Transcriptional Profiling of PRKG2-Null Growth Plate Identifies Putative Down-Stream Targets of PRKG2

Kinase activity of cGMP-dependent, type II, protein kinase (PRKG2) is required for the proliferative to hypertrophic transition of growth plate chondrocytes during endochondral ossification. Loss of PRKG2 function in rodent and bovine models results in dwarfism. The objective of this study was to identify pathways regulated or impacted by PRKG2 loss of function that may be responsible for disproportionate dwarfism at the molecular level. Microarray technology was used to compare growth plate cartilage gene expression in dwarf versus unaffected Angus cattle to identify putative downstream targets of PRGK2. Pathway enrichment of 1284 transcripts (nominal p \u3c 0.05) was used to identify candidate pathways consistent with the molecular phenotype of disproportionate dwarfism. Analysis with the DAVID pathway suite identified differentially expressed genes that clustered in the MHC, cytochrome B, WNT, and Muc1 pathways. A second analysis with pathway studio software identified differentially expressed genes in a host of pathways (e.g. CREB1, P21, CTNNB1, EGFR, EP300, JUN, P53, RHOA, and SRC). As a proof of concept, we validated the differential expression of five genes regulated by P53, including CEBPA, BRCA1, BUB1, CD58, and VDR by real-time PCR (p \u3c 0.05). Known and novel targets of PRKG2 were identified as enriched pathways in this study. This study indicates that loss of PRKG2 function results in differential expression of P53 regulated genes as well as additional pathways consistent with increased proliferation and apoptosis in the growth plate due to achondroplastic dwarfism

BEAP: The BLAST Extension and Alignment Program- a tool for contig construction and analysis of preliminary genome sequence

<p>Abstract</p> <p>Background</p> <p>Fine-mapping projects require a high density of SNP markers and positional candidate gene sequences. In species with incomplete genomic sequence, the DNA sequences needed to generate markers for fine-mapping within a linkage analysis confidence interval may be available but may not have been assembled. To manually piece these sequences together is laborious and costly. Moreover, annotation and assembly of short, incomplete DNA sequences is time consuming and not always straightforward.</p> <p>Findings</p> <p>We have created a tool called BEAP that combines BLAST and CAP3 to retrieve sequences and construct contigs for localized genomic regions in species with unfinished sequence drafts. The rational is that a completed genome can be used as a template to query target genomic sequence for closing the gaps or extending contig sequence length in species whose genome is incomplete on the basis that good homology exists. Each user must define what template sequence is appropriate based on comparative mapping data such as radiation hybrid (RH) maps or other evidence linking the gene sequence of the template species to the target species.</p> <p>Conclusion</p> <p>The BEAP software creates contigs suitable for discovery of orthologous genes for positional cloning. The resulting sequence alignments can be viewed graphically with a Java graphical user interface (GUI), allowing users to evaluate contig sequence quality and predict SNPs. We demonstrate the successful use of BEAP to generate genomic template sequence for positional cloning of the Angus dwarfism mutation. The software is available for free online for use on UNIX systems at <url>http://www.animalgenome.org/bioinfo/tools/beap/</url>.</p

Standard Genetic Nomenclature

Genetics includes the study of genotypes and phenotypes, the mechanisms of genetic control between them, and information transfer between generations. Genetic terms describe processes, genes and traits with which genetic phenomena are examined and described. While the genetic terminologies are extensively discussed in this book and elsewhere, the standardization of their names has been an ongoing process. Therefore, this chapter will only concentrate on discussions about the issues involved in the standardization of gene and trait terminologies

High-Density SNP Genotypes for Predicting Genetic Merit of Beef Cattle

Current selection strategies result in annual rates of genetic improvement less than one-quarter of the progress that is theoretically possible if merit could be accurately predicted by breeding age. Tens of thousands of single gene markers (called SNPs), spread throughout the genome, enable the ancestral inheritance of small chromosome fragments to be tracked. Genetic merit of new, perhaps unrelated cattle can be predicted by summing up the values of all the fragments they have inherited. Such predictions at young ages will facilitate faster rates of genetic gain, especially for traits that are difficult to measure

Meta-Analysis of Quantitative Trait Association and Mapping Studies using Parametric and Non-Parametric Models

Meta-analysis is an important method for integration of information from multiple studies. In quantitative trait association and mapping experiments, combining results from several studies allows greater statistical power for detection of causal loci and more precise estimation of their effects, and thus can yield stronger conclusions than individual studies. Various meta-analysis methods have been proposed for synthesizing information from multiple candidate gene studies and QTL mapping experiments, but there are several questions and challenges associated with these methods. For example, meta-analytic fixed-effect models assume homogeneity of outcomes from individual studies, which may not always be true. Whereas random-effect models takes into account the heterogeneity among studies they typically assume a normal distribution of study-specific outcomes. However in reality, the observed distribution pattern tends to be multi-modal, suggesting a mixture whose underlying components are not directly observable. In this paper, we examine several existing parametric meta-analysis methods, and propose the use of a non-parametric model with a Dirichlet process prior (DPP), which relaxes the normality assumptions about study- specific outcomes. With a DPP model, the posterior distribution of outcomes is discrete, reflecting a clustering property that may have biological implications. Features of these methods were illustrated and compared using both simulation data and real QTL data extracted from the Animal QTLdb (http://www.animalgenome.org/cgi-bin/QTLdb/index). The meta analysis of reported average daily body weight gain (ADG) QTL suggested that there could be from six to eight distinct ADG QTL on swine chromosome 1

Whole genome analysis of infectious bovine keratoconjunctivitis in Angus cattle using Bayesian threshold models

Infectious bovine keratoconjunctivitis (IBK), also known as pinkeye, is characterized by damage to the cornea and is an economically important, lowly heritable, categorical disease trait in beef cattle. Scores of eye damage were collected at weaning on 858 Angus cattle. SNP genotypes for each animal were obtained from BovineSNP50 Infinium-beadchips. Simultaneous associations of all SNP with IBK phenotype were determined using Bayes-C that treats SNP effects as random with equal variance for an assumed fraction (π=0.999) of SNP having no effect on IBK scores. Bayes-C threshold models were used to estimate SNP effects by classifying IBK into two, three or nine ordered categories. Magnitudes of genetic variances estimated in localized regions across the genome indicated that SNP within the most informative regions accounted for much of the genetic variance of IBK and pointed out some degree of association to IBK. There are many candidate genes in these regions which could include a gene or group of genes associated with bacterial disease in cattle

Characterization of Gene Expression in Double-Muscled and Normal-Muscled Bovine Embryos

Myostatin, a member of the transforming growth factor-beta superfamily, is a negative regulator of skeletal muscle growth. Cattle with mutations that inactivate myostatin exhibit a remarkable increase in mass of skeletal muscle called double muscling that is accompanied by an equally remarkable decrease in carcass fat. Although a mouse knockout model has been created which results in mice with a 200% increase in skeletal muscle mass, molecular mechanisms whereby myostatin regulates skeletal muscle and fat mass are not fully understood. Using suppressive subtractive hybridization, genes that were differentially expressed in double-muscled vs. normal-muscled cattle embryos were identified. Genetic variation at other loci was minimized by using embryonic samples collected from related Piedmontese x Angus dams or Belgian Blue x Hereford dams bred to a single sire of the same breed composition. Embryos were collected at 31-33 days of gestation, which is 2-4 days after high-level expression of myostatin in the developing bovine embryo. The suppressive subtraction resulted in 30 clones that were potentially differentially expressed, 19 of which were confirmed by macroarray analysis. Several of these genes have biological functions that suggest that they are directly involved in myostatin\u27s regulation of skeletal muscle development. Furthermore, several of these genes map to quantitative trait loci known to interact with variation in the myostatin gene

Quantitative Trait Locus on Sus scrofa Chromosome 4 Associated with Host Response to Experimental Infection with Porcine Reproductive and Respiratory Syndrome Virus

The objective of this study was to conduct a genomewide association study to discover the genetic basis of host response to PRRS virus using data from the PRRS Host Genetics Consortium NPB and PRRS-CAP project. Approximately 1,600 commercial crossbred piglets were experimentally infected with the Porcine Reproductive and Respiratory Syndrome (PRRS) virus. Blood samples and body weights were collected up to 42 days post infection (dpi). Experimental pigs and their parents were genotyped with Illumina’s Porcine 60k BeadChip. Phenotypes analyzed were viral load (VL = area under the curve for log-transformed qRT-PCR based serum virus from 0-21 dpi) and weight gain from 0-42 dpi (WG). Heritabilities estimated using pedigree information were moderate at 0.41 for VL and 0.29 for WG. A 1 Mb region on Sus scrofa chromosome (SSC) 4 was found to be associated with VL and WG and explained a substantial amount of genetic variation. The frequency of the favorable allele for the most significant single nucleotide polymorphism (SNP) was 0.15. These results show that there is a host genetic component to PRRS virus infection and that there is room for genetic improvement

Genome-Wide Association and Genomic Prediction for Host Response to Porcine Reproductive and Respiratory Syndrome Virus Infection

Host genetics has been shown to play a role in porcine reproductive and respiratory syndrome (PRRS), which is the most economically important disease in the swine industry. A region on Sus scrofa chromosome (SSC) 4 has been previously reported to have a strong association with serum viremia and weight gain in pigs experimentally infected with the PRRS virus (PRRSV). The objective here was to identify haplotypes associated with the favorable phenotype, investigate additional genomic regions associated with host response to PRRSV, and to determine the predictive ability of genomic estimated breeding values (GEBV) based on the SSC4 region and based on the rest of the genome. Phenotypic data and 60 K SNP genotypes from eight trials of ~200 pigs from different commercial crosses were used to address these objectives. Across the eight trials, heritability estimates were 0.44 and 0.29 for viral load (VL, area under the curve of log-transformed serum viremia from 0 to 21 days post infection) and weight gain to 42 days post infection (WG), respectively. Genomic regions associated with VL were identified on chromosomes 4, X, and 1. Genomic regions associated with WG were identified on chromosomes 4, 5, and 7. Apart from the SSC4 region, the regions associated with these two traits each explained less than 3% of the genetic variance. Due to the strong linkage disequilibrium in the SSC4 region, only 19 unique haplotypes were identified across all populations, of which four were associated with the favorable phenotype. Through cross-validation, accuracies of EBV based on the SSC4 region were high (0.55), while the rest of the genome had little predictive ability across populations (0.09). Traits associated with response to PRRSV infection in growing pigs are largely controlled by genomic regions with relatively small effects, with the exception of SSC4. Accuracies of EBV based on the SSC4 region were high compared to the rest of the genome. These results show that selection for the SSC4 region could potentially reduce the effects of PRRS in growing pigs, ultimately reducing the economic impact of this disease