Rhodomyrtus tomentosa is an important fleshy-fruited tree and a well-known medicinal plant of the Myrtaceae family that is widely cultivated in tropical and subtropical areas of the world. However, studies on the evolution and genomics breeding potential of R. tomentosa were hindered by the lack of a reference genome. Here, we present a chromosome-level gap-free T2T genomic assembly of R. tomentosa using PacBio and ONT long read sequencing. We assembled the R. tomentosa with size of 470.35 Mb and contig N50 of ~43.80 Mb with 11 pseudochromosomes. We annotated a total of 33,382 genes and 239.31 Mb of repetitive sequences in this genome. Phylogenetic analysis elucidated the independent evolution of R. tomentosa start from 14.37MYA and shared a recent WGD event in Myrtaceae. We identified four major compounds of anthocyanins and their synthetic pathways in R. tomentosa. Comparative genomic and gene expression analysis suggested the coloring and high anthocyanin accumulation in R. tomentosa tends to be determined by the activation of anthocyanin synthesis pathway. The positive selection and up-regulation of MYB transcriptome factors was the implicit factors in this process, while the increase of downstream anthocyanin transport-related OMT and GST gene copy numbers were detected in R. tomentosa. Expression analysis and pathway identification enriched the importance of starch degradation, response to stimuli, effect of hormones, and cell wall metabolism during the fleshy fruit development in Myrtaceae. Our genomic assembly provide a foundation for investigating the origins and differentiation of Myrtaceae and accelerate the genetic improvement of R. tomentosa.

Recent 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 the indica/japonica differentiation 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).