Genome-wide characterization of SDR gene family and its potential role in seed dormancy of Brassica napus L.

Rapeseed (Brassica napus L.) with short or no dormancy period are easy to germinate before harvest (pre-harvest sprouting, PHS). PHS has seriously decreased seed weight and oil content in B. napus. Short-chain dehydrogenase/ reductase (SDR) genes have been found to related to seed dormancy by promoting ABA biosynthesis in rice and Arabidopsis. In order to clarify whether SDR genes are the key factor of seed dormancy in B. napus, homology sequence blast, protein physicochemical properties, conserved motif, gene structure, cis-acting element, gene expression and variation analysis were conducted in present study. Results shown that 142 BnaSDR genes, unevenly distributed on 19 chromosomes, have been identified in B. napus genome. Among them, four BnaSDR gene clusters present in chromosome A04、A05、C03、C04 were also identified. These 142 BnaSDR genes were divided into four subfamilies on phylogenetic tree. Members of the same subgroup have similar protein characters, conserved motifs, gene structure, cis-acting elements and tissue expression profiles. Specially, the expression levels of genes in subgroup A, B and C were gradually decreased, but increased in subgroup D with the development of seeds. Among seven higher expressed genes in group D, six BnaSDR genes were significantly higher expressed in weak dormancy line than that in nondormancy line. And the significant effects of BnaC01T0313900ZS and BnaC03T0300500ZS variation on seed dormancy were also demonstrated in present study. These findings provide a key information for investigating the function of BnaSDRs on seed dormancy in B. napus.

Melatonin Promotes SGT1-Involved Signals to Ameliorate Drought Stress Adaption in Rice.

Drought has become one of the environmental threats to agriculture and food security. Applications of melatonin (MT) serve as an effective way to alleviate drought stress, but the underlying mechanism remains poorly understood. Here, we found that foliar spray of 100-µM MT greatly mitigated the severe drought stress-induced damages in rice seedlings, including improved survival rates, enhanced antioxidant system, and adjusted osmotic balance. However, mutation of the suppressor of the G2 allele of skp1 (OsSGT1) and ABSCISIC ACID INSENSITIVE 5 (OsABI5) abolished the effects of MT. Furthermore, the upregulated expression of OsABI5 was detected in wild type (WT) under drought stress, irrespective of MT treatment, whereas OsABI5 was significantly downregulated in sgt1 and sgt1abi5 mutants. In contrast, no change of the OsSGT1 expression level was detected in abi5. Moreover, mutation of OsSGT1 and OsABI5 significantly suppressed the expression of genes associated with the antioxidant system. These results suggested that the functions of OsSGT1 in the MT-mediated alleviation of drought stress were associated with the ABI5-mediated signals. Collectively, we demonstrated that OsSGT1 was involved in the drought response of rice and that melatonin promoted SGT1-involved signals to ameliorate drought stress adaption.

Identification and Expression Analysis of DFR Gene Family in Brassica napus L.

Dihydroflavonol 4-reductase (DFR) is a key enzyme in the flavonoid biosynthetic pathway and is essential for the formation of plants' color. In this study, 26 BnDFR genes were identified using 6 Arabidopsis DFR genes as reference. The physicochemical properties, subcellular localization, and conserved structure of BnDFR proteins were analyzed; the evolutionary relationship, collinearity analysis, and expression characteristics of BnDFR genes were studied; and the correlation between the expression level of BnDFR genes and anthocyanin content in rape petals were analyzed. The results showed that the 26 BnDFRs were located in chloroplasts, cytoplasm, nuclei, and mitochondria, distributed on 17 chromosomes, and divided into 4 groups; members of the same group have a similar function, which may be related to the environmental response elements and plant hormone response elements. Intraspecific collinearity analysis showed 51 pairs of collinear genes, and interspecific collinearity analysis showed 30 pairs of collinear genes. Analysis of the expression levels of BnDFRs and anthocyanin content in different color rape petals showed that BnDFR6 and BnDFR26 might play an important role in the synthesis of anthocyanins in rape petals. This provides theoretical guidance for further analysis of the anthocyanin anabolism mechanism involved in the DFR gene in Brassica napus.

A Zero-Padding Frequency Domain Convolutional Neural Network for SSVEP Classification.

The brain-computer interface (BCI) of steady-state visual evoked potential (SSVEP) is one of the fundamental ways of human-computer communication. The main challenge is that there may be a nonlinear relationship between different SSVEP in other states. For improving the performance of SSVEP BCI, a novel CNN algorithm model is proposed in this study. Based on the discrete Fourier transform to calculate the signal's power spectral density (PSD), we perform zero-padding in the signal's time domain to improve its performance on the PSD and make it more refined. In this way, the frequency point interval in the PSD of the SSVEP is consistent with the minimum gap between the stimulation frequency. Combining the nonlinear transformation capabilities of CNN in deep learning, a zero-padding frequency domain convolutional neural network (ZPFDCNN) model is proposed. Extensive experiments based on the SSVEP dataset validate the effectiveness of our method. The study verifies that the proposed ZPFDCNN method can improve the effectiveness of the SSVEP-based high-speed BCI ITR. It has massive potential in the application of BCI.

A review of starch biosynthesis in cereal crops and its potential breeding applications in rice (Oryza Sativa L.).

Starch provides primary storage of carbohydrates, accounting for approximately 85% of the dry weight of cereal endosperm. Cereal seeds contribute to maximum annual starch production and provide the primary food for humans and livestock worldwide. However, the growing demand for starch in food and industry and the increasing loss of arable land with urbanization emphasizes the urgency to understand starch biosynthesis and its regulation. Here, we first summarized the regulatory signaling pathways about leaf starch biosynthesis. Subsequently, we paid more attention to how transcriptional factors (TFs) systematically respond to various stimulants via the regulation of the enzymes during starch biosynthesis. Finally, some strategies to improve cereal yield and quality were put forward based on the previous reports. This review would collectively help to design future studies on starch biosynthesis in cereal crops.

Automatic Sleep Staging Algorithm Based on Time Attention Mechanism.

The most important part of sleep quality assessment is the automatic classification of sleep stages. Sleep staging is helpful in the diagnosis of sleep-related diseases. This study proposes an automatic sleep staging algorithm based on the time attention mechanism. Time-frequency and non-linear features are extracted from the physiological signals of six channels and then normalized. The time attention mechanism combined with the two-way bi-directional gated recurrent unit (GRU) was used to reduce computing resources and time costs, and the conditional random field (CRF) was used to obtain information between tags. After five-fold cross-validation on the Sleep-EDF dataset, the values of accuracy, WF1, and Kappa were 0.9218, 0.9177, and 0.8751, respectively. After five-fold cross-validation on the our own dataset, the values of accuracy, WF1, and Kappa were 0.9006, 0.8991, and 0.8664, respectively, which is better than the result of the latest algorithm. In the study of sleep staging, the recognition rate of the N1 stage was low, and the imbalance has always been a problem. Therefore, this study introduces a type of balancing strategy. By adopting the proposed strategy, SEN-N1 and ACC of 0.7 and 0.86, respectively, can be achieved. The experimental results show that compared to the latest method, the proposed model can achieve significantly better performance and significantly improve the recognition rate of the N1 period. The performance comparison of different channels shows that even when the EEG channel was not used, considerable accuracy can be obtained.