背景:枸杞富含类胡萝卜素,黄酮类化合物,维生素,生物碱,甜菜碱和其他生物活性成分。2000多年来,枸杞已在中国用作药用和食用植物资源。然而,生物活性成分的含量因品种而异,导致枸杞品种和品种的质量参差不齐。迄今为止,研究几乎没有揭示类黄酮代谢的潜在分子机制,类胡萝卜素,和其他生物活性成分的枸杞。
结果:在这种情况下,枸杞品种的转录组使用IlluminaNovaSeq6000测序平台在果实成熟阶段比较了1'和枸杞,随后,分析了两种枸杞基因表达谱的变化。总的来说,获得256,228,924个干净的读数,并鉴定了8817个差异表达基因(DEGs),然后通过基本局部比对搜索工具(BLAST)进行相似性搜索并使用基因本体(GO)进行注释,直系同源蛋白质群(KOG),和京都基因和基因组百科全书(KEGG)。通过将这些转录组数据与PubMed数据库中的数据相结合,36DEGs与生物活性成分的代谢有关,涉及类胡萝卜素的代谢途径,黄酮类化合物,萜类化合物,生物碱,维生素,等。,已确定。此外,在9种差异表达的转录因子中,LbAPL,LbPHL11和LbKAN4引起了人们的关注。蛋白质的理化性质,结构预测和系统发育分析表明,LbAPL和LbPHL11可能是参与调控枸杞类黄酮代谢途径的候选基因。
结论:本研究为不同枸杞品种在转录水平上的生物活性成分含量差异提供了初步证据,以及筛选的研究和理论基础,枸杞生物活性成分代谢关键基因的克隆与功能分析.
BACKGROUND: Wolfberry is rich in carotenoids, flavonoids, vitamins, alkaloids, betaines and other bioactive ingredients. For over 2,000 years, wolfberry has been used in
China as a medicinal and edible plant resource. Nevertheless, the content of bioactive ingredients varies by cultivars, resulting in uneven quality across wolfberry cultivars and species. To date, research has revealed little about the underlying molecular mechanism of the metabolism of flavonoids, carotenoids, and other bioactive ingredients in wolfberry.
RESULTS: In this context, the transcriptomes of the Lycium barbarum L. cultivar \'Ningqi No. 1\' and Lycium chinense Miller were compared during the fruit maturity stage using the Illumina NovaSeq 6000 sequencing platform, and subsequently, the changes of the gene expression profiles in two types of wolfberries were analysed. In total, 256,228,924 clean reads were obtained, and 8817 differentially expressed genes (DEGs) were identified, then assembled by Basic Local Alignment Search Tool (BLAST) similarity searches and annotated using Gene Ontology (GO), Clusters of Orthologous Groups of proteins (KOG), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). By combining these transcriptome data with data from the PubMed database, 36 DEGs related to the metabolism of bioactive ingredients and implicated in the metabolic pathway of carotenoids, flavonoids, terpenoids, alkaloids, vitamins, etc., were identified. In addition, among the 9 differentially expressed transcription factors, LbAPL, LbPHL11 and LbKAN4 have raised concerns. The protein physicochemical properties, structure prediction and phylogenetic analysis indicated that LbAPL and LbPHL11 may be good candidate genes involved in regulating the flavonoid metabolism pathway in wolfberry.
CONCLUSIONS: This study provides preliminary evidence for the differences in bioactive ingredient content at the transcription level among different wolfberry species, as well as a research and theoretical basis for the screening, cloning and functional analysis of key genes involved in the metabolism of bioactive ingredients in wolfberry.