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

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

Widespread Gene Conversion in Centromere Cores

Data from maize show that centromeres strongly suppress crossing over and instead undergo frequent genetic exchange in the form of gene conversion

DATABASE M ss

Sherwood et al. BMC Ecology 2012, 12:2

A comparative analysis of COI, LSU and UPA marker data for the Hawaiian florideophyte Rhodophyta: implications for DNA barcoding of red algae

Le code-barres mitochondrial ADN COI, un segment partiel du gène rARN LSU et le marqueur plastidial rARN UPA, ont été séquencés sur un total de 290 échantillons de Florideophytes (représentant 17 ordres) issus du projet "Hawaiian Rhodophyta Biodiversity Survey". Le marqueur COI est globalement plus riche en A-T (&gt; 60 ) comparé aux deux autres marqueurs rARN, mais aussi le moins conservé, avec la troisième position des codons présentant une forte substitution. Sur la base d\u27un modèle F84, la saturation est atteinte à une distance d\u27environ 0,11 pour COI and 0,30 pour LSU, mais absente pour UPA, et certaines différences existent quand les ordres ou groupes de familles sont examinés individuellement. Le taux de réussite du séquençage pour les trois marqueurs varient de 46,8 pour COI, 64,7 pour UPA et 79,6 pour LSU, indiquant des différences substantielles pour l\u27obtention de données. La concaténation successive des marqueurs, en démarrant du moins saturé (UPA), et en ajoutant LSU et COI par ordre de saturation (UPA LSU, puis UPA LSU COI) conduit à une augmentation forte du soutien bootstrap par la méthode d\u27analyse du neighbor-joining, indiquant l\u27utilité phylogénétique de séquences courtes d\u27ADN ("barcode-like") obtenues dans le cadre de projets d\u27exploration de la biodiversité.Également disponible sur Connect.barcodeoflife A total of 290 florideophyte samples from the Hawaiian Rhodophyta Biodiversity Survey, spanning 17 orders of red algae, were sequenced for the mitochondrial COI DNA barcode, partial nuclear LSU rRNA gene, and plastid UPA rRNA marker. COI was A-T rich (&gt; 60 overall) in comparison to the two rRNA markers, and was also the least conserved, with the third codon position showing the most substitution. Saturation was reached at F84 distances of approximately 0.11 for COI and 0.30 for LSU, but not at all for UPA, and some differences were found when orders or groups of families were individually examined. Rates of sequencing success for the three markers ranged from 46.8 for COI to 64.7 for UPA and 79.6 for LSU, indicating substantial differences in ease of data acquisition. Concatenation of marker sequences starting with the least saturated marker (UPA), and adding in order of degree of saturation (UPA+LSU, followed by UPA+LSU+COI) resulted in a strong increase in bootstrap support with neighbor-joining analysis, indicating that some phylogenetic utility can be gained from barcode-like sequences that are obtained for biodiversity surveys.Also available on Connect.barcodeoflife </p