelbvieh, Hereford, Limousin, Red Angus, and Simmental). Genotypes and birth, weaning, and yearling BW records were used in whole-genome association analyses to estimate effects of individual SNP on growth. Traits analyzed included growth component traits: birth weight (BWT), 205-d adjusted birth to weaning BW gain (WG), 160-d adjusted postweaning BW gain (PWG); cumulative traits: 205-d adjusted weaning weight (WW = BWT + WG) and 365-d adjusted yearling weight (YW = BWT + WG + PWG); and indexes of relative differences between postnatal growth and birth weight. Modeled fixed effects included additive effects of calf and dam SNP genotype, year-sex-management contemporary groups, and covariates for calf and dam breed composition and heterosis. Direct and maternal additive polygenic effects and maternal permanent environment effects were random. Missing genotypes, including 50K genotypes of most dams, were approximated with a single-locus BLUP procedure from pedigree relationships and known 50K genotypes. Various association criteria were applied: stringent tests to account for multiple testing but with limited power to detect associations with small effects, and relaxed nominal P that may detect SNP associated with small effects but include excessive false positive associations. Genomic locations of the 231 SNP meeting stringent criteria generally coincided with described previously QTL affecting growth traits. The 12,425 SNP satisfying relaxed tests were located throughout the genome. Most SNP associated with BWT and postnatal growth affected components in the same direction, although detection of SNP associated with one component independent of others presents a possible opportunity for SNP-assisted selection to increase postnatal growth relative to BWT.

MicroRNA transcriptome profiles during swine skeletal muscle development

BackgroundMicroRNA (miR) are a class of small RNAs that regulate gene expression by inhibiting translation of protein encoding transcripts. To evaluate the role of miR in skeletal muscle of swine, global microRNA abundance was measured at specific developmental stages including proliferating satellite cells, three stages of fetal growth, day-old neonate, and the adult.ResultsTwelve potential novel miR were detected that did not match previously reported sequences. In addition, a number of miR previously reported to be expressed in mammalian muscle were detected, having a variety of abundance patterns through muscle development. Muscle-specific miR-206 was nearly absent in proliferating satellite cells in culture, but was the highest abundant miR at other time points evaluated. In addition, miR-1 was moderately abundant throughout developmental stages with highest abundance in the adult. In contrast, miR-133 was moderately abundant in adult muscle and either not detectable or lowly abundant throughout fetal and neonate development. Changes in abundance of ubiquitously expressed miR were also observed. MiR-432 abundance was highest at the earliest stage of fetal development tested (60 day-old fetus) and decreased throughout development to the adult. Conversely, miR-24 and miR-27 exhibited greatest abundance in proliferating satellite cells and the adult, while abundance of miR-368, miR-376, and miR-423-5p was greatest in the neonate.ConclusionThese data present a complete set of transcriptome profiles to evaluate miR abundance at specific stages of skeletal muscle growth in swine. Identification of these miR provides an initial group of miR that may play a vital role in muscle development and growth.

MicroRNA expression profile in bovine cumulus-oocyte complexes: Possible role of let-7 and miR-106a in the development of bovine oocytes

The objectives of this study included: (1) identify the expression of miRNAs specific to bovine cumulus-oocyte complexes (COCs) during late oogenesis, (2) characterize the expression of candidate miRNAs as well as some miRNA processing genes, and (3) computationally identify and characterize the expression of target mRNAs for candidate miRNAs. Small RNAs in the 16-27 bp range were isolated from pooled COCs aspirated from 1- to 10-mm follicles of beef cattle ovaries and used to construct a cDNA library. A total 1798 putative miRNA sequences from the cDNA library of small RNA were compared to known miRNAs. Sixty-four miRNA clusters matched previously reported sequences in the miRBase database and 5 miRNA clusters had not been reported. TaqMan miRNA assays were used to confirm the expression of let-7b, let-7i, and miR-106a from independent collections of COCs. Real-time PCR assays were used to characterize expression of miRNA processing genes and target mRNAs (MYC and WEE1A) for the candidate miRNAs from independent collections of COCs. Expression data were analyzed using general linear model procedures for analysis of variance. The expression of let-7b and let-7i were not different between the cellular populations from various sized follicles. However, miR-106a expression was greater (P<0.01) in oocytes compared with COCs and granulosa cells. Furthermore, all the miRNA processing genes have greater expression (P<0.001) in oocytes compared with COCs and granulosa cells. The expression of potential target mRNAs for let-7 and let-7i (i.e., MYC), and miR-106a (i.e., WEE1A) were decreased (P<0.05) in oocytes compared with COCs and granulosa cells. These results demonstrate specific miRNAs within bovine COCs during late oogenesis and provide some evidence that miRNAs may play a role regulating maternal mRNAs in bovine oocytes.

A deletion mutation in bovine SLC4A2 is associated with osteopetrosis in Red Angus cattle

BackgroundOsteopetrosis is a skeletal disorder of humans and animals characterized by the formation of overly dense bones, resulting from a deficiency in the number and/or function of bone-resorbing osteoclast cells. In cattle, osteopetrosis can either be induced during gestation by viral infection of the dam, or inherited as a recessive defect. Genetically affected calves are typically aborted late in gestation, display skull deformities and exhibit a marked reduction of osteoclasts. Although mutations in several genes are associated with osteopetrosis in humans and mice, the genetic basis of the cattle disorder was previously unknown.ResultsWe have conducted a whole-genome association analysis to identify the mutation responsible for inherited osteopetrosis in Red Angus cattle. Analysis of >54,000 SNP genotypes for each of seven affected calves and nine control animals localized the defective gene to the telomeric end of bovine chromosome 4 (BTA4). Homozygosity analysis refined the interval to a 3.4-Mb region containing the SLC4A2 gene, encoding an anion exchanger protein necessary for proper osteoclast function. Examination of SLC4A2 from normal and affected animals revealed a ~2.8-kb deletion mutation in affected calves that encompasses exon 2 and nearly half of exon 3, predicted to prevent normal protein function. Analysis of RNA from a proven heterozygous individual confirmed the presence of transcripts lacking exons 2 and 3, in addition to normal transcripts. Genotyping of additional animals demonstrated complete concordance of the homozygous deletion genotype with the osteopetrosis phenotype. Histological examination of affected tissues revealed scarce, morphologically abnormal osteoclasts displaying evidence of apoptosis.ConclusionsThese results indicate that a deletion mutation within bovine SLC4A2 is associated with osteopetrosis in Red Angus cattle. Loss of SLC4A2 function appears to induce premature cell death, and likely results in cytoplasmic alkalinization of osteoclasts which, in turn, may disrupt acidification of resorption lacunae.

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.

Predicting breed composition using breed frequencies of 50,000 markers from the US Meat Animal Research Center 2,000 Bull Project

Knowledge of breed composition can be useful in multiple aspects of cattle production, and can be critical for analyzing the results of whole genome-wide association studies currently being conducted around the world. We examine the feasibility and accuracy of using genotype data from the most prevalent bovine genome-wide association studies platform, the Illumina BovineSNP50 array (Illumina Inc., San Diego, CA), to estimate breed composition for individual breeds of cattle. First, allele frequencies (of Illumina-defined allele B) of SNP on the array for each of 16 beef cattle breeds were defined by genotyping a large set of more than 2,000 bulls selected in cooperation with the respective breed associations to be representative of their breed. With these breed-specific allele frequencies, the breed compositions of approximately 2,000 two-, three-, and four-way cross (of 8 breeds) cattle produced at the US Meat Animal Research Center were predicted by using a simple multiple regression technique or Mendel (http://www.genetics.ucla.edu/software/mendel) and their genotypes from the Illumina BovineSNP50 array, and were then compared with pedigree-based estimates of breed composition. The accuracy of marker-based breed composition estimates was 89% when using either estimation method for all breeds except Angus and Red Angus (averaged 79%), based on comparing estimates with pedigree-based average breed composition. Accuracy increased to approximately 88% when these 2 breeds were combined into an aggregate Angus group. Additionally, we used a subset of these markers, approximately 3,000 that populate the Illumina Bovine3K (Illumina Inc.), to see whether breed composition could be estimated with similar accuracy when using this reduced panel of SNP makers. When breed composition was estimated using only SNP in common with the Bovine 3K array, accuracy was slightly reduced to 83%. These results suggest that SNP data from these arrays could be used to estimate breed composition in most US beef cattle in situations where pedigree is not known (e.g., multiple-sire natural service matings, non-source-verified animals in feedlots or at slaughter). This approach can aid analyses that depend on knowledge of breed composition, including identification and adjustment of breed-based population stratification, when performing genome-wide association studies on populations with incomplete pedigrees. In addition, SNP-based breed composition estimates may facilitate fitting cow germplasm to the environment, managing cattle in the feedlot, and tracing disease cases back to the geographic region or farm of origin.

Physiology and Endocrinology Symposium: How single nucleotide polymorphism chips will advance our knowledge of factors controlling puberty and aid in selecting replacement beef females.

The promise of genomic selection is accurate prediction of the genetic potential of animals from their genotypes. Simple DNA tests might replace low-accuracy predictions for expensive or lowly heritable measures of puberty and fertility based on performance and pedigree. Knowing with some certainty which DNA variants (e.g., SNP) affect puberty and fertility is the best way to fulfill the promise. Several SNP from the BovineSNP50 assay have tentatively been associated with reproductive traits including age at puberty, antral follicle count, and pregnancy observed on different sets of heifers. However, sample sizes are too small and SNP density is too sparse to definitively determine genomic regions harboring causal variants affecting reproductive success. Additionally, associations between individual SNP and similar phenotypes are inconsistent across data sets, and genomic predictions do not appear to be globally applicable to cattle of different breeds. Discrepancies may be a result of different QTL segregating in the sampled populations, differences in linkage disequilibrium (LD) patterns such that the same SNP are not correlated with the same QTL, and spurious correlations with phenotype. Several approaches can be used independently or in combination to improve detection of genomic factors affecting heifer puberty and fertility. Larger samples and denser SNP will increase power to detect real associations with SNP having more consistent LD with underlying QTL. Meta-analysis combining results from different studies can also be used to effectively increase sample size. High-density genotyping with heifers pooled by pregnancy status or early and late puberty can be a cost-effective means to sample large numbers. Networks of genes, implicated by associations with multiple traits correlated with puberty and fertility, could provide insight into the complex nature of these traits, especially if corroborated by functional annotation, established gene interaction pathways, and transcript expression. Example analyses are provided to demonstrate how integrating information about gene function and regulation with statistical associations from whole-genome SNP genotyping assays might enhance knowledge of genomic mechanisms affecting puberty and fertility, enabling reliable DNA tests to guide heifer selection decisions.

Y are you not pregnant: Identification of Y chromosome segments in female cattle with decreased reproductive efficiency

Reproductive efficiency is of economic importance in commercial beef cattle production, since failure to achieve pregnancy reduces the number of calves marketed. Identification of genetic markers with predictive merit for reproductive success would facilitate early selection of females and avoid inefficiencies associated with sub-fertile cows. To identify regions of the genome harboring variation affecting reproductive success, we applied a genome-wide association approach based on the >700,000 SNP marker assay. To include the largest number of individuals possible under the available budget, cows from several populations were assigned to extremes for reproductive efficiency, and DNA was pooled within population and phenotype before genotyping. Surprisingly, pools prepared from DNA of low reproductive cattle returned fluorescence intensity data intermediate between fertile females and males for SNP mapped to the Y chromosome (i.e., male sex chromosome). The presence of Y-associated material in low reproductive heifers or cows was confirmed by Y-directed PCR, which revealed that 21 to 29% of females in the low reproductive category were positive by a Y chromosome PCR test normally used to sex embryos. The presence of the Y chromosome anomaly was further confirmed with application of additional Y-specific PCR amplicons, indicating the likelihood of the presence of some portion of male sex chromosome in female cattle in various beef cattle herds across the U.S. Discovery of this Y anomaly in low reproductive females may make an important contribution to management of reproductive failures in beef cattle operations.

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.

Gene number determination and genetic polymorphism of the gamma delta T cell co-receptor WC1 genes.

BackgroundWC1 co-receptors belong to the scavenger receptor cysteine-rich (SRCR) superfamily and are encoded by a multi-gene family. Expression of particular WC1 genes defines functional subpopulations of WC1+ γδ T cells. We have previously identified partial or complete genomic sequences for thirteen different WC1 genes through annotation of the bovine genome Btau_3.1 build. We also identified two WC1 cDNA sequences from other cattle that did not correspond to sequences in the Btau_3.1 build. Their absence in the Btau_3.1 build may have reflected gaps in the genome assembly or polymorphisms among animals. Since the response of γδ T cells to bacterial challenge is determined by WC1 gene expression, it was critical to understand whether individual cattle or breeds differ in the number of WC1 genes or display polymorphisms.ResultsReal-time quantitative PCR using DNA from the animal whose genome was sequenced (“Dominette”) and sixteen other animals representing ten breeds of cattle, showed that the number of genes coding for WC1 co-receptors is thirteen. The complete coding sequences of those thirteen WC1 genes is presented, including the correction of an error in the WC1-2 gene due to mis-assembly in the Btau_3.1 build. All other cDNA sequences were found to agree with the previous annotation of complete or partial WC1 genes. PCR amplification and sequencing of the most variable N-terminal SRCR domain (domain 1 which has the SRCR “a” pattern) of each of the thirteen WC1 genes showed that the sequences are highly conserved among individuals and breeds. Of 160 sequences of domain 1 from three breeds of cattle, no additional sequences beyond the thirteen described WC1 genes were found. Analysis of the complete WC1 cDNA sequences indicated that the thirteen WC1 genes code for three distinct WC1 molecular forms.ConclusionThe bovine WC1 multi-gene family is composed of thirteen genes coding for three structural forms whose sequences are highly conserved among individual cattle and breeds. The sequence diversity necessary for WC1 genes to function as a multi-genic pattern recognition receptor array is encoded in the genome, rather than generated by recombinatorial diversity or hypermutation.