Cardiac Genetic Predisposition in Sudden Infant Death Syndrome

Background

Sudden infant death syndrome (SIDS) is a leading cause of postneonatal mortality. Genetic heart diseases (GHDs) underlie some cases of SIDS.

Rhesus monkey tryptophan hydroxylase-2 coding region haplotypes affect mRNA stability

Tryptophan hydroxylase-2 (TPH2) synthesizes neuronal 5-HT and its genetic variance is associated with numerous behavioral traits and psychiatric disorders. This study characterized the functional significance of two nonsynonymous single nucleotide polymorphisms (SNPs) (C74A and G223A) in rhesus monkey TPH2 (mTPH2). Four haplotypes of mTPH2 were cloned into pcDNA3.1 and stably transfected into PC12 cells. The levels of mTPH2 mRNA and protein were assessed by quantitative real-time PCR and Western blot, respectively, while the intracellular 5-HT was measured by enzyme-linked immunosorbent assay (ELISA). The variant A-A haplotype showed significantly higher levels of mTPH2 mRNA and protein, as well as significantly higher 5-HT production than the wild-type C-G haplotype, while the other two variant haplotypes (C-A and A-G) also tended to produce more 5-HT than C-G haplotype when stably expressed in PC12 cells. Both C74A and G223A were predicted to change mRNA secondary structure, and analysis of the mRNA stability showed that the wild-type C-G haplotype mRNA degrades more quickly than mRNAs of the mutant mTPH2 haplotypes in both stable PC12 and transient HEK-293 cells. This study demonstrates that nonsynonymous SNPs in mTPH2 can affect mRNA stability. Our findings provide an additional mechanism by which nonsynonymous SNPs affect TPH2 function, and further our understanding of TPH2 gene expression regulation.     

Dynamic programming procedure for searching optimal models to estimate substitution rates based on the maximum-likelihood method

The substitution rate in a gene can provide valuable information for understanding its functionality and evolution. A widely used method to estimate substitution rates is the maximum-likelihood method implemented in the CODEML program in the PAML package. A limited number of branch models, chosen based on a priori information or an interest in a particular lineage(s), are tested, whereas a large number of potential models are neglected. A complementary approach is also needed to test all or a large number of possible models to search for the globally optional model(s) of maximum likelihood. However, the computational time for this search even in a small number of sequences becomes impractically long. Thus, it is desirable to explore the most probable spaces to search for the optimal models. Using dynamic programming techniques, we developed a simple computational method for searching the most probable optimal branch-specific models in a practically feasible computational time. We propose three search methods to find the optimal models, which explored O(n) (method 1) to O(n(2)) (method 2 and method 3) models when the given phylogeny has n branches. In addition, we derived a formula to calculate the number of all possible models, revealing the complexity of finding the optimal branch-specific model. We show that in a reanalysis of over 50 previously published studies, the vast majority obtained better models with significantly higher likelihoods than the conventional hypothesis model methods.     

Functional characterization of naturally occurring genetic variants in the human TLR1-2-6 gene family

Toll-like receptors (TLRs) are considered an essential component of the innate immune system, initiating inflammatory responses following infection of the host. Humans have 10 functional TLRs, differing in their subcellular distributions and the microbial agonists they sense. The phylogenetically conserved TLR1-2-6 family is unique in that TLR1 and TLR6 form heterodimers with TLR2 to mediate signalling in response to agonists. Epidemiological genetic studies have identified several TLR variants that appear to influence susceptibility to infectious diseases, but the functional consequences of which remain largely unknown. Here, we assessed the functional impact of the TLR1-2-6 variants with altered amino acid sequences segregating naturally in the human population. We used an NF-κB reporter assay in TLR-transfected human embryonic kidney 293T cells stimulated with the corresponding TLR agonists. We found that among the 41 naturally occurring variants with amino acid alterations identified in the TLR1-2-6 family, 14 of them (five TLR1, four TLR2, and five TLR6 variants) displayed marked impairment of NF-κB activation. Most of these variants are present at very low population frequencies and are population-specific. These observations suggest that rare, nonsynonymous TLR mutations are likely to have deleterious effects on immune responses and may therefore contribute to complex susceptibility to infection at the population level.     

Nonsynonymous SNPs: validation characteristics, derived allele frequency patterns, and suggestive evidence for natural selection

We experimentally investigated more than 1,200 entries in dbSNP that would change amino-acids (nsSNPs), using various subsets of DNA samples drawn from 18 global populations (approximately 1,000 subjects in total). First, we mined the data for any SNP features that correlated with a high validation rate. Useful predictors of valid SNPs included multiple submissions to dbSNP, having a dbSNP validation statement, and being present in a low number of ESTs. Together, these features improved validation rates by almost 10-fold. Higher-abundance SNPs (e.g., T/C variants) also validated more frequently. Second, we considered derived alleles and noted a considerably (approximately 10%) increased average derived allele frequency (DAF) in Europeans vs. Africans, plus a further increase in some other populations. This was not primarily due to an SNP ascertainment bias, nor to the effects of natural selection. Instead, it can be explained as a drift-based, progressive increase in DAF that occurs over many generations and becomes exaggerated during population bottlenecks. This observation could be used as the basis for novel DAF-based tests for comparing demographic histories. Finally, we considered individual marker patterns and identified 37 SNPs with allele frequency variance or FST values consistent with the effects of population-specific natural selection. Four particularly striking clusters of these markers were apparent, and three of these coincide with genes/regions from among only several dozen such domains previously suggested by others to carry signatures of selection.     

Follow-up of potential novel Graves' disease susceptibility loci, identified in the UK WTCCC genome-wide nonsynonymous SNP study

A recent association scan using a genome-wide set of nonsynonymous coding single-nucleotide polymorphisms (nsSNPs) conducted in four diseases including Graves'' disease (GD), identified nine novel possible regions of association with GD. We used a case–control approach in an attempt to replicate association of these nine regions in an independent collection of 1578 British GD patients and 1946 matched Caucasian controls. Although none of these loci showed evidence of association with GD in the independent data set, when combined with the original Wellcome Trust Case–Control Consortium study group, minor differences in allele frequencies (P⩾10⁻³) remained in the combined collection of 5924 subjects for four of the nsSNPs, present within HDLBP, TEKT1, JSRP1 and UTX. An additional 29 Tag SNPs were screened within these four gene regions to determine if further associations could be detected. Similarly, minor differences only (P=0.042–0.002) were detected in two HDLBP and two TEKT1 Tag SNPs in the combined UK GD collection. In conclusion, it is unlikely that the SNPs selected in this replication study have a significant effect on the risk of GD in the United Kingdom. Our study confirms the need for large data sets and stringent analysis criteria when searching for susceptibility loci in common diseases.     

Evolution of the V, D, and J gene segments used in the primate gammadelta T-cell receptor reveals a dichotomy of conservation and diversity

γδ T cells are an immunological enigma in that both their function in the immune response and the molecular mechanisms behind their activation remain unclear. These cells predominate in the epithelia and can be rapidly activated to provide an array of responses. However, no homologous γδ T-cell populations have been identified between humans and mice, and our understanding of what these cells recognize as ligands is limited. Here we take an alternative approach to understanding human γδ T-cell ligand recognition by studying the evolutionary forces that have shaped the V, D, and J gene segments that are used during somatic rearrangement to generate the γδ T-cell receptor. We find that distinctly different forces have shaped the γ and δ loci. The Vδ and Jδ genes are highly conserved, some even through to mouse. In contrast, the γ-locus is split: the Vγ9, Vγ10, and Vγ11 genes represent the conserved region of the Vγ gene locus whereas the remaining Vγ genes have been evolving rapidly, such that orthology throughout the primate lineage is unclear. We have also analyzed the coding versus silent substitutions between species within the V and J gene segments and find a preference for coding substitutions in the complementarity determining region loops of many of the V gene segments. Our results provide a different perspective on investigating human γδ T-cell recognition, demonstrating that diversification at particular γδ gene loci has been favored during primate evolution, suggesting adaptation of particular V domains to a changing ligand environment.     

Protein-protein interaction sites are hot spots for disease-associated nonsynonymous SNPs

Many nonsynonymous single nucleotide polymorphisms (nsSNPs) are disease causing due to effects at protein-protein interfaces. We have integrated a database of the three-dimensional (3D) structures of human protein/protein complexes and the humsavar database of nsSNPs. We analyzed the location of nsSNPS in terms of their location in the protein core, at protein-protein interfaces, and on the surface when not at an interface. Disease-causing nsSNPs that do not occur in the protein core are preferentially located at protein-protein interfaces rather than surface noninterface regions when compared to random segregation. The disruption of the protein-protein interaction can be explained by a range of structural effects including the loss of an electrostatic salt bridge, the destabilization due to reduction of the hydrophobic effect, the formation of a steric clash, and the introduction of a proline altering the main-chain conformation.