DNA Methylation and Normal Chromosome Behavior in Neurospora Depend on Five Components of a Histone Methyltransferase Complex, DCDC

Methylation of DNA and of Lysine 9 on histone H3 (H3K9) is associated with gene silencing in many animals, plants, and fungi. In Neurospora crassa, methylation of H3K9 by DIM-5 directs cytosine methylation by recruiting a complex containing Heterochromatin Protein-1 (HP1) and the DIM-2 DNA methyltransferase. We report genetic, proteomic, and biochemical investigations into how DIM-5 is controlled. These studies revealed DCDC, a previously unknown protein complex including DIM-5, DIM-7, DIM-9, CUL4, and DDB1. Components of DCDC are required for H3K9me3, proper chromosome segregation, and DNA methylation. DCDC-defective strains, but not HP1-defective strains, are hypersensitive to MMS, revealing an HP1-independent function of H3K9 methylation. In addition to DDB1, DIM-7, and the WD40 domain protein DIM-9, other presumptive DCAFs (DDB1/CUL4 associated factors) co-purified with CUL4, suggesting that CUL4/DDB1 forms multiple complexes with distinct functions. This conclusion was supported by results of drug sensitivity tests. CUL4, DDB1, and DIM-9 are not required for localization of DIM-5 to incipient heterochromatin domains, indicating that recruitment of DIM-5 to chromatin is not sufficient to direct H3K9me3. DIM-7 is required for DIM-5 localization and mediates interaction of DIM-5 with DDB1/CUL4 through DIM-9. These data support a two-step mechanism for H3K9 methylation in Neurospora

De novo Assembly of a 40 Mb Eukaryotic Genome from Short Sequence Reads: Sordaria macrospora, a Model Organism for Fungal Morphogenesis

Filamentous fungi are of great importance in ecology, agriculture, medicine, and biotechnology. Thus, it is not surprising that genomes for more than 100 filamentous fungi have been sequenced, most of them by Sanger sequencing. While next-generation sequencing techniques have revolutionized genome resequencing, e.g. for strain comparisons, genetic mapping, or transcriptome and ChIP analyses, de novo assembly of eukaryotic genomes still presents significant hurdles, because of their large size and stretches of repetitive sequences. Filamentous fungi contain few repetitive regions in their 30–90 Mb genomes and thus are suitable candidates to test de novo genome assembly from short sequence reads. Here, we present a high-quality draft sequence of the Sordaria macrospora genome that was obtained by a combination of Illumina/Solexa and Roche/454 sequencing. Paired-end Solexa sequencing of genomic DNA to 85-fold coverage and an additional 10-fold coverage by single-end 454 sequencing resulted in ∼4 Gb of DNA sequence. Reads were assembled to a 40 Mb draft version (N50 of 117 kb) with the Velvet assembler. Comparative analysis with Neurospora genomes increased the N50 to 498 kb. The S. macrospora genome contains even fewer repeat regions than its closest sequenced relative, Neurospora crassa. Comparison with genomes of other fungi showed that S. macrospora, a model organism for morphogenesis and meiosis, harbors duplications of several genes involved in self/nonself-recognition. Furthermore, S. macrospora contains more polyketide biosynthesis genes than N. crassa. Phylogenetic analyses suggest that some of these genes may have been acquired by horizontal gene transfer from a distantly related ascomycete group. Our study shows that, for typical filamentous fungi, de novo assembly of genomes from short sequence reads alone is feasible, that a mixture of Solexa and 454 sequencing substantially improves the assembly, and that the resulting data can be used for comparative studies to address basic questions of fungal biology

Coupling a Lagrangian–Eulerian Spark-Ignition (LESI) model with LES combustion models for engine simulations

In the United States transportation sector, Light-Duty Vehicles (LDVs) are the largest energy consumers and CO2 emitters. Electrification of LDVs is posed as a potential solution, but SI engines can still contribute to decarbonization. Car manufacturers have turned to unconventional engine operation to increase the efficiency of Spark-Ignition (SI) engines and reduce the carbon emissions of their fleets. Dilute, lean, and stratified-charge engine operation has the potential for engine efficiency improvements at the expense of increased cyclic variability and combustion instability. At such demanding engine conditions, the spark ignition event is key for flame initiation and propagation and for enhanced combustion stability. Reliable and accurate spark ignition models can help design ignition systems that reduce cyclic variability. Multiple computational spark-ignition models exist that perform well under conventional conditions, but the underlying physics needs to be expanded, for unconventional engine operation. In this paper, a hybrid Lagrangian–Eulerian Spark-Ignition (LESI) model is coupled with different turbulent flame propagation models for engine simulations. LESI relies on Lagrangian arc tracking and Eulerian energy deposition. The LESI model is coupled with the Well-Stirred Reactor (WSR), Thickened Flame Model (TFM), and g-equation model and used to simulate several cycles of a Direct-Injection Spark-Ignition (DISI) engine using a commercial Computational Fluid Dynamics (CFD) engine solver. The results showcase the successful coupling of LESI with the combustion models. Global engine metrics, such as pressure and Apparent Heat Release Rate (AHRR), for each simulation setup are compared to experimental engine results, for validation. In addition, results highlight the successful prediction of spark channel movement by comparing simulation images to experimental optical engine images. Finally, the successful coupling of LESI to combustion models, making it a usable model in the engine modeling community, is emphasized and future development details are discussed

High-fidelity energy deposition ignition model coupled with flame propagation models at engine-like flow conditions

With the heightened pressure on car manufacturers to increase the efficiency and reduce the carbon emissions of their fleets, more challenging engine operation has become a viable option. Highly dilute, boosted, and stratified charge, among others, promise engine efficiency gains and emissions reductions. At such demanding engine conditions, the spark-ignition process is a key factor for the flame initiation propagation and the combustion event. From a computational standpoint, there exists multiple spark-ignition models that perform well under conventional conditions but are not truly predictive under strenuous engine operation modes, where the underlying physics needs to be expanded. In this paper, a hybrid Lagrangian-Eulerian spark-ignition (LESI) model is coupled with different turbulence models, grid sizes, and combustion models. The ignition model, previously developed, relies on coupling Eulerian energy deposition with a Lagrangian particle evolution of the spark channel, at every time-step. The spark channel is attached to the electrodes and allowed to elongate at a speed derived from the flow velocity. The LESI model is used to simulate spark ignition in a non-quiescent crossflow environment at engine-like conditions, using CONVERGE commercial CFD solver. The results highlight the consistency, robustness, and versatility of the model in a range of engine-like setups, from typical with RANS and a larger grid size to high fidelity with LES and a finer grid size. The flame kernel growth is then evaluated against schlieren images from an optical constant volume ignition chamber with a focus on the performance of flame propagation models, such as G-equation and thickened flame model, versus the baseline well-stirred reactor model. Finally, future development details are discussed