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Background With the advent of whole exome (ES) and genome sequencing (GS) as tools for disease gene discovery, rare variant filtering, prioritization and data sharing have become essential components of the search for disease genes and variants potentially contributing to disease phenotypes. The computational storage, data manipulation, and bioinformatic interpretation of thousands to millions of variants identified in ES and GS, respectively, is a challenging task. To aid in that endeavor, we constructed PhenoDB, GeneMatcher and VariantMatcher. Results PhenoDB is an accessible, freely available, web-based platform that allows users to store, share, analyze and interpret their patients’ phenotypes and variants from ES/GS data. GeneMatcher is accessible to all stakeholders as a web-based tool developed to connect individuals (researchers, clinicians, health care providers and patients) around the globe with interest in the same gene(s), variant(s) or phenotype(s). Finally, VariantMatcher was developed to enable public sharing of variant-level data and phenotypic information from individuals sequenced as part of multiple disease gene discovery projects. Here we provide updates on PhenoDB and GeneMatcher applications and implementation and introduce VariantMatcher. Conclusion Each of these tools has facilitated worldwide data sharing and data analysis and improved our ability to connect genes to phenotypic traits. Further development of these platforms will expand variant analysis, interpretation, novel disease-gene discovery and facilitate functional annotation of the human genome for clinical genomics implementation and the precision medicine initiative.

Background Fabry disease is a rare X-linked inherited disorder caused by deficiency of α-Galactosidase A. Hundreds of mutations and non-coding haplotypes in the GLA gene have been described; however, many are variants of unknown significance, prompting doubts about the diagnosis and treatment. The α-Galactosidase A enzymatic activity in dried blood spot (DBS) samples are widely used for screening purposes; however, even when values below the normal are found, new tests are required to confirm the diagnosis. Here we describe an analysis of GLA variants and their correlation with DBS α-Galactosidase A enzymatic activity in a large Brazilian population with Fabry disease symptoms. Results We analyzed GLA variants by DNA sequencing of 803 male patients with suspected Fabry disease or belonging to high-risk populations; in 179 individuals, 58 different exonic variants were detected. From these, 50 are variants described as pathogenic and eight described as variants of unknown significance. The other individuals presented complex non-coding haplotypes or had no variants. Interestingly, the enzymatic activity in DBS was different among pathogenic variants and the other genotypes, including variants of unknown significance; the first presented mean of 12% of residual activity, while the others presented levels above 70% of the activity found in healthy controls. Conclusion The activity of α-Galactosidase A in DBS was markedly reduced in males with known pathogenic variants when compared with subjects presenting variants of unknown significance, non-coding haplotypes, or without variants, indicating a possible non-pathogenic potential of these latter genotypes. These findings bring a better understanding about the biochemical results of α-Galactosidase A in DBS samples, as well as the possible non-pathogenic potential of non-coding haplotypes and variants of unknown significance in GLA gene. These results certainly will help clinicians to decide about the treatment of patients carrying variants in the gene causing this rare but life-threatening disease.