ABBA

ABBA enhances de novo genome assembly by integrating predicted amino acid sequences from proteins to guide assembly and improve accuracy and scaffold continuity for short-read sequencing data.

Key Features:

• Comparative Gene Assembly: ABBA incorporates amino acid sequences from predicted proteins and comparative genomics to improve assembly accuracy and completeness when a closely related reference genome is available.
• Gene-Boosting Algorithm: A gene-boosting algorithm aligns predicted protein sequences with nucleotide reads to resolve ambiguities and improve scaffold continuity.
• Application to Short-Read Sequencing: Optimized for very short-read sequencing technologies, ABBA assembles bacterial genomes from millions of short reads and has been applied to the clinical isolate Pseudomonas aeruginosa strain PAb1.

Scientific Applications:

• Whole-Genome Sequencing: Enables whole-genome sequencing of novel organisms using short-read data by leveraging protein-guided comparative assembly, particularly for bacterial genomes with related sequenced species.
• Clinical Microbiology: Supports assembly and genomic characterization of clinical isolates, aiding identification and analysis of pathogenic strains such as Pseudomonas aeruginosa strain PAb1.

Methodology:

ABBA processes large volumes of short nucleotide reads together with predicted amino acid sequences and uses a gene-boosting algorithm to align protein sequences to nucleotide reads to enhance scaffold formation, resolve gaps and ambiguities, and produce contigs and scaffolds.