29 research outputs found

    Rapid generation of a transgene-free powdery mildew resistant tomato by genome deletion

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    Genome editing has emerged as a technology with a potential to revolutionize plant breeding. In this study, we report on generating, in less than ten months, Tomelo, a non-transgenic tomato variety resistant to the powdery mildew fungal pathogen using the CRISPR/Cas9 technology. We used whole-genome sequencing to show that Tomelo does not carry any foreign DNA sequences but only carries a deletion that is indistinguishable from naturally occurring mutations. We also present evidence for CRISPR/Cas9 being a highly precise tool, as we did not detect off-target mutations in Tomelo. Using our pipeline, mutations can be readily introduced into elite or locally adapted tomato varieties in less than a year with relatively minimal effort and investment

    The independence of neutral and ionized gas outflows in low-z galaxies

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    Using a large sample of emission line galaxies selected from the Sloan Digital Sky Survey, we investigate the kinematics of the neutral gas in the interstellar medium (ISM) based on the Na Iλλ\lambda\lambda5890,5896 (Na D) doublet absorption line. By removing the Na D contribution from stellar atmospheres, we isolate the line profile of the Na D excess, which represents the neutral gas in the ISM. The kinematics traced by the Na D excess show high velocity and velocity dispersion for a fraction of galaxies, indicating the presence of neutral gas outflows. We find that the kinematics measured from the Na D excess are similar between AGNs and star-forming galaxies. Moreover, by comparing the kinematics traced by the Na D excess and those by the [O III]λ\lambda5007 line taken from Woo et al. (2017), which traces ionized outflows driven by AGNs, we find no correlation between them. These results demonstrate that the neutral gas in the ISM traced by the Na D excess and the ionized gas traced by [O III] are kinematically independent, and AGN has no impact on the neutral gas outflows. In contrast to [O III], we find that the measured line-of-sight velocity shift and velocity dispersion of the Na D excess increase for more face-on galaxies due to the projection effect, supporting that Na D outflows are radially driven (i.e., perpendicular to the major axis of galaxies), presumably due to star formation.Comment: 7 pages, 6 figures; Accepted for publication in ApJ, corrected the titl

    A novel compression tool for efficient storage of genome resequencing data

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    With the advent of DNA sequencing technologies, more and more reference genome sequences are available for many organisms. Analyzing sequence variation and understanding its biological importance are becoming a major research aim. However, how to store and process the huge amount of eukaryotic genome data, such as those of the human, mouse and rice, has become a challenge to biologists. Currently available bioinformatics tools used to compress genome sequence data have some limitations, such as the requirement of the reference single nucleotide polymorphisms (SNPs) map and information on deletions and insertions. Here, we present a novel compression tool for storing and analyzing Genome ReSequencing data, named GRS. GRS is able to process the genome sequence data without the use of the reference SNPs and other sequence variation information and automatically rebuild the individual genome sequence data using the reference genome sequence. When its performance was tested on the first Korean personal genome sequence data set, GRS was able to achieve ∼159-fold compression, reducing the size of the data from 2986.8 to 18.8 MB. While being tested against the sequencing data from rice and Arabidopsis thaliana, GRS compressed the 361.0 MB rice genome data to 4.4 MB, and the A. thaliana genome data from 115.1 MB to 6.5 KB. This de novo compression tool is available at http://gmdd.shgmo.org/Computational-Biology/GRS

    ANAP: An Integrated Knowledge Base for Arabidopsis Protein Interaction Network Analysis1[C][W][OA]

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    Protein interactions are fundamental to the molecular processes occurring within an organism and can be utilized in network biology to help organize, simplify, and understand biological complexity. Currently, there are more than 10 publicly available Arabidopsis (Arabidopsis thaliana) protein interaction databases. However, there are limitations with these databases, including different types of interaction evidence, a lack of defined standards for protein identifiers, differing levels of information, and, critically, a lack of integration between them. In this paper, we present an interactive bioinformatics Web tool, ANAP (Arabidopsis Network Analysis Pipeline), which serves to effectively integrate the different data sets and maximize access to available data. ANAP has been developed for Arabidopsis protein interaction integration and network-based study to facilitate functional protein network analysis. ANAP integrates 11 Arabidopsis protein interaction databases, comprising 201,699 unique protein interaction pairs, 15,208 identifiers (including 11,931 The Arabidopsis Information Resource Arabidopsis Genome Initiative codes), 89 interaction detection methods, 73 species that interact with Arabidopsis, and 6,161 references. ANAP can be used as a knowledge base for constructing protein interaction networks based on user input and supports both direct and indirect interaction analysis. It has an intuitive graphical interface allowing easy network visualization and provides extensive detailed evidence for each interaction. In addition, ANAP displays the gene and protein annotation in the generated interactive network with links to The Arabidopsis Information Resource, the AtGenExpress Visualization Tool, the Arabidopsis 1,001 Genomes GBrowse, the Protein Knowledgebase, the Kyoto Encyclopedia of Genes and Genomes, and the Ensembl Genome Browser to significantly aid functional network analysis. The tool is available open access at http://gmdd.shgmo.org/Computational-Biology/ANAP

    An effective approach for identification of <it>in vivo </it>protein-DNA binding sites from paired-end ChIP-Seq data

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    <p>Abstract</p> <p>Background</p> <p>ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with high-throughput massively parallel sequencing, is increasingly being used for identification of protein-DNA interactions <it>in vivo </it>in the genome. However, to maximize the effectiveness of data analysis of such sequences requires the development of new algorithms that are able to accurately predict DNA-protein binding sites.</p> <p>Results</p> <p>Here, we present SIPeS (<b>S</b>ite <b>I</b>dentification from <b>P</b>aired-<b>e</b>nd <b>S</b>equencing), a novel algorithm for precise identification of binding sites from short reads generated by paired-end solexa ChIP-Seq technology. In this paper we used ChIP-Seq data from the <it>Arabidopsis </it>basic helix-loop-helix transcription factor ABORTED MICROSPORES (AMS), which is expressed within the anther during pollen development, the results show that SIPeS has better resolution for binding site identification compared to two existing ChIP-Seq peak detection algorithms, Cisgenome and MACS.</p> <p>Conclusions</p> <p>When compared to Cisgenome and MACS, SIPeS shows better resolution for binding site discovery. Moreover, SIPeS is designed to calculate the mappable genome length accurately with the fragment length based on the paired-end reads. Dynamic baselines are also employed to effectively discriminate closely adjacent binding sites, for effective binding sites discovery, which is of particular value when working with high-density genomes.</p
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