Transcriptome Phase Distribution Analysis Reveals Diurnal Regulated Biological Processes and Key Pathways in Rice Flag Leaves and Seedling Leaves

Plant diurnal oscillation is a 24-hour period based variation. The correlation between diurnal genes and biological pathways was widely revealed by microarray analysis in different species. Rice (Oryza sativa) is the major food staple for about half of the world's population. The rice flag leaf is essential in providing photosynthates to the grain filling. However, there is still no comprehensive view about the diurnal transcriptome for rice leaves. In this study, we applied rice microarray to monitor the rhythmically expressed genes in rice seedling and flag leaves. We developed a new computational analysis approach and identified 6,266 (10.96%) diurnal probe sets in seedling leaves, 13,773 (24.08%) diurnal probe sets in flag leaves. About 65% of overall transcription factors were identified as flag leaf preferred. In seedling leaves, the peak of phase distribution was from 2:00am to 4:00am, whereas in flag leaves, the peak was from 8:00pm to 2:00am. The diurnal phase distribution analysis of gene ontology (GO) and cis-element enrichment indicated that, some important processes were waken by the light, such as photosynthesis and abiotic stimulus, while some genes related to the nuclear and ribosome involved processes were active mostly during the switch time of light to dark. The starch and sucrose metabolism pathway genes also showed diurnal phase. We conducted comparison analysis between Arabidopsis and rice leaf transcriptome throughout the diurnal cycle. In summary, our analysis approach is feasible for relatively unbiased identification of diurnal transcripts, efficiently detecting some special periodic patterns with non-sinusoidal periodic patterns. Compared to the rice flag leaves, the gene transcription levels of seedling leaves were relatively limited to the diurnal rhythm. Our comprehensive microarray analysis of seedling and flag leaves of rice provided an overview of the rice diurnal transcriptome and indicated some diurnal regulated biological processes and key functional pathways in rice

ProFITS of maize: a database of protein families involved in the transduction of signalling in the maize genome

<p>Abstract</p> <p>Background</p> <p>Maize (<it>Zea mays </it>ssp. <it>mays </it>L.) is an important model for plant basic and applied research. In 2009, the B73 maize genome sequencing made a great step forward, using clone by clone strategy; however, functional annotation and gene classification of the maize genome are still limited. Thus, a well-annotated datasets and informative database will be important for further research discoveries. Signal transduction is a fundamental biological process in living cells, and many protein families participate in this process in sensing, amplifying and responding to various extracellular or internal stimuli. Therefore, it is a good starting point to integrate information on the maize functional genes involved in signal transduction.</p> <p>Results</p> <p>Here we introduce a comprehensive database 'ProFITS' (Protein Families Involved in the Transduction of Signalling), which endeavours to identify and classify protein kinases/phosphatases, transcription factors and ubiquitin-proteasome-system related genes in the B73 maize genome. Users can explore gene models, corresponding transcripts and FLcDNAs using the three abovementioned protein hierarchical categories, and visualize them using an AJAX-based genome browser (JBrowse) or Generic Genome Browser (GBrowse). Functional annotations such as GO annotation, protein signatures, protein best-hits in the <it>Arabidopsis </it>and rice genome are provided. In addition, pre-calculated transcription factor binding sites of each gene are generated and mutant information is incorporated into ProFITS. In short, ProFITS provides a user-friendly web interface for studies in signal transduction process in maize.</p> <p>Conclusion</p> <p>ProFITS, which utilizes both the B73 maize genome and full length cDNA (FLcDNA) datasets, provides users a comprehensive platform of maize annotation with specific focus on the categorization of families involved in the signal transduction process. ProFITS is designed as a user-friendly web interface and it is valuable for experimental researchers. It is freely available now to all users at <url>http://bioinfo.cau.edu.cn/ProFITS</url>.</p

agriGO: a GO analysis toolkit for the agricultural community

Gene Ontology (GO), the de facto standard in gene functionality description, is used widely in functional annotation and enrichment analysis. Here, we introduce agriGO, an integrated web-based GO analysis toolkit for the agricultural community, using the advantages of our previous GO enrichment tool (EasyGO), to meet analysis demands from new technologies and research objectives. EasyGO is valuable for its proficiency, and has proved useful in uncovering biological knowledge in massive data sets from high-throughput experiments. For agriGO, the system architecture and website interface were redesigned to improve performance and accessibility. The supported organisms and gene identifiers were substantially expanded (including 38 agricultural species composed of 274 data types). The requirement on user input is more flexible, in that user-defined reference and annotation are accepted. Moreover, a new analysis approach using Gene Set Enrichment Analysis strategy and customizable features is provided. Four tools, SEA (Singular enrichment analysis), PAGE (Parametric Analysis of Gene set Enrichment), BLAST4ID (Transfer IDs by BLAST) and SEACOMPARE (Cross comparison of SEA), are integrated as a toolkit to meet different demands. We also provide a cross-comparison service so that different data sets can be compared and explored in a visualized way. Lastly, agriGO functions as a GO data repository with search and download functions; agriGO is publicly accessible at http://bioinfo.cau.edu.cn/agriGO/

Delineating the molecular landscape of different histopathological growth patterns in colorectal cancer liver metastases

BackgroundHistopathological growth patterns (HGPs) have shown important prognostic values for patients with colorectal cancer liver metastases, but the potential molecular mechanisms remain largely unknown.MethodsWe performed an exploratory analysis by conducting the RNA sequencing of primary colorectal lesions, colorectal liver metastatic lesions and normal liver tissues.FindingsWe found that desmoplastic HGPs of the metastatic lesions were significantly enriched in EMT, angiogenesis, stroma, and immune signaling pathways, while replacement HGPs were enriched in metabolism, cell cycle, and DNA damage repair pathways. With the exception of immune-related genes, the differentially expressed genes of the two HGPs from colorectal liver metastases were mostly inherited from the primary tumor. Moreover, normal liver tissue in the desmoplastic HGP subgroup was markedly enriched in the fibrinous inflammation pathway.ConclusionsWe surmised that HGPs are observable morphological changes resulting from the regulation of molecular expressions, which is the combined effect of the heterogeneity and remodeling of primary tumors seeds and liver soils

Band inversion and topological aspects in a TiNI monolayer

To achieve a device application of the quantum spin Hall (QSH) effect, increasing the critical temperature is crucial. A two-dimensional topological insulator (2D-TI) with a sizeable bulk band gap is one of the most promising strategies to reach this goal. Using first-principles calculations, we propose a new 2D-TI, titanium nitride iodide (TiNI) monolayer, which can be exfoliated from a bulk TiNI crystal, thanks to the weak interlayer interaction. We demonstrate that the TiNI monolayer has an inverted band structure accompanied by topologically nontrivial states characterized by a topological invariant of <span class="italic">Z</span><small>₂</small> = 1. The band gap (∼50 meV) opened due to spin–orbit coupling (SOC) is available for achieving the QSH effect at room temperature. The band inversion and topologically nontrivial states are robust under external strain, suggesting that the 2D TiNI monolayer lattice could be a versatile platform for hosting nontrivial topological states with potential applications in 2D spintronics and computer technology

Nitrogen-Doped Carbon Nanotube Arrays with High Electrocatalytic Activity for Oxygen Reduction

The large- scale practical application of fuel cells will be difficult to realize if the expensive platinum- based electrocatalysts for oxygen reduction reactions ( ORRs) cannot be replaced by other efficient, low- cost, and stable electrodes. Here, we report that vertically aligned nitrogen- containing carbon nanotubes ( VA- NCNTs) can act as a metal- free electrode with a much better electrocatalytic activity, long- term operation stability, and tolerance to crossover effect than platinum for oxygen reduction in alkaline fuel cells. In air- saturated 0.1 molar potassium hydroxide, we observed a steady- state output potential of - 80 millivolts and a current density of 4.1 milliamps per square centimeter at - 0.22 volts, compared with - 85 millivolts and 1.1 milliamps per square centimeter at - 0.20 volts for a platinum- carbon electrode. The incorporation of electron- accepting nitrogen atoms in the conjugated nanotube carbon plane appears to impart a relatively high positive charge density on adjacent carbon atoms. This effect, coupled with aligning the NCNTs, provides a four- electron pathway for the ORR on VA- NCNTs with a superb performance.close1542136

Measurement-based Admission Control Using Wavelets for Broadband Networks

The current broadband networks allow a number of widely disparate traffic streams to share common resources through statistical multiplexing. How efficiently the resource sharing can be managed depends critically upon the analysis of statistical characteristics of the traffic. Numerous analyses of traffic measurements have shown that a large variety of network traffic, in WAN as well as in LAN, exhibits self-similar bursty behavior or long-range dependency (LRD). Self-similar traffic shows structural similarities across a wide range of time-scales (milliseconds, seconds, minutes, etc) and can be characterized by just one parameter (Hurst parameter). Many studies have shown that self-similar network traffic may have a detrimental impact on network performance, including increased queuing delay and packet loss rate under traditional queuing analysis and simulations [8]. It has been shown that network traffic traces exhibit only asymptotically self-similar behavior rather than strict self-similarity. Furthermore, the multifractal nature of WAN traffic was recently revealed [5]. With multifractal nature of traffic, buffer queueing prediction may be over-optimistic even when taking LRD into consideration [4]. The implications of those complex traffic behaviors add increased difficulty to optimizing resource usage such as call admission control. We also believe that analyzing large rapi