LncRNA DANA1 promotes drought tolerance and histone deacetylation of drought responsive genes in Arabidopsis.

Although many long noncoding RNAs have been discovered in plants, little is known about their biological function and mode of action. Here we show that the drought-induced long intergenic noncoding RNA DANA1 interacts with the L1p/L10e family member protein DANA1-INTERACTING PROTEIN 1 (DIP1) in the cell nucleus of Arabidopsis, and both DANA1 and DIP1 promote plant drought resistance. DANA1 and DIP1 increase histone deacetylase HDA9 binding to the CYP707A1 and CYP707A2 loci. DIP1 further interacts with PWWP3, a member of the PEAT complex that associates with HDA9 and has histone deacetylase activity. Mutation of DANA1 enhances CYP707A1 and CYP707A2 acetylation and expression resulting in impaired drought tolerance, in agreement with dip1 and pwwp3 mutant phenotypes. Our results demonstrate that DANA1 is a positive regulator of drought response and that DANA1 works jointly with the novel chromatin-related factor DIP1 on epigenetic reprogramming of the plant transcriptome during the response to drought.

The U1 small nuclear RNA enhances drought tolerance in Arabidopsis.

Alternative splicing (AS) is an important posttranscriptional regulatory mechanism that improves plant tolerance to drought stress by modulating gene expression and generating proteome diversity. The interaction between the 5' end of U1 small nuclear RNA (U1 snRNA) and the conserved 5' splice site of precursor messenger RNA (pre-mRNA) is pivotal for U1 snRNP involvement in AS. However, the roles of U1 snRNA in drought stress responses remain unclear. This study provides a comprehensive analysis of AtU1 snRNA in Arabidopsis (Arabidopsis thaliana), revealing its high conservation at the 5' end and a distinctive four-leaf clover structure. AtU1 snRNA is localized in the nucleus and expressed in various tissues, with prominent expression in young floral buds, flowers, and siliques. The overexpression of AtU1 snRNA confers enhanced abiotic stress tolerance, as evidenced in seedlings by longer seedling primary root length, increased fresh weight, and a higher greening rate compared with the wild-type. Mature AtU1 snRNA overexpressor plants exhibit higher survival rates and lower water loss rates under drought stress, accompanied by a significant decrease in H2O2 and an increase in proline. This study also provides evidence of altered expression levels of drought-related genes in AtU1 snRNA overexpressor or genome-edited lines, reinforcing the crucial role of AtU1 snRNA in drought stress responses. Furthermore, the overexpression of AtU1 snRNA influences the splicing of downstream target genes, with a notable impact on SPEECHLESS (SPCH), a gene associated with stomatal development, potentially explaining the observed decrease in stomatal aperture and density. These findings elucidate the critical role of U1 snRNA as an AS regulator in enhancing drought stress tolerance in plants, contributing to a deeper understanding of the AS pathway in drought tolerance and increasing awareness of the molecular network governing drought tolerance in plants.

RNA splicing modulates the postharvest physiological deterioration of cassava storage root.

Rapid postharvest physiological deterioration (PPD) of cassava (Manihot esculenta Crantz) storage roots is a major constraint that limits the potential of this plant as a food and industrial crop. Extensive studies have been performed to explore the regulatory mechanisms underlying the PPD processes in cassava to understand their molecular and physiological responses. However, the exceptional functional versatility of alternative splicing (AS) remains to be explored during the PPD process in cassava. Here, we identified several aberrantly spliced genes during the early PPD stage. An in-depth analysis of AS revealed that the abscisic acid (ABA) biosynthesis pathway might serve as an additional molecular layer in attenuating the onset of PPD. Exogenous ABA application alleviated PPD symptoms through maintaining ROS generation and scavenging. Interestingly, the intron retention transcript of MeABA1 (ABA DEFICIENT 1) was highly correlated with PPD symptoms in cassava storage roots. RNA yeast 3-hybrid and RNA immunoprecipitation (RIP) assays showed that the serine/arginine-rich protein MeSCL33 (SC35-like splicing factor 33) binds to the precursor mRNA of MeABA1. Importantly, overexpressing MeSCL33 in cassava conferred improved PPD resistance by manipulating the AS and expression levels of MeABA1 and then modulating the endogenous ABA levels in cassava storage roots. Our results uncovered the pivotal role of the ABA biosynthesis pathway and RNA splicing in regulating cassava PPD resistance and proposed the essential roles of MeSCL33 for conferring PPD resistance, broadening our understanding of SR proteins in cassava development and stress responses.

PSEUDO-RESPONSE REGULATOR 3b and transcription factor ABF3 modulate abscisic acid-dependent drought stress response in soybean.

The circadian system plays a pivotal role in facilitating the ability of crop plants to respond and adapt to fluctuations in their immediate environment effectively. Despite the increasing comprehension of PSEUDO-RESPONSE REGULATORs and their involvement in the regulation of diverse biological processes, including circadian rhythms, photoperiodic control of flowering, and responses to abiotic stress, the transcriptional networks associated with these factors in soybean (Glycine max (L.) Merr.) remain incompletely characterized. In this study, we provide empirical evidence highlighting the significance of GmPRR3b as a crucial mediator in regulating the circadian clock, drought stress response, and abscisic acid (ABA) signaling pathway in soybeans. A comprehensive analysis of DNA affinity purification sequencing and transcriptome data identified 795 putative target genes directly regulated by GmPRR3b. Among them, a total of 570 exhibited a significant correlation with the response to drought, and eight genes were involved in both the biosynthesis and signaling pathways of ABA. Notably, GmPRR3b played a pivotal role in the negative regulation of the drought response in soybeans by suppressing the expression of abscisic acid-responsive element-binding factor 3 (GmABF3). Additionally, the overexpression of GmABF3 exhibited an increased ability to tolerate drought conditions, and it also restored the hypersensitive phenotype of the GmPRR3b overexpressor. Consistently, studies on the manipulation of GmPRR3b gene expression and genome editing in plants revealed contrasting reactions to drought stress. The findings of our study collectively provide compelling evidence that emphasizes the significant contribution of the GmPRR3b-GmABF3 module in enhancing drought tolerance in soybean plants. Moreover, the transcriptional network of GmPRR3b provides valuable insights into the intricate interactions between this gene and the fundamental biological processes associated with plant adaptation to diverse environmental conditions.

Identification of GmPT proteins and investigation of their expressions in response to abiotic stress in soybean.

MAIN CONCLUSION: Investigation the expression patterns of GmPT genes in response to various abiotic stresses and overexpression of GmPT11 in soybean hairy roots and Arabidopsis exhibited hypersensitivity to salt stress. Soybean is considered to be one of the significant oil crops globally, as it offers a diverse range of essential nutrients that contribute to human health. Salt stress seriously affects the yield of soybean through negative impacts on the growth, nodulation, reproduction, and other agronomy traits. The phosphate transporters 1(PHT1) subfamily, which is a part of the PHTs family in plants, is primarily found in the cell membrane and responsible for the uptake and transport of phosphorus. However, the role of GmPT (GmPT1-GmPT14) genes in response to salt stress has not been comprehensively studied. Here, we conducted a systematic analysis to ascertain the distribution and genomic duplications of GmPT genes, as well as their expression patterns in response to various abiotic stresses. Promoter analysis of GmPT genes revealed that six stress-related cis-elements were enriched in these genes. The overexpression of GmPT11 in soybean hairy roots and Arabidopsis exhibited hypersensitivity to salt stress, while no significant change was observed under low phosphate treatment, suggesting a crucial role in the response to salt stress. These findings provide novel insights into enhancing plant tolerance to salt stress.

A novel natural variation in the promoter of GmCHX1 regulates conditional gene expression to improve salt tolerance in soybean.

Identification and characterization of soybean germplasm and gene(s)/allele(s) for salt tolerance is an effective way to develop improved varieties for saline soils. Previous studies identified GmCHX1 (Glyma03g32900) as a major salt tolerance gene in soybean, and two main functional variations were found in the promoter region (148/150 bp insertion) and the third exon with a retrotransposon insertion (3.78 kb). In the current study, we identified four salt-tolerant soybean lines, including PI 483460B (Glycine soja), carrying the previously identified salt-sensitive variations at GmCHX1, suggesting new gene(s) or new functional allele(s) of GmCHX1 in these soybean lines. Subsequently, we conducted quantitative trait locus (QTL) mapping in a recombinant-inbred line population (Williams 82 (salt-sensitive) × PI 483460B) to identify the new salt tolerance loci/alleles. A new locus, qSalt_Gm18, was mapped on chromosome 18 associated with leaf scorch score. Another major QTL, qSalt_Gm03, was identified to be associated with chlorophyll content ratio and leaf scorch score in the same chromosomal region of GmCHX1 on chromosome 3. Novel variations in a STRE (stress response element) cis-element in the promoter region of GmCHX1 were found to regulate the salt-inducible expression of the gene in these four newly identified salt-tolerant lines including PI 483460B. This new allele of GmCHX1 with salt-inducible expression pattern provides an energy cost efficient (conditional gene expression) strategy to protect soybean yield in saline soils without yield penalty under non-stress conditions. Our results suggest that there might be no other major salt tolerance locus similar to GmCHX1 in soybean germplasm, and further improvement of salt tolerance in soybean may rely on gene-editing techniques instead of looking for natural variations.

Wide-Band Unambiguous Quantum Sensing via Geodesic Evolution.

We present a quantum sensing technique that utilizes a sequence of π pulses to cyclically drive the qubit dynamics along a geodesic path of adiabatic evolution. This approach effectively suppresses the effects of both decoherence noise and control errors while simultaneously removing unwanted resonance terms, such as higher harmonics and spurious responses commonly encountered in dynamical decoupling control. As a result, our technique offers robust, wide-band, unambiguous, and high-resolution quantum sensing capabilities for signal detection and individual addressing of quantum systems, including spins. To demonstrate its versatility, we showcase successful applications of our method in both low-frequency and high-frequency sensing scenarios. The significance of this quantum sensing technique extends to the detection of complex signals and the control of intricate quantum environments. By enhancing detection accuracy and enabling precise manipulation of quantum systems, our method holds considerable promise for a variety of practical applications.

Identification of the domestication gene GmCYP82C4 underlying the major quantitative trait locus for the seed weight in soybean.

KEY MESSAGE: A major quantitative trait locus (QTL) for the hundred-seed weight (HSW) was identified and confirmed in the two distinct soybean populations, and the target gene GmCYP82C4 underlying this locus was identified that significantly associated with soybean seed weight, and it was selected during the soybean domestication and improvement process. Soybean is a major oil crop for human beings and the seed weight is a crucial goal of soybean breeding. However, only a limited number of target genes underlying the quantitative trait loci (QTLs) controlling seed weight in soybean are known so far. In the present study, six loci associated with hundred-seed weight (HSW) were detected in the first population of 573 soybean breeding lines by genome-wide association study (GWAS), and 64 gene models were predicted in these candidate QTL regions. The QTL qHSW_1 exhibits continuous association signals on chromosome four and was also validated by region association study (RAS) in the second soybean population (409 accessions) with wild, landrace, and cultivar soybean accessions. There were seven genes in qHSW_1 candidate region by linkage disequilibrium (LD) block analysis, and only Glyma.04G035500 (GmCYP82C4) showed specifically higher expression in flowers, pods, and seeds, indicating its crucial role in the soybean seed development. Significant differences in HSW trait were detected when the association panels are genotyped by single-nucleotide polymorphisms (SNPs) in putative GmCYP82C4 promoter region. Eight haplotypes were generated by six SNPs in GmCYP82C4 in the second soybean population, and two superior haplotypes (Hap2 and Hap4) of GmCYP82C4 were detected with average HSW of 18.27 g and 18.38 g, respectively. The genetic diversity of GmCYP82C4 was analyzed in the second soybean population, and GmCYP82C4 was most likely selected during the soybean domestication and improvement process, leading to the highest proportion of Hap2 of GmCYP82C4 both in landrace and cultivar subpopulations. The QTLs and GmCYP82C4 identified in this study provide novel genetic resources for soybean seed weight trait, and the GmCYP82C4 could be used for soybean molecular breeding to develop desirable seed weight in the future.

Green Synthesis of Polyurethane Sponge-Grafted Calcium Alginate with Carbon Ink Aerogel with High Water Vapor Harvesting Capacity for Solar-Driven All-Weather Atmospheric Water Harvesting.

Atmospheric water harvesting (AWH) technology is a new strategy for alleviating freshwater scarcity. Adsorbent materials with high hygroscopicity and high photothermal conversion efficiency are the key to AWH technology. Hence, in this study, a simple and large-scale preparation for a hygroscopic compound of polyurethane (PU) sponge-grafted calcium alginate (CA) with carbon ink (SCAC) was developed. The PU sponge in the SCAC aerogel acts as a substrate, CA as a moisture adsorber, and carbon ink as a light adsorber. The SCAC aerogel exhibits excellent water absorption of 0.555-1.40 g·g-1 within a wide range of relative humidity (40-80%) at 25 °C. The SCAC aerogel could release adsorbed water driven by solar energy, and more than 92.17% of the adsorbed water could be rapidly released over a wide solar intensity range of 1.0-2.0 sun. In an outdoor experiment, 57.517 g of SCAC was able to collect 32.8 g of clean water in 6 h, and the water quality meets the drinking water standards set by the World Health Organization. This study suggests a new approach to design promising AWH materials and infers the potential practical application of SCAC aerogel-based adsorbents.

RBNE-CMI: An Efficient Method for Predicting circRNA-miRNA Interactions via Multiattribute Incomplete Heterogeneous Network Embedding.

Circular RNA (circRNA)-microRNA (miRNA) interaction (CMI) plays crucial roles in cellular regulation, offering promising perspectives for disease diagnosis and therapy. Therefore, it is necessary to employ computational methods for the rapid and cost-effective prediction of potential circRNA-miRNA interactions. However, the existing methods are limited by incomplete data; therefore, it is difficult to model molecules with different attributes on a large scale, which greatly hinders the efficiency and performance of prediction. In this study, we propose an effective method for predicting circRNA-miRNA interactions, called RBNE-CMI, and introduce a framework that can embed incomplete multiattribute CMI heterogeneous networks. By combining the proposed method, we integrate different data sets in the CMI prediction field into one incomplete network for modeling, achieving superior performance in 5-fold cross-validation. Moreover, in the prediction task based on complete data, the proposed method still achieves better performance than the known model. In addition, in the case study, we successfully predicted 18 of the 20 potential cancer biomarkers. The data and source code can be found at https://github.com/1axin/RBNE-CMI.