Full-Field Displacement Measurements of Helicopter Rotor Blades Using Stereophotogrammetry

This study presents a stereophotogrammetry approach to achieve full-field displacement measurements of helicopter rotor blades. The method is demonstrated in the wind tunnel test of a 2 m diameter rotor, conducted at the 5.5 m×4 m Aeroacoustic Wind Tunnel of China Aerodynamics Research and Development Center (CARDC). By arranging the retroreflective targets on the special hat installed directly above the rotor hub, the dynamic motion of the rotor shaft was tracked accurately, and a unified coordinate system was established on the rotor. Therefore, three-dimensional coordinates of instantaneously measured targets attached on the blade could be transformed to the unified rotor coordinate system, thereby providing a basis for consistently calculating the blade displacements at different test conditions. Moreover, location deviations of the blade caused by the vibration of the measuring system or the rotor due to freestream and rotor rotation were also effectively corrected through coordinate transformation. Comparisons of experimental and simulation results for a range of hover and forward flight conditions show good magnitude and trend agreements

Genome-Wide Identification and Characterization of RNA/DNA Differences Associated with Drought Response in Wheat

RNA/DNA difference (RDD) is a post-transcriptional RNA modification to enrich genetic information, widely involved in regulating diverse biological processes in eukaryotes. RDDs in the wheat nuclear genome, especially those associated with drought response or tolerance, were not well studied up to now. In this study, we investigated the RDDs related to drought response based on the RNA-seq data of drought-stressed and control samples in wheat. In total, 21,782 unique RDDs were identified, of which 265 were found to be drought-induced, representing the first drought-responsive RDD landscape in the wheat nuclear genome. The drought-responsive RDDs were located in 69 genes, of which 35 were differentially expressed under drought stress. Furthermore, the effects of RNA/DNA differences were investigated, showing that they could result in changes of RNA secondary structure, miRNA-target binding as well as protein conserved domains in the RDD-containing genes. In particular, the A to C mutation in TraesCS2A02G053100 (orthology to OsRLCK) led to the loss of tae-miR9657b-5p targeting, indicating that RNA/DNA difference might mediate miRNA to regulate the drought-response process. This study reported the first drought-responsive RDDs in the wheat nuclear genome. It sheds light on the roles of RDD in drought tolerance, and may also contribute to wheat genetic improvement based on epi-transcriptome methods

Genome-Wide Identification, Evolution and Expressional Analysis of <i>OSCA</i> Gene Family in Barley (<i>Hordeum vulgare</i> L.)

The hyperosmolality-gated calcium-permeable channel gene family (OSCA) is one kind of conserved osmosensors, playing a crucial role in maintaining ion and water homeostasis and protecting cellular stability from the damage of hypertonic stress. Although it has been systematically characterized in diverse plants, it is necessary to explore the role of the OSCA family in barley, especially its importance in regulating abiotic stress response. In this study, a total of 13 OSCA genes (HvOSCAs) were identified in barley through an in silico genome search method, which were clustered into 4 clades based on phylogenetic relationships with members in the same clade showing similar protein structures and conserved motif compositions. These HvOSCAs had many cis-regulatory elements related to various abiotic stress, such as MBS and ARE, indicating their potential roles in abiotic stress regulation. Furthermore, their expression patterns were systematically detected under diverse stresses using RNA-seq data and qRT-PCR methods. All of these 13 HvOSCAs were significantly induced by drought, cold, salt and ABA treatment, demonstrating their functions in osmotic regulation. Finally, the genetic variations of the HvOSCAs were investigated using the re-sequencing data, and their nucleotide diversity in wild barley and landrace populations were 0.4966 × 10−3 and 0.391 × 10−3, respectively, indicating that a genetic bottleneck has occurred in the OSCA family during the barley evolution process. This study evaluated the genomic organization, evolutionary relationship and genetic expression of the OSCA family in barley, which not only provides potential candidates for further functional genomic study, but also contributes to genetically improving stress tolerance in barley and other crops

Additional file 1 of Population transcriptomic analysis identifies the comprehensive lncRNAs landscape of spike in wheat (Triticum aestivum L.)

Additional file 1: Table S1. Summary of all lncRNAs. Table S2. Summary of all lncRNA-mRNA pairs. Table S3. GO and KEGG enrichment of all target mRNAs. Table S4. Homologous lncRNAs between wheat and other species. Table S5. Sequence conservation of wheat lncRNAs based on results of whole-genome alignment. Table S6. Message of samples in population analysis. Table S7. Nucleotide diversity in each group. Table S8. Detail information of haplotype in lncRNA or target mRNA. (Yellow annotation indicates that gene has different haplotypes in different populations). Table S9. Interrelationship of ceRNA network between lncRNA, miRNA and mRNA. Table S10. Overlap between lncRNA or target mRNA and GWAS signals. Table S11. Overlap between lncRNA or target mRNA and known QTLs. Table S12. Overlap between lncRNA or target mRNA and introgression regions. Table S13. Information of 93 wheat lines. Table S14. Primers used for qRT-PCR analysis

Additional file 2 of Population transcriptomic analysis identifies the comprehensive lncRNAs landscape of spike in wheat (Triticum aestivum L.)

Additional file 2: Figure S1. Enrichment analysis of mRNA targets of lncRNAs. (a) GO enrichment analysis of target mRNAs. Different colors represent different GO term categories. (b) KEGG enrichment analysis of mRNA targets. Pathways were sorted by rich factor on the x-axis, which is determined by rich factor = (significant gene count of GO term)/(total gene count of GO term). Figure S2. Phylogenetic relationships of lncRNAs and target mRNAs on A subgenome. (a) Phylogenetic tree of lncRNA-mRNA pairs on A subgenome. (b) Phylogenetic tree of lncRNAs on A subgenome. (c). Phylogenetic tree of mRNAs on A subgenome. Figure S3. Phylogenetic relationships of lncRNAs and target mRNAs in B subgenome. (a) Phylogenetic tree of lncRNA-mRNA pairs on B subgenome. (b) Phylogenetic tree of lncRNAs on B subgenome. (c). Phylogenetic tree of mRNAs on B subgenome. Figure S4. Phylogenetic relationships of lncRNAs and target mRNAs in D subgenome. (a). Phylogenetic tree of lncRNA-mRNA pairs on D subgenome. (b) Phylogenetic tree of lncRNAs on D subgenome. (c). Phylogenetic tree of mRNAs on D subgenome. Figure S5. Expression and functional enrichment of lncRNAs and target mRNAs in chromosome 1BS. (a). Heatmap of expression levels of lncRNAs and target mRNAs in the 1B1R region. (b). Boxplots of expression levels of lncRNAs and target mRNAs in the 1B1R region in the two groups of samples. (c). GO and KEGG enrichment analysis of target mRNAs within 1B1R region. Figure S6. qRT-PCR validation of lncRNAs between 1B1R samples and non-1B1R samples. (a). qRT-PCR validation of 1B1R lineage-specific lncRNAs. (b). qRT-PCR validation of non-1B1R lineage-specific lncRNAs. The significance of expression level between 1B1R and non-1B1R groups was statistically analyzed by student's t-test. Figure S7. Phylogenetic relationships of TraesCS2A02G518500 in A subgenome. Figure S8. Genome-wide average LD decay estimated from 93 samples