The Hawaiian Algal Database: a laboratory LIMS and online resource for biodiversity data

<p>Abstract</p> <p>Background</p> <p>Organization and presentation of biodiversity data is greatly facilitated by databases that are specially designed to allow easy data entry and organized data display. Such databases also have the capacity to serve as Laboratory Information Management Systems (LIMS). The Hawaiian Algal Database was designed to showcase specimens collected from the Hawaiian Archipelago, enabling users around the world to compare their specimens with our photographs and DNA sequence data, and to provide lab personnel with an organizational tool for storing various biodiversity data types.</p> <p>Description</p> <p>We describe the Hawaiian Algal Database, a comprehensive and searchable database containing photographs and micrographs, geo-referenced collecting information, taxonomic checklists and standardized DNA sequence data. All data for individual samples are linked through unique accession numbers. Users can search online for sample information by accession number, numerous levels of taxonomy, or collection site. At the present time the database contains data representing over 2,000 samples of marine, freshwater and terrestrial algae from the Hawaiian Archipelago. These samples are primarily red algae, although other taxa are being added.</p> <p>Conclusion</p> <p>The Hawaiian Algal Database is a digital repository for Hawaiian algal samples and acts as a LIMS for the laboratory. Users can make use of the online search tool to view and download specimen photographs and micrographs, DNA sequences and relevant habitat data, including georeferenced collecting locations. It is publicly available at <url>http://algae.manoa.hawaii.edu</url>.</p

Distinct influences of tandem repeats and retrotransposons on CENH3 nucleosome positioning

Abstract Background Unique structural characteristics of centromere chromatin enable it to support assembly of the kinetochore and its associated tensions. The histone H3 variant CENH3 (centromeric histone H3) is viewed as the key element of centromere chromatin and its interaction with centromere DNA is epigenetic in that its localization to centromeres is not sequence-dependent. Results In order to investigate what influence the DNA sequence exerts on CENH3 chromatin structure, we examined CENH3 nucleosome footprints on maize centromere DNA. We found a predominant average nucleosome spacing pattern of roughly 190-bp intervals, which was also the dominant arrangement for nucleosomes genome-wide. For CENH3-containing nucleosomes, distinct modes of nucleosome positioning were evident within that general spacing constraint. Over arrays of the major ~156-bp centromeric satellite sequence (tandem repeat) CentC, nucleosomes were not positioned in register with CentC monomers but in conformity with a striking ~10-bp periodicity of AA/TT dimers within the sequence. In contrast, nucleosomes on a class of centromeric retrotransposon (CRM2) lacked a detectable AA/TT periodicity but exhibited tightly phased positioning. Conclusions These data support a model in which general chromatin factors independent of both DNA sequence and CENH3 enforce roughly uniform centromeric nucleosome spacing while allowing flexibility in the mode in which nucleosomes are positioned. In the case of tandem repeat DNA, the natural bending effects related to AA/TT periodicity produce an energetically-favourable arrangement consistent with conformationally rigid nucleosomes and stable chromatin at centromeres. </jats:sec

The Hawaiian Freshwater Algal Database (HfwADB): a laboratory LIMS and online biodiversity resource

BACKGROUND: Biodiversity databases serve the important role of highlighting species-level diversity from defined geographical regions. Databases that are specially designed to accommodate the types of data gathered during regional surveys are valuable in allowing full data access and display to researchers not directly involved with the project, while serving as a Laboratory Information Management System (LIMS). The Hawaiian Freshwater Algal Database, or HfwADB, was modified from the Hawaiian Algal Database to showcase non-marine algal specimens collected from the Hawaiian Archipelago by accommodating the additional level of organization required for samples including multiple species. DESCRIPTION: The Hawaiian Freshwater Algal Database is a comprehensive and searchable database containing photographs and micrographs of samples and collection sites, geo-referenced collecting information, taxonomic data and standardized DNA sequence data. All data for individual samples are linked through unique 10-digit accession numbers (“Isolate Accession”), the first five of which correspond to the collection site (“Environmental Accession”). Users can search online for sample information by accession number, various levels of taxonomy, habitat or collection site. HfwADB is hosted at the University of Hawaii, and was made publicly accessible in October 2011. At the present time the database houses data for over 2,825 samples of non-marine algae from 1,786 collection sites from the Hawaiian Archipelago. These samples include cyanobacteria, red and green algae and diatoms, as well as lesser representation from some other algal lineages. CONCLUSIONS: HfwADB is a digital repository that acts as a Laboratory Information Management System for Hawaiian non-marine algal data. Users can interact with the repository through the web to view relevant habitat data (including geo-referenced collection locations) and download images of collection sites, specimen photographs and micrographs, and DNA sequences. It is publicly available at http://algae.manoa.hawaii.edu/hfwadb/

JunctionViewer: customizable annotation software for repeat-rich genomic regions

<p>Abstract</p> <p>Background</p> <p>Repeat-rich regions such as centromeres receive less attention than their gene-rich euchromatic counterparts because the former are difficult to assemble and analyze. Our objectives were to 1) map all ten centromeres onto the maize genetic map and 2) characterize the sequence features of maize centromeres, each of which spans several megabases of highly repetitive DNA. Repetitive sequences can be mapped using special molecular markers that are based on PCR with primers designed from two unique "repeat junctions". Efficient screening of large amounts of maize genome sequence data for repeat junctions, as well as key centromere sequence features required the development of specific annotation software.</p> <p>Results</p> <p>We developed JunctionViewer to automate the process of identifying and differentiating closely related centromere repeats and repeat junctions, and to generate graphical displays of these and other features within centromeric sequences. JunctionViewer generates NCBI BLAST, WU-BLAST, cross_match and MUMmer alignments, and displays the optimal alignments and additional annotation data as concise graphical representations that can be viewed directly through the graphical interface or as PostScript^®output.</p> <p>This software enabled us to quickly characterize millions of nucleotides of newly sequenced DNA ranging in size from single reads to assembled BACs and megabase-sized pseudochromosome regions. It expedited the process of generating repeat junction markers that were subsequently used to anchor all 10 centromeres to the maize map. It also enabled us to efficiently identify key features in large genomic regions, providing insight into the arrangement and evolution of maize centromeric DNA.</p> <p>Conclusions</p> <p>JunctionViewer will be useful to scientists who wish to automatically generate concise graphical summaries of repeat sequences. It is particularly valuable for those needing to efficiently identify unique repeat junctions. The scalability and ability to customize homology search parameters for different classes of closely related repeat sequences make this software ideal for recurring annotation (e.g., genome projects that are in progress) of genomic regions that contain well-defined repeats, such as those in centromeres. Although originally customized for maize centromere sequence, we anticipate this software to facilitate the analysis of centromere and other repeat-rich regions in other organisms.</p

Classification of Plant Associated Bacteria Using RIF, a Computationally Derived DNA Marker

A DNA marker that distinguishes plant associated bacteria at the species level and below was derived by comparing six sequenced genomes of Xanthomonas, a genus that contains many important phytopathogens. This DNA marker comprises a portion of the dnaA replication initiation factor (RIF). Unlike the rRNA genes, dnaA is a single copy gene in the vast majority of sequenced bacterial genomes, and amplification of RIF requires genus-specific primers. In silico analysis revealed that RIF has equal or greater ability to differentiate closely related species of Xanthomonas than the widely used ribosomal intergenic spacer region (ITS). Furthermore, in a set of 263 Xanthomonas, Ralstonia and Clavibacter strains, the RIF marker was directly sequenced in both directions with a success rate approximately 16% higher than that for ITS. RIF frameworks for Xanthomonas, Ralstonia and Clavibacter were constructed using 682 reference strains representing different species, subspecies, pathovars, races, hosts and geographic regions, and contain a total of 109 different RIF sequences. RIF sequences showed subspecific groupings but did not place strains of X. campestris or X. axonopodis into currently named pathovars nor R. solanacearum strains into their respective races, confirming previous conclusions that pathovar and race designations do not necessarily reflect genetic relationships. The RIF marker also was sequenced for 24 reference strains from three genera in the Enterobacteriaceae: Pectobacterium, Pantoea and Dickeya. RIF sequences of 70 previously uncharacterized strains of Ralstonia, Clavibacter, Pectobacterium and Dickeya matched, or were similar to, those of known reference strains, illustrating the utility of the frameworks to classify bacteria below the species level and rapidly match unknown isolates to reference strains. The RIF sequence frameworks are available at the online RIF database, RIFdb, and can be queried for diagnostic purposes with RIF sequences obtained from unknown strains in both chromatogram and FASTA format

DATABASE M ss

Sherwood et al. BMC Ecology 2012, 12:2