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2% using classic data augmentation and 22% using synthetic samples without LSR.The asymmetric flower, lacking any plane of symmetry, is rare among angiosperms. Canna indica L. has conspicuously asymmetric flowers resulting from the presence of a half-fertile stamen, while the other androecial members develop as petaloid staminodes or abort early during development. The molecular basis of the asymmetric distribution of fertility and petaloidy in the androecial whorls remains unknown. Ontogenetic studies have shown that Canna flowers are borne on monochasial (cincinnus) partial florescences within a racemose inflorescence, with floral asymmetry likely corresponding to the inflorescence architecture. Given the hypothesized role of CYC/TB1 genes in establishing floral symmetry in response to the influence of the underlying inflorescence architecture, the spatiotemporal expression patterns of three Canna CYC/TB1 homologs (CiTBL1a, CiTBL1b-1, and CiTBL1b-2) were analyzed during inflorescence and floral development using RNA in situ hybridization and qRT-PCR. In the young inflorescence, both CCYC/TB1 homologs in the development of the asymmetric Cannaceae flower.Anti-sense transcription is increasingly being recognized as an important regulator of gene expression. But the transcriptome complementation of anti-sense RNA in hybrid relative to their inbred parents was largely unknown. In this study, we profiled strand-specific RNA sequencing (RNA-seq) in a maize hybrid and its inbred parents (B73 and Mo17) in two tissues. More anti-sense transcripts were present in the hybrid compared with the parental lines. We detected 293 and 242 single-parent expression of anti-sense (SPEA) transcripts in maize immature ear and leaf tissues, respectively. There was little overlap of the SPEA transcripts between the two maize tissues. These results suggested that SPEA is a general mechanism that drives extensive complementation in maize hybrids. More importantly, extremely high-level expression of anti-sense transcripts was associated with low-level expression of the cognate sense transcript by reducing the level of histone H3 lysine 36 methylation (H3K36me3). In summary, these SPEA transcripts increased our knowledge about the transcriptomic complementation in hybrid.As a primary food crop, maize is widely grown around the world. However, the deficiency of essential amino acids, such as lysine, tryptophan, and methionine, results in poor nutritional quality of maize. In addition, the protein concentration of maize declines with the increase in yield, which further reduces the nutritional quality. Here, the photosynthesis of leaves, grain amino acid composition, and stoichiometry of N and S are explored. The results show that N and S maintained the redox balance by increasing the content of glutathione in maize leaves, thereby enhancing the photosynthetic rate and maize yield. Simultaneously, the synergy of N and S increased the grain protein concentration and promoted amino acid balance by increasing the cysteine concentration in maize grains. The maize yield, grain protein concentration, and concentration of essential amino acids, such as lysine, tryptophan, and methionine, could be simultaneously increased in the NS ratio range of 11.0 to 12.0. Overall, the synergy of N and S simultaneously improved the maize yield and nutritional quality by regulating the redox balance of maize leaves and the amino acids balance of grains, which provides a new theoretical basis and practical method for sustainable production of maize.Drought stress is an important abiotic factor limiting common bean yield, with great impact on the production worldwide. Understanding the genetic basis regulating beans' yield and seed weight (SW) is a fundamental prerequisite for the development of superior cultivars. The main objectives of this work were to conduct genome-wide marker discovery by genotyping a Mesoamerican panel of common bean germplasm, containing cultivated and landrace accessions of broad origin, followed by the identification of genomic regions associated with productivity under two water regimes using different genome-wide association study (GWAS) approaches. A total of 11,870 markers were genotyped for the 339 genotypes, of which 3,213 were SilicoDArT and 8,657 SNPs derived from DArT and CaptureSeq. The estimated linkage disequilibrium extension, corrected for structure and relatedness (r2 sv ), was 98.63 and 124.18 kb for landraces and breeding lines, respectively. Germplasm was structured into landraces and lines/cultivars. We carrils to be used in marker-assisted breeding. The findings also allowed the identification of genetic material (germplasm) with better yield performance under drought, promising to a common bean breeding program. Finally, the availability of this highly diverse Mesoamerican panel is of great scientific value for the analysis of any relevant traits in common bean.To achieve rapid, accurate, and non-destructive diagnoses of nitrogen deficiency in cold land japonica rice, hyperspectral data were collected from field experiments to investigate the relationship between the nitrogen (N) content and the difference in the spectral reflectance relationship and to establish the hyperspectral reflectance difference inversion model of differences in the N content of rice. Selleck Bromopyruvic In this study, the hyperspectral reflectance difference was used to invert the nitrogen deficiency of rice and provide a method for the implementation of precision fertilization without reducing the yield of chemical fertilizer. For the purpose of constructing the standard N content and standard spectral reflectance the principle of minimum fertilizer application at maximum yield was used as a reference standard, and the acquired rice leaf nitrogen content and leaf spectral reflectance were differenced from the standard N content and standard spectral reflectance to obtain N content. The difference and spectral reflectance differential were then subjected to discrete wavelet multiscale decomposition, successive projections algorithm, principal component analysis, and iteratively retaining informative variables (IRIVs); the results were treated as partial least squares (PLSR), extreme learning machine (ELM), and genetic algorithm-extreme learning machine (GA-ELM). The results of hyperspectral dimensionality reduction were used as input to establish the inverse model of N content differential in japonica rice. The results showed that the GA-ELM inversion model established by discrete wavelet multi-scale decomposition obtained the optimal results in data set modeling and training. Both the R2 of the training data set and the validation data set were above 0.68, and the root mean square errors (RMSEs) were less then 0.6 mg/g and were more predictive, stable, and generalizable than the PLSR and ELM predictive models.

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