Reconstrucción del metabolismo de triglicéridos de tres especies de microalgas oleaginosas promisorias para la producción sustentable de biodiesel en la Amazonía Peruana
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Universidad de la Amazonía Peruana
Abstract
Las microalgas tienen un gran potencial como materia prima para producir
biocombustibles de próxima generación. La escasez de información a nivel
genómico, sin embargo, previene el diseño racional de novo de cepas microalgales.
El objetivo principal de esta investigación fue reconstruir el metabolismo de
triglicéridos de tres especies de microalgas oleaginosas (Ankystrodesmus sp.,
Scenedesmus sp. y Chlorella sp.) promisorias para la producción sustentable de
biodiesel en la Amazonía Peruana. En total se ha generado de 5,11 a 5,52 Gb de
información genética y de 5,0 x 107 a 5,4 x 107 secuencias de 100 pb. Después del
ensamblado, se ha producido un total de 38,414 unigenes para Ankistrodesmus sp.,
61,171 unigenes para Scenedesmus sp. y 86,927 unigenes para Chlorella sp. En base
a los asignamientos de las vías del KEGG, las vías de biosíntesis de ácidos grasos y
triglicéridos fueron reconstruídos. Los resultados demuestran que la sinergia entre las
tecnologías de secuenciamiento masivo y las herramientas bioinformáticas
apropiadas proporcionan una estrategia apropiada para generar información
genómica invaluable en especies no modelos de microalgas, como las microalgas
oleaginosas de la Amazonía peruana.
Microalgae have great potential as feedstock to produce next-generation biofuels. The scarceness of genomic level information, however, prevents the rational de novo microalgae strain design. The principal objective of this research was the reconstruction of triacylglycerides metabolism of three oleaginous microalgae species (Ankystrodesmus sp., Chlorella sp. and Scenedesmus sp.) promisory for sustainable production of biodiesel in the Peruvian Amazon. In total from 5.11 to 5.52 Gb of genetic information and from 5.0 x 107 to 5.4 x 107 sequences of 100 bp were generated. After assembly, a total of 38,414 unigenes for Ankistrodesmus sp., 61,171 unigenes for Scenedesmus sp. and 86,927 unigenes for Chlorella sp. were produced. Based on the KEGG pathway assignment, the fatty acids and the triacylglycerol biosynthesis pathways were reconstructed. Our results demonstrate that the synergy among high-throughput sequencing technologies and appropriate bioinformatic tools provides a fast, low-cost, and effective approach to generate invaluable functional genomic information in non-model microalgae species, like oleaginous microalgae from the Peruvian Amazon.
Microalgae have great potential as feedstock to produce next-generation biofuels. The scarceness of genomic level information, however, prevents the rational de novo microalgae strain design. The principal objective of this research was the reconstruction of triacylglycerides metabolism of three oleaginous microalgae species (Ankystrodesmus sp., Chlorella sp. and Scenedesmus sp.) promisory for sustainable production of biodiesel in the Peruvian Amazon. In total from 5.11 to 5.52 Gb of genetic information and from 5.0 x 107 to 5.4 x 107 sequences of 100 bp were generated. After assembly, a total of 38,414 unigenes for Ankistrodesmus sp., 61,171 unigenes for Scenedesmus sp. and 86,927 unigenes for Chlorella sp. were produced. Based on the KEGG pathway assignment, the fatty acids and the triacylglycerol biosynthesis pathways were reconstructed. Our results demonstrate that the synergy among high-throughput sequencing technologies and appropriate bioinformatic tools provides a fast, low-cost, and effective approach to generate invaluable functional genomic information in non-model microalgae species, like oleaginous microalgae from the Peruvian Amazon.
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Microalgas, Triglicéridos, Metabolismo, Biocombustibles
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