Structure-based mutagenesis reveals the albumin-binding site of the neonatal Fc receptor

Albumin is the most abundant protein in blood where it has a pivotal role as a transporter of fatty acids and drugs. Like IgG, albumin has long serum half-life, protected from degradation by pH-dependent recycling mediated by interaction with the neonatal Fc receptor, FcRn. Although the FcRn interaction with IgG is well characterized at the atomic level, its interaction with albumin is not. Here we present structure-based modelling of the FcRn–albumin complex, supported by binding analysis of site-specific mutants, providing mechanistic evidence for the presence of pH-sensitive ionic networks at the interaction interface. These networks involve conserved histidines in both FcRn and albumin domain III. Histidines also contribute to intramolecular interactions that stabilize the otherwise flexible loops at both the interacting surfaces. Molecular details of the FcRn–albumin complex may guide the development of novel albumin variants with altered serum half-life as carriers of drugs

Genome wide in silico SNP-tumor association analysis

BACKGROUND: Carcinogenesis occurs, at least in part, due to the accumulation of mutations in critical genes that control the mechanisms of cell proliferation, differentiation and death. Publicly accessible databases contain millions of expressed sequence tag (EST) and single nucleotide polymorphism (SNP) records, which have the potential to assist in the identification of SNPs overrepresented in tumor tissue. METHODS: An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106). RESULTS: A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigation CONCLUSIONS: This novel in silico approach can assist in prioritization of genes and SNPs in the effort to elucidate the genetic mechanisms underlying the development of cancer

Genes to Diseases (G2D) Computational Method to Identify Asthma Candidate Genes

Asthma is a complex trait for which different strategies have been used to identify its environmental and genetic predisposing factors. Here, we describe a novel methodological approach to select candidate genes for asthma genetic association studies. In this regard, the Genes to Diseases (G2D) computational tool has been used in combination with a genome-wide scan performed in a sub-sample of the Saguenay−Lac-St-Jean (SLSJ) asthmatic familial collection (n = 609) to identify candidate genes located in two suggestive loci shown to be linked with asthma (6q26) and atopy (10q26.3), and presenting differential parent-of-origin effects. This approach combined gene selection based on the G2D data mining analysis of the bibliographic and protein public databases, or according to the genes already known to be associated with the same or a similar phenotype. Ten genes (LPA, NOX3, SNX9, VIL2, VIP, ADAM8, DOCK1, FANK1, GPR123 and PTPRE) were selected for a subsequent association study performed in a large SLSJ sample (n = 1167) of individuals tested for asthma and atopy related phenotypes. Single nucleotide polymorphisms (n = 91) within the candidate genes were genotyped and analysed using a family-based association test. The results suggest a protective association to allergic asthma for PTPRE rs7081735 in the SLSJ sample (p = 0.000463; corrected p = 0.0478). This association has not been replicated in the Childhood Asthma Management Program (CAMP) cohort. Sequencing of the regions around rs7081735 revealed additional polymorphisms, but additional genotyping did not yield new associations. These results demonstrate that the G2D tool can be useful in the selection of candidate genes located in chromosomal regions linked to a complex trait

Functional Polymorphisms in IL13 Are Protective against High Schistosoma mansoni Infection Intensity in a Brazilian Population

IL-13 is a signature cytokine of the helper T cell type 2 (TH2) pathway which underlies host defense to helminthic infection and activates production of IgE in both parasitized populations and in urban settings after allergen exposure.Two functional polymorphisms in IL13, rs1800925 (or c.1-1111C>T) and rs20541 (or R130Q) were previously found to be associated with Schistosoma hematobium infection intensity. They have not been thoroughly explored in S. mansoni-endemic populations, however, and were selected along with 5 tagging SNPs for genotyping in 812 individuals in 318 nuclear families from a schistosomiasis-endemic area of Conde, Bahia, in Brazil. Regression models using GEE to account for family membership and family-based quantitative transmission disequilibrium tests (QTDT) were used to evaluate associations with total serum IgE (tIgE) levels and S. mansoni fecal egg counts adjusted for non-genetic covariates. We identified a protective effect for the T allele at rs20541 (P = 0.005) against high S. mansoni egg counts, corroborated by QTDT (P = 0.014). Our findings also suggested evidence for protective effects for the T allele at rs1800925 and A allele at rs2066960 after GEE analysis only (P = 0.050, 0.0002).The two functional variants in IL13 are protective against high S. mansoni egg counts. These markers showed no evidence of association with tIgE levels, unlike tIgE levels previously studied in non-parasitized or atopic study populations

Inverted Expression Profiles of Sex-Biased Genes in Response to Toxicant Perturbations and Diseases

10.1371/journal.pone.0056668PLoS ONE82

Genetic Interactions between Chromosomes 11 and 18 Contribute to Airway Hyperresponsiveness in Mice

We used two-dimensional quantitative trait locus analysis to identify interacting genetic loci that contribute to the native airway constrictor hyperresponsiveness to methacholine that characterizes A/J mice, relative to C57BL/6J mice. We quantified airway responsiveness to intravenous methacholine boluses in eighty-eight (C57BL/6J X A/J) F2 and twenty-seven (A/J X C57BL/6J) F2 mice as well as ten A/J mice and six C57BL/6J mice; all studies were performed in male mice. Mice were genotyped at 384 SNP markers, and from these data two-QTL analyses disclosed one pair of interacting loci on chromosomes 11 and 18; the homozygous A/J genotype at each locus constituted the genetic interaction linked to the hyperresponsive A/J phenotype. Bioinformatic network analysis of potential interactions among proteins encoded by genes in the linked regions disclosed two high priority subnetworks - Myl7, Rock1, Limk2; and Npc1, Npc1l1. Evidence in the literature supports the possibility that either or both networks could contribute to the regulation of airway constrictor responsiveness. Together, these results should stimulate evaluation of the genetic contribution of these networks in the regulation of airway responsiveness in humans

Species-Specific Expansion and Molecular Evolution of the 3-hydroxy-3-methylglutaryl Coenzyme A Reductase (HMGR) Gene Family in Plants

Kazakh dandelion (Taraxacum kok-saghyz, Tk) is a rubber-producing plant currently being investigated as a source of natural rubber for industrial applications. Like many other isoprenoids, rubber is a downstream product of the mevalonate pathway. The 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) enzyme catalyzes the conversion of 3-hydroxy-3-methylglutaryl-CoA to mevalonic acid, a key regulatory step in the MVA pathway. Such regulated steps provide targets for increases in isoprenoid and rubber contents via genetic engineering to increase enzyme activities. In this study, we identify a TkHMGR1 gene that is highly expressed in the roots of Kazakh dandelion, the main tissue where rubber is synthesized and stored. This finding paves the way for further molecular and genetic studies of the TkHMGR1 gene, and its role in rubber biosynthesis in Tk and other rubber-producing plants

Epistasis: Obstacle or Advantage for Mapping Complex Traits?

Identification of genetic loci in complex traits has focused largely on one-dimensional genome scans to search for associations between single markers and the phenotype. There is mounting evidence that locus interactions, or epistasis, are a crucial component of the genetic architecture of biologically relevant traits. However, epistasis is often viewed as a nuisance factor that reduces power for locus detection. Counter to expectations, recent work shows that fitting full models, instead of testing marker main effect and interaction components separately, in exhaustive multi-locus genome scans can have higher power to detect loci when epistasis is present than single-locus scans, and improvement that comes despite a much larger multiple testing alpha-adjustment in such searches. We demonstrate, both theoretically and via simulation, that the expected power to detect loci when fitting full models is often larger when these loci act epistatically than when they act additively. Additionally, we show that the power for single locus detection may be improved in cases of epistasis compared to the additive model. Our exploration of a two step model selection procedure shows that identifying the true model is difficult. However, this difficulty is certainly not exacerbated by the presence of epistasis, on the contrary, in some cases the presence of epistasis can aid in model selection. The impact of allele frequencies on both power and model selection is dramatic