BioAider

BioAider performs visualization and analysis of genome-sequencing datasets to enable gene annotation and rapid mutation screening for genomic variation studies.

Key Features:

• Visualization and analysis: Performs visualization and analysis of genome-sequencing datasets across multiple genomes.
• Gene annotation: Conducts gene annotation across analyzed genome sequences.
• Mutation screening: Performs rapid mutation screening and identification of polymorphisms.
• Dataset-scale analysis: Was applied to analyze 3,240 SARS-CoV-2 genome sequences.
• Substitution hotspot detection: Identified 14 substitution hotspots, including 10 non-synonymous and 4 synonymous mutations.
• Functional impact prediction: Predicted mutation impacts, exemplified by NSP13-Y541C predicted to affect the unwinding activity of NSP13.
• Linked hotspot grouping: Revealed three groups of potentially linked substitution hotspots.
• SR-rich region detection: Identified an SR-rich region (amino acids 184–204) on the SARS-CoV-2 N protein distinct from SARS-CoV.
• SRXX repeat correlation: Reported that the quantity of SRXX repeat fragments within the SR-rich region correlates with evolutionary relationships among SARS-CoV-2 and related animal coronaviruses.

Scientific Applications:

• Viral genomic surveillance: Enables rapid identification of mutations and substitution hotspots in viral genomes.
• Antiviral target screening: Supports screening and prioritization of potential antiviral target sites.
• Functional mutation prioritization: Prioritizes candidate mutations for functional impact assessment, such as NSP13-Y541C.
• Replication and interaction studies: Facilitates investigation of SARS-CoV-2 replication mechanisms and nucleocapsid-matrix interactions via the SR-rich region.
• Evolutionary and zoonotic analysis: Supports analysis of evolutionary relationships and zoonotic origins through SRXX repeat fragment correlation.

Methodology:

Performs visualization and analysis of genome-sequencing datasets, gene annotation, mutation screening, identification of substitution hotspots, grouping of potentially linked hotspots, and prediction of mutation impacts applied to SARS-CoV-2 genomes.