Interactive Effects of Lanthanum and Calcium on Cadmium Accumulation in Wheat with Special Reference to TaNramp5 Expression Regulated by Calmodulin.

Lanthanum (La), calcium (Ca), and cadmium (Cd) have similar physical and chemical properties because of their similar ionic radius. Although the interactions between La, Ca, and Cd have been frequently reported in plants, few studies have investigated the interactive effects of La and Ca on the growth and Cd accumulation in plants. Therefore, we investigated the interactive effects of La and Ca on the growth and Cd accumulation in wheat under Cd exposure by a hydroponic experiment. The results indicated that wheat growth was significantly affected by La-Cd and La-Ca interactions. The accumulation of Cd in wheat was significantly affected by La-Ca and La-Cd interactions and La-Ca-Cd interplay. Correlation analysis indicated that Ca deficiency stimulated La to promote wheat growth and mitigate Cd toxicity. Simultaneously, a low Ca supply stimulated La to decrease Cd accumulation in wheat and induce TaNramp5 expression. In addition, Cd accumulation in wheat was significantly affected by the W7-La interaction and W7-La-Ca interplay. All of the results suggested that La, Ca, and Cd probably share the same binding sites in calmodulin (TaCaM) and La could affect Cd accumulation in wheat by interacting with TaCaM and then downregulating the expression of TaNramp5.

Comparison and Characterization of a Cell Wall Invertase Promoter from Cu-Tolerant and Non-Tolerant Populations of Elsholtzia haichowensis.

Cell wall invertase (CWIN) activity and the expression of the corresponding gene were previously observed to be significantly elevated in a Cu-tolerant population of Elsholtzia haichowensis relative to a non-tolerant population under copper stress. To understand the differences in CWIN gene regulation between the two populations, their CWIN promoter ß-glucuronidase (GUS) reporter vectors were constructed. GUS activity was measured in transgenic Arabidopsis in response to copper, sugar, and phytohormone treatments. Under the copper treatment, only the activity of the CWIN promoter from the Cu-tolerant population was slightly increased. Glucose and fructose significantly induced the activity of CWIN promoters from both populations. Among the phytohormone treatments, only salicylic acid induced significantly higher (p < 0.05) activity of the Cu-tolerant CWIN promoter relative to the non-tolerant promoters. Analysis of 5'-deletion constructs revealed that a 270-bp promoter fragment was required for SA induction of the promoter from the Cu-tolerant population. Comparison of this region in the two CWIN promoters revealed that it had 10 mutation sites and contained CAAT-box and W-box cis-elements in the Cu-tolerant promoter only. This work provides insights into the regulatory role of SA in CWIN gene expression and offers an explanation for differences in CWIN expression between E. haichowensis populations.

Differential expression of vacuolar and defective cell wall invertase genes in roots and seeds of metalliferous and non-metalliferous populations of Rumex dentatus under copper stress.

Acid invertase activities in roots and young seeds of a metalliferous population (MP) of Rumex dentatus were previously observed to be significantly higher than those of a non-metalliferous population (NMP) under Cu stress. To date, no acid invertase gene has been cloned from R. dentatus. Here, we isolated four full-length cDNAs from the two populations of R. dentatus, presumably encoding cell wall (RdnCIN1 and RdmCIN1 from the NMP and MP, respectively) and vacuolar invertases (RdnVIN1 and RdmVIN1 from the NMP and MP, respectively). Unexpectedly, RdnCIN1 and RdmCIN1 most likely encode special defective invertases with highly attenuated sucrose-hydrolyzing capacity. The transcript levels of RdmCIN1 were significantly higher than those of RdnCIN1 in roots and young seeds under Cu stress, whereas under control conditions, the former was initially lower than the latter. Unexpected high correlations were observed between the transcript levels of RdnCIN1 and RdmCIN1 and the activity of cell wall invertase, even though RdnCIN1 and RdmCIN1 do not encode catalytically active invertases. Similarly, the transcript levels of RdmVIN1 in roots and young seeds were increased under Cu stress, whereas those of RdnVIN1 were decreased. The high correlations between the transcript levels of RdnVIN1 and RdmVIN1 and the activity of vacuolar invertase indicate that RdnVIN1 and RdmVIN1 might control distinct vacuolar invertase activities in the two populations. Moreover, a possible indirect role for acid invertases in Cu tolerance, mediated by generating a range of sugars used as nutrients and signaling molecules, is discussed.

Assessing semantic similarity measures for the characterization of human regulatory pathways.

MOTIVATION: Pathway modeling requires the integration of multiple data including prior knowledge. In this study, we quantitatively assess the application of Gene Ontology (GO)-derived similarity measures for the characterization of direct and indirect interactions within human regulatory pathways. The characterization would help the integration of prior pathway knowledge for the modeling. RESULTS: Our analysis indicates information content-based measures outperform graph structure-based measures for stratifying protein interactions. Measures in terms of GO biological process and molecular function annotations can be used alone or together for the validation of protein interactions involved in the pathways. However, GO cellular component-derived measures may not have the ability to separate true positives from noise. Furthermore, we demonstrate that the functional similarity of proteins within known regulatory pathways decays rapidly as the path length between two proteins increases. Several logistic regression models are built to estimate the confidence of both direct and indirect interactions within a pathway, which may be used to score putative pathways inferred from a scaffold of molecular interactions.

Histone acetylation and transcriptional regulation in the genome of Saccharomyces cerevisiae.

MOTIVATION: In eukaryotic genomes, histone acetylation and thereafter departure from the chromatin are essential for gene transcription initiation. Because gene transcription is tightly regulated by transcription factors, there are some speculations on the cooperation of histone acetylation and transcription factor binding. However, systematic statistical analyses of this relationship on a genomic scale have not been reported. RESULTS: We apply several statistical methods to explore this relationship on two recent genomic datasets: acetylation levels on 11 histone lysines and binding activities of 203 transcription factors, both in promoter regions across the yeast genome. By canonical correlation analysis, we find that a histone acetylation pattern is correlated with a certain profile of transcription factor binding in the genome. Furthermore, after clustering the genes by their acetylation levels on the 11 histone lysines, the genes within clusters show distinct transcription factor binding profiles, as discovered by principle component analysis. Even after applying fairly stringent statistical measurement, most of these clusters have transcription factors with binding activities significantly deviated from the overall genome. We conclude that in the yeast genome, there is a strong correlation between histone acetylation and transcription factor binding in the promoter regions.

Computational identification of transcription factors involved in early cellular response to a stimulus.

The response of genes to cell stimuli is often measured by microarrays. However, studying the function of these genes rarely elucidate as to how the stimuli activate or suppress these genes. To understand the mechanisms of cell stimulation, we describe a computational method for analyzing mammalian promoters of early response genes to detect the transcription factors activated by cell stimulation. We first analyzed promoters of the response genes, for transcription factor binding sites conserved between human and mouse. We then applied hypergeometric statistics in conjunction with Bonferroni correction to identify the top transcription factors whose binding sites were significantly over-represented among these promoters. In five data sets with early response genes, a significantly larger than expected number of genes had binding sites in their promoters for transcription factors previously known to be involved in response to the stimulus, while data sets with measurements at longer time points (24 hours) failed to show such over-representation. Because the end points of signal transduction pathways are transcription factors, this methodology is useful for exploring signaling pathways activated by various stimuli through microarray studies.

Computationally identifying novel NF-kappa B-regulated immune genes in the human genome.

Identifying novel NF-kappa B-regulated immune genes in the human genome is important to our understanding of immune mechanisms and immune diseases. We fit logistic regression models to the promoters of 62 known NF-kappa B-regulated immune genes, to find patterns of transcription factor binding in the promoters of genes with known immune function. Using these patterns, we scanned the promoters of additional genes to find matches to the patterns, selected those with NF-kappa B binding sites conserved in the mouse or fly, and then confirmed them as NF-kappa B-regulated immune genes based on expression data. Among 6440 previously identified promoters in the human genome, we found 28 predicted immune gene promoters, 19 of which regulate genes with known function, allowing us to calculate specificity of 93%-100% for the method. We calculated sensitivity of 42% when searching the 62 known immune gene promoters. We found nine novel NF-kappa B-regulated immune genes which are consistent with available SAGE data. Our method of predicting gene function, based on characteristic patterns of transcription factor binding, evolutionary conservation, and expression studies, would be applicable to finding genes with other functions.

Consensus promoter identification in the human genome utilizing expressed gene markers and gene modeling.

Deciphering the human genome includes locating the promoters that initiate transcription and identifying the exons of genes. Many promoter prediction programs have been proposed, but when they are applied to extended regions of the genome, most of their predictions are false-positives. The extensive collection of gene transcript sequences is an important new source of information, which has not been used previously in promoter predictions. Our approach is to enhance the specificity of predictions by restricting the genomic regions that are searched using gene transcript alignments as anchors in the genome for gene modeling. We developed a consensus promoter prediction method combining previously developed algorithms with the GENSCAN gene modeling program. Our method, CONPRO (CONsensus PROmoter), identifies promoters with very high confidence, and the predicted promoters are guaranteed to be associated with genes. On our test data set, the method correctly detects promoters for approximately half of all human genes (37%-71%), and most predictions are true promoters (85%-90%). Applying our method to the human genome and human genes from the Unigene data set, we find the promoters for 13,744 genes. Of these, 6440 are genes with a functionally cloned mRNA, and 7304 are novel genes for which only expressed sequence tags (ESTs) are available. Candidate promoters for many novel genes will be a useful resource in elucidating complex biological response mechanisms.