40 research outputs found

    Phosphazene-Catalyzed Alternating Copolymerization of Dihydrocoumarin and Ethylene Oxide: Weaker Is Better

    No full text
    Metal-free alternating copolymerization of 3,4-dihydrocoumarin (DHC) and ethylene oxide (EO) was realized by relatively mild phosphazene bases (<i>t</i>-BuP<sub>2</sub> and <i>t</i>-BuP<sub>1</sub>), which unexpectedly outperformed previously employed <i>t</i>-BuP<sub>4</sub> superbase in terms of polymerization rate, monomer conversion, and copolymer molar mass, though macrocycles were still generated when long chains were targeted. Such facts have indicated the occurrence of proton shuttling between phosphazenium cation and alkoxide which reduced chain-end nucleophilicity and thus alleviated side reactions such as backbiting. It was surprising that <i>t</i>-BuP<sub>1</sub> whose basicity was too low for the homopolymerization of EO triggered alternating copolymerization, indicating that generation of anionic species (phenoxide) was essential for the epoxide-opening step. Well-defined short-chain diols were subjected to one-pot subsequent chain extension by addition of an aliphatic lactone or a diisocyanate leading to, respectively, block copolymer or polyurethane constituted by alternating segments. Poly­(DHC-<i>alt</i>-EO) showed a better thermal stability than those of the substituted epoxides. This study has suggested that mild and non-nucleophilic organobases may be more suitable catalysts for epoxide-based metal-free alternating copolymerization toward well-defined macromolecular structures

    Haplotype analysis of the <i>E4</i> gene region.

    No full text
    <p>The SNPViz clustering pictorial displayed the SNPs in a 12.6-kb region on chromosome 20, which included Glyma20g22160. Nucleotide polymorphisms were examined in A) the wild (black) and cultivated (red) lines from the Chinese collection and B) the NAM parents (blue). Details about the SNPViz clustering pictorial were described in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094150#pone-0094150-g001" target="_blank">Figure 1</a> legend.</p

    Major Soybean Maturity Gene Haplotypes Revealed by SNPViz Analysis of 72 Sequenced Soybean Genomes

    No full text
    <div><p>In this Genomics Era, vast amounts of next-generation sequencing data have become publicly available for multiple genomes across hundreds of species. Analyses of these large-scale datasets can become cumbersome, especially when comparing nucleotide polymorphisms across many samples within a dataset and among different datasets or organisms. To facilitate the exploration of allelic variation and diversity, we have developed and deployed an in-house computer software to categorize and visualize these haplotypes. The SNPViz software enables users to analyze region-specific haplotypes from single nucleotide polymorphism (SNP) datasets for different sequenced genomes. The examination of allelic variation and diversity of important soybean [<i>Glycine max</i> (L.) Merr.] flowering time and maturity genes may provide additional insight into flowering time regulation and enhance researchers' ability to target soybean breeding for particular environments. For this study, we utilized two available soybean genomic datasets for a total of 72 soybean genotypes encompassing cultivars, landraces, and the wild species <i>Glycine soja</i>. The major soybean maturity genes <i>E1</i>, <i>E2</i>, <i>E3</i>, and <i>E4</i> along with the <i>Dt1</i> gene for plant growth architecture were analyzed in an effort to determine the number of major haplotypes for each gene, to evaluate the consistency of the haplotypes with characterized variant alleles, and to identify evidence of artificial selection. The results indicated classification of a small number of predominant haplogroups for each gene and important insights into possible allelic diversity for each gene within the context of known causative mutations. The software has both a stand-alone and web-based version and can be used to analyze other genes, examine additional soybean datasets, and view similar genome sequence and SNP datasets from other species.</p></div

    Maturity and growth determinate genotypes for the 41 NAM parents.

    No full text
    1<p>The <i>E4</i> genotype is not shown because the causative SNP was not identified in the data.</p>2<p>DNA was unavailable for <i>E3/e3</i> genotyping.</p

    Reported polymorphic alleles of major maturity genes with reference to the Williams 82 sequence.

    No full text
    1<p>Uppercase allele designations indicate the dominant functional versions of the gene. In each case, the recessive mutant version of the gene is earlier flowering and maturing than the functional dominant version of the gene. The Williams 82 genome contains an earlier maturing missense version of <i>E1</i> (<i>e1-as</i>; T15R compared to the wild-type functional <i>E1</i>) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094150#pone.0094150-Xia1" target="_blank">[5]</a>. Allele names are taken or modified from the published descriptions for clarity.</p>2<p>The underlined alleles were identified and described in the literature but were not present in the two datasets used for this analysis.</p>3<p>Although the Williams 82 <i>E3</i> allele is considered functional, it was shown to contain an insertion in intron three consisting of transposable element-like sequences when compared to other functional <i>E3</i> alleles without the insertion in intron 3 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094150#pone.0094150-Watanabe2" target="_blank">[7]</a>. We herein denote the <i>E3</i> from Williams 82 as <i>E3</i> and the equivalently functional shorter <i>E3</i> allele as <i>E3 (short)</i>.</p

    Major flowering time/maturity genes present in the Williams 82 reference sequence and positions used around those genes for haplotype analysis.

    No full text
    1<p>Gene location based on the Williams 82 reference sequence Glyma1.1.</p>2<p>Gene location based on the Williams 82 reference sequence Glyma1.0.</p

    Haplotype analysis of the <i>Dt1</i> gene region.

    No full text
    <p>The SNPViz clustering pictorial displayed the SNPs in an 8.6-kb region on chromosome 19, which included Glyma19g37890. Nucleotide polymorphisms were examined in A) the wild (black) and cultivated (red) lines from the Chinese collection and B) the NAM parents (blue). Details about the SNPViz clustering pictorial were described in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094150#pone-0094150-g001" target="_blank">Figure 1</a> legend.</p

    Maturity and growth determinate genotypes for wild soybean.

    No full text
    1<p><i>E3</i> and <i>E4</i> genotypes are not shown because the causative SNP was not identified in the data.</p

    Haplotype analysis of the <i>E1</i> gene region.

    No full text
    <p>The SNPViz clustering pictorial displayed the SNPs in a 7.8-kb region on chromosome six, which included Glyma06g23026. UPGMA grouped samples by calculating their sequence identity to the reference, Williams 82. Each soybean line was represented by a column with nucleotides only shown for the reference. All base positions that are identical to the reference are white, those that are different are black, and positions with no data or missing data are gray. Since an annotation file was included in this analysis, the gene locations, DNA strand, and exon start and end site are shown to the right of SNP position. Nucleotide polymorphisms were examined in A) the wild (black) and cultivated (red) lines from the Chinese collection and B) the NAM parents (blue).</p

    Additional file 1: of RNA virus receptor Rig-I monitors gut microbiota and inhibits colitis-associated colorectal cancer

    No full text
    Figure S1. Scoring criteria of RIG-I immunohistochemical staining. Figure S2. Analytical procedures of high-throughput sequencing data. Figure S3. Induction of colorectal tumors in mice. a The induction procedure of colorectal tumor. Wt mice (n = 10) and Rig-I −/− littermates (n = 11) were treated with AOM and DSS. All mice were sacrificed at the end of the procedure. b Colon length and diameter of wt and Rig-I −/− mice were shown. c H & E staining of untreated colon sections related to Fig 2c. Scale bar, 100 μm. Figure S4. Diversity of the gut microbiota between wild-type and Rig-I −/− mice. a P-values of P-tests on the NJ tree. The letter “W” and numbers represented week number. b Principal Component Analysis (PCA) was used to compare bacterial families across different groups. The percentage of variation explained by each principal component was indicated on the axis. Figure S5. Western blot analysis. a Western blot analysis in untreated mouse colons. b Western blot analysis in AOM/DSS-treated adjacent or tumor colons. Table S1. Primers used in this study. Table S2. Numbers of cases for each given score related to Fig. 2d and e. (DOCX 1089 kb
    corecore