Genome-wide association and genomic prediction for host response to porcine reproductive and respiratory syndrome virus infection

Background

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.

Results

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).

Conclusions

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.     

Dramatic down-regulation of oxidoreductases in human hepatocellular carcinoma hepG2 cells: proteomics and gene ontology unveiling new frontiers in cancer enzymology

Background

Oxidoreductases are enzymes that catalyze many redox reactions in normal and neoplastic cells. Their actions include catalysis of the transformation of free, neutral oxygen gas into oxygen free radicals, superoxide, hydroperoxide, singlet oxygen and hydrogen peroxide. These activated forms of oxygen contribute to oxidative stress that modifies lipids, proteins, DNA and carbohydrates. On the other hand, oxidoreductases constitute one of the most important free radical scavenger systems typified by catalase, superoxide dismutase and glutathione peroxidase. In this work, proteomics, Gene Ontology mapping and Directed Acyclic Graphs (DAG) are employed to detect and quantify differential oxidoreductase enzyme expressions between HepG2 cells and normal human liver tissues.

Results

For the set of bioinformatics calculations whose BLAST searches are performed using the BLAST program BLASTP 2.2.13 [Nov-27-2005], DAG of the Gene Ontology's Molecular Function annotations show that oxidoreductase activity parent node of the liver proteome contains 331 annotated protein sequences, 7 child nodes and an annotation score of 188.9, whereas that of HepG2 cells has 188 annotated protein sequences, 3 child nodes and an annotation score of only 91.9. Overwhelming preponderance of oxidoreductases in the liver is additionally supported by the isomerase DAGs: nearly all the reactions described in the normal liver isomerase DAG are oxidoreductase isomerization reactions, whereas only one of the three child nodes in the HepG2 isomerase DAG is oxidoreductase. Upon normalization of the annotation scores to the parent Molecular Function nodes, oxidoreductases are down-regulated in HepG2 cells by 58%. Similarly, for the set of bioinformatics calculations whose BLAST searches are carried out using BLASTP 2.2.15 [Oct-15-2006], oxidoreductases are down-regulated in HepG2 cells by 56%.

Conclusion

Proteomics and Gene Ontology reveal, for the first time, differential enzyme activities between HepG2 cells and normal human liver tissues, which may be a promising new prognostic marker of Hepatocellular carcinoma. Two independent sets of bioinformatics calculations that employ two BLAST program versions, and searched different databases, arrived at essentially the same conclusion: oxidoreductases are down-regulated in HepG2 cells by approximately 57%, when compared to normal human liver tissues. Down-regulation of oxidoreductases in hepatoma is additionally supported by Gene Ontology analysis of isomerises.     

Sample prep for proteomics of breast cancer: proteomics and gene ontology reveal dramatic differences in protein solubilization preferences of radioimmunoprecipitation assay and urea lysis buffers

Background

An important step in the proteomics of solid tumors, including breast cancer, consists of efficiently extracting most of proteins in the tumor specimen. For this purpose, Radio-Immunoprecipitation Assay (RIPA) buffer is widely employed. RIPA buffer's rapid and highly efficient cell lysis and good solubilization of a wide range of proteins is further augmented by its compatibility with protease and phosphatase inhibitors, ability to minimize non-specific protein binding leading to a lower background in immunoprecipitation, and its suitability for protein quantitation.

Results

In this work, the insoluble matter left after RIPA buffer extraction of proteins from breast tumors are subjected to another extraction step, using a urea-based buffer. It is shown that RIPA and urea lysis buffers fractionate breast tissue proteins primarily on the basis of molecular weights. The average molecular weight of proteins that dissolve exclusively in urea buffer is up to 60% higher than in RIPA. Gene Ontology (GO) and Directed Acyclic Graphs (DAG) are used to map the collective biological and biophysical attributes of the RIPA and urea proteomes. The Cellular Component and Molecular Function annotations reveal protein solubilization preferences of the buffers, especially the compartmentalization and functional distributions. It is shown that nearly all extracellular matrix proteins (ECM) in the breast tumors and matched normal tissues are found, nearly exclusively, in the urea fraction, while they are mostly insoluble in RIPA buffer. Additionally, it is demonstrated that cytoskeletal and extracellular region proteins are more soluble in urea than in RIPA, whereas for nuclear, cytoplasmic and mitochondrial proteins, RIPA buffer is preferred. Extracellular matrix proteins are highly implicated in cancer, including their proteinase-mediated degradation and remodelling, tumor development, progression, adhesion and metastasis. Thus, if they are not efficiently extracted by RIPA buffer, important information may be missed in cancer research.

Conclusion

For proteomics of solid tumors, a two-step extraction process is recommended. First, proteins in the tumor specimen should be extracted with RIPA buffer. Second, the RIPA-insoluble material should be extracted with the urea-based buffer employed in this work.     

A comparison of alternative methods to compute conditional genotype probabilities for genetic evaluation with finite locus models

An increased availability of genotypes at marker loci has prompted the development of models that include the effect of individual genes. Selection based on these models is known as marker-assisted selection (MAS). MAS is known to be efficient especially for traits that have low heritability and non-additive gene action. BLUP methodology under non-additive gene action is not feasible for large inbred or crossbred pedigrees. It is easy to incorporate non-additive gene action in a finite locus model. Under such a model, the unobservable genotypic values can be predicted using the conditional mean of the genotypic values given the data. To compute this conditional mean, conditional genotype probabilities must be computed. In this study these probabilities were computed using iterative peeling, and three Markov chain Monte Carlo (MCMC) methods – scalar Gibbs, blocking Gibbs, and a sampler that combines the Elston Stewart algorithm with iterative peeling (ESIP). The performance of these four methods was assessed using simulated data. For pedigrees with loops, iterative peeling fails to provide accurate genotype probability estimates for some pedigree members. Also, computing time is exponentially related to the number of loci in the model. For MCMC methods, a linear relationship can be maintained by sampling genotypes one locus at a time. Out of the three MCMC methods considered, ESIP, performed the best while scalar Gibbs performed the worst.     

Survival of Escherichia coli, Enterococci, and Campylobacter spp. in sheep feces on pastures

The survival of enteric bacteria in 10 freshly collected sheep fecal samples on pastures was measured in each of four seasons. Ten freshly collected feces were placed on pasture, and concentrations of Escherichia coli, enterococci, and Campylobacter spp. were monitored until exhaustion of the fecal samples. In all four seasons, there was an increase in enterococcal concentrations by up to 3 orders of magnitude, with peak concentrations recorded between 11 and 28 days after deposition. E. coli concentrations increased in three out of four seasons by up to 1.5 orders of magnitude, with peak concentrations recorded between 8 and 14 days after deposition. The apparent growth of E. coli and enterococci was strongly influenced by the initial water content of the feces and the moisture gained during periods of rehydration following rainfalls. Conversely, the results suggested that dehydration promoted inactivation. Campylobacter spp. did not grow and were rapidly inactivated at a rate that tended to be faster at higher temperatures. Pulsed-field gel electrophoresis (PFGE) of a selection of Campylobacter spp. suggested that these survival data are applicable to a range of Campylobacter spp., including the most frequently isolated PFGE genotype from sheep in New Zealand, and to genotypes previously observed to cause disease in humans. The results of this study are currently being incorporated into a fecal microbe reservoir model that is designed to assist water managers' abilities to estimate microbial loads on pastures grazed by sheep, including the influence of factors such as rainfall and temperature.     

Flying lemurs – The 'flying tree shrews'? Molecular cytogenetic evidence for a Scandentia-Dermoptera sister clade

Background  

Flying lemurs or Colugos (order Dermoptera) represent an ancient mammalian lineage that contains only two extant species. Although molecular evidence strongly supports that the orders Dermoptera, Scandentia, Lagomorpha, Rodentia and Primates form a superordinal clade called Supraprimates (or Euarchontoglires), the phylogenetic placement of Dermoptera within Supraprimates remains ambiguous.     

Expression of the poly-glutamine-ataxin-3 transgene causes loss of orexin expression: A rat model of narcolepsy

Sleep and Biological Rhythms -     

BAC libraries construction from the ancestral diploid genomes of the allotetraploid cultivated peanut

Background

Cultivated peanut, Arachis hypogaea is an allotetraploid of recent origin, with an AABB genome. In common with many other polyploids, it seems that a severe genetic bottle-neck was imposed at the species origin, via hybridisation of two wild species and spontaneous chromosome duplication. Therefore, the study of the genome of peanut is hampered both by the crop's low genetic diversity and its polyploidy. In contrast to cultivated peanut, most wild Arachis species are diploid with high genetic diversity. The study of diploid Arachis genomes is therefore attractive, both to simplify the construction of genetic and physical maps, and for the isolation and characterization of wild alleles. The most probable wild ancestors of cultivated peanut are A. duranensis and A. ipaënsis with genome types AA and BB respectively.

Results

We constructed and characterized two large-insert libraries in Bacterial Artificial Chromosome (BAC) vector, one for each of the diploid ancestral species. The libraries (AA and BB) are respectively c. 7.4 and c. 5.3 genome equivalents with low organelle contamination and average insert sizes of 110 and 100 kb. Both libraries were used for the isolation of clones containing genetically mapped legume anchor markers (single copy genes), and resistance gene analogues.

Conclusion

These diploid BAC libraries are important tools for the isolation of wild alleles conferring resistances to biotic stresses, comparisons of orthologous regions of the AA and BB genomes with each other and with other legume species, and will facilitate the construction of a physical map.

     

Differential responsiveness to immunoablative therapy in refractory rheumatoid arthritis is associated with level and avidity of anti-cyclic citrullinated protein autoantibodies: a case study

In order to identify pathogenic correlates of refractory rheumatoid arthritis (RA), antibodies against anti-cyclic citrullinated protein (ACPAs) were investigated in RA patients in whom the dysregulated immune system had been ablated by high-dose chemotherapy (HDC) and autologous haematopoietic stem cell transplantation (HSCT). Six patients with refractory RA were extensively characterized in terms of levels of total immunoglobulins, RA-specific autoantibodies (ACPAs and rheumatoid factor) and antibodies against rubella, tetanus toxoid (TT) and phosphorylcholine before and after HDC plus HSCT. Additionally, the avidity of ACPAs was measured before and after treatment and compared with the avidity of TT antibodies following repeated immunizations. Synovial biopsies were obtained by arthroscopy before HDC plus HSCT, and analyzed by immunohistochemistry. In the three patients with clinically long-lasting responses to HDC plus HSCT (median 423 days), significant reductions in ACPA-IgG levels after therapy were observed (median level dropped from 215 to 34 arbitrary units/ml; P = 0.05). In contrast, stable ACPA-IgG levels were observed in three patients who relapsed shortly after HDC plus HSCT (median of 67 days). Clinical responders had ACPA-IgG of lower avidity (r = 0.75; P = 0.08) and higher degree of inflammation histologically (r = 0.73; P = 0.09). Relapse (after 38 to 530 days) in all patients was preceded by rising levels of low avidity ACPA-IgG (after 30 to 388 days), in contrast to the stable titres of high avidity TT antibodies. In conclusion, humoral autoimmune responses were differentially modulated by immunoablative therapy in patients with synovial inflammation and low avidity ACPA-IgG autoantibodies as compared with patients with high levels of high avidity ACPA-IgG. The distinct clinical disease course after immunoablative therapy based on levels and avidity of ACPA-IgG indicates that refractory RA is not a single disease entity.