Ile90Met, a novel mutation in the cardiac troponin T gene for familial hypertrophic cardiomyopathy in a Chinese pedigree

A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits

BACKGROUND

Genomic selection is an effective tool for animal and plant breeding, allowing effective individual selection without phenotypic records through the prediction of genomic breeding value (GBV). To date, genomic selection has focused on a single trait. However, actual breeding often targets multiple correlated traits, and, therefore, joint analysis taking into consideration the correlation between traits, which might result in more accurate GBV prediction than analyzing each trait separately, is suitable for multi-trait genomic selection. This would require an extension of the prediction model for single-trait GBV to multi-trait case. As the computational burden of multi-trait analysis is even higher than that of single-trait analysis, an effective computational method for constructing a multi-trait prediction model is also needed.

RESULTS

We described a Bayesian regression model incorporating variable selection for jointly predicting GBVs of multiple traits and devised both an MCMC iteration and variational approximation for Bayesian estimation of parameters in this multi-trait model. The proposed Bayesian procedures with MCMC iteration and variational approximation were referred to as MCBayes and varBayes, respectively. Using simulated datasets of SNP genotypes and phenotypes for three traits with high and low heritabilities, we compared the accuracy in predicting GBVs between multi-trait and single-trait analyses as well as between MCBayes and varBayes. The results showed that, compared to single-trait analysis, multi-trait analysis enabled much more accurate GBV prediction for low-heritability traits correlated with high-heritability traits, by utilizing the correlation structure between traits, while the prediction accuracy for uncorrelated low-heritability traits was comparable or less with multi-trait analysis in comparison with single-trait analysis depending on the setting for prior probability that a SNP has zero effect. Although the prediction accuracy with varBayes was generally lower than with MCBayes, the loss in accuracy was slight. The computational time was greatly reduced with varBayes.

CONCLUSIONS

In genomic selection for multiple correlated traits, multi-trait analysis was more beneficial than single-trait analysis and varBayes was much advantageous over MCBayes in computational time, which would outweigh the loss of prediction accuracy caused by the approximation procedure, and is thus considered a practical method of choice.

Mutations in the beta-myosin heavy chain gene in southern Chinese families with hypertrophic cardiomyopathy

In this study, 14 unrelated hypertrophic cardiomyopathy (HCM) probands were scanned by polymerase chain reaction-single-strand conformation polymorphism analysis and DNA sequencing. Three mis-sense mutations of the beta-myosin heavy chain gene, MYH7, were found: valine (Val) 606 methionine (Met), arginine (Arg) 694 leucine (Leu), and Arg 723 glycine (Gly). All are reported here for the first time in Chinese subjects. The results showed that: Val606Met is an intermediate malignancy mutation; Arg694Leu is a novel mutation with a benign phenotype; and the Arg723Gly mutation is linked to malignancy - it can lead not only to HCM but also to dilated cardiomyopathy at various ages. The clinical symptoms associated with Arg723Gly emerged early and caused more severe clinical manifestation and poorer prognosis in females than in males. Mis-sense mutations were not detected in the myosin binding protein C, cardiac, cardiac troponin T type 2, or cardiac troponin I type 3 genes. The MYH7 gene may be an HCM mutation hotspot in the Chinese and have unique features in this study population.

Pathogenic peptide deviations support a model of adaptive evolution of chordate cardiac performance by troponin mutations

In cardiac muscle, the troponin (cTn) complex is a key regulator of myofilament calcium sensitivity because it serves as a molecular switch required for translating myocyte calcium fluxes into sarcomeric contraction and relaxation. Studies of several species suggest that ectotherm chordates have myofilaments with heightened calcium responsiveness. However, genetic polymorphisms in cTn that cause increased myofilament sensitivity to activating calcium in mammals result in cardiac disease including arrhythmias, diastolic dysfunction, and increased susceptibility to sudden cardiac death. We hypothesized that specific residue modifications in the regulatory arm of troponin I (TnI) were critical in mediating the observed decrease in myofilament calcium sensitivity within the mammalian taxa. We performed large-scale phylogenetic analysis, atomic resolution molecular dynamics simulations and modeling, and computational alanine scanning. This study provides evidence that a His to Ala substitution within mammalian cardiac TnI (cTnI) reduced the thermodynamic potential at the interface between cTnI and cardiac TnC (cTnC) in the calcium-saturated state by disrupting a strong intermolecular electrostatic interaction. This key residue modification reduced myofilament calcium sensitivity by making cTnI molecularly untethered from cTnC. To meet the requirements for refined mammalian adult cardiac performance, we propose that compensatory evolutionary pressures favored mutations that enhanced the relaxation properties of cTn by decreasing its sensitivity to activating calcium.