VAAST

VAAST identifies and prioritizes disease-causing genetic variants by annotating, analyzing, and searching genomic sequencing data to support discovery of rare or previously undescribed pathogenic mutations.

Key Features:

• Probabilistic Algorithm: Employs a probabilistic algorithm to enhance discovery and pinpoint pathogenic variants, including rare events, in genomic sequences.
• X Chromosome Exon Sequencing: Integrates X chromosome exon sequencing data to enable detailed examination of X-linked variation and was used to identify a lethal X-linked disorder with aged appearance, craniofacial anomalies, hypotonia, global developmental delays, cryptorchidism, and cardiac arrhythmias.
• Variant Identification: Enabled identification of the c.109T>C (p.Ser37Pro) variant in the NAA10 gene, which encodes the catalytic subunit of the major human N-terminal acetyltransferase (NAT).
• Pathogenicity Assessment: Assesses pathogenic potential using criteria including absence in control populations, amino-acid conservation, predicted functional impact, and recurrence across unrelated families.
• Functional Validation Support: Facilitates linkage to biochemical assays and supported demonstration that the NAA10 p.Ser37Pro mutant protein (hNaa10p) has significantly impaired biochemical activity, consistent with reduced N-terminal acetylation.

Scientific Applications:

• Novel variant discovery: Identification and prioritization of novel disease-causing variants from sequencing data.
• X-linked disorder analysis: Detection and characterization of pathogenic variants on the X chromosome using exon sequencing data.
• Functional consequence inference: Prioritization of variants for biochemical validation and interpretation of effects on N-terminal acetylation (hNaa10p/NAT).
• Mechanistic insight: Integration of variant data with conservation and predicted impact to provide insights into molecular mechanisms underlying human genetic diseases.

Methodology:

Combines high-throughput sequencing data with probabilistic and other bioinformatics algorithms for variant annotation, analysis, and search, incorporating X chromosome exon sequencing and assessments such as absence in control populations, amino-acid conservation, and predicted functional impact.