A genome-wide transcriptional activity survey of rice transposable element-related genes

BACKGROUND: Transposable element (TE)-related genes comprise a significant portion of the gene catalog of grasses, although their functions are insufficiently characterized. The recent availability of TE-related gene annotation from the complete genome sequence of rice (Oryza sativa) has created an opportunity to conduct a comprehensive evaluation of the transcriptional activities of these potentially mobile elements and their related genes. RESULTS: We conducted a genome-wide survey of the transcriptional activity of TE-related genes associated with 15 developmental stages and stress conditions. This dataset was obtained using a microarray encompassing 2,191 unique TE-related rice genes, which were represented by oligonucleotide probes that were free from cross-hybridization. We found that TE-related genes exhibit much lower transcriptional activities than do non-TE-related genes, although representative transcripts were detected from all superfamilies of both type I and II TE-related genes. The strongest transcriptional activities were detected in TE-related genes from among the MULE and CACTA superfamilies. Phylogenetic analyses suggest that domesticated TE-related genes tend to form clades with active transcription. In addition, chromatin-level regulations through histone and DNA modifications, as well as enrichment of certain cis elements in the promoters, appear to contribute to the transcriptional activation of representative TE-related genes. CONCLUSION: Our findings reveal clear, albeit low, general transcription of TE-related genes. In combination with phylogenetic analysis, transcriptional analysis has the potential to lead to the identification of domesticated TEs with adapted host functions

The dark side of clock-controlled flowering

Perception of seasonal changes in day length allows plants to properly maintain daily biological rhythms and determine the most favorable time for flowering. Important knowledge has been gained recently on the molecular basis of this process, which depends not only on light perception at certain times of day but also on its dark phase

Quantized Quasi-Two Dimensional Bose-Einstein Condensates with Spatially Modulated Nonlinearity

We investigate the localized nonlinear matter waves of the quasi-two dimensional Bose-Einstein condensates with spatially modulated nonlinearity in harmonic potential. It is shown that the whole Bose-Einstein condensates, similar to the linear harmonic oscillator, can have an arbitrary number of localized nonlinear matter waves with discrete energies, which are mathematically exact orthogonal solutions of the Gross-Pitaevskii equation. Their novel properties are determined by the principle quantum number n and secondary quantum number l: the parity of the matter wave functions and the corresponding energy levels depend only on n, and the numbers of density packets for each quantum state depend on both n and l which describe the topological properties of the atom packets. We also give an experimental protocol to observe these novel phenomena in future experiments.Comment: 5 pages, 5 figure

An initial biochemical and cell biological characterization of the mammalian homologue of a central plant developmental switch, COP1

BACKGROUND: Constitutive photomorphogenic 1 (COP1) has been defined as a central regulator of photomorphogenic development in plants, which targets key transcription factors for proteasome-dependent degradation. Although COP1 mammalian homologue has been previously reported, its function and distribution in animal kingdom are not known. RESULTS: Here we report the characterization of full-length human and mouse COP1 cDNAs and the genomic structures of the COP1 genes from several different species. Mammalian COP1 protein binds to ubiquitinated proteins in vivo and is itself ubiquitinated. Furthermore, mammalian COP1 is predominately nuclear localized and exists primarily as a complex of over 700 kDa. Through mutagenesis studies, we have defined a leucine-rich nuclear export signal (NES) within the coiled-coil domain of mammalian COP1 and a nuclear localization signal (NLS), which is composed of two clusters of positive-charged amino acids, bridged by the RING finger. Disruption of the RING finger structure abolishes the nuclear import, while deletion of the entire RING finger restores the nuclear import. CONCLUSIONS: Our data suggest that mammalian COP1, similar to its plant homologue, may play a role in ubiquitination. Mammalian COP1 contains a classic leucine-rich NES and a novel bipartite NLS bridged by a RING finger domain. We propose a working model in which the COP1 RING finger functions as a structural scaffold to bring two clusters of positive-charged residues within spatial proximity to mimic a bipartite NLS. Therefore, in addition to its well-characterized role in ubiquitination, the RING finger domain may also play a structural role in nuclear import

Classification of Time-Series Images Using Deep Convolutional Neural Networks

Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the majority of Time-Series Classification (TSC) literature is focused on 1D signals, this paper uses Recurrence Plots (RP) to transform time-series into 2D texture images and then take advantage of the deep CNN classifier. Image representation of time-series introduces different feature types that are not available for 1D signals, and therefore TSC can be treated as texture image recognition task. CNN model also allows learning different levels of representations together with a classifier, jointly and automatically. Therefore, using RP and CNN in a unified framework is expected to boost the recognition rate of TSC. Experimental results on the UCR time-series classification archive demonstrate competitive accuracy of the proposed approach, compared not only to the existing deep architectures, but also to the state-of-the art TSC algorithms.Comment: The 10th International Conference on Machine Vision (ICMV 2017