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Sci Rep. 2017 Jul 10;7(1):4961. doi: 10.1038/s41598-017-05200-8.

Transcriptomic profiling of hemp bast fibres at different developmental stages.

Author information

1
Luxembourg Institute of Science and Technology (LIST), Environmental Research and Innovation (ERIN) Department, Esch/Alzette, L-4362, Luxembourg. gea.guerriero@list.lu.
2
Luxembourg Institute of Science and Technology (LIST), Environmental Research and Innovation (ERIN) Department, Esch/Alzette, L-4362, Luxembourg.
3
Université catholique de Louvain, Groupe de Recherche en Physiologie Végétale, Earth and Life Institute-Agronomy, Louvain-la-Neuve, B-1348, Belgium.
4
Institut National de la Recherche Agronomique, Université de Lorraine, UMR 1136, Interactions Arbres-Microorganismes, Champenoux, F-54280, France.

Abstract

Bast fibres are long extraxylary cells which mechanically support the phloem and they are divided into xylan- and gelatinous-type, depending on the composition of their secondary cell walls. The former, typical of jute/kenaf bast fibres, are characterized by the presence of xylan and a high degree of lignification, while the latter, found in tension wood, as well as flax, ramie and hemp bast fibres, have a high abundance of crystalline cellulose. During their differentiation, bast fibres undergo specific developmental stages: the cells initially elongate rapidly by intrusive growth, subsequently they cease elongation and start to thicken. The goal of the present study is to provide a transcriptomic close-up of the key events accompanying bast fibre development in textile hemp (Cannabis sativa L.), a fibre crop of great importance. Bast fibres have been sampled from different stem regions. The developmental stages corresponding to active elongation and cell wall thickening have been studied using RNA-Seq. The results show that the fibres sampled at each stem region are characterized by a specific transcriptomic signature and that the major changes in cell wall-related processes take place at the internode containing the snap point. The data generated also identify several interesting candidates for future functional analysis.

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