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Genome Studies for Effective Management and Utilization of Coconut Genetic Resources

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Coconut Biotechnology: Towards the Sustainability of the ‘Tree of Life’

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Abstract

Coconut belongs to a typically South American subtribe (Attalinae), yet at the dawn of agriculture, it was in both the Indian and Pacific Oceans. How it reached this pre-historic distribution remains unclear. During the last 20 years, molecular markers have been developed to study coconut genetic diversity, assess gene flows and identify markers of agronomic traits. They have proven useful to identify coconut cultivars and to track genetic exchange between populations and human migrations. Two well-differentiated gene pools, originating from the Indian and the Pacific Oceans, were identified. Self-pollinating Dwarf coconuts resulted from a single domestication event in Southeast Asia. Markers for various agronomic traits were identified through linkage mapping and association studies. More recently, genome expression was studied in various organs, providing a representation of the coconut proteome and of its regulation, allowing to identify key genes involved in the metabolism of the endosperm and in somatic embryogenesis. Several research teams undertook its sequencing, and two draft sequences have been published. This large genome was recently assembled into 16 pseudomolecules by anchoring it on a linkage map. The biology of the coconut makes genetic improvement difficult. Genomic selection and marker-assisted selection can speed up the first stages of varietal development based on advanced generations of crosses between genetically distant populations. This will require profound changes in the methods used in field observation, aiming to acquire more phenotypic data at the individual level as well as the open availability of genomic resources.

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Notes

  1. 1.

    DNA (deoxyribonucleic acid) is a molecule forming a long chain (the double helix) which holds the genetic information of a living organism. It is in the nucleus of the cell. It contains genes which are transcribed into messenger ribonucleic acid (mRNA), which are, in turn, translated into polypeptide chains in ribosomes. Other types of RNA are ribosomal RNA (rRNA), transfer RNA (tRNA), microRNA (miRNA), etc.

  2. 2.

    Central Plantation Crops Research Institute, India.

  3. 3.

    Centre International de Recherche en Agronomie pour le Développement, France

  4. 4.

    Centre National de Recherche Agronomique, Côte d’Ivoire.

  5. 5.

    NCBI is one of three major genomics and biological information repositories, located in the USA. The other ones are EMBL-EBI in Europe and DDBJ in Japan. NCBI proposes numerous databases such those devoted to non-redundant (nr) proteins and to Clusters of Orthologous Groups of proteins (COG). KEGG is the Kyoto Encyclopedia of Genes.

  6. 6.

    King Abdulaziz City for Science and Technology.

  7. 7.

    Chinese Academy of Sciences.

  8. 8.

    Indonesian Oil Palm Research Institute, Indonesia.

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  1. CIRAD, UMR AGAP, F-34398 Montpellier, France

    Luc Baudouin

  2. AGAP, Université de Montpellier, CIRAD, INRA, Montpellier Supagro, Montpellier, France

    Luc Baudouin

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  1. Luc Baudouin
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Correspondence to Luc Baudouin .

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Editors and Affiliations

  1. School of Agriculture and Food Sciences, The University of Queensland, St Lucia, QLD, Australia

    Steve Adkins

  2. School of Agriculture and Food Sciences, The University of Queensland, St Lucia, QLD, Australia

    Mike Foale

  3. Biological Systems Department, Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), Montpellier, QLD, Australia

    Roland Bourdeix

  4. School of Agriculture and Food Sciences, The University of Queensland, St Lucia, QLD, Australia

    Quang Nguyen

  5. School of Agriculture and Food Science, University of Queensland, St. Lucia, QLD, Australia

    Julianne Biddle

Appendix: Genomic Resources for Coconut – Databases, Data Sets and Useful Tools

Appendix: Genomic Resources for Coconut – Databases, Data Sets and Useful Tools

The CGRD platform (“CGRD Version 6.1” 2012) offers a wealth of data on ex situ coconut genetic resource collections. It provides information on the microsatellite kit for coconut and data on allele frequencies in many cultivars. Much more complete is the coconut part of TropGeneDB (Hamelin et al. 2013; “Tropgene” 2013). It holds genotypic data on 1791 individuals using up to 30 microsatellite markers. The QTL section lists 63 QTLs for 15 traits, and the marker section documents 296 SSR markers, of which 72 are mapped (along with 196 AFLP and 6 RFLP markers).

PalmComparomics (Armero et al. 2017; “PalmComparomics” 2017) is devoted to comparative genomics of palms. It was constructed before the coconut genome sequence was available and uses the oil palm genome sequence (Singh et al. 2013), as its backbone. In this environment, the user can identify coconut genes matching a given sequence (blast) or, using a number of keywords (annotation terms, gene ontologies, etc.), explore coconut metabolic pathways and more. The site will be considerably enhanced once the coconut genome sequence is integrated. Of course, large amounts of data can be recovered from international databases such as NCBI (“National Center for Biotechnology Information” n.d.), DDBJ (“Bioinformation and DDBJ Center” n.d.) and EMBL-EBI (“The European Bioinformatics Institute < EMBL-EBI” n.d.) and various other specialized databases such as KEGG (“KEGG: Kyoto Encyclopedia of Genes and Genomes” n.d.) and many others.

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Baudouin, L. (2020). Genome Studies for Effective Management and Utilization of Coconut Genetic Resources. In: Adkins, S., Foale, M., Bourdeix, R., Nguyen, Q., Biddle, J. (eds) Coconut Biotechnology: Towards the Sustainability of the ‘Tree of Life’. Springer, Cham. https://doi.org/10.1007/978-3-030-44988-9_7

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