SapBase (Sapinaceae Genomic DataBase): a central portal for functional and comparative genomics of Sapindaceae species

Abstract

Sapindaceae is a family of flowering plants, also known as the soapberry family, comprising 141 genera and about 1900 species (Pedro et al., 2010). Most of them are distributed in tropical and subtropical regions, including trees, shrubs, also woody or herbaceous vines. Some are dioecious, while others are monoecious. Many Sapindaceae species possess great economic value; some furnish delicious fruits, like lychee (Litchi chinensis), longan (Dimocarpus longan), rambutan (Nephelium lappaceum); and ackee (Blighia sapida) - the national fruit of Jamaica; some produce abundance secondary metabolites, like saponin from soapberry (Sapindus mukorossi), and seed oil from yellowhorn (Xanthoceras sorbifolium); some yield valuable timber including maple (Acer spp.) and buckeye (Aesculus glabra); and some are of great herbal medicinal value, like balloon-vine (Cardiospermum halicacabum). In the last decade, with the rocketing of next generation sequencing (NGS) and genomic technologies, the full genome sequences of several Sapindaceae plants have been resolved (Lin et al., 2017; Liang et al., 2019; Yang et al., 2019; Zhang et al., 2021; Hu et al., 2022; Xue et al., 2022). Among them, our recent publication of the lychee genome attracted broad attention (Edger, 2022; Hu et al., 2022; Lyu, 2022). Now the post-genome era arrives for Sapindaceae, however, there is no public genomic database available for any Sapindaceae species, let alone an integrative database for the whole Sapindaceae family. A unified data platform is in urgent need to collect, manage and share relevant data resources. Therefore, we integrated our home-brew NGS data with all publicly available data for seven Sapindaceae plants and constructed the Sapinaceae Genomic DataBase, named SapBase (www.sapindaceae.com), in order to provide genomic resources and an online powerful analytic platform for scientific research on Sapinaceae species and comparative studies with other plants.

Genome-wide identification of Mg2+ transporters and functional characteristics of DlMGT1 in Dimocarpus longan

“…We used BLAST to match sequences, E values ≤10 -7 , homologous to AtMGTs in the genome of the longan Shixia cultivar (cv.) ( Li et al., 2022 ) using TBtools software ( Chen et al., 2020 ). We finally obtained 12 DlMGTs after removing two members (Dil.06g013540.1 and Dil.11g004700.1) lacking a transmembrane domain ( Table 1 ).…”

MicroRNA482/2118 is lineage‐specifically involved in gibberellin signalling via the regulation of GID1 expression by targeting noncoding PHAS genes and subsequently instigated phasiRNAs

“…For phylogenetic analysis, the genome and amino acid sequence of all species used in this study were obtained from Phytozome ( https://phytozome‐next.jgi.doe.gov/ ) and Sapbase (Li et al ., 2022 ). Full length of LcTASL1 and LcTASL2 were used to blast to other genome sequences by TBtools (Chen et al ., 2020 ) to identify homolog genes.…”

HortGenome Search Engine, a universal genomic search engine for horticultural crops

“…These genomic databases integrate genomes, genes, and functional annotation information, as well as transcriptome and variome data, and implement widely used data mining and analysis tools such as BLAST, functional enrichment analysis, and genome browsers [ 11–14 ]. It is noteworthy that some plant genome databases extend the integration by including non-coding RNAs or other types of ‘omics’ data [ 15–17 ]. Additionally, some databases distinguish themselves by developing unique analytical tools tailored to specific research needs or data types, such as the ‘Syntenic Gene @ Subgenome’ and ‘MicroSynteny’ modules in BRAD [ 18 ], sRNA target prediction in SapBase [ 15 ], as well as CRISPR design and GWAS tools in CPBD [ 17 ].…”

“…It is noteworthy that some plant genome databases extend the integration by including non-coding RNAs or other types of ‘omics’ data [ 15–17 ]. Additionally, some databases distinguish themselves by developing unique analytical tools tailored to specific research needs or data types, such as the ‘Syntenic Gene @ Subgenome’ and ‘MicroSynteny’ modules in BRAD [ 18 ], sRNA target prediction in SapBase [ 15 ], as well as CRISPR design and GWAS tools in CPBD [ 17 ]. Most of these databases manage genomic data for plants from a single family or species [ 19 ].…”