Using diverse U.S. beef cattle genomes to identify missense mutations in EPAS1, a gene associated with pulmonary hypertension.

The availability of whole genome sequence (WGS) data has made it possible to discover protein variants in silico. However, existing bovine WGS databases do not show data in a form conducive to protein variant analysis, and tend to under represent the breadth of genetic diversity in global beef cattle. Thus, our first aim was to use 96 beef sires, sharing minimal pedigree relationships, to create a searchable and publicly viewable set of mapped genomes relevant for 19 popular breeds of U.S. cattle. Our second aim was to identify protein variants encoded by the bovine endothelial PAS domain-containing protein 1 gene ( EPAS1), a gene associated with pulmonary hypertension in Angus cattle. The identity and quality of genomic sequences were verified by comparing WGS genotypes to those derived from other methods. The average read depth, genotype scoring rate, and genotype accuracy exceeded 14, 99%, and 99%, respectively. The 96 genomes were used to discover four amino acid variants encoded by EPAS1 (E270Q, P362L, A671G, and L701F) and confirm two variants previously associated with disease (A606T and G610S). The six EPAS1 missense mutations were verified with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry assays, and their frequencies were estimated in a separate collection of 1154 U.S. cattle representing 46 breeds. A rooted phylogenetic tree of eight polypeptide sequences provided a framework for evaluating the likely order of mutations and potential impact of EPAS1 alleles on the adaptive response to chronic hypoxia in U.S. cattle. This public, whole genome resource facilitates in silico identification of protein variants in diverse types of U.S. beef cattle, and provides a means of translating WGS data into a practical biological and evolutionary context for generating and testing hypotheses.

Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications.

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced) or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus population. The utility of this MOLO algorithm was also demonstrated in a real application, in which a 6K SNP panel was optimized conditional on 5,260 obligatory SNP selected based on SNP-trait association in U.S. Holstein animals. With this MOLO algorithm, both imputation error rate and genomic prediction error rate were minimal.

SNPchiMp v.3: integrating and standardizing single nucleotide polymorphism data for livestock species.

BACKGROUND: In recent years, the use of genomic information in livestock species for genetic improvement, association studies and many other fields has become routine. In order to accommodate different market requirements in terms of genotyping cost, manufacturers of single nucleotide polymorphism (SNP) arrays, private companies and international consortia have developed a large number of arrays with different content and different SNP density. The number of currently available SNP arrays differs among species: ranging from one for goats to more than ten for cattle, and the number of arrays available is increasing rapidly. However, there is limited or no effort to standardize and integrate array- specific (e.g. SNP IDs, allele coding) and species-specific (i.e. past and current assemblies) SNP information. RESULTS: Here we present SNPchiMp v.3, a solution to these issues for the six major livestock species (cow, pig, horse, sheep, goat and chicken). Original data was collected directly from SNP array producers and specific international genome consortia, and stored in a MySQL database. The database was then linked to an open-access web tool and to public databases. SNPchiMp v.3 ensures fast access to the database (retrieving within/across SNP array data) and the possibility of annotating SNP array data in a user-friendly fashion. CONCLUSIONS: This platform allows easy integration and standardization, and it is aimed at both industry and research. It also enables users to easily link the information available from the array producer with data in public databases, without the need of additional bioinformatics tools or pipelines. In recognition of the open-access use of Ensembl resources, SNPchiMp v.3 was officially credited as an Ensembl E!mpowered tool. Availability at http://bioinformatics.tecnoparco.org/SNPchimp.

SNPs for parentage testing and traceability in globally diverse breeds of sheep.

DNA-based parentage determination accelerates genetic improvement in sheep by increasing pedigree accuracy. Single nucleotide polymorphism (SNP) markers can be used for determining parentage and to provide unique molecular identifiers for tracing sheep products to their source. However, the utility of a particular "parentage SNP" varies by breed depending on its minor allele frequency (MAF) and its sequence context. Our aims were to identify parentage SNPs with exceptional qualities for use in globally diverse breeds and to develop a subset for use in North American sheep. Starting with genotypes from 2,915 sheep and 74 breed groups provided by the International Sheep Genomics Consortium (ISGC), we analyzed 47,693 autosomal SNPs by multiple criteria and selected 163 with desirable properties for parentage testing. On average, each of the 163 SNPs was highly informative (MAF≥0.3) in 48±5 breed groups. Nearby polymorphisms that could otherwise confound genetic testing were identified by whole genome and Sanger sequencing of 166 sheep from 54 breed groups. A genetic test with 109 of the 163 parentage SNPs was developed for matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry. The scoring rates and accuracies for these 109 SNPs were greater than 99% in a panel of North American sheep. In a blinded set of 96 families (sire, dam, and non-identical twin lambs), each parent of every lamb was identified without using the other parent's genotype. In 74 ISGC breed groups, the median estimates for probability of a coincidental match between two animals (PI), and the fraction of potential adults excluded from parentage (PE) were 1.1×10(-39) and 0.999987, respectively, for the 109 SNPs combined. The availability of a well-characterized set of 163 parentage SNPs facilitates the development of high-throughput genetic technologies for implementing accurate and economical parentage testing and traceability in many of the world's sheep breeds.

Imputation of microsatellite alleles from dense SNP genotypes for parentage verification across multiple Bos taurus and Bos indicus breeds.

To assist cattle producers transition from microsatellite (MS) to single nucleotide polymorphism (SNP) genotyping for parental verification we previously devised an effective and inexpensive method to impute MS alleles from SNP haplotypes. While the reported method was verified with only a limited data set (N = 479) from Brown Swiss, Guernsey, Holstein, and Jersey cattle, some of the MS-SNP haplotype associations were concordant across these phylogenetically diverse breeds. This implied that some haplotypes predate modern breed formation and remain in strong linkage disequilibrium. To expand the utility of MS allele imputation across breeds, MS and SNP data from more than 8000 animals representing 39 breeds (Bos taurus and B. indicus) were used to predict 9410 SNP haplotypes, incorporating an average of 73 SNPs per haplotype, for which alleles from 12 MS markers could be accurately be imputed. Approximately 25% of the MS-SNP haplotypes were present in multiple breeds (N = 2 to 36 breeds). These shared haplotypes allowed for MS imputation in breeds that were not represented in the reference population with only a small increase in Mendelian inheritance inconsistancies. Our reported reference haplotypes can be used for any cattle breed and the reported methods can be applied to any species to aid the transition from MS to SNP genetic markers. While ~91% of the animals with imputed alleles for 12 MS markers had ≤1 Mendelian inheritance conflicts with their parents' reported MS genotypes, this figure was 96% for our reference animals, indicating potential errors in the reported MS genotypes. The workflow we suggest autocorrects for genotyping errors and rare haplotypes, by MS genotyping animals whose imputed MS alleles fail parentage verification, and then incorporating those animals into the reference dataset.

The sub-chronic toxicity in rats of isoparaffinic solvents.

Results from a 13-week inhalation study in rats on a C10-C12 isoparaffinic solvent are compared to the results of repeated inhalation and oral toxicity studies of four other isoparaffinic hydrocarbon solvents. Statistically significant findings which were consistent across all studies included: nephropathy and small but significant changes in hematological parameters in male rats and liver enlargement in both male and female rats. The male rat kidney changes were due to an alpha 2u globulin process and not relevant for human health or risk assessment. The liver enlargement without pathologic changes or elevations in liver enzyme markers was considered to be an adaptive response. The reason for the reductions in hematological parameters that were observed in males only is not clear, but it is suggested that these were either due to normal variation or a secondary consequence of the nephropathy. The overall No Observed Adverse Effect Concentration (NOAEC) was the highest concentration tested in the study, >10,000 mg/m(3). Because of the overall pattern of response, this solvent is considered to be representative of low aromatic C9-C14 aliphatic solvents in general. The data are useful for risk assessment and other purposes including the development of occupational exposure recommendations.

The relationship between repeat-dose toxicity and aromatic-ring class profile of high-boiling petroleum substances.

A study was undertaken within the context of the U.S. EPA HPV Chemical Challenge Program to (1) characterize relationships between PAC content and repeat-dose toxicities of high-boiling petroleum substances (HBPS) and (2) develop statistical models that could be used to predict the repeat-dose toxicity of similar untested substances. The study evaluated 47 repeat-dose dermal toxicity and 157 chemical compositional studies. The four most sensitive endpoints of repeat-dose toxicity were platelet count, hemoglobin concentration, relative liver weight and thymus weight. Predictive models were developed for the dose-response relationships between the wt.% concentration of each of seven ring classes of aromatic compounds (the "ARC profile") and specific effects, with high correlations (r=0.91-0.94) between the observed and model-predicted data. The development of the mathematical models used to generate the results reported in this study is described by Nicolich et al. (2013). Model-generated dose-response curves permit the prediction of either the effect at a given dose or the dose that causes a given effect. The models generate values that are consistent with other standard measures. The models, using compositional data, can be used for predicting the repeat-dose toxicity of untested HBPS.

The relationship between developmental toxicity and aromatic-ring class profile of high-boiling petroleum substances.

In response to the US EPA HPV Challenge Program, this study was conducted to: (1) evaluate the relationship between PAC content and the developmental toxicity of high-boiling petroleum substances (HBPS) and (2) develop mathematical models to predict the developmental toxicity of similar untested substances based on their aromatic ring class (ARC) profiles. For this investigation, 68 developmental toxicity studies were reviewed. The ARC models relied on data from 21 rat dermal developmental toxicity studies conducted with similar experimental designs to ensure a consistent data set for comparison. The most sensitive general endpoints of developmental toxicity (i.e., decreased fetal survival and growth) were chosen for modeling. The ARC models demonstrated a strong correlation between the predicted vs. observed values for specific sensitive endpoints of these developmental toxicities (percent resorptions, r=0.99; live fetuses per litter, r=0.98; fetal body weight, r=0.94). Such associations provide a promising approach for predicting the developmental toxicity of untested HBPS. Efforts to corroborate the ARC models using test substances that were not used to build the ARC models produced mixed results, and further development and refinement of the ARC models is recommended before they can be reliably applied to all HBPS.

Evaluating the male and female reproductive toxicity of high-boiling petroleum substances.

To meet the EPA HPV Chemical Challenge Program requirement for reproductive toxicity data on sponsored high-boiling petroleum substances (HBPS), an analysis was conducted using the results of 39 repeat-dose and 59 developmental rat dermal toxicity studies on HBPS samples spanning the boiling range of the sponsored substances, and the results of three one-generation reproductive toxicity studies on two samples spanning the concentration range of polycyclic aromatic compounds of sponsored substances. The analysis found little evidence of male or female reproductive tract toxicity based on histopathology, reproductive organ weight, and sperm parameters, and no evidence of effects on fertility, while significant developmental toxicity and/or systemic repeat-dose toxicity were frequently observed. Among 14 samples of HBPS tested in both repeat-dose toxicity and developmental toxicity studies, there were no studies in which an adverse reproductive tract finding occurred at a dose lower than that producing developmental toxicity or other adverse effects in repeat-dose toxicity studies. The current analysis supports the hypothesis that effects in developmental and/or repeat-dose toxicity studies of HBPS occur at doses lower than those that might affect fertility in rat one-generation reproductive studies. When adequate developmental and repeat-dose toxicity studies are available, a reproductive toxicity study of HBPS appears unnecessary.

Genetic testing for TMEM154 mutations associated with lentivirus susceptibility in sheep.

In sheep, small ruminant lentiviruses cause an incurable, progressive, lymphoproliferative disease that affects millions of animals worldwide. Known as ovine progressive pneumonia virus (OPPV) in the U.S., and Visna/Maedi virus (VMV) elsewhere, these viruses reduce an animal's health, productivity, and lifespan. Genetic variation in the ovine transmembrane protein 154 gene (TMEM154) has been previously associated with OPPV infection in U.S. sheep. Sheep with the ancestral TMEM154 haplotype encoding glutamate (E) at position 35, and either form of an N70I variant, were highly-susceptible compared to sheep homozygous for the K35 missense mutation. Our current overall aim was to characterize TMEM154 in sheep from around the world to develop an efficient genetic test for reduced susceptibility. The average frequency of TMEM154 E35 among 74 breeds was 0.51 and indicated that highly-susceptible alleles were present in most breeds around the world. Analysis of whole genome sequences from an international panel of 75 sheep revealed more than 1,300 previously unreported polymorphisms in a 62 kb region containing TMEM154 and confirmed that the most susceptible haplotypes were distributed worldwide. Novel missense mutations were discovered in the signal peptide (A13V) and the extracellular domains (E31Q, I74F, and I102T) of TMEM154. A matrix-assisted laser desorption/ionization-time-of flight mass spectrometry (MALDI-TOF MS) assay was developed to detect these and six previously reported missense and two deletion mutations in TMEM154. In blinded trials, the call rate for the eight most common coding polymorphisms was 99.4% for 499 sheep tested and 96.0% of the animals were assigned paired TMEM154 haplotypes (i.e., diplotypes). The widespread distribution of highly-susceptible TMEM154 alleles suggests that genetic testing and selection may improve the health and productivity of infected flocks.

The development of statistical models to determine the relationship between aromatic-ring class profile and repeat-dose and developmental toxicities of high-boiling petroleum substances.

The repeat-dose and developmental toxicities of certain petroleum refinery streams are related to their polycyclic aromatic compound (PAC) content (Feuston et al., 1994). Building on this foundation, and working within the context of the US EPA High Production Volume (HPV) Chemical Challenge Program, we: (1) characterized relationships between PAC content and repeat-dose and developmental toxicities of high boiling petroleum substances (HBPS), and (2) developed statistical models that can be used to predict critical effects of similar untested substances. Data from 39 dermal toxicity studies of HBPS were used to develop statistical models to predict the dose-response relationships between the weight percent concentration of each of their 1-7 aromatic ring classes and 4 repeat-dose and 3 developmental endpoints (absolute thymus weight, hemoglobin count, platelet count, liver to body weight, live fetus count, fetal weight, and percent resorptions). The correlations between the observed and model-predicted values are >0.90. The predictive ability of the models was tested via a series of evaluation or corroboration methods. As is shown in the paper, using only compositional data of untested HBPS, the models can be used to predict the effect at a given dose or the dose that causes an effect of a stipulated magnitude.

Assessing the mammalian toxicity of high-boiling petroleum substances under the rubric of the HPV program.

In 1998, the US EPA announced the HPV Challenge Program, a voluntary chemical data collection effort. The Petroleum HPV Testing Group (PHPVTG(1)) volunteered to provide data on approximately 110 high boiling petroleum substances (HBPS), i.e. substances with final boiling points ≥ approximately 650°F (343°C). These HBPS are substances of unknown and variable composition (UVCBs) that are composed of numerous individual constituents. Toxicity studies have shown that some HBPS can produce systemic (repeat-dose) and developmental effects, and some are mutagenic under in vitro conditions. The papers in this supplement show that these effects are related to the profiles of aromatic constituents in these substances. Further, it is shown that the effects on selected repeat-dose and developmental toxicity endpoints and mutagenic activity in bacterial assays can be predicted from compositional information using models based on the aromatic-ring class profile, "ARC profile" as defined by gas chromatographic separation of the DMSO-soluble fraction of the starting materials. This chromatographic method and the predictive models provide an efficient means of characterizing for screening purposes the potential for repeat-dose, developmental effects and bacterial mutagenicity of HBPS and can reduce the number of animal tests that would be required if these tests were conducted on all 110 HBPS.