KaGE: Kappaphycus alvarezii Genome Explorer

Welcome to KaGE - the Kappaphycus alvarezii Genome Explorer.
Use this platform to browse the complete, assembled genome of Kappaphycus alvarezii, accompanying annotations and perform basic analyses on this data.

For more information about the genome assembly consult the following:
High-quality de novo genome assembly of Kappaphycus alvarezii based on both PacBio and HiSeq sequencing (Jia et al., 2020)

To cite KaGE resources please refer to:
The Kappaphycus alvarezii Genome Explorer (KaGE): Bioinformatics Resources for a globally cultivated seaweed" (Fahrenkrug SC, Crisostomo B, and Roleda M, 2023)


The sustainability of eucheumatoid production must balance the productivity of monoculture with the need for genetic variation, to adapt to increasing biotic and abiotic pressures. We are characterizing the genetic composition and variation in wild and farmed Kappaphycus alvarezii (Kalv) in the Philippines and Brasil.

To facilitate these studies we have developed the Kappaphycus alvarezii Genome Explorer (KaGE) by annotating and integrating the Kalv reference genome (BRAKER2) and curated public and private gene expression data (FINDER), and predicting a proteome based on homology, phylogeny and hidden Markov models (eggNOG, MCL, BLAST2GO, InterProScan, Kofam-KOALA, dbCAN2). Further, we built a JBrowse genome explorer that tracks the location and structure of coding and non-coding genes, repetitive elements, telomeres, polymorphisms, gene expression data, and DNA sequences targetable by CRISPR. KaGE is integrated with a functional annotation explorer that enables navigation of gene and transcript models, gene ontology, protein clusters, and metabolic networks & pathways (KEGG, BiGG, MetaCyc, REACTOME). Finally, we implemented a Galaxy pipeline to pre-process, map and quantify user data, with an RShiny Web application for conducting and visualizing over-representation and gene set enrichment analysis (ORA and GSEA).

Comparing the gene and repetitive-element complement in Kalv to other Rhodophytes, reveals genome expansions and apparent endosymbiotic gene transfer. Furthermore, SNP and RNAseq data effectively differentiated wildtype (brown vs green) and commercial cultivars, revealing metabolic pathways responsible for strain compositional differences. Additional DNA sequence, genotypes and gene expression data will facilitate the development of molecular genetic systems for managing and improving Kalv cultivars.

Our Gene prediction Workflow

Our Functional Annotation Pipeline