The banana genome hub: a community database for genomics in the Musaceae

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Received: 13 July 2022; Accepted: 22 September 2022; Published: 28 September 2022; Corrected and Typeset: 1 December 2022
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Horticulture Research, 2022, 9: uhac221
https://doi.org/10.1093/hr/uhac221
Article
The banana genome hub: a community database for
genomics in the Musaceae
Gaëtan Droc1,2,3,*, Guillaume Martin1,2,3, Valentin Guignon3,4, Marilyne Summo1,2,3, Guilhem Sempéré3,5,6, Eloi Durant3,7,8, Alexandre Soriano1,2,3,
Franc-Christophe Baurens1,2, Alberto Cenci3,4, Catherine Breton3,4, Trushar Shah9, Jean-Marc Aury10, Xue-Jun Ge11 ,12 , Pat Heslop Harrison11, 13,
Nabila Yahiaoui1,2, Angélique D’Hont1,2 and Mathieu Rouard3,4,*
1CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
2UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
3French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
4Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier, France
5CIRAD, UMR INTERTRYP, F-34398 Montpellier, France
6INTERTRYP, Université de Montpellier, CIRAD, IRD, 34398 Montpellier, France
7Syngenta Seeds SAS, Saint-Sauveur, 31790, France
8DIADE, Univ Montpellier, CIRAD, IRD, Montpellier, 34830, France
9IITA, Nairobi P.O. Box 30709-00100, Kenya
10Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 2 rue Gaston Crémieux, 91057 Evry, France
11Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510520,
China
12Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences,Guangzhou 510520, China
13Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, UK
*Corresponding authors. E-mail: m.rouard@cgiar.org; gaetan.droc@cirad.fr
Abstract
The Banana Genome Hub provides centralized access for genome assemblies, annotations, and the extensive related omics resources
available for bananas and banana relatives. A series of tools and unique interfaces are implemented to harness the potential of
genomics in bananas, leveraging the power of comparative analysis, while recognizing the differences between datasets. Besides
effective genomic tools like BLAST and the JBrowse genome browser, additional interfaces enable advanced gene search and gene family
analyses including multiple alignments and phylogenies. A synteny viewer enables the comparison of genome structures between
chromosome-scale assemblies. Interfaces for differential expression analyses, metabolic pathways and GO enrichment were also added.
A catalogue of variants spanning the banana diversity is made available for exploration, filtering, and export to a wide variety of
software. Furthermore, we implemented new ways to graphically explore gene presence-absence in pangenomes as well as genome
ancestry mosaics for cultivated bananas. Besides, to guide the community in future sequencing efforts, we provide recommendations
for nomenclature of locus tags and a curated list of public genomic resources (assemblies, resequencing, high density genotyping) and
upcoming resources—planned, ongoing or not yet public. The Banana Genome Hub aims at supporting the banana scientific community
for basic, translational, and applied research and can be accessed at https://banana-genome- hub.southgreen.fr.
Introduction
The Musaceae, known as the banana family, belongs to the mono-
cotyledons, that comprise crops of great economic value as well
as ornamental plants. Notably, Musaceae includes the genus Musa
with bananas, a top-ten crop for food security, and arguably the
favorite fruit worldwide [1]. Its sister genus, Ensete, contains Ensete
ventricosum, an important crop for food security in Ethiopia [2]
and ornamental plants like Ensete glaucum widely distributed in
Asia. The final monospecific genus in Musaceae includes Musella
lasiocarpa from southwest China and possibly extinct in the wild.
Wild species within Musaceae are diploids, with basic chromo-
some numbers of x = 9, 10 and 11. The Musa cultivars grown
for fruit result from hybridization between different wild diploid
Musa species and subspecies. They are parthenocarpic, sterile or
poorly fertile and mostly cultivated as vegetatively propagated
triploids (2n = 3x = 33) although some cultivars are diploids or
tetraploids, most of cultivars bear large structural variations in
their chromosomes, transmitted from different wild ancestors.
All these features make banana breeding very complex. Genomic
characterization has a great potential to significantly contribute
to better conservation strategies, improved use of banana genetic
resources and increased sustainability of crop production [3,4].
Increasing the availability of genomic resources and facilitating
their use has been much needed [5,6].
In 2012, the first Musaceae reference genome, representa-
tive of Musa acuminata (A genome), was published [7]along-
side the Banana Genome Hub [8](https://banana- genome-hub.
southgreen.fr). In the last decade, this reference was iteratively
improved [9,10] while a number of new genome assemblies of
different Musaceae species have also been generated. The next
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2|Horticulture Research, 2022, 9: uhac221
sequenced genome was that of Musa balbisiana (B genome) [11],
first as a draft genome and later as a chromosome-scale assembly
from a double haploid [12]. In the meantime, draft assemblies of
Musa itinerans [13], E. ventricosum [14], Musa textilis [15] and other
subspecies of M. acuminata were produced [16]. A pangenome
composed of the 15 individuals belonging to Ensete and Musa was
also developed [17]. Benefiting from easier and cheaper access
to long reads sequencing technologies and scaffolding methods,
chromosome scale genome assemblies were released for Musa
schizocarpa [18], Ensete glaucum [19] and a telomere-to-telomere
assembly of M. acuminata was published [10]. Thanks to available
reference genomes, a broad range of studies have been conducted
to explore multiple aspects including genetic diversity [20], plant
genome evolution [21–23], chromosome structural variation [24],
gene family analyses [25–28], trait-phenotype [29,30], association
genetics [31–33] and genetic engineering [34]. All these topics
need access to various types of datasets and related query or
visualisation interfaces.
Here, we present an overhauled and enriched version of the
Banana Genome Hub (BGH), a community database that serves
as a central online platform for whole genome sequences and
related omics data on Musaceae. We detail the implemented inter-
faces, and the way data were collected and curated. Finally, we
list and discuss the status of sequencing projects and propose a
locus name nomenclature for future projects about the genomics
of Musaceae.
Tools and interfaces
We implemented a list of web interface and collected data to facil-
itate functional and comparative genomics-oriented data analy-
ses (Figure 1). Some interfaces focus on exploration of individual
genes or of a list of genes to check their location on the genome,
presence in gene families, their expression patterns, their func-
tional annotations (i.e. Gene Ontologoy (GO)) as well as associated
SNP markers. Other tools enable a more global exploration of
chromosome structures by looking at synteny, presence absence
variation and genome ancestry mosaics. From a technical per-
spective, the BGH core has been developed with the Tripal toolkit
(i.e. Drupal v7, Tripal v3), an open-source project supporting the
development of biological databases [8,35,36] complemented by
the development of additional modules [37]. All these elements
are further described below.
Gene(s) query including orthogroups and
omics-related datasets
Users have multiple ways tosearch for genes in the system, either
using a gene locus (or a list of them), keywords, genomic coordi-
nates powered by MegaSearch [38] or using the BLAST graphical
interface searches from Sequenceserver [39](Figure 2A). Results
are connected to genome browsers [37] specific to each genome.
Comparisons between genomes are facilitated by tracks showing
gene annotations projected on other genomes using the lift-over
tool. It allows at a glance to see missing genes and investigate
possible errors in the prediction of structural gene annotation [40]
(Figure 2B).
Any gene search result lists several information including
gene membership to orthogroups or gene families in Musaceae.
The three versions corresponding to the M. acuminata reference
genome (“DH Pahang” v1, v2 and v4) were conserved in the system
for traceability. To enable orthogroup visualization, we developed
extension modules that support visualisation of multiple
genome alignment and phylogenetic tree with all functionalities
provided by MSAviewer [41] and PhyloTree [42] respectively
(Figure 2C).
For users interested in gene expression patterns for specific
gene(s), we built interactive interfaces based on the shiny apps
technology (R package) to enable manipulation of data results
from published studies [29,43,44]. For instance, it is possible
to search for genes annotated as RGA2, a putative nucleotide-
binding and leucine-rich repeat (NB-LRR)-type resistance (R) gene
known to be involved in the resistance to Fusarium wilt when
overexpressed [45], and to check their level of expression in a
study linked to Fusarium wilt [29](Figure 3A).
Also, additional datasets can be uploaded in the Diane suite
[46] to perform differential gene expression analyses, expression-
based clustering and gene regulatory network analyses in which
Musa references genomes were added. Besides, when a list of
genes is identified, users can quickly test in a few clicks for
Gene Ontology enrichment for several genomes and without the
need to extract functional annotations and use external software
(Figure 3B).
With regards to other OMICS, there have been increasing num-
bers of proteomics and metabolomics experiments in banana
[30,47–50]. To complement these resources and enable various
options like experimental data overlay on metabolic pathways,
we set up the latest version of PathwayTools v25 [51], named
MusaCyc, that comprises a comprehensive set of interfaces to
cover user needs. For instance, the carotenoid pathway has been
actively studied in banana [52–54] and the Phytoene desaturase
(PDS) enzyme, that can cause albinism when disrupted, was used
as a proof of concept for gene editing. Using MusaCyc, the PDS
gene can be easily found (Figure 3C).
Genetic variant search and usage
This section, powered by the GIGWA tool [55,56], gives access
to a range of studies related to genetic diversity [57], GWAS [31,
33], Genomic selection or chromosome structure exploration [58,
59]. Notably, available studies include SNPs of the diploid banana
panel that was designed specifically for GWAS analyses [31] while
corresponding plant material for this panel can be ordered for
phenotyping at the International Transit Center (ITC) via the Musa
Germplasm Information System (MGIS) website [60,61]. After fil-
tering with advanced functionality, the datasets can be exported
in multiple formats for subsequent analyses such as genetic
diversity studies or directly visualized in JBrowse, IGV, Flapjack
(and flapjack-bytes) (Figure 4). In addition, this catalogue of vari-
ants is compliant with BrAPI v1 & v2 [62] and can be accessed
programmatically and used in third party client or databases.
Pangenome viewer and exploration
A single reference genome is not enough to capture genetic diver-
sity in a species or a genus [63,64]. To capture the diversity of
gene content across Musaceae, a draft cross genus (Musa-Ensete)
pangenome was built. It revealed distinct presence/absence
patterns between genera [17]. While global results were analysed,
exploration of specific regions along pan-chromosomes is still
to be done. To make this easier, we implemented an instance of
the Panache software [65] which enables the exploration of gene
presence/absence variations (PAV) within pan-chromosomes.
With it, users can automatically search for PAV areas and visualize
them in the interface, where each line corresponds to one of the
re-sequenced individuals (Figure 5A). Multiple sorting options
(taxonomy, presence or absence of a given gene,etc.) are proposed
to guide users toward genomic regions rich in PAV or showing a
particular pattern.
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Droc et al.|3
Figure 1. Screenshot of the Banana Genome Hub homepage showing a subset of available genome sequence and visualisation and analytical tools.
Genome ancestry mosaics viewer
Cultivated bananas result from a relatively limited number of sex-
ual events with inter(sub) specific hybridizations and recombina-
tion [67]. The different ancestral contributions can be represented
as genomic segments of distinct origin along the chromosomes.
To provide access to recent studies that reported recombination
between A and B genomes [59] and genome ancestry mosaics for
a panel of diploid and triploid bananas [66], we embedded a new
tool, called GeMo [67]. By selecting an samples like “Grande Naine”
(AAA), an autotriploid cultivar belonging to the Cavendish sub-
group, users can immediately spot the ancestral contributors of
the M. acuminata subspecies, predominantly “banksii”, “zebrina”,
“malaccensis” (Figure 5B). This viewer is intended to become a
registry for any future studies performing in silico chromosome
painting on Musaceae individuals but also enable user to manip-
ulate their own data in a non-persistent way.
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Figure 2. (A) Gene search interface enabling access results hits that can be visualized in (B) genome browser (JBrowse) with Liftoff tracks. Red arrows
indicate region that are inconsistent between gene prediction and that might need curation and (C) in an orthogroup context with associated multiple
alignments and phylogenetic tree
Figure 3. (A) Transcriptomic interface with a list of RGA2 genes from M. acuminata “DH Pahang” submitted to visualize their level of expression for a
study on Fusarium wilt. (B) GO enrichment interface with a list of genes submitted. (C) First steps of the carotenoid pathways with Phytoene
desaturase (PDS) identified by MusaCyc in the Musa acuminata genome.
Synteny viewer
The Zingiberales order evolution was shaped by lineage spe-
cific ancient whole genome duplications [7,22] and within the
Musaceae, for which the crown age was estimated at 59.19 Ma [68],
a large number of chromosome rearrangements occurred [24,69].
As an example, M. acuminata and M. balbisiana differ by a large
translocation on chromosome1/3 and a large inversion on chro-
mosome 5 [12]. To explore the chromosome structure between
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Figure 4. Overview of the genetic variant interface powered by GIGWA (A) Main interface for the GWAS panel with discriminated variants between 2
groups (seeded vs non-seeded) (B) Statistics of SNPs along Chromosome 2. (C) SNP visualization in JBrowse from the GIGWA interface (D) Data export
online for graphical previews of genotype data in Flapjack-bytes.
genome assemblies, SynVisio [70] was implemented for syntenic
block visualization. It enables the comparison of two or more
genomes (Figure 5C) and supports multi-resolution analysis and
interactive filtering. Users can compare genomes one to one or
in multi-genome mode. Conveniently, it also allows downloading
high-quality images. Such a tool will be increasingly relevant as
new assemblies are produced to visualize and understand fusion
and fission events between chromosomes in Musaceae where dif-
ferent basic chromosome numbers exist (from 7 to 11 haploid
chromosomes).
Database construction and content
Collection of genome assemblies and gene
annotation
We collected 16 publicly released Musaceae nuclear genome
sequences (8 high-quality and 8 draft sequences) that were
released publicly (Table 1) as well as 91 chloroplast assemblies
[68,71–75]. Functional annotations from InterPro were obtained
using InterProScan [76]. Gene ontology (GO) were retrieved by
combining results from interpro2go and BlastP on SwissProt and
TrEM B L [77]. For each assembly, they were compared and mapped
using Liftoff [40]. When available, TE annotations from published
studies were inserted into JBrowse.
Only minimal modifications of the assemblies or annota-
tions from their description in publications are intended, to
facilitate comparisons and traceability. In some cases, however,
we improved the gene annotation: in agreement with data
providers, we filtered M. balbisiana PKW for TE and released
a new annotation; we also released a new annotation for M.
balbisiana “DH PKW” where we reversed some chromosomes to be
consistent with the orientation in M. acuminata “DH Pahang” and
Musa schizocarpa.
Transcriptomics and pathway related datasets
Transcriptomics data supplied by the community were included
[12,43,44,79,81]. RNAseq data were mapped using STAR [82]
and added in JBrowse as mapped tracks and in the download
section. Whenever possible, derived reads count from published
transcriptomics studies were collected and connected to the tran-
scriptomics interface [29,43,44]. For pathway related informa-
tion, enzymes and metabolic pathways were predicted from the
protein-coding genes of M. acuminata “DH Pahang” v4. Enzyme
Classification (EC) numbers were predicted combining both tools
PRIAM [83] and BlastKOALA [84]. As a result, data were inferred
for 774 pathways, 6762 enzymatic reactions and 97 transport
reactions. A total of 8220 enzymes have been annotated and are
available in the pathway tools section of the BGH.
Comparative genomic analysis
We identified syntenic genes in the five chromosome scale assem-
blies available for Musaceae. Protein-coding genes were processed
to identify reciprocal best hits (RBH) with BLASTP (e-value 1e-10)
followed by MCScanX (e-value 1e-5, max gaps 25) [85].
Gene family identification
Protein-coding genes from E. glaucum v1, M. acuminata (“DH
Pahang” v2, Zebrina “Maia Oa”, “Calcutta 4” and “Banksii”),
M. balbisiana v1.1 and M. schizocarpa v1 were processed using
OrthoFinder v2.5.2 [86] with default parameters. We built the
alignments and gene trees by applying our phylogenomic
workflow, as implemented in GreenPhylDB [87].
Genetic variants
SNP markers from multiple studies were retrieved and inserted
into the GIGWA v2 genotyping database [55]. Quality checks, read
mapping on reference genomes, SNP calling and variant effect in
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Figure 5. Overview of proposed web interfaces for comparative genomics within Musaceae. (A) Overview of the Musaceae Pangenome represented with
the Panache interface. (B) Examples of genome ancestry mosaics. (C) Synteny between Ensete glaucum,Musa acuminata,Musa balbisiana and M.
schizocarpa using Synvisio.
genic regions were conducted as described in [1]. The outputs of
the analyses were produced in the variant call format (VCF), then
loaded in GIGWA with associated metadata [55].
Pangenome
Pangenome assembly, gene annotation and PAV matrix were col-
lected from [17]. The study was based on 15 accessions across
Musa and Ensete sequenced with short read technologies.To define
the presence-absence of genes in the different accessions, they
assembled the pangenome iteratively and annotated the genes in
the new contigs, then proceeded with read mapping.
Genome and transcriptome sequencing status
The curated list of SRA genomic resources was searched on NCBI
SRA [88] by filtering on Taxonomic ids for Musa and Ensete and
metadata was extracted from BioSample metadata descriptions.
Information on ongoing projects was obtained by personal com-
munications and interactions within the scientific community.
Discussion and perspectives
The Banana Genome Hub is a comprehensive platform dedicated
to the genomics of a specific plant family – the Musaceae -as
it has been developed for other families such as the Rosaceae
[89] or the Juglandaceae [90]. The core functionalities are similar
by providing access to genome datasets via JBrowse [91], BLAST,
synteny and gene families viewers. However, the BGH has some
specificities taking into account the nature of the plant and the
existing ecosystems of tools and databases in the community.
An innovative pangenomics-related interface, Panache [65],
has been implemented to support exploration of presence-
absence variation (PAV).Both provides possible valuable resources
for the design and exploration of precision genetics studies being
conducted in the genus Musa [52,92]. Besides, as a vegetatively
propagated plant with low fertility, unravelling the genome
ancestry mosaics of cultivated bananas has been initiated to
decipher it complex domestication history [66] and we provide
a unique way to store and visualize, through GeMo, future work
in that direction. For functional oriented studies, users have now
access to handy interface to check gene expression and functional
enrichment.
Furthermore, the BGH intends to complement other databases
on bananas and contribute to a better conservation and use of
Ensete and Musa genetic resources. Contrary to the other portal [89,
90], the BGH does not intend to develop its own breeding module
but rather proposes to implement BrAPI standards [62] to increase
interoperability with the Banana instance of Breedbase [93]; which
has been specifically designed for this purpose and that is actively
supported by some banana breeding programs. Like GDR [89], a
catalogue of variants is curated to provide facilitated access to
data for SNP-based published studies. This catalogue, maintained
by a different system, is shared with the Musa Germplasm Infor-
mation System (MGIS) [60] to connect with the existing diversity
of genetic resources conserved and documented in genebanks.
While the Musaceae family contains 80 species classified in
three genera, the Banana Genome Hub includes all publicly avail-
able whole genomes for eight species from two genera. Therefore,
the BGH is designed to hold more whole genomes, and still has
high potential to grow and to propose new tools to efficiently
exploit new datasets considering specificities of the crop (e.g.
polyploidy, structural variations). We will continue to curate and
add new genome assemblies and related OMICS data as they
become publicly available. Given the level of structural variation
including chromosome rearrangements that are now well docu-
mented between the six species, high quality (N50 nearing average
chromosome length) genome sequences (currently supported by
Hi-C and/or long-molecule sequencing and genetic mapping data)
are required as references.
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Tab le 1. List of genome sequence assemblies accessible via Banana Genome Hub. (CS: chromosome scale; SR: short reads; LR: long
reads)
Species Genotype Version Technology Status Comments References
Musa acuminata DH Pahang 1 Sanger +Illumina SR High quality draft 1st reference (A
genome)
[7]
M. acuminata DH Pahang 2 Illumina SR +optical
map
Improved high
quality draft
[9]
M. acuminata DH Pahang 4 Nanopore
LR +Illumina
Tel omere t o
telomere
Final version [10]
M. acuminata Banksii 2 Illumina +PacBio LR Draft CS in progress [16]
M. acuminata Maia Oa 1 Illumina SR Draft CS in progress [16]
M. acuminata Calcutta 4 1 Illumina SR Draft CS in progress [16]
Musa balbisiana PKW 1 Illumina SR Draft [11]
M. balbisiana DH PKW 1.1 Illumina SR, PacBio
LR +Hi-C
Chromosome scale B genome reference [12]
Musa itinerans - 1 Illumina SR Draft [13]
Musa schizocarpa -1Nanopore
LR +Bionano
Chromosome scale S genome [18]
Ensete glaucum -1NanoporeLR+Hi-C Chromosome scale [19]
Ensete ventricosum Bedadeti 3 Illumina SR Draft (download
only)
[14,78]
Musa textilis (abaca) abuad - Illumina SR PacBio LR Draft (download
only)
CS in progress [15]
M. acuminata Dwarf
Cavendish
1 Illumina SR Draft (download
only)
[79]
Musa troglodytarum Karat 1 Nanopore
LR +Illumina
SR +PacBio LR +Hi-C
Chromosome scale [80]
Musa beccarii 1 Nanopore LR +Hi-C Chromosome scale Early advance
Tab le 2. Examples of genebanks or germplasm collection where material can be requested for research purposes
Collection name Country # Available
Accessions
Distribution Conditions Access
International Transit Center
(ITC)
Belgium 990 International Free of charges
(SMTA)
https://www.crop-diversity.org/
mgis/moos/how-to-order
CRB Plantes Tropicales Antilles
CIRAD-INRAe (CRB-PT)
Guadeloupe,
France
381 International Free except
transport (SMTA)
http://crb-tropicaux.com/Portail
International Institute of
Tropical Agriculture (IITA)
Nigeria 275 Regional
(Africa)
Free of charges
(SMTA)
https://www.genesys-pgr.org
To guide sampling for future sequencing projects and in
an attempt to manage redundancy in data generation, we
compile information from public sources or gleaned in confer-
ences or from personal communications that will be regularly
updated online (https://banana-genome-hub.southgreen.fr/
content/sequencing-status). The first observation is that if no
genome assembly of known Musa cultivars, mostly triploids,
has been released at chromosome-scale, some are underway as
well as for additional wild species. Increasing accuracy of long-
molecule sequencing is important to assembling haplotypes in
triploid hybrids that are so important regionally and in trade. High
quality whole-genome assemblies underpin exploitation of sur-
vey sequence data for allele mining or GWAS (Genome Wide Asso-
ciation Studies) to identify functional variants. Re-sequencing
is ongoing in several germplasm collections, which will help
identifying allelic and potentially copy number variation. Also,
assemblies are available for chloroplast genomes on wild species,
sometimes redundantly, and future effort might focus on culti-
vated groups and systematically cover the diversity of the family.
Whenever possible, plant material used to generate genomic
data should be deposited in genebanks or national collections
(Table 2) where passport data, possibly associated with phenotype
information, is documented and material distribution processes
are streamlined. For instance, use of accessions from the Interna-
tional Transit Center (ITC) [60,61] or the CRB Plantes Tropicales
Antilles CIRAD-INRAe can facilitate traceability, reproducibility,
and data integration with previous and future experiments since
accessions can be sent internationally, virus indexed and free of
charge for research purposes. Furthermore, missing accessions of
interest can be also proposed to ITC for conservation.
Regarding gene annotation, we recommend adopting a defined
nomenclature for locus tag that would consider the wide range
of wild Musaceae species (Table S1). However, we acknowledge
that further work is necessary to address the case of groups and
subgroups in cultivated bananas.
Finally, we encourage scientists generating genomics data in
Musaceae to contact us or the Genomics Thematic group of
MusaNet (https://musanet.org) early in the publication process to
make sure that general standards (chromosome orientation,gene
locus) are consistent with existing resources and eventually to get
support to create dedicated pages and associated tools (BLAST,
JBrowse, download).
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Acknowledgements
This work was partially supported of the CGIAR Research Pro-
gram on Roots, Tubers and Bananas (RTB), the Agropolis Founda-
tion (ID 1504-006) “GenomeHarvest” project through the French
Investissements d’avenir programme (Labex Agro: ANR-10-LABX-
0001-01). XJ. G. acknowledges support of the National Natural
Science Foundation of China (No. 32070237, 31261140366). This
work is technically supported by the South Green Bioinformat-
ics platform and the CIRAD - UMR AGAP HPC Data Center. We
warmly thank all data providers who proactively enrich the BGH
with datasets and feedback including Sebastien Carpentier, Julie
Sardos, Sijun Zheng, Nicolas Roux (Alliance Bioversity Interna-
tional - CIAT), David Studholme (University of Exeter),Boas Pucker
(CeBiTec), Chunyan Xu, Xiaodong Fang (BGI), Ana Almeida (Cal-
ifornia State University East Bay), Wei Hu (CATAS), Mark Davey
(KU Leuven), Dave Edwards, Philipp Bayer (University of Western
Australia), Jose de Vega (Earlham Institute). We are grateful to
Gabriel Sachter-Smith, Pat Heslop-Harrison, Julie Sardos, Ziwei
Wang and Megan Hansen who provided the beautiful pictures for
the homepage.
Author Contributions
M.R. and G.D. designed and managed the project. G.D. constructed
the core database; V.G., M.S., E.D., G.S. developed additional
modules. G.D., G.M., F-C.B., C.B. and M.R. collected and analysed
datasets. P. H-H., T.S., XJ. G., N.Y., A.DH. supported the Hub with
key resources. M.R. drafted the manuscript, and all authors were
involved in manuscript revision and approved the submitted
version.
Data availability statement
For data download, the BGH is structured by organism with
regards to individual genome assemblies and also by studies
that provide directory listing of the related datasets. A global
download section, supported by Drupal Filebrowser module,
provides FTP-like browsing capabilities for datasets (e.g. FASTA,
GFF, BAM/CRAM, VCF). The catalogue of variants can also be
accessed using Breeding API (BrAPI) [62]. The BGH is proposed
as a FAIR (Findable, Accessible, Interoperable and Re-usable)
compliant resource [94](https://bio.tools/Banana_Genome_Hub),
and according to FAIR checker (https://fair-checker.france-
bioinformatique.fr/check), it scored a high level in terms of
accessibility and findability (Figure S1).
Conflict of interests
The authors declare that they have no conflict of interest.
Supplementary data
Supplementary data is available at Horticulture Research online.
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