SPDI: Data Model for Variants and Applications at NCBI

Abstract

MotivationNormalizing diverse representations of sequence variants is critical to the elucidation of the genetic basis of disease and biological function. NCBI has long wrestled with integrating data from multiple submitters to build databases such as dbSNP and ClinVar. Inconsistent representation of variants among variant callers, local databases, and tools results in discrepancies and duplications that complicate analysis. Current tools are not robust enough to manage variants in different formats and different reference sequence coordinates. ResultsThe SPDI (pronounced "speedy") data model defines variants as a sequence of 4 operations: start at the boundary before the first position in the sequence S , advance P positions, delete D positions, then insert the sequence in the string I, giving the data 1 model its name, SPDI. The SPDI model can thus be applied to both nucleotide and protein variants, but the services discussed here are limited to the nucleotide. Current services convert representations between HGVS, VCF, and SPDI and provide two forms of normalization. The first, based on the NCBI Variant Overprecision Correction Algorithm, returns a unique, normalized representation termed the "Contextual Allele" for any input. The SPDI name, with its four operations, defines exactly the reference subsequence potentially affected by the variant, even in low complexity regions such as homopolymer and dinucleotide sequence repeats. The second level of normalization depends on alignment dataset (ADS). SPDI services perform remapping (AKA lift-over) of variants from the input reference sequence to return a list of all equivalent Contextual Alleles based on the transcript or genomic sequences that were aligned. One of these contextual alleles is selected to represent all, usually, that based on the latest genomic assembly such as GRCh38 and is designated as the unique "Canonical Allele". ADS includes alignments between non-assembly RefSeq sequences (prefixed NM, NR, NG), as well inter-and intra-assembly-associated genomic sequences (NCs, NTs, and NWs) and this allows for robust remapping and normalization of variants across sequences and assembly versions. Availability and implementationThe SPDI services are available for open access at: https://api.ncbi.nlm.nih.gov/variation/v0/

Deletion of Sphingosine 1-Phosphate Receptor 1 in cardiomyocytes during development leads to abnormal ventricular conduction and fibrosis

“…In terms of genetic cardiomyopathies, pathogenic S1PR1 variants have not been described in humans. However, the Genome Aggregation Database (gnomAD), a data set of 125,748 exome sequences and 15,708 whole-genome sequences from unrelated individuals, identified two unique frameshift variant alleles at amino acid positions 255 and 256 (rs1166435525 and rs1395550411 in the dbSNP database, respectively) [39,40]. These two variants disrupt S1P1 at the origin of transmembrane domain six.…”

The GA4GH Variation Representation Specification (VRS): a Computational Framework for the Precise Representation and Federated Identification of Molecular Variation

“…That is, the same empirical resulting sequence could be represented with multiple variation expressions. Normalization is the process by which a representation is converted into a single canonical form 11,[28][29][30] . VRS adopts the use of a fully-justified representation (Figure 3b), ensuring that insertions and deletions in repetitive regions are not arbitrarily located to a specific position within a sequence, but instead describe the alteration over the entire region of ambiguity.…”

“…Coordinates are the location of the insertion on the reference sequence depicted in panel A, using residue or inter-residue coordinates as specified by the corresponding representation system. (C) Full-justification Allele normalization is enabled by a specified normalization algorithm extended from VOCA 28 . In this example, the unnormalized Allele “reference” and “alternate” sequences (step 0) are trimmed of their common suffix “CA” (step 1).…”

“…VRS adopts the use of a fully-justified representation ( Figure 3b ), ensuring that insertions and deletions in repetitive regions are not arbitrarily located to a specific position within a sequence, but instead describe the alteration over the entire region of ambiguity. This is achieved through the VRS Allele Normalization algorithm ( Figure 3c ; Supplemental Methods ), which is an extension of NCBI’s Variant Overprecision Correction Algorithm (VOCA) 28 . Notably, the normalization method used to describe ambiguous insertions in repetitive regions only applies to Literal Sequence insertions, analogous to the use of the 3’ rule for HGVS insertions in these regions.…”

Progress, Challenges, and Surprises in Annotating the Human Genome

“…As early as 1993, a standard gene-based nomenclature was proposed ( 11 ) that would later become the Human Genome Variation Society notation. This approach, however, produces several ambiguous edge cases that hamper exact determination ( 68 ).…”