29 research outputs found

    Construction of reference chromosome-scale pseudomolecules for potato: integrating the potato genome with genetic and physical maps

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    The genome of potato, a major global food crop, was recently sequenced. The work presented here details the integration of the potato reference genome (DM) with a new STS marker based linkage map and other physical and genetic maps of potato and the closely related species tomato. Primary anchoring of the DM genome assembly was accomplished using a diploid segregating population, which was genotyped with several types of molecular genetic markers to construct a new ~936 cM linkage map comprising 2,469 marker loci. In silico anchoring approaches employed genetic and physical maps from the diploid potato genotype RH and tomato. This combined approach has allowed 951 superscaffolds to be ordered into pseudomolecules corresponding to the 12 potato chromosomes. These pseudomolecules represent 674 Mb (~93%) of the 723 Mb genome assembly and 37,482 (~96%) of the 39,031 predicted genes. The superscaffold order and orientation within the pseudomolecules is closely collinear with independently constructed high density linkage maps. Comparisons between marker distribution and physical location reveal regions of greater and lesser recombination, as well as regions exhibiting significant segregation distortion. The work presented here has led to a greatly improved ordering of the potato reference genome superscaffolds into chromosomal 'pseudomolecules'.Fil: Carboni, Martín Federico. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires. Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: D'ambrosio, Juan Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional San Cristobal de Huamanga. Laboratorio de Genética y Biotecnología Vegetal; PerúFil: Sharma, Sanjeev Kumar. The James Hutton Institute; Reino UnidoFil: Bolser, Daniel. University of Dundee; Reino UnidoFil: de Boer, Jan. Wageningen University & Researc; Países BajosFil: Sønderkær, Mads . Aalborg University; DinamarcaFil: Amoros, Walter. International Potato Center; PerúFil: de la Cruz, Germán. Universidad Nacional San Cristobal de Huamanga; PerúFil: Di Genova, Alex. Universidad de Chile; ChileFil: Douches, David S.. Michigan State University; Estados UnidosFil: Eguiluz, Maria. Universidad Peruana Cayetano Heredia; PerúFil: Guo, Xiao. Shandong Academy of Agricultural Sciences; ChinaFil: Guzman, Frank. Universidad Peruana Cayetano Heredia; PerúFil: Hackett, Christine A.. Biomathematics and Statistics Scotland; Reino UnidoFil: Hamilton, John P.. Crops Environment and Land Use Programme; IrlandaFil: Li, Guangcun. Shandong Academy of Agricultural Sciences; ChinaFil: Li, Ying. The New Zealand Institute for Plant & Food Research; Nueva ZelandaFil: Lozano, Roberto. Universidad Peruana Cayetano Heredia; PerúFil: Maass, Alejandro. Universidad de Chile; ChileFil: Marshall, David. The James Hutton Institute; Reino UnidoFil: Martinez, Diana. Universidad Peruana Cayetano Heredia; PerúFil: McLean, Karen. The James Hutton Institute; Reino UnidoFil: Mejía, Nilo. Instituto de Investigaciones Agropecuarias. Centro Regional de Investigación La Platina; ChileFil: Milne, Linda. The James Hutton Institute; Reino UnidoFil: Munive, Susan. International Potato Center; PerúFil: Nagy, Istvan. Crops Environment and Land Use Programme; IrlandaFil: Ponce, Olga. Universidad Peruana Cayetano Heredia; PerúFil: Ramirez, Manuel. Universidad Peruana Cayetano Heredia; PerúFil: Simon, Reinhard. International Potato Center; PerúFil: Thomson, Susan J.. Chinese Academy of Agricultural Sciences; Chin

    MetaBase--the wiki-database of biological databases.

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    Biology is generating more data than ever. As a result, there is an ever increasing number of publicly available databases that analyse, integrate and summarize the available data, providing an invaluable resource for the biological community. As this trend continues, there is a pressing need to organize, catalogue and rate these resources, so that the information they contain can be most effectively exploited. MetaBase (MB) (http://MetaDatabase.Org) is a community-curated database containing more than 2000 commonly used biological databases. Each entry is structured using templates and can carry various user comments and annotations. Entries can be searched, listed, browsed or queried. The database was created using the same MediaWiki technology that powers Wikipedia, allowing users to contribute on many different levels. The initial release of MB was derived from the content of the 2007 Nucleic Acids Research (NAR) Database Issue. Since then, approximately 100 databases have been manually collected from the literature, and users have added information for over 240 databases. MB is synchronized annually with the static Molecular Biology Database Collection provided by NAR. To date, there have been 19 significant contributors to the project; each one is listed as an author here to highlight the community aspect of the project

    Construction of a map-based reference genome sequence for barley, Hordeum vulgare L.

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    Barley (Hordeum vulgare L.) is a cereal grass mainly used as animal fodder and raw material for the malting industry. The map-based reference genome sequence of barley cv. `Morex' was constructed by the International Barley Genome Sequencing Consortium (IBSC) using hierarchical shotgun sequencing. Here, we report the experimental and computational procedures to (i) sequence and assemble more than 80,000 bacterial artificial chromosome (BAC) clones along the minimum tiling path of a genome-wide physical map, (ii) find and validate overlaps between adjacent BACs, (iii) construct 4,265 non-redundant sequence scaffolds representing clusters of overlapping BACs, and (iv) order and orient these BAC clusters along the seven barley chromosomes using positional information provided by dense genetic maps, an optical map and chromosome conformation capture sequencing (Hi-C). Integrative access to these sequence and mapping resources is provided by the barley genome explorer (BARLEX).Peer reviewe

    Ensembl Genomes 2016: more genomes, more complexity

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    Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces

    A chromosome conformation capture ordered sequence of the barley genome

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    Raw electromyographic traces of swallow stimulated by the three conditions.

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    <p>Note the increased burst amplitude of the mylohyoid and post-swallow cricopharyngeus with the addition of water, and increased duration of the parasternal muscle electromyogram during pharyngeal swabbing.</p

    Pearson product moment correlation scatter plot examples for the comparisons with the largest <i>r</i> values.

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    <p>Pearson product moment correlation scatter plot examples for the comparisons with the largest <i>r</i> values.</p

    Pearson Correlations comparing electromyogram amplitude and duration during swallowing.

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    <p>All data was pooled over the three conditions: water only, water plus punctate mechanical stimulation and pharyngeal swabbing.</p><p>Pearson Correlations comparing electromyogram amplitude and duration during swallowing.</p

    Effect of swallow stimuli on normalized electromyogram amplitude (% of maximum) and durations (ms) of selected swallow-related muscles, over the three stimulus conditions.

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    <p>*Significant effect (repeated measures ANOVA, P<0.05), significant difference (post-hoc test) from both other stimuli conditions (P<0.05).</p><p>Effect of swallow stimuli on normalized electromyogram amplitude (% of maximum) and durations (ms) of selected swallow-related muscles, over the three stimulus conditions.</p
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