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Details

Autor(en) / Beteiligte
Titel
Comparative NGS Transcriptomics Unravels Molecular Components Associated with Mosaic Virus Infection in a Bioenergy Plant Species, Jatropha curcas L
Ist Teil von
  • Bioenergy research, 2017-03, Vol.10 (1), p.129-145
Ort / Verlag
New York: Springer US
Erscheinungsjahr
2017
Link zum Volltext
Quelle
SpringerLink (Online service)
Beschreibungen/Notizen
  • Jatropha curcas , a promising bioenergy crop is becoming vulnerable to various biotic stresses due to large-scale cultivation of selected genotypes, thereby affecting its yield potential. Virus causing mosaic disease is prevalent in Jatropha plantations and causing significant reduction in seed yield and quality. To better understand the molecular mechanisms associated with virus infection response, we performed RNA-seq-based comprehensive transcriptome sequencing of symptomatic virus-infected (JV) and healthy (JH) leaf tissues of J. curcas . Through reference genome-based mapping approach, 55,755 genes expressed in both samples were identified. Differential expression analysis identified genes linked to various pathways, upregulated and downregulated during mosaic virus infection. Upon KEGG-based functional annotation, it was observed that various metabolism-associated processes along with oxidative phosphorylation, endocytosis, terpenoid biosynthesis, and hormone signal transduction were upregulated whereas photosynthesis, anthocyanin biosynthesis, plant-pathogen interaction, and calcium signaling were downregulated in response to virus infection. Significantly, genes associated with hormone signal transduction were upregulated as physiological symptoms induced upon mosaic virus infection is due to the interplay of various phytohormones regulating general growth and development of plant. Also, many genes regulating photosynthesis which were downregulated during virus infection showed repressed rate of photosynthesis and also reduction in seed yield and oil content upon mosaic virus infection in J. curcas . RT-qPCR-based experimental validation approach was supplemented to confirm the computational identification. The study provides a repertoire of molecular components which have been affected in response to virus infection, and their precise role can be further functionally validated.

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