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  • MDPI AG  (2)
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  • MDPI AG  (2)
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  • 1
    Online Resource
    Online Resource
    Transcriptome Analyses Reveal the Aroma Terpeniods Biosynthesis Pathways of Primula forbesii Franch. and the Functional Characterization of the PfDXS2 Gene
    MDPI AG ; 2023
    In:  International Journal of Molecular Sciences Vol. 24, No. 16 ( 2023-08-12), p. 12730-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 24, No. 16 ( 2023-08-12), p. 12730-
    Abstract: Primula forbesii Franch. is a unique biennial herb with a strong floral fragrance, making it an excellent material for studying the aroma characteristics of the genus Primula. The floral scent is an important ornamental trait that facilitates fertilization. However, the molecular mechanism regulating the floral scent in Primula is unknown. In order to better understand the biological mechanisms of floral scents in this species, this study used RNA sequencing analysis to discuss the first transcriptome sequence of four flowering stages of P. forbesii, which generated 12 P. forbesii cDNA libraries with 79.64 Gb of clean data that formed 51,849 unigenes. Moreover, 53.26% of the unigenes were annotated using public databases. P. forbesii contained 44 candidate genes covering all known enzymatic steps for the biosynthesis of volatile terpenes, the major contributor to the flower’s scent. Finally, 1-deoxy-d-xylulose 5-phosphate synthase gene of P. forbesii (PfDXS2, MK370094), the first key enzyme gene in the 2-c-methyl-d-erythritol 4-phosphate (MEP) pathway of terpenoids, was cloned and functionally verified using virus-induced gene silencing (VIGs). The results showed that PfDXS2-silencing significantly reduced the relative concentrations of main volatile terpenes. This report is the first to present molecular data related to aroma metabolites biosynthesis pathways and the functional characterization of any P. forbesii gene. The data on RNA sequencing provide comprehensive information for further analysis of other plants of the genus Primula.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms241612730
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Signal Control Method for Through and Left-Turn Shared Lane by Setting Left-Turn Waiting Area at Signalized Intersections
    MDPI AG ; 2021
    In:  Sustainability Vol. 13, No. 23 ( 2021-11-27), p. 13154-
    Details
    In: Sustainability, MDPI AG, Vol. 13, No. 23 ( 2021-11-27), p. 13154-
    Abstract: This paper proposes a signal control method for the through and left-turn shared lanes at signalized intersections to solve traffic conflicts between left-turn vehicles and opposing through vehicles by setting left-turn waiting area (LWA). Delays and stops are weighted to form an integrated performance index (PI) in a vehicle-to-infrastructure cooperation system. The PI models pertaining to all vehicles are established based on the LWA intersection. In addition, an optimized method of signal timing parameters is constructed by minimizing the average PI. VISSIM simulation shows that the average PI decreases by 6.51% compared with the original layout and signal timing plan of the intersection, since the increased delay of the side-road left-turn vehicles is insufficient to offset the reduced delay of the side-road through vehicles after the improvement. The sensitivity analysis shows that the greater the traffic volume of the phase including the through and left-turn shared lanes, the higher the operation efficiency of the LWA intersection compared with the typical permitted phase intersection. When the left-turn vehicles of the shared lanes in each cycle are less than the stop spaces, the LWA intersection can effectively reduce the average PI of the shared lanes. Furthermore, the more the stop spaces in the LWA, the lower the average PI in the same traffic conditions.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su132313154
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2518383-7
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