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.     

Threonine phosphorylation prevents promoter DNA binding of the Group B Streptococcus response regulator CovR

All living organisms communicate with the external environment for their survival and existence. In prokaryotes, communication is achieved by two-component systems (TCS) comprising histidine kinases and response regulators. In eukaryotes, signalling is accomplished by serine/threonine and tyrosine kinases. Although TCS and serine/threonine kinases coexist in prokaryotes, direct cross-talk between these families was first described in Group B Streptococcus (GBS). A serine/threonine kinase (Stk1) and a TCS (CovR/CovS) co-regulate toxin expression in GBS. Typically, promoter binding of regulators like CovR is controlled by phosphorylation of the conserved active site aspartate (D53). In this study, we show that Stk1 phosphorylates CovR at threonine 65. The functional consequence of threonine phosphorylation of CovR in GBS was evaluated using phosphomimetic and silencing substitutions. GBS encoding the phosphomimetic T65E allele are deficient for CovR regulation unlike strains encoding the non-phosphorylated T65A allele. Further, compared with wild-type or T65A CovR, the T65E CovR is unable to bind promoter DNA and is decreased for phosphorylation at D53, similar to Stk1-phosphorylated CovR. Collectively, we provide evidence for a novel mechanism of response regulator control that enables GBS (and possibly other prokaryotes) to fine-tune gene expression for environmental adaptation.     

Haplotype inference in crossbred populations without pedigree information

Background

Current methods for haplotype inference without pedigree information assume random mating populations. In animal and plant breeding, however, mating is often not random. A particular form of nonrandom mating occurs when parental individuals of opposite sex originate from distinct populations. In animal breeding this is called crossbreeding and hybridization in plant breeding. In these situations, association between marker and putative gene alleles might differ between the founding populations and origin of alleles should be accounted for in studies which estimate breeding values with marker data. The sequence of alleles from one parent constitutes one haplotype of an individual. Haplotypes thus reveal allele origin in data of crossbred individuals.

Results

We introduce a new method for haplotype inference without pedigree that allows nonrandom mating and that can use genotype data of the parental populations and of a crossbred population. The aim of the method is to estimate line origin of alleles. The method has a Bayesian set up with a Dirichlet Process as prior for the haplotypes in the two parental populations. The basic idea is that only a subset of the complete set of possible haplotypes is present in the population.

Conclusion

Line origin of approximately 95% of the alleles at heterozygous sites was assessed correctly in both simulated and real data. Comparing accuracy of haplotype frequencies inferred with the new algorithm to the accuracy of haplotype frequencies inferred with PHASE, an existing algorithm for haplotype inference, showed that the DP algorithm outperformed PHASE in situations of crossbreeding and that PHASE performed better in situations of random mating.     

You can't always get what you want: size assortative mating by mutual mate choice as a resolution of sexual conflict

Background  

Assortative mating patterns for mate quality traits like body size are often observed in nature. However, the underlying mechanisms that cause assortative mating patterns are less well known. Sexual selection is one important explanation for assortment, suggesting that i) one (usually the female) or both sexes could show preferences for mates of similar size or ii) mutual mate choice could resolve sexual conflict over quality traits into assortment. We tested these hypotheses experimentally in the socially monogamous cichlid fish Pelvicachromis taeniatus, in which mate choice is mutual.     

Mechanical strain to maxillary incisors during direct laryngoscopy

Dexmedetomidine is a highly selective adrenergic receptor agonist, which has a dose-dependent sedative hypnotic effect. Furthermore, it also has pharmacological properties, and the ability to inhibit sympathetic activity and improve cardiovascular stability during an operation. However, its protective effect on patients with severe craniocerebral injury in the perioperative period remains unclear. Eighty adult male SD rats were used and divided into two groups (n = 40, each group): dexmedetomidine injury group (experimental group), and sodium chloride injury group (control group). Models of severe craniocerebral injury were established in these two groups using the modified Feeney’s free-fall method. As soon as the establishment of models was succeed, rat in the experimental group received 1 μg of dexmedetomidine (0.1 ml), while each rat in the control group was given 0.1 ml of 0.9% sodium chloride. Blood was sampled from an incision at the femoral vein to detect TNF-α and IL-2 levels at 1, 12, 24,36,48 and 72 h after establishing the model in the two groups. After severe craniocerebral injury, TNF-α levels of rats were lower in every stage and at different degrees in the experimental group than in the control group (P < 0.05), while IL-2 levels were lower in the experimental group to different extents (P < 0.05). Dexmedetomidine protects the brain of rats with severe craniocerebral injury by reducing the release of inflammatory mediators.     

Munc18c phosphorylation by the insulin receptor links cell signaling directly to SNARE exocytosis

How the Sec1/Munc18-syntaxin complex might transition to form the SNARE core complex remains unclear. Toward this, Munc18c tyrosine phosphorylation has been correlated with its dissociation from syntaxin 4. Using 3T3-L1 adipocytes subjected to small interfering ribonucleic acid reduction of Munc18c as a model of impaired insulin-stimulated GLUT4 vesicle exocytosis, we found that coordinate expression of Munc18c-wild type or select phosphomimetic Munc18c mutants, but not phosphodefective mutants, restored GLUT4 vesicle exocytosis, suggesting a requirement for Munc18c tyrosine phosphorylation at Tyr219 and Tyr521. Surprisingly, the insulin receptor (IR) tyrosine kinase was found to target Munc18c at Tyr521 in vitro, rapidly binding and phosphorylating endogenous Munc18c within adipocytes and skeletal muscle. IR, but not phosphatidylinositol 3-kinase, activation was required. Altogether, we identify IR as the first known tyrosine kinase for Munc18c as part of a new insulin-signaling step in GLUT4 vesicle exocytosis, exemplifying a new model for the coordination of SNARE assembly and vesicle mobilization events in response to a single extracellular stimulus.     

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.