Biomedical subjects

Xingwang Deng

Publications and source records attributed to Xingwang Deng.

3 recordsLinked to original sources

PubMed2006

An auxin-inducible F-box protein CEGENDUO negatively regulates auxin-mediated lateral root formation in Arabidopsis.

Previously, we characterized 92 Arabidopsis genes (AtSFLs) similar to the S-locus F-box genes involved in S-RNase-based self-incompatibility and found that they likely play diverse roles in Arabidopsis. In this study, we investigated the role of one of these genes, CEGENDUO (CEG, AtSFL61), in the lateral root formation. A T-DNA insertion in CEG led to an increased lateral root production, which was complemented by transformation of the wild-type gene. Its downregulation by RNAi also produced more lateral roots in transformed Arabidopsis plants whereas its overexpression generated less lateral roots compared to wild-type, indicating that CEG acts as a negative regulator for the lateral root formation. It was found that CEG was expressed abundantly in vascular tissues of the primary root, but not in newly formed lateral root primordia and the root meristem, and induced by exogenous auxin NAA (alpha-naphthalene acetic acid). In addition, the ceg mutant was hyposensitive to NAA, IAA (indole-3-acetic acid) and 2,4-D (2,4-dichlorophenoxyacetic acid), as well as the auxin transport inhibitor TIBA (3,3,5-triiodobenzoic acid), showing that CEG is an auxin-inducible gene. Taken together, our results show that CEG is a novel F-box protein negatively regulating the auxin-mediated lateral root formation in Arabidopsis.

Arabidopsis↗

PubMed2005

Genome-wide analysis of S-Locus F-box-like genes in Arabidopsis thaliana.

The Antirrhinum S-locus F-box gene, AhSLF-S2, has been shown to determine the pollen function of S-RNase-mediated self-incompatibility (SI). Its initial identification led to the discovery of a large family of plant-specific F-box proteins, named the SLF (S-Locus F-box) family, including members from species with or without S-RNase SI system. To investigate the evolution and function of its family members in Arabidopsis, we first identified 92 Arabidopsis F-box proteins related to AhSLF-S2, referred to as AtSFL (S-locus F-box-like) in this report. Phylogenetic analyses with family members from several plant species revealed that they could be classified into five subgroups, and the SLF genes appeared to have had a monophyletic origin. Yeast two-hybrid analyses showed that most AtSFL proteins could interact with one or more ASK (Arabidopsis Skp1-like) proteins, a component of the SCF (Skp1/Cullin or CDC53/F-box) complex, suggesting that AtSFLs may function in the process of ubiquitin/26S proteasome-mediated proteolysis. Transcript analysis found that most of AtSFL genes are expressed ubiquitously and only three of them (AtSFL61, 79 and 85) displayed a tissue-specific pattern. In consistent, phenotypic observations for T-DNA insertion lines of 37 AtSFL genes revealed that most of them are functionally redundant, but inactivation of two AtSFL genes (AtSFL 61 and 70) appears to have caused developmental defects in embryo or female gametophyte. Our results show that a diversified expression and functional pattern are associated with AtSFL genes, indicating that they play important roles in various biological processes in Arabidopsis.

Arabidopsis↗

PubMed2003

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis.

BACKGROUND: To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. RESULTS: We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. CONCLUSION: PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s).

Arabidopsis↗