alexa Abstract | Transcriptome analysis of Leucaena leucocephala and identification of highly expressed genes in roots and shoots
ISSN: 2329-8936

Transcriptomics: Open Access
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Research Article Open Access


Leucaena leucocephala (leucaena) is a fast-growing tree legume highly tolerant to various abiotic and biotic stresses. Because of its abilities to withstand high temperature and prolonged drought and to grow as a disease-free plant, it is an interesting model plant to investigate genetics of stress resistance. The high-level stress resistance may be correlated with higher expression of certain genes in the root, which is the primary site for nutrient and water uptake and also infection by soil-borne pathogens. The objectives of this study were to characterize the transcriptome of leucaena and to identify root-specific genes that may be involved in drought tolerance and disease resistance. Transcriptomes of leucaena were analyzed through Illumina-based sequencing and de novo assembly, which generated 62,299 and 61,591 unigenes (≥ 500 bp) from the root and shoot, respectively. Through a 4 x 180,000 microarray analysis, the expression of 10,435 unigenes were compared between the root and shoot. Upregulated sequences in the root were mostly represented by unigenes that were related to secondary metabolism, while in the shoot, upregulated sequences were mostly represented by unigenes that were involved in carbohydrate and lipid metabolism. The unigenes sharing homology with terpenoid biosynthesis genes and a nicotianamine synthase gene were upregulated more than 100-fold in the root, which indicates that these genes may have important roles in high stress tolerance of leucaena. Cataloging of actively transcribed sequences in the root and shoot will lead to identification of genes for drought tolerance and disease resistance in leucaena.

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Author(s): Kazue L. Ishihara, Michael D.H. Honda, Dung T. Pham, Dulal Borthakur


Leucaena-leucocephala, transcriptome, disease resistance, drought tolerance, tree legume, microarray, qRT-PCR, Glycome, Microarray, Transcriptome

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