Metabolite profiling characterises chemotypes of Musa diploids and triploids at juvenile and pre-flowering growth stages

Genetic Diversity Analysis of Banana Cultivars (Musa sp.) in Saudi Arabia Based on AFLP Marker

Banana plantation has been introduced recently to a temperate zone in the southeastern parts of Saudi Arabia (Fifa, Dhamadh, and Beesh, located in Jazan province). The introduced banana cultivars were of a clear origin without a recorded genetic background. In the current study, the genetic variability and structure of five common banana cultivars (i.e., Red, America, Indian, French, and Baladi) were analyzed using the fluorescently labeled AFLP technique. Nine different primer pairs combinations yielded 1468 loci with 88.96% polymorphism. Among all locations, high expected heterozygosity under the Hardy–Weinberg assumption was found (0.249 ± 0.003), where Dhamadh was the highest, followed by Fifa and Beesh, respectively. Based on the PCoA and Structure analysis, the samples were not clustered by location but in pairs in accordance with the cultivar’s names. However, the Red banana cultivar was found to be a hybrid between the American and Indian cultivars. Based on ΦST, 162 molecular markers (i.e., loci under selection) were detected among cultivars. Identifying those loci using NGS techniques can reveal the genetic bases and molecular mechanisms involved in the domestication and selection indicators among banana cultivars.

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

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.

Datasets from harmonised metabolic phenotyping of root, tuber and banana crop

Biochemical characterisation of germplasm collections and crop wild relatives (CWRs) facilitates the assessment of biological potential and the selection of breeding lines for crop improvement. Data from the biochemical characterisation of staple root, tuber and banana (RTB) crops, i.e. banana (Musa spp.), cassava (Manihot esculenta), potato (Solanum tuberosum), sweet potato (Ipomoea batatas) and yam (Dioscorea spp.), using a metabolomics approach is presented. The data support the previously published research article “Metabolite database for root, tuber, and banana crops to facilitate modern breeding in understudied crops” (Price et al., 2020) [1].

Diversity panels for each crop, which included a variety of species, accessions, landraces and CWRs, were characterised. The biochemical profile for potato was based on five elite lines under abiotic stress. Metabolites were extracted from the tissue of foliage and storage organs (tuber, root and banana pulp) via solvent partition. Extracts were analysed via a combination of liquid chromatography – mass spectrometry (LC-MS), gas chromatography (GC)-MS, high pressure liquid chromatography with photodiode array detector (HPLC-PDA) and ultra performance liquid chromatography (UPLC)-PDA. Metabolites were identified by mass spectral matching to in-house libraries comprised from authentic standards and comparison to databases or previously published literature.

Assessment of genetic diversity and volatile content of commercially grown banana (Musa spp.) cultivars

Banana is an important fruit crop in the tropics and subtropics; however, limited information on biomarkers and signature volatiles is available for selecting commercial cultivars. Clonal fidelity is a major contributor to banana yield and aroma; however, there are no useful biomarkers available to validate clonal fidelity. In this study, we performed the molecular profiling of 20 banana cultivars consisting of diploid (AA or AB) and triploid (AAA or AAB or ABB) genomic groups. We screened 200 molecular markers, of which 34 markers (11 RAPD, 11 ISSR, and 12 SSR) yielded unequivocally scorable biomarker profiles. About 75, 69, and 24 allelic loci per marker were detected for RAPD, ISSR, and SSR markers, respectively. The statistical analysis of molecular variance (AMOVA) exhibited a high genetic difference of 77% with a significant FST value of 0.23 (p < 0.001). Interestingly, the UBC-858 and SSR CNMPF-13 markers were unique to Grand Nain and Ardhapuri cultivars, respectively, which could be used for clonal fidelity analysis. Furthermore, the analysis of banana fruit volatilome using headspace solid-phase microextraction-gas chromatography-tandem mass spectrometry (HS-SPME-GCMS) revealed a total of fifty-four volatile compounds in nine banana cultivars with 56% of the total volatile compounds belonging to the ester group as the significant contributor of aroma. The study assumes significance with informative biomarkers and signature volatiles which could be helpful in breeding and for the authentic identification of commercial banana cultivars.

Transcriptome and metabolome profiling provide insights into molecular mechanism of pseudostem elongation in banana

BACKGROUND

Banana plant height is an important trait for horticultural practices and semi-dwarf cultivars show better resistance to damages by wind and rain. However, the molecular mechanisms controlling the pseudostem height remain poorly understood. Herein, we studied the molecular changes in the pseudostem of a semi-dwarf banana mutant Aifen No. 1 (Musa spp. Pisang Awak sub-group ABB) as compared to its wild-type dwarf cultivar using a combined transcriptome and metabolome approach.

RESULTS

A total of 127 differentially expressed genes and 48 differentially accumulated metabolites were detected between the mutant and its wild type. Metabolites belonging to amino acid and its derivatives, flavonoids, lignans, coumarins, organic acids, and phenolic acids were up-regulated in the mutant. The transcriptome analysis showed the differential regulation of genes related to the gibberellin pathway, auxin transport, cell elongation, and cell wall modification. Based on the regulation of gibberellin and associated pathway-related genes, we discussed the involvement of gibberellins in pseudostem elongation in the mutant banana. Genes and metabolites associated with cell wall were explored and their involvement in cell extension is discussed.

CONCLUSIONS

The results suggest that gibberellins and associated pathways are possibly developing the observed semi-dwarf pseudostem phenotype together with cell elongation and cell wall modification. The findings increase the understanding of the mechanisms underlying banana stem height and provide new clues for further dissection of specific gene functions.

Assessment of metabolic variability and diversity present in leaf, peel and pulp tissue of diploid and triploid Musa spp

Banana (Musa spp.) plants produce many health promoting compounds in leaf, peel and pulp. For a robust metabolic analysis of these tissues, leaf at five developmental stages were compared to assess suitable sampling practices. Results confirmed that the common sampling practise of leaf 3 is applicable for metabolic comparisons. The developed work flow was applied to analyse the metabolite diversity present in 18 different Musa varieties, providing baseline levels of metabolites in leaf, peel and pulp tissue. Correlation analysis was then used to ascertain whether similar trends can be detected in the three plant tissues of the diversity panel. The genome group displayed a dominant role in the composition of the metabolome in all three tissues. This led to the conclusion that a correlation between tissues was only possible within a genome group as the different parental backgrounds caused too great a variation in the metabolomes. It also suggests the metabolome could be used to monitor the interaction/hybridisation of genomes during breeding programmes.

Metabolite database for root, tuber, and banana crops to facilitate modern breeding in understudied crops

Roots, tubers, and bananas (RTB) are vital staples for food security in the world's poorest nations. A major constraint to current RTB breeding programmes is limited knowledge on the available diversity due to lack of efficient germplasm characterization and structure. In recent years large-scale efforts have begun to elucidate the genetic and phenotypic diversity of germplasm collections and populations and, yet, biochemical measurements have often been overlooked despite metabolite composition being directly associated with agronomic and consumer traits. Here we present a compound database and concentration range for metabolites detected in the major RTB crops: banana (Musa spp.), cassava (Manihot esculenta), potato (Solanum tuberosum), sweet potato (Ipomoea batatas), and yam (Dioscorea spp.), following metabolomics-based diversity screening of global collections held within the CGIAR institutes. The dataset including 711 chemical features provides a valuable resource regarding the comparative biochemical composition of each RTB crop and highlights the potential diversity available for incorporation into crop improvement programmes. Particularly, the tropical crops cassava, sweet potato and banana displayed more complex compositional metabolite profiles with representations of up to 22 chemical classes (unknowns excluded) than that of potato, for which only metabolites from 10 chemical classes were detected. Additionally, over 20% of biochemical signatures remained unidentified for every crop analyzed. Integration of metabolomics with the on-going genomic and phenotypic studies will enhance 'omics-wide associations of molecular signatures with agronomic and consumer traits via easily quantifiable biochemical markers to aid gene discovery and functional characterization.