Additional file 1: of Chromosome-scale comparative sequence analysis unravels molecular mechanisms of genome dynamics between two wheat cultivars
AuthorsThind, Anupriya Kaur
International Wheat Genome Sequencing Consortium
Ackermann, Patrick M.
Wulff, Brande B. H.
Twardziok, Sven O.
Mayer, Klaus F. X.
Krattinger, Simon G.
Permanent link to this recordhttp://hdl.handle.net/10754/664152
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AbstractFigure S1. Haploblocks a, b and d show sequence homology in the intergenic regions between Chinese Spring and CH Campala Lr22a (PDF). Figure S2. Dot plot of the haploblock c region from Chinese Spring and CH Campala Lr22a with Ae. tauschii. Figure S3. Gene collinearity between Chinese Spring and CH Campala Lr22a. (PDF 3408 kb)
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Thind AK, Wicker T, Müller T, Ackermann PM, et al. (2018) Chromosome-scale comparative sequence analysis unravels molecular mechanisms of genome dynamics between two wheat cultivars. Genome Biology 19. Available: http://dx.doi.org/10.1186/s13059-018-1477-2.. DOI: 10.1186/s13059-018-1477-2 HANDLE: 10754/628478
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Impact of data preprocessing on cell-type clustering based on single-cell RNA-seq dataWang, Chunxiang; Gao, Xin; Liu, Juntao (figshare, 2020) [Dataset]Abstract Background Advances in single-cell RNA-seq technology have led to great opportunities for the quantitative characterization of cell types, and many clustering algorithms have been developed based on single-cell gene expression. However, we found that different data preprocessing methods show quite different effects on clustering algorithms. Moreover, there is no specific preprocessing method that is applicable to all clustering algorithms, and even for the same clustering algorithm, the best preprocessing method depends on the input data. Results We designed a graph-based algorithm, SC3-e, specifically for discriminating the best data preprocessing method for SC3, which is currently the most widely used clustering algorithm for single cell clustering. When tested on eight frequently used single-cell RNA-seq data sets, SC3-e always accurately selects the best data preprocessing method for SC3 and therefore greatly enhances the clustering performance of SC3. Conclusion The SC3-e algorithm is practically powerful for discriminating the best data preprocessing method, and therefore largely enhances the performance of cell-type clustering of SC3. It is expected to play a crucial role in the related studies of single-cell clustering, such as the studies of human complex diseases and discoveries of new cell types.
Additional file 4: of Silica diatom shells tailored with Au nanoparticles enable sensitive analysis of molecules for biological, safety and environment applicationsOnesto, V.; Villani, M.; Coluccio, M. L.; Majewska, R.; Alabastri, A.; Battista, E.; Schirato, A.; Calestani, D.; Coppedé, N.; Cesarelli, M.; Amato, F.; Di Fabrizio, Enzo M.; Gentile, F. (figshare, 2018) [Dataset]Supporting figures to the Numerical Simulation Methods of the main text. (DOCX 608Â kb)
A transcriptional analysis of carotenoid, chlorophyll and plastidial isoprenoid biosynthesis genes during development and osmotic stress responses in Arabidopsis thalianaMeier, Stuart Kurt; Tzfadia, Oren; Vallabhaneni, Ratnakar; Gehring, Christoph A; Wurtzel, Eleanore T (BMC Systems Biology, Springer Nature, 2011-05-19) [Article]Background: The carotenoids are pure isoprenoids that are essential components of the photosynthetic apparatus and are coordinately synthesized with chlorophylls in chloroplasts. However, little is known about the mechanisms that regulate carotenoid biosynthesis or the mechanisms that coordinate this synthesis with that of chlorophylls and other plastidial synthesized isoprenoid-derived compounds, including quinones, gibberellic acid and abscisic acid. Here, a comprehensive transcriptional analysis of individual carotenoid and isoprenoid-related biosynthesis pathway genes was performed in order to elucidate the role of transcriptional regulation in the coordinated synthesis of these compounds and to identify regulatory components that may mediate this process in Arabidopsis thaliana.Results: A global microarray expression correlation analysis revealed that the phytoene synthase gene, which encodes the first dedicated and rate-limiting enzyme of carotenogenesis, is highly co-expressed with many photosynthesis-related genes including many isoprenoid-related biosynthesis pathway genes. Chemical and mutant analysis revealed that induction of the co-expressed genes following germination was dependent on gibberellic acid and brassinosteroids (BR) but was inhibited by abscisic acid (ABA). Mutant analyses further revealed that expression of many of the genes is suppressed in dark grown plants by Phytochrome Interacting transcription Factors (PIFs) and activated by photoactivated phytochromes, which in turn degrade PIFs and mediate a coordinated induction of the genes. The promoters of PSY and the co-expressed genes were found to contain an enrichment in putative BR-auxin response elements and G-boxes, which bind PIFs, further supporting a role for BRs and PIFs in regulating expression of the genes. In osmotically stressed root tissue, transcription of Calvin cycle, methylerythritol 4-phosphate pathway and carotenoid biosynthesis genes is induced and uncoupled from that of chlorophyll biosynthesis genes in a manner that is consistent with the increased synthesis of carotenoid precursors for ABA biosynthesis. In all tissues examined, induction of ?-carotene hydroxylase transcript levels are linked to an increased demand for ABA.Conclusions: This analysis provides compelling evidence to suggest that coordinated transcriptional regulation of isoprenoid-related biosynthesis pathway genes plays a major role in coordinating the synthesis of functionally related chloroplast localized isoprenoid-derived compounds. 2011 Meier et al; licensee BioMed Central Ltd.