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Towards decoding the conifer giga-genome

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Abstract

Several new initiatives have been launched recently to sequence conifer genomes including pines, spruces and Douglas-fir. Owing to the very large genome sizes ranging from 18 to 35 gigabases, sequencing even a single conifer genome had been considered unattainable until the recent throughput increases and cost reductions afforded by next generation sequencers. The purpose of this review is to describe the context for these new initiatives. A knowledge foundation has been acquired in several conifers of commercial and ecological interest through large-scale cDNA analyses, construction of genetic maps and gene mapping studies aiming to link phenotype and genotype. Exploratory sequencing in pines and spruces have pointed out some of the unique properties of these giga-genomes and suggested strategies that may be needed to extract value from their sequencing. The hope is that recent and pending developments in sequencing technology will contribute to rapidly filling the knowledge vacuum surrounding their structure, contents and evolution. Researchers are also making plans to use comparative analyses that will help to turn the data into a valuable resource for enhancing and protecting the world’s conifer forests.

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Acknowledgments

The preparation of this article was supported by FoResTTraC (2440096 FP7) and ProCoGen (289841-FP7) UE projects. The authors are very grateful to Susana Ferrándiz for helping with the preparation of the manuscript.

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Authors and Affiliations

  1. Center for Forest Research, Institute for Integrative and Systems Biology, Université Laval, Québec, Québec, G1V 0A6, Canada

    John Mackay & Nathalie Pavy

  2. Department of Biochemistry and Molecular Biology, Warnell School of Forestry and Natural Resources, Davison Life Sciences, University of Georgia, Complex B314B, Athens, GA, 30602, USA

    Jeffrey F. D. Dean

  3. UMR BIOGECO, INRA, 69 Route d’Arcachon, 33612, Cestas, France

    Christophe Plomion

  4. Institute for Genomics, Biocomputing and Biotechnology (IGBB), Mississippi State University, 2 Research Blvd., Box 9627, Mississippi State, MS, 39762, USA

    Daniel G. Peterson

  5. Departamento de Biología Molecular y Bioquímica, Facultad de Ciencias, Universidad de Málaga, Campus Teatinos, 29071, Málaga, Spain

    Francisco M. Cánovas

  6. Department of Ecology and Environmental Science, Umeå Plant Science Centre, Umeå University, Linneaus väg 6, 901 87, Umeå, Sweden

    Pär K. Ingvarsson

  7. Department of Biology and Biocenter Oulu, University of Oulu, 90014, Oulu, Finland

    Outi Savolainen

  8. Genomics and Forest Ecology, Forest Research Centre INIA-CIFOR, National Research Institute for Agricultural and Food Technology (INIA), Carretera de La Coruña km 7,5, 28040, Madrid, Spain

    M. Ángeles Guevara & María-Teresa Cervera

  9. Health and Environment Department, Platform for Integrated Clone Management (PICME), AIT Austrian Institute of Technology GmbH, Konrad-Lorenz-Straße 24, 3430, Tulln, Austria

    Silvia Fluch

  10. Bioversity International, Via dei Tre Denari 472/a, 00057, Maccarese (Fiumicino) Rome, Italy

    Barbara Vinceti

  11. Department of Plant Biology, University of Alcalá, Ctra. Madrid-Barcelona Km. 33,600, 28871, Alcalá de Henares, Madrid, Spain

    Dolores Abarca & Carmen Díaz-Sala

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  1. John Mackay
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  2. Jeffrey F. D. Dean
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  3. Christophe Plomion
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  4. Daniel G. Peterson
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  5. Francisco M. Cánovas
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  6. Nathalie Pavy
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  7. Pär K. Ingvarsson
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  8. Outi Savolainen
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  9. M. Ángeles Guevara
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  10. Silvia Fluch
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  11. Barbara Vinceti
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  12. Dolores Abarca
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  13. Carmen Díaz-Sala
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  14. María-Teresa Cervera
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Corresponding author

Correspondence to María-Teresa Cervera.

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Mackay, J., Dean, J.F.D., Plomion, C. et al. Towards decoding the conifer giga-genome. Plant Mol Biol 80, 555–569 (2012). https://doi.org/10.1007/s11103-012-9961-7

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  • DOI: https://doi.org/10.1007/s11103-012-9961-7

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