CrustyBase: an interactive online database for crustacean transcriptomes
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CrustyBase: an interactive online database for crustacean transcriptomes Cameron J. Hyde1* , Quinn P. Fitzgibbon2, Abigail Elizur1, Gregory G. Smith2 and Tomer Ventura1
Abstract Transcriptome sequencing has opened the field of genomics to a wide variety of researchers, owing to its efficiency, applicability across species and ability to quantify gene expression. The resulting datasets are a rich source of information that can be mined for many years into the future, with each dataset providing a unique angle on a specific context in biology. Maintaining accessibility to this accumulation of data presents quite a challenge for researchers. The primary focus of conventional genomics databases is the storage, navigation and interpretation of sequence data, which is typically classified down to the level of a species or individual. The addition of expression data adds a new dimension to this paradigm – the sampling context. Does gene expression describe different tissues, a temporal distribution or an experimental treatment? These data not only describe an individual, but the biological context surrounding that individual. The structure and utility of a transcriptome database must therefore reflect these attributes. We present an online database which has been designed to maximise the accessibility of crustacean transcriptome data by providing intuitive navigation within and between datasets and instant visualization of gene expression and protein structure. The site is accessible at https://crustybase.org and currently holds 10 datasets from a range of crustacean species. It also allows for upload of novel transcriptome datasets through a simple web interface, allowing the research community to contribute their own data to a pool of shared knowledge. Keywords: RNA-seq, Crab, Lobster, Shrimp, Crayfish, Gene, Expression, Search, Visualize, Genomics
Background In recent years, the advancement of next-generation sequencing (NGS) technologies have provided new and exciting opportunities for biologists in a variety of disciplines. A distinguishing feature of NGS technologies is that they can be applied with relatively few taxonomic limitations, thereby extending their utility well beyond model species such as the fruit fly Drosophila melanogaster or the mouse Mus musculus. While the latter species provide us with an increasing depth of knowledge in the fields of genetics and genomics, NGS technologies * Correspondence: [email protected] 1 Genecology Research Centre, University of the Sunshine Coast, Sippy Downs, Queensland 4556, Australia Full list of author information is available at the end of the article
provide an opportunity to expand and contextualize our theories and hypotheses in a variety of taxonomic and biological settings [1]. However, a lack of appropriate infrastructure presents a significant bottleneck in taking advantage of this breadth of information. Total RNA sequencing, commonly known as RNA-seq or transcriptome sequencing, has been an effective tool for curating and charact
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