The Genomes of Oryza sativa: A History of Duplications

We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family

Optimization of Cellulase Production by a Novel Endophytic Fungus Penicillium oxalicum R4 Isolated from Taxus cuspidata

Endophytic fungi inside a plant can degrade a portion of plant lignin and cellulose. Endophytic Penicillium is one of the industrial microorganisms with the advantage of producing enzymes with a complete enzyme system that can be secreted into the extracellular space. The natural evolution of ancient tree species from special natural geographic environments to screen out cellulase-producing strains with excellent characteristics provides a promising direction for future industrial enzymes. The present study successfully isolated and screened a novel fungal endophyte, Penicillium oxalicum R4, with higher cellulase activity from Taxus cuspidata. Under the optimized culture conditions obtained by a Box–Behnken design (BBD) and an artificial neural network–genetic algorithm (ANN–GA), yields of Filter Paperase (FPase), Carboxymethyl Cellulase (CMCase) and β-glucosidase (βGLase) produced by P. oxalicum R4 were 1.45, 5.27 and 6.35 U/mL, which were approximately 1.60-fold, 1.59-fold and 2.16-fold higher than those of the non-optimized culture, respectively. The discovery of cellulase-producing strains of endophytic fungi located in special natural geographic environments, such as Taxus cuspidata, which is known as a living plant fossil, provides new research directions for future industrial enzymes

Probing Enzymatic Activity inside Living Cells Using a Nanowire–Cell “Sandwich” Assay

Developing a detailed understanding of enzyme function in the context of an intracellular signal transduction pathway requires minimally invasive methods for probing enzyme activity <i>in situ</i>. Here, we describe a new method for monitoring enzyme activity in living cells by sandwiching live cells between two vertical silicon nanowire (NW) arrays. Specifically, we use the first NW array to immobilize the cells and then present enzymatic substrates intracellularly via the second NW array by utilizing the NWs’ ability to penetrate cellular membranes without affecting cells’ viability or function. This strategy, when coupled with fluorescence microscopy and mass spectrometry, enables intracellular examination of protease, phosphatase, and protein kinase activities, demonstrating the assay’s potential in uncovering the physiological roles of various enzymes

Functional Classifications from GO, Focused on Plant-Specific Categories Outlined by Gramene

<p>(A) compares predicted genes from <i>Arabidopsis</i> and Beijing <i>indica</i>. (B) compares predicted genes from Beijing <i>indica</i> with nr-KOME cDNAs. We ignore categories with less than 0.1% of the genes.</p