Due to its ease of genetic manipulation and transparency, Caenorhabditis elegans (C. elegans) has become a preferred model system to study gene function by microscopy. The use of Aequorea victoria green fluorescent protein (GFP) fused to proteins or targeting sequences of interest, further expanded upon the utility of C. elegans by labeling subcellular structures, which enables following their disposition during development or in the presence of genetic mutations. Fluorescent proteins with excitation and emission spectra different from that of GFP accelerated the use of multifluorophore imaging in real time. We have expanded the repertoire of fluorescent proteins for use in C. elegans by developing a codon-optimized version of Orange2 (CemOrange2). Proteins or targeting motifs fused to CemOrange2 were distinguishable from the more common fluorophores used in the nematode; such as GFP, YFP, and mKate2. We generated a panel of CemOrange2 fusion constructs, and confirmed they were targeted to their correct subcellular addresses by colocalization with independent markers. To demonstrate the potential usefulness of this new panel of fluorescent protein markers, we showed that CemOrange2 fusion proteins could be used to: 1) monitor biological pathways, 2) multiplex with other fluorescent proteins to determine colocalization and 3) gain phenotypic knowledge of a human ABCA3 orthologue, ABT-4, trafficking variant in the C. elegans model organism.

Seeds serve as a great model to study plant responses to drought stress, which is largely mediated by abscisic acid (ABA). The ABA responsive element (ABRE) is a key cis-regulatory element in ABA signalling. However, its consensus sequence (ACGTG(G/T)C) is present in the promoters of only about 40% of ABA-induced genes in rice aleurone cells, suggesting other ABREs may exist. To identify novel ABREs, RNA sequencing was performed on aleurone cells of rice seeds treated with 20 μM ABA. Gibbs sampling was used to identify enriched elements, and particle bombardment-mediated transient expression studies were performed to verify the function. Gene ontology analysis was performed to predict the roles of genes containing the novel ABREs. This study revealed 2443 ABA-inducible genes and a novel ABRE, designated as ABREN, which was experimentally verified to mediate ABA signalling in rice aleurone cells. Many of the ABREN-containing genes are predicted to be involved in stress responses and transcription. Analysis of other species suggests that the ABREN may be monocot specific. This study also revealed interesting expression patterns of genes involved in ABA metabolism and signalling. Collectively, this study advanced our understanding of diverse cis-regulatory sequences and the transcriptomes underlying ABA responses in rice aleurone cells.

Summary: Transcript Structure and Domain Display (TSDD) is a publicly available, web-based program that provides publication quality images of transcript structures and domains. TSDD is capable of producing transcript structures from GFF/GFF3 and BED files. Alternatively, the GFF files of several model organisms have been pre-loaded so that users only needs to enter the locus IDs of the transcripts to be displayed. Visualization of transcripts provides many benefits to researchers, ranging from evolutionary analysis of DNA-binding domains to predictive function modeling. Availability and implementation: TSDD is freely available for non-commercial users at

Annotation of the rice (Oryza sativa) genome has evolved significantly since release of its draft sequence, but it is far from complete. Several published transcript assembly programmes were tested on RNA-sequencing (RNA-seq) data to determine their effectiveness in identifying novel genes to improve the rice genome annotation. Cufflinks, a popular assembly software, did not identify all transcripts suggested by the RNA-seq data. Other assembly software was CPU intensive, lacked documentation, or lacked software updates. To overcome these shortcomings, a heuristic ab initio transcript assembly algorithm, Tiling Assembly, was developed to identify genes based on short read and junction alignment. Tiling Assembly was compared with Cufflinks to evaluate its gene-finding capabilities. Additionally, a pipeline was developed to eliminate false-positive gene identification due to noise or repetitive regions in the genome. By combining Tiling Assembly and Cufflinks, 767 unannotated genes were identified in the rice genome, demonstrating that combining both programmes proved highly efficient for novel gene identification. We also demonstrated that Tiling Assembly can accurately determine transcription start sites by comparing the Tiling Assembly genes with their corresponding full-length cDNA. We applied our pipeline to additional organisms and identified numerous unannotated genes, demonstrating that Tiling Assembly is an organism-independent tool for genome annotation.

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