ArticleMolecular ecology2013
Extending the Arabidopsis flowering paradigm to a mass flowering phenomenon in the tropics.
Article in Molecular ecology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Flowering time is a critical life history trait, one that is shaped by evolution to maximize fecundity, reproductive success and fitness (Amasino 2010). This is especially true of annual plants where the cycle of floral initiation, pollination and seed production occur at regular intervals to ensure the survival of the species. In long-lived perennials, however, flowering can be an intermittent phenomenon and thus a challenge to understand. In this issue of Molecular Ecology, Kobayashi et al. (2013) tackle this particular challenge by applying modern-day molecular techniques to the ‘spectacular and mysterious’ mass flowering that takes places in mixed dipterocarp forests of South-East Asia. Here, amidst an almost unimaginable diversity of forbs, shrubs and trees, these authors used next-generation sequencing technology to characterize what they refer to as the ‘ecological transcriptome’ in an attempt to glimpse into the functional genomic reprogramming of Shorea beccariana at pre- and postflowering developmental transitions. They encountered many of the challenges that are often underappreciated yet typical for tropical ecological research including sample collection within a ~40-m high tree canopy, unpredictable flowering intervals and determining the most appropriate preflowering state for sampling. Despite these challenges, the authors were able to integrate gene ontology relationships with gene-clustering algorithms and environmental data to support the hypothesis that drought is a key trigger for flowering in S. beccariana. The cloning and transgenic expression of selected S. beccariana genes to corroborate presumed protein function is a key feature of their work and seldom applied within an ecological framework. As illustrated by Kobayashi et al. (2013), the inclusion of molecular biology, genomics and bioinformatics has the potential to shed light on long-standing questions of ecological concern.
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