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Isolation and analysis of the promoter of an anthocyanin synthase gene from purple-fleshed sweet potato tubers

100%

Dong W. , You Y. , Niu L. , Gao F.

nr 10

Purple-fleshed sweet potato (Ipomoea batatas (L.) Lam) accumulates a large amount of anthocyanins in its tubers. Activation of anthocyanin gene expression requires transcription factors such as MYB domain, basic helix-loop-helix domain, or WD40-repeat domain-containing proteins. However, the mechanisms controlling pigmentation in underground organs remain unresolved. We used a principal component analysis to identify the most important gene in anthocyanin biosynthesis in pigmented sweet potato tubers, because this gene was the most likely to be regulated by IbMYB1. Anthocyanidin synthase was identified as the most important gene. Functional analysis of its promoter identified four MYB DNA-binding sites. In gel mobility shift experiments with recombinant IbMYB1, the IbMYB1 protein bound specifically to TAACCG box and TATCC box motifs in vitro. We conducted transient expression experiments in which various promoter fragments were used to drive expression of the LUC reporter gene. The reporter gene was strongly expressed under the control of the full-length promoter, but weakly expressed under the control of promoter fragments that lacked the MYB DNA-binding domains. This provided direct evidence that IbMYB1 activates the expression of this structural anthocyanin gene. Together, these results show that IbMYB1 is important in controlling the expression of genes in the anthocyanin biosynthetic pathway in cells.

Particle swarm optimization-based Fast Relevance Victor Machine for forecasting dissolved gases content in Power transformer oil

88%

Liang Y. , Li K. , Zhao B. , Zhao J. , Niu L.

2013

tom R. 89, nr 1b

290--293

Forecasting of dissolved gases concentration in power transformer is very significant to detect incipient failures of transformer early and ensure hassle free operation of entire power system. A forecasting model based on Particle Swarm Optimization –Fast Relevance Vector Machine (PSO-FRVM) is proposed in this paper. PSO is utilized to optimize the free parameter of the Gaussian kernel function to improve the forecasting performance. The Matlab program testify the correctness and validity of the model.

W artykule przedstawiono metodę prognozowania rozpływu gazów w transformatorze elektrycznym, opartą na zbudowanym modelu. W tworzeniu modelu wykorzystano Optymalizację Stadną Cząsteczek z maszyną opartą na wektorach istotnych (ang. PSO-FRVM). Metoda PSO wykorzystana została do optymalizacji doboru parametru wolnego w funkcji jądra Gaussa dla polepszenia jakości prognozowania. Weryfikację przeprowadzono w programie Matlak.

Proteomic identification of lipid-bodies-associated proteins in maize seeds

75%

Du C. , Liu A. , Niu L. , Cao D. , Liu H. , Wu X. , Wang W.

nr 05

Seeds store lipids in the form of lipid bodies (LBs) for germination and early seedling growth. LBs can be easily isolated by the established floating-extraction method from oleaginous seeds containing a large quantity of LBs. Compared to oleaginous seeds, maize and other cereal seeds contain a small quantity of LBs, so it is difficult to isolate a sufficient quantity of LBs from their embryos for 2DE-based proteomic analysis. At present, only a limited number of LBs-associated proteins in maize embryos have been identified. We here reported a modified floating-extraction method using polyvinylidene difluoride disc to collect floating LBs from maize embryo extracts. The LBs-associated proteins were resolved with two-dimensional electrophoresis and identified with mass spectrometry. As a result, several well-known LBs proteins were identified in the purified LBs fraction, such as oleosin, caleosin, and steroleosin. We also identified another two LBs proteins, corticosteroid 11-β-dehydrogenase 1 and 11-β-hydroxysteroid dehydrogenase-like 5. In particular, steroleosin, corticosteroid 11-β-dehydrogenase 1, 11-β-hydroxysteroid dehydrogenase-like, and hydroxyproline-rich glycoprotein were found as the most abundant protein components in maize LBs. The data set of maize LBs subproteome would provide insights into functional research of LBs-associated proteins during seed development and germination. Additionally, the protocol developed here is expected to be applicable for isolating LBs in other seeds or tissues containing a low quantity of LBs.