GARFIELD-NGS: Genomic vARiants FIltering by dEep Learning moDels in NGS.

Summary: Exome sequencing approach is extensively used in research and diagnostic laboratories to discover pathological variants and study genetic architecture of human diseases. However, a significant proportion of identified genetic variants are actually false positive calls, and this pose serious challenge for variants interpretation. Here, we propose a new tool named Genomic vARiants FIltering by dEep Learning moDels in NGS (GARFIELD-NGS), which rely on deep learning models to dissect false and true variants in exome sequencing experiments performed with Illumina or ION platforms. GARFIELD-NGS showed strong performances for both SNP and INDEL variants (AUC 0.71-0.98) and outperformed established hard filters. The method is robust also at low coverage down to 30X and can be applied on data generated with the recent Illumina two-colour chemistry. GARFIELD-NGS processes standard VCF file and produces a regular VCF output. Thus, it can be easily integrated in existing analysis pipeline, allowing application of different thresholds based on desired level of sensitivity and specificity. Availability and implementation: GARFIELD-NGS available at https://github.com/gedoardo83/GARFIELD-NGS. Supplementary information: Supplementary data are available at Bioinformatics online.

Real-world clinical applicability of pathogenicity predictors assessed on SERPINA1 mutations in alpha-1-antitrypsin deficiency.

The growth of publicly available data informing upon genetic variations, mechanisms of disease, and disease subphenotypes offers great potential for personalized medicine. Computational approaches are likely required to assess a large number of novel genetic variants. However, the integration of genetic, structural, and pathophysiological data still represents a challenge for computational predictions and their clinical use. We addressed these issues for alpha-1-antitrypsin deficiency, a disease mediated by mutations in the SERPINA1 gene encoding alpha-1-antitrypsin. We compiled a comprehensive database of SERPINA1 coding mutations and assigned them apparent pathological relevance based upon available data. "Benign" and "pathogenic" variations were used to assess performance of 31 pathogenicity predictors. Well-performing algorithms clustered the subset of variants known to be severely pathogenic with high scores. Eight new mutations identified in the ExAC database and achieving high scores were selected for characterization in cell models and showed secretory deficiency and polymer formation, supporting the predictive power of our computational approach. The behavior of the pathogenic new variants and consistent outliers were rationalized by considering the protein structural context and residue conservation. These findings highlight the potential of computational methods to provide meaningful predictions of the pathogenic significance of novel mutations and identify areas for further investigation.

Genomic and biochemical characterization of sialic acid acetylesterase (siae) in zebrafish.

Sialic acid acetylesterase (SIAE) removes acetyl moieties from the carbon 9 and 4 hydroxyl groups of sialic acid and recently a debate has been opened on its association to autoimmunity. Trying to get new insights on this intriguing enzyme we have studied siae in zebrafish (Danio rerio). In this teleost siae encodes for a polypeptide with a high degree of sequence identity to human and mouse counterparts. Zebrafish Siae behavior upon transient expression in COS7 cells is comparable to human enzyme concerning pH optimum of enzyme activity, subcellular localization and glycosylation. In addition, and as already observed in case of human SIAE, the glycosylated form of the enzyme from zebrafish is released into the culture media. During embryogenesis, in situ hybridization experiments demonstrate that siae transcript is always detectable during development, with a more specific expression in the central nervous system, in pronephric ducts and liver in the more advanced stages of the embryo development. In adult fish an increasing amount of siae mRNA is detectable in heart, eye, muscle, liver, brain, kidney and ovary. These results provide novel information about Siae and point out zebrafish as animal model to better understand the biological role(s) of this rather puzzling enzyme in vertebrates, regarding immune system function and the development of central nervous system.

Author Correction: A novel homozygous mutation in GAD1 gene described in a schizophrenic patient impairs activity and dimerization of GAD67 enzyme.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A novel homozygous mutation in GAD1 gene described in a schizophrenic patient impairs activity and dimerization of GAD67 enzyme.

Recently, by whole exome sequencing of schizophrenia (SCZ) patients, we identified a subject that was homozygous for a novel missense substitution (c.391 A > G) in the glutamate acid decarboxylase 1 (GAD1) gene. GAD1 encodes for GAD67 enzyme, catalyzing the production of gamma-aminobutyric acid (GABA) from L-glutamic acid. Here, we studied the impact of this mutation on GAD67 activity, dimerization and subcellular localization. Biochemical assay revealed that c.391 A > G reduces GAD67 enzymatic activity by ~30%, probably due to the impaired homodimerization of homozygous mutants as highlighted by proximity ligation assays. The mutational screening of 120 genes of the "GABAergic system" in a cohort of 4,225 SCZ cases and 5,834 controls (dbGaP: phs000473.v1.p2), did not identify other cases that were homozygous for ultra-rare variants in GAD1, but highlighted an increased frequency of cases that were homozygous for rare variants in genes of the GABA system (SCZ: 0.14% vs. Controls: 0.00%; p-value = 0.0055). In conclusion, this study demonstrates the functional impact of c.391 A > G variant and its biological effect makes it a good candidate as risk variant for SCZ. This study also supports an involvement of ultra-rare variants in GABAergic genes in the etiopathogenesis of SCZ.

In silico identification of new putative pathogenic variants in the NEU1 sialidase gene affecting enzyme function and subcellular localization.

The NEU1 gene is the first identified member of the human sialidases, glycohydrolitic enzymes that remove the terminal sialic acid from oligosaccharide chains. Mutations in NEU1 gene are causative of sialidosis (MIM 256550), a severe lysosomal storage disorder showing autosomal recessive mode of inheritance. Sialidosis has been classified into two subtypes: sialidosis type I, a normomorphic, late-onset form, and sialidosis type II, a more severe neonatal or early-onset form. A total of 50 causative mutations are reported in HGMD database, most of which are missense variants. To further characterize the NEU1 gene and identify new functionally relevant protein isoforms, we decided to study its genetic variability in the human population using the data generated by two large sequencing projects: the 1000 Genomes Project (1000G) and the NHLBI GO Exome Sequencing Project (ESP). Together these two datasets comprise a cohort of 7595 sequenced individuals, making it possible to identify rare variants and dissect population specific ones. By integrating this approach with biochemical and cellular studies, we were able to identify new rare missense and frameshift alleles in NEU1 gene. Among the 9 candidate variants tested, only two resulted in significantly lower levels of sialidase activity (p<0.05), namely c.650T>C and c.700G>A. These two mutations give rise to the amino acid substitutions p.V217A and p.D234N, respectively. NEU1 variants including either of these two amino acid changes have 44% and 25% residual sialidase activity when compared to the wild-type enzyme, reduced protein levels and altered subcellular localization. Thus they may represent new, putative pathological mutations resulting in sialidosis type I. The in silico approach used in this study has enabled the identification of previously unknown NEU1 functional alleles that are widespread in the population and could be tested in future functional studies.