Ambient Light Promotes Selective Subcellular Proteotoxicity after Endogenous and Exogenous Porphyrinogenic Stress

Hepatic accumulation of protoporphyrin-IX (PP-IX) in erythropoietic protoporphyria (EPP) or X-linked-dominant protoporphyria (XLP) cause liver damage. Hepatocyte nuclear lamin aggregation is a sensitive marker for PP-IX-mediated liver injury. We tested the hypothesis that extracellular or intracellular protoporphyria cause damage to different subcellular compartments, in a light-triggered manner. Three hepatoma cell lines (HepG2, Hepa-1, and Huh-7) were treated with exogenous PP-IX (mimicking XLP extrahepatic protoporphyria) or with the iron chelator deferoxamine and the porphyrin precursor 5-aminolevulinic acid (ALA) (mimicking intracellular protoporphyrin accumulation in EPP). Exogenous PP-IX accumulated predominantly in the nuclear fraction and caused nuclear shape deformation and cytoplasmic vacuoles containing electron-dense particles, whereas ALA+deferoxamine treatment resulted in higher PP-IX in the cytoplasmic fraction. Protein aggregation in the nuclear and cytoplasmic fractions paralleled PP-IX levels and, in cell culture, the effects were exclusively ambient light-mediated. PP-IX and ALA caused proteasomal inhibition, whereas endoplasmic reticulum protein aggregation was more prominent in ALA-treated cells. The enhanced ALA-related toxicity is likely due to generation of additional porphyrin intermediates including uroporphyrin and coproporphyrin, based on HPLC analysis of cell lysates and the culture medium, as well as cell-free experiments with uroporphyrin/coproporphyrin. Mouse livers from drug-induced porphyria phenocopied the in vitro findings, and mass spectrometry of liver proteins isolated in light/dark conditions showed diminished (as compared with light-harvested) but detectable aggregation under dark-harvested conditions. Therefore, PP-IX leads to endoplasmic reticulum stress and proteasome inhibition in a manner that depends on the source of porphyrin buildup and light exposure. Porphyrin-mediated selective protein aggregation provides a potential mechanism for porphyria-associated tissue injury.     

Ants in their plants: Pseudomyrmex ants reduce primate,parrot and squirrel predation on Macrolobium acaciifolium (Fabaceae) seeds in Amazonian Brazil

Although plant‐inhabiting ants are known to act as effective deterrents to a variety of vertebrate and invertebrate herbivores, this has been reported only once before for primates, a group better known for their predation of ants. In the present study, we investigated the effects that colonies of Pseudomyrmex viduus ants living in individual Macrolobium acaciifolium (Fabaceae) trees have on the rates of visitation and fruit removal by four taxa of seed‐predating vertebrates: the primate Cacajao melanocephalus ouakary; macaws (Ara spp.); large parrots (Amazona spp.); and the Northern Amazonian red squirrel (Sciurus igniventris). We found that ant presence significantly reduced both rates of visitation and of fruit removal by C. m. ouakary. The same pattern of reduced fruit removal was also observed for other seed predators (parrots, macaws, and squirrels) but not for visitation rates (although this may be a result of the small sample size). This appears to be only the second‐known demonstration of the repellent effect of ants on primates and, indeed, the first for squirrels and psittacine birds. © 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 114 , 260–273.     

Genome-wide association study for calving performance using high-density genotypes in dairy and beef cattle

Background

Calving difficulty and perinatal mortality are prevalent in modern-day cattle production systems. It is well-established that there is a genetic component to both traits, yet little is known about their underlying genomic architecture, particularly in beef breeds. Therefore, we performed a genome-wide association study using high-density genotypes to elucidate the genomic architecture of these traits and to identify regions of the bovine genome associated with them.

Results

Genomic regions associated with calving difficulty (direct and maternal) and perinatal mortality were detected using two statistical approaches: (1) single-SNP (single nucleotide polymorphism) regression and (2) a Bayesian approach. Data included high-density genotypes on 770 Holstein-Friesian, 927 Charolais and 963 Limousin bulls. Several novel or previously identified genomic regions were detected but associations differed by breed. For example, two genomic associations, one each on chromosomes 18 and 2 explained 2.49 % and 3.13 % of the genetic variance in direct calving difficulty in the Holstein-Friesian and Charolais populations, respectively. Imputed Holstein-Friesian sequence data was used to refine the genomic regions responsible for significant associations. Several candidate genes on chromosome 18 were identified and four highly significant missense variants were detected within three of these genes (SIGLEC12, CTU1, and ZNF615). Nevertheless, only CTU1 contained a missense variant with a putative impact on direct calving difficulty based on SIFT (0.06) and Polyphen (0.95) scores. Using imputed sequence data, we refined a genomic region on chromosome 4 associated with maternal calving difficulty in the Holstein-Friesian population and found the strongest association with an intronic variant in the PCLO gene. A meta-analysis was performed across the three breeds for each calving performance trait to identify common variants associated with these traits in the three breeds. Our results suggest that a portion of the genetic variation in calving performance is common to all three breeds.

Conclusion

The genomic architecture of calving performance is complex and mainly influenced by many polymorphisms of small effect. We identified several associations of moderate effect size but the majority were breed-specific, indicating that breed-specific alleles exist for calving performance or that the linkage phase between genotyped allele and causal mutation varies between breeds.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0126-4) contains supplementary material, which is available to authorized users.     

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle

Background

While several studies have examined the accuracy of direct genomic breeding values (DGV) within and across purebred cattle populations, the accuracy of DGV in crossbred or multi-breed cattle populations has been less well examined. Interest in the use of genomic tools for both selection and management has increased within the hybrid seedstock and commercial cattle sectors and research is needed to determine their efficacy. We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals. Our objective was to compare alternate models with different assumptions regarding the distributions of single nucleotide polymorphism (SNP) effects to determine the optimal model for enhancing feasibility of multi-breed DGV prediction for the commercial beef industry.

Results

Realized accuracies ranged from 0.40 to 0.78. Randomly assigning 60 to 70% of animals to training (n ≈ 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesCπ) and models that allow SNP effects to be sampled from distributions with unequal variances (BayesA, BayesB95) were advantageous for traits that appear or are known to be influenced by large-effect genes. For other traits, models differed little in prediction accuracy (~0.3 to 0.6%), suggesting that they are mainly controlled by small-effect loci.

Conclusions

The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations. Larger effects were estimated for some SNPs using BayesA and BayesB95 models because they allow unequal SNP variances. This substantially increased DGV accuracy for Warner-Bratzler Shear Force, for which large-effect quantitative trait loci (QTL) are known, while no loss in accuracy was observed for traits that appear to follow the infinitesimal model. Large decreases in accuracy (up to 0.07) occurred when SNPs that presumably tag large-effect QTL were over-regressed towards the mean in BayesC0 analyses. The DGV accuracies achieved here indicate that genomic selection has predictive utility in the commercial beef industry and that using models that reflect the genomic architecture of the trait can have predictive advantages in multi-breed populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0106-8) contains supplementary material, which is available to authorized users.