A mutation map for human glycoside hydrolase genes

Glycoside hydrolases (GHs) are found in all domains of life, and at least 87 distinct genes encoding proteins related to GHs are found in the human genome. GHs serve diverse functions from digestion of dietary polysaccharides to breakdown of intracellular oligosaccharides, glycoproteins, proteoglycans and glycolipids. Congenital disorders of GHs (CDGHs) represent more than 30 rare diseases caused by mutations in one of the GH genes. We previously used whole-exome sequencing of a homogenous Danish population of almost 2000 individuals to probe the incidence of deleterious mutations in the human glycosyltransferases (GTs) and developed a mutation map of human GT genes (GlyMAP-I). While deleterious disease-causing mutations in the GT genes were very rare, and in many cases lethal, we predicted deleterious mutations in GH genes to be less rare and less severe given the higher incidence of CDGHs reported worldwide. To probe the incidence of GH mutations, we constructed a mutation map of human GH-related genes (GlyMAP-II) using the Danish WES data, and correlating this with reported disease-causing mutations confirmed the higher prevalence of disease-causing mutations in several GH genes compared to GT genes. We identified 76 novel nonsynonymous single-nucleotide variations (nsSNVs) in 32 GH genes that have not been associated with a CDGH phenotype, and we experimentally validated two novel potentially damaging nsSNVs in the congenital sucrase-isomaltase deficiency gene, SI. Our study provides a global view of human GH genes and disease-causing mutations and serves as a discovery tool for novel damaging nsSNVs in CDGHs.

A new NOTCH3 damaging variant in a thrombocytopenia family of Miao ethnic group

BACKGROUND

Pediatric inherited thrombocytopenia, also known as a deficiency of platelets in children, is caused by genetic factors and it is hard to obtain an effective treatment. Thus, it is necessary to identify the possible genetic variants that are responsible for thrombocytopenia.

METHODS

Whole exome sequencing was used to detect genetic variants in two members of a thrombocytopenia family of Miao ethnic group. Multiple in silico analyses were performed to evaluate the effects of the novel missense variants.

RESULTS

Finally, a novel variant (chr19: g.15170364G>A) in the NOTCH3 gene was found, as confirmed with Sanger sequencing, which could result in a R1694Q substitution in the protein. This variant was consistently suggested to be damaging by sift (Sorting Tolerant From Intolerant; http://sift.jcvi.org), polyphen (Polymorphism Phenotyping, version 2.0; http://genetics.bwh.harvard.edu/pph2) and mutationtaster (http://www.mutationtaster.org) software. By building the 3D model of the key region of NOTCH3 protein and performing the structure simulation, we found that (i) this variant affected the 3D structure model with a root-mean-square deviation = 0.46 between wild-type and mutant type; (ii) this variant caused the protein to reduce the solvent accessible surface area by 421 Å² ; and (iii) compared to the wild-type protein, the mutant protein had two less amino acids to maintain protein stability.

CONCLUSIONS

A novel damaging variant in the NOTCH3 gene was identified in a thrombocytopenia family with respect to decreasing the stability of NOTCH3, which may help with the prognosis and therapy of inherited thrombocytopenia.

Building a Hybrid Physical-Statistical Classifier for Predicting the Effect of Variants Related to Protein-Drug Interactions

A key issue in drug design is how population variation affects drug efficacy by altering binding affinity (BA) in different individuals, an essential consideration for government regulators. Ideally, we would like to evaluate the BA perturbations of millions of single-nucleotide variants (SNVs). However, only hundreds of protein-drug complexes with SNVs have experimentally characterized BAs, constituting too small a gold standard for straightforward statistical model training. Thus, we take a hybrid approach: using physically based calculations to bootstrap the parameterization of a full model. In particular, we do 3D structure-based docking on ∼10,000 SNVs modifying known protein-drug complexes to construct a pseudo gold standard. Then we use this augmented set of BAs to train a statistical model combining structure, ligand and sequence features and illustrate how it can be applied to millions of SNVs. Finally, we show that our model has good cross-validated performance (97% AUROC) and can also be validated by orthogonal ligand-binding data.

Deleterious effects of non-synonymous single nucleotide variants of human IL-1β gene

The IL-1β gene is currently topic of interest for its important role in the pathogenesis of intervertebral disk degeneration. The new sequencing technology makes it crucial to study the effects of variants in IL-1β. Thus, 714 IL-1β variants with evidence supporting were collected from the EMBL database. Among them, 62 were non-synonymous single nucleotide variants (nsSNVs). Furthermore, six common nsSNVs were predicted to have damaging effects by SIFT, PolyPhen, PROVEAN and SNPs&GO. Based on the constructed three-dimensional structure of pro-IL-1β, rs375479974 with a mutation of Phe to Ser was proposed to reduce the stability of the pro-IL-1β protein. The rs375479974 variant was found to cause least common stabilizing amino acid residues, decrease hydrophilic and increase hydrophobic surface areas in the greatest degree, and have the lowest free energy alterations in I-Mutant 2.0 sequence analysis. When analyzing the interaction between the experimental 3D structure of mature IL-1β and its neutralizing McAb canakinumab complex, the rs775174784 substitution of Leu with Phe was found to attenuate this interaction by reducing binding energy, while rs375479974 not. Molecular dynamics simulation results in intervertebral disk environment supported rs775174784's effects. These results suggest that both rs375479974 and rs775174784 may have potential clinical and drug target implications.

Identification of Damaging nsSNVs in HumanERCC2 Gene

The hERCC2 gene is an important DNA repair molecule for initiating Cutaneous melanoma (CM). Therefore, it is advisable to study the possible functional SNVs in hERCC2. To achieve this goal, we collected total 2, 253 SNVs in hERCC2from the EMBL website, of which 303 are non-synonymous single nucleotide variants (nsSNVs). Then, SIFT and PolyPhen were used to predict the damaging nsSNVs, and four nsSNVs (rs368866996, rs377739017, rs370819591, and rs121913022) were suggested to be damaging mutations. Since I-Mutant2.0 showed a decrease in stability for the mutants containing each of the four nsSNVs, a 3D protein structure was modeled. Based on the comparison of the energy after minimization, RMSD and stabilizing residues between the native and mutant proteins' structure, rs121913022 was proposed to be the most damaging variant among the nsSNVs in hERCC2 gene by decreasing the stability of protein. The mutant G713R of hERCC2 protein caused by rs121913022 was found to have less expression level than native hERCC2 protein in melanoma cells. These results suggest that rs121913022 may have potentially important clinical and drug target implications.

A glycogene mutation map for discovery of diseases of glycosylation

Glycosylation of proteins and lipids involves over 200 known glycosyltransferases (GTs), and deleterious defects in many of the genes encoding these enzymes cause disorders collectively classified as congenital disorders of glycosylation (CDGs). Most known CDGs are caused by defects in glycogenes that affect glycosylation globally. Many GTs are members of homologous isoenzyme families and deficiencies in individual isoenzymes may not affect glycosylation globally. In line with this, there appears to be an underrepresentation of disease-causing glycogenes among these larger isoenzyme homologous families. However, genome-wide association studies have identified such isoenzyme genes as candidates for different diseases, but validation is not straightforward without biomarkers. Large-scale whole-exome sequencing (WES) provides access to mutations in, for example, GT genes in populations, which can be used to predict and/or analyze functional deleterious mutations. Here, we constructed a draft of a functional mutational map of glycogenes, GlyMAP, from WES of a rather homogenous population of 2000 Danes. We cataloged all missense mutations and used prediction algorithms, manual inspection and in case of carbohydrate-active enzymes family GT27 experimental analysis of mutations to map deleterious mutations. GlyMAP (http://glymap.glycomics.ku.dk) provides a first global view of the genetic stability of the glycogenome and should serve as a tool for discovery of novel CDGs.