BackgroundChinese fir (Cunninghamia lanceolata) is an important timber species that accounts for 20–30% of the total commercial timber production in China. However, the available genomic information of Chinese fir is limited, and this severely encumbers functional genomic analysis and molecular breeding in Chinese fir. Recently, major advances in transcriptome sequencing have provided fast and cost-effective approaches to generate large expression datasets that have proven to be powerful tools to profile the transcriptomes of non-model organisms with undetermined genomes.ResultsIn this study, the transcriptomes of nine tissues from Chinese fir were analyzed using the Illumina HiSeq™ 2000 sequencing platform. Approximately 40 million paired-end reads were obtained, generating 3.62 gigabase pairs of sequencing data. These reads were assembled into 83,248 unique sequences (i.e. Unigenes) with an average length of 449 bp, amounting to 37.40 Mb. A total of 73,779 Unigenes were supported by more than 5 reads, 42,663 (57.83%) had homologs in the NCBI non-redundant and Swiss-Prot protein databases, corresponding to 27,224 unique protein entries. Of these Unigenes, 16,750 were assigned to Gene Ontology classes, and 14,877 were clustered into orthologous groups. A total of 21,689 (29.40%) were mapped to 119 pathways by BLAST comparison against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The majority of the genes encoding the enzymes in the biosynthetic pathways of cellulose and lignin were identified in the Unigene dataset by targeted searches of their annotations. And a number of candidate Chinese fir genes in the two metabolic pathways were discovered firstly. Eighteen genes related to cellulose and lignin biosynthesis were cloned for experimental validating of transcriptome data. Overall 49 Unigenes, covering different regions of these selected genes, were found by alignment. Their expression patterns in different tissues were analyzed by qRT-PCR to explore their putative functions.ConclusionsA substantial fraction of transcript sequences was obtained from the deep sequencing of Chinese fir. The assembled Unigene dataset was used to discover candidate genes of cellulose and lignin biosynthesis. This transcriptome dataset will provide a comprehensive sequence resource for molecular genetics research of C. lanceolata.

Natural wind is stochastic, being characterized by its speed and direction which change randomly and frequently. Because of the certain lag in control systems and the yaw body itself, wind turbines cannot be accurately aligned toward the wind direction when the wind speed and wind direction change frequently. Thus, wind turbines often suffer from a series of engineering issues during operation, including frequent yaw, vibration overruns and downtime. This paper aims to study the effects of yaw error on wind turbine running characteristics at different wind speeds and control stages by establishing a wind turbine model, yaw error model and the equivalent wind speed model that includes the wind shear and tower shadow effects. Formulas for the relevant effect coefficients Tc, Sc and Pc were derived. The simulation results indicate that the effects of the aerodynamic torque, rotor speed and power output due to yaw error at different running stages are different and that the effect rules for each coefficient are not identical when the yaw error varies. These results may provide theoretical support for optimizing the yaw control strategies for each stage to increase the running stability of wind turbines and the utilization rate of wind energy.

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Inorganic phosphate (Pi) is often lacking in natural and agro-climatic environments, which impedes the growth of economically important woody species. Plants have developed strategies to cope with low Pi (LP) availability. MicroRNAs (miRNAs) play important roles in responses to abiotic stresses, including nutrition stress, by regulating target gene expression. However, the miRNA-mediated regulation of these adaptive responses and their underlying coordinating signals are still poorly understood in forestry trees such as Betula luminifera. Transcriptomic libraries, small RNA (sRNA) libraries, and a mixed degradome cDNA library of B. luminifera roots and shoots treated under LP and normal conditions (CK) were constructed and sequenced using next-generation deep sequencing. A comprehensive B. luminifera transcriptome derived from its roots and shoots was constructed, and a total of 76,899 unigenes were generated. Analysis of the transcriptome identified 8,095 and 5,584 differentially expressed genes in roots and shoots, respectively, under LP conditions. sRNA sequencing analyses indicated that 66 and 60 miRNAs were differentially expressed in roots and shoots, respectively, under LP conditions. A total of 109 and 112 miRNA–target pairs were further validated in the roots and shoots, respectively, using degradome sequencing. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of differential miRNA targets indicated that the “ascorbate and aldarate metabolism” pathway responded to LP, suggesting miRNA-target pairs might participating in the removing of reactive oxidative species under LP stress. Moreover, a putative network of miRNA–target interactions involved in responses to LP stress in B. luminifera is proposed. Taken together, these findings provide useful information to decipher miRNA functions and establish a framework for exploring P signaling networks regulated by miRNAs in B. luminifera and other woody plants. It may provide new insights into the genetic engineering of high use efficiency of Pi in forestry trees.

BackgroundAmyotrophic lateral sclerosis (ALS), partly caused by the mutations and aggregation of human copper, zinc superoxide dismutase (SOD1), is a fatal degenerative disease of motor neurons. Because SOD1 is a major copper-binding protein present at relatively high concentration in motor neurons and copper can be a harmful pro-oxidant, we want to know whether aberrant copper biochemistry could underlie ALS pathogenesis. In this study, we have investigated and compared the effects of cupric ions on the aggregation of ALS-associated SOD1 mutant A4V and oxidized wild-type SOD1.Methodology/Principal FindingsAs revealed by 90° light scattering, dynamic light scattering, SDS-PAGE, and atomic force microscopy, free cupric ions in solution not only induce the oxidation of either apo A4V or Zn2-A4V and trigger the oligomerization and aggregation of oxidized A4V under copper-mediated oxidative conditions, but also trigger the aggregation of non-oxidized form of such a pathogenic mutant. As evidenced by mass spectrometry and SDS-PAGE, Cys-111 is a primary target for oxidative modification of pathological human SOD1 mutant A4V by either excess Cu2+ or hydrogen peroxide. The results from isothermal titration calorimetry show that A4V possesses two sets of independent binding sites for Cu2+: a moderate-affinity site (106 M-1) and a high-affinity site (108 M-1). Furthermore, Cu2+ binds to wild-type SOD1 oxidized by hydrogen peroxide in a way similar to A4V, triggering the aggregation of such an oxidized form.Conclusions/SignificanceWe demonstrate that excess cupric ions induce the oxidation and trigger the aggregation of A4V SOD1, and suggest that Cu2+ plays a key role in the mechanism of aggregation of both A4V and oxidized wild-type SOD1. A plausible model for how pathological SOD1 mutants aggregate in ALS-affected motor neurons with the disruption of copper homeostasis has been provided.