Visualization and review of reads alignment on the graphical pan-genome with VAG

Abstract

AbstractRecent advances in pangenomics have led to the rapid development of graph-based pangenomes that code genetic variant as nodes and edges preserve the contiguity of the sequence and structural variation between individuals. Data visualization is an essential component of genomic data analysis. However, the further application of the graph-based pangenome is still suffered from lacking bioinformatics tools to visualize graph format pangenomes and understand the reads alignment on graph pangenomes. In this research, we developed a novel bioinformatics platform, VAG (Visualizing read alignments in graph genomes), to overcome these challenges. VAG includes multifunctional modules integrated into a single command line and an online visualization platform supported through a web server. This tool can extract specific sequence regions from a graph pangenome and display read alignments on different paths of a graph pangenome. In addition, VAG provides population-level presence/absence variations frequency analysis and sequence path navigation to identify the population differentiation regions. To demonstrate the usage, we investigated genetic variations using a rice graph pangenome with population-level sequencing data to identify important genes and gene clusters underlying theindica–japonicadifferentiation with VAG. After investigating read alignments on the graph pangenome, we identified many false-positive alignments due to TE insertions. To reduce the impact of these misleading alignments, we developed a navigation module to determine and filter those false-positive alignments based on the pair-end alignment information. The utilization of mate-pair information in VAG provides a reliable reference for variation identification. Additionally, we developed a VAG web server to provide a user-friendly and interactive platform to visualize the read alignment data. VAG was also applied to SV discovery in the cucumber and soybean graph-based pangenome and details of VAG can be accessed by the following website (https://ricegenomichjx.xiaomy.net/VAG/sequenceextraction.php).