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How DNA barcoding can be more effective in microalgae identification: a case of cryptic diversity revelation in Scenedesmus (Chlorophyceae)
Microalgae identification is extremely difficult. The efficiency of DNA barcoding in microalgae identification involves ideal gene markers and approaches employed, which however, is still under the way. Although Scenedesmus has obtained much research in producing lipids its identification is difficu...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5101840/ https://www.ncbi.nlm.nih.gov/pubmed/27827440 http://dx.doi.org/10.1038/srep36822 |
Sumario: | Microalgae identification is extremely difficult. The efficiency of DNA barcoding in microalgae identification involves ideal gene markers and approaches employed, which however, is still under the way. Although Scenedesmus has obtained much research in producing lipids its identification is difficult. Here we present a comprehensive coalescent, distance and character-based DNA barcoding for 118 Scenedesmus strains based on rbcL, tufA, ITS and 16S. The four genes, and their combined data rbcL + tufA + ITS + 16S, rbcL + tufA and ITS + 16S were analyzed by all of GMYC, P ID, PTP, ABGD, and character-based barcoding respectively. It was apparent that the three combined gene data showed a higher proportion of resolution success than the single gene. In comparison, the GMYC and PTP analysis produced more taxonomic lineages. The ABGD generated various resolution in discrimination among the single and combined data. The character-based barcoding was proved to be the most effective approach for species discrimination in both single and combined data which produced consistent species identification. All the integrated results recovered 11 species, five out of which were revealed as potential cryptic species. We suggest that the character-based DNA barcoding together with other approaches based on multiple genes and their combined data could be more effective in microalgae diversity revelation. |
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