Comprehensive Evaluation and Analysis of the Mechanism of Cold Tolerance Based on the Transcriptome of Weedy Rice Seedlings

Genetic dissection of cold tolerance at the budding stage of rice in an indica-japonica recombination inbred line population

Rice is highly cold-sensitive, and thus, the promotion of cold resistance in buds is essential. In this study, we conducted a mapping analysis to identify quantitative trait loci (QTLs) associated with cold tolerance in buds. The analysis was performed using a recombinant inbred line (RIL) population consisting of 192 lines derived from the cold-tolerant strain 02428 and the cold-sensitive strain YZX. Seven additive loci on chromosomes 1, 4, 5, and 6 were identified, of which loci 3 and 7 were found in two crop seasons, indicating stability. Three epistatic interactions, one present over two seasons, were found. Loci 3 and 7 pyramided with two main-effect QTLs observed to control the rate of low-temperature germination in our previous study. Two materials with good cold resistance at the germination and bud stages were obtained, namely, G93 and G146. Transcriptome sequencing analysis of the two parent buds after cold treatment found that genes expressed differentially between the two parents were related to photosynthesis, energy metabolism, and reactive oxygen scavenging. Five candidate genes, namely, Os01g0385400, Os01g0388000, Os06g0287700, Os06g0289200, and Os06g0291100, were selected in the two stable intervals based on gene expression profiles and annotations. These genetic loci exhibit strong potential as targets for breeding cold tolerance in buds and require additional investigation. In conclusion, this work provides valuable genetic resources that can be utilized to improve the cold tolerance of rice.

Identification of Wheat Ideotype under Multiple Abiotic Stresses and Complex Environmental Interplays by Multivariate Analysis Techniques

Multiple abiotic stresses negatively impact wheat production all over the world. We need to increase productivity by 60% to provide food security to the world population of 9.6 billion by 2050; it is surely time to develop stress-tolerant genotypes with a thorough comprehension of the genetic basis and the plant's capacity to tolerate these stresses and complex environmental reactions. To approach these goals, we used multivariate analysis techniques, the additive main effects and multiplicative interaction (AMMI) model for prediction, linear discriminant analysis (LDA) to enhance the reliability of the classification, multi-trait genotype-ideotype distance index (MGIDI) to detect the ideotype, and the weighted average of absolute scores (WAASB) index to recognize genotypes with stability that are highly productive. Six tolerance multi-indices were used to test twenty wheat genotypes grown under multiple abiotic stresses. The AMMI model showed varying differences with performance indices, which disagreed with the trait and genotype differences used. The G01, G12, G16, and G02 were selected as the appropriate and stable genotypes using the MGIDI with the six tolerance multi-indices. The biplot features the genotypes (G01, G03, G11, G16, G17, G18, and G20) that were most stable and had high tolerance across the environments. The pooled analyses (LDA, MGIDI, and WAASB) showed genotype G01 as the most stable candidate. The genotype (G01) is considered a novel genetic resource for improving productivity and stabilizing wheat programs under multiple abiotic stresses. Hence, these techniques, if used in an integrated manner, strongly support the plant breeders in multi-environment trials.

Low temperature response index for monitoring freezing injury of tea plant

Freezing damage has been a common natural disaster for tea plantations. Quantitative detection of low temperature stress is significant for evaluating the degree of freezing injury to tea plants. Traditionally, the determination of physicochemical parameters of tea leaves and the investigation of freezing damage phenotype are the main approaches to detect the low temperature stress. However, these methods are time-consuming and laborious. In this study, different low temperature treatments were carried out on tea plants. The low temperature response index (LTRI) was established by measuring seven low temperature-induced components of tea leaves. The hyperspectral data of tea leaves was obtained by hyperspectral imaging and the feature bands were screened by successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS) and uninformative variable elimination (UVE). The LTRI and seven indexes of tea plant were modeled by partial least squares (PLS), support vector machine (SVM), random forests (RF), back propagation (BP) machine learning methods and convolutional neural networks (CNN), long short-term memory (LSTM) deep learning methods. The results indicated that: (1) the best prediction model for the seven indicators was LTRI-UVE-CNN (R^{2 =} 0.890, RMSEP=0.325, RPD=2.904); (2) the feature bands screened by UVE algorithm were more abundant, and the later modeling effect was better than CARS and SPA algorithm; (3) comparing the effects of the six modeling algorithms, the overall modeling effect of the CNN model was better than other models. It can be concluded that out of all the combined models in this paper, the LTRI-UVE-CNN was a promising model for predicting the degree of low temperature stress in tea plants.

Multi-omics approach reveals the contribution of OsSEH1 to rice cold tolerance

As low environmental temperature adversely affects the growth, development and geographical distribution, plants have evolved multiple mechanisms involving changing physiological and metabolic processes to adapt to cold stress. In this study, we revealed that nucleoporin-coding gene OsSEH1 was a positive regulator of cold stress in rice. Physiological assays showed that the activity of antioxidant enzymes showed a significant difference between osseh1 knock-out lines and wild type under cold stress. Metabolome analysis revealed that the contents of large-scale flavonoids serving as ROS scavengers were lower in osseh1 mutants compared with wild type under cold stress. Transcriptome analysis indicated that the DEGs between osseh1 knock-out lines and wild type plants were enriched in defense response, regulation of hormone levels and oxidation-reduction process. Integration of transcriptomic and metabolic profiling revealed that OsSEH1 plays a role in the oxidation-reduction process by coordinately regulating genes expression and metabolite accumulation involved in phenylpropanoid and flavonoid biosynthetic pathway. In addition, Exogenous ABA application assays indicated that osseh1 lines had hypersensitive phenotypes compared with wild type plants, suggesting that OsSEH1 may mediate cold tolerance by regulating ABA levels.

Phenotypic and transcriptomic analysis reveals early stress responses in transgenic rice expressing Arabidopsis DREB1a

Overexpression of Arabidopsis dehydration response element binding 1a (DREB1a) is a well-known approach for developing salinity, cold and/or drought stress tolerance. However, understanding of the genetic mechanisms associated with DREB1a expression in rice is generally limited. In this study, DREB1a-associated early responses were investigated in a transgenic rice line harboring cold-inducible DREB1a at a gene stacked locus. Although the function of other genes in the stacked locus was not relevant to stress tolerance, this study demonstrates DREB1a can be co-localized with other genes for multigenic trait enhancement. As expected, the transgenic lines displayed improved tolerance to salinity stress and water withholding as compared with non-transgenic controls. RNA sequencing and transcriptome analysis showed upregulation of complex transcriptional networks and metabolic reprogramming as DREB1a expression led to the upregulation of multiple transcription factor gene families, suppression of photosynthesis, and induction of secondary metabolism. In addition to the detection of previously described mechanisms such as production of protective molecules, potentially novel pathways were also revealed. These include jasmonate, auxin, and ethylene signaling, induction of JAZ and WRKY regulons, trehalose synthesis, and polyamine catabolism. These genes regulate various stress responses and ensure timely attenuation of the stress signal. Furthermore, genes associated with heat stress response were downregulated in DREB1a expressing lines, suggesting antagonism between heat and dehydration stress response pathways. In summary, through a complex transcriptional network, multiple stress signaling pathways are induced by DREB1a that presumably lead to early perception and prompt response toward stress tolerance as well as attenuation of the stress signal to prevent deleterious effects of the runoff response.

Evaluation of salt tolerance of oat cultivars and the mechanism of adaptation to salinity

Soil salinity is a threat to agricultural production worldwide. Oat (Avena sativa L.) is an irreplaceable crop in areas with fragile ecological conditions. However, there is a lack of research on salt tolerance evaluation of oat germplasm resources. Therefore, the purpose of this work was to evaluate the salt tolerance of oat cultivars and investigate the mechanism of salt-tolerant oat cultivars' adaptation to salinity. Salt tolerance of 100 oat cultivars was evaluated, and then two salt-tolerant cultivars and two salt-sensitive cultivars were used to compare their physiological responses and expression patterns of Na⁺- and K⁺-transport-related genes under salinity. Principal component analysis and membership function analysis had good predictability for salt tolerance evaluation of oat and other crops. The 100 oat cultivars were clustered into three categories, with three salt tolerance levels. Under saline condition, salt-tolerant cultivars maintained higher growth rate, leaf cell membrane integrity, and osmotic adjustment capability via enhancing the activities of antioxidant enzymes and accumulating more osmotic regulators. Furthermore, salt-tolerant cultivars had stronger capability to restrict root Na ⁺ uptake through reducing AsAKT1 and AsHKT2;1 expression, exclude more Na⁺ from root through increasing AsSOS1 expression, compartmentalize more Na ⁺ into root vacuoles through increasing AsNHX1 and AsVATP-P1 expression, and absorb more K⁺ through increasing AsKUP1 expression, compared with salt-sensitive cultivars. The evaluation procedure developed in this work can be applied for screening cereal crop cultivars with higher salt tolerance, and the elucidated mechanism of oat adaptation to salinity lays a foundation for identifying more functional genes related to salt tolerance.

Evidence for evolution and selection of drought-resistant genes based on high-throughput resequencing in weedy rice

Weedy rice (Oryza sativa f. spontanea) is a relative of cultivated rice that propagates in paddy fields and has strong drought resistance. In this study, we used 501 rice accessions to reveal the selection mechanism of drought resistance in weedy rice through a combination of selection analysis, genome-wide association studies, gene knockout and overexpression analysis, and Ca2+ and K+ ion flux assays. The results showed that the weedy rice species investigated have gene introgression with cultivated rice, which is consistent with the hypothesis that weedy rice originated from de-domestication of cultivated rice. Regions related to tolerance have particularly diversified during de-domestication and three drought-tolerance genes were identified. Of these, Os01g0800500 was also identified using an assay of the degree of leaf withering under drought, and it was named as PAPH1, encoding a PAP family protein. The drought-resistance capacity of PAPH1-knockout lines was much lower than that of the wild type, while that of overexpression lines was much higher. Concentrations of Ca2+ and K+ were lower in the knockout lines and higher in the overexpression lines compared with those of the wild type, suggesting that PAPH1 plays important roles in coping with drought stress. Our study therefore provides new insights into the genetic mechanisms underlying adaptive tolerance to drought in wild rice and highlights potential new resistance genes for future breeding programs in cultivated rice.

Low Temperature Antioxidant Activity QTL Associate with Genomic Regions Involved in Physiological Cold Stress Tolerance Responses in Rice (Oryza sativa L.)

Boosting cold stress tolerance in crop plants can minimize stress-mediated yield losses. Asian rice (Oryza sativa L.), one of the most consumed cereal crops, originated from subtropical regions and is generally sensitive to low temperature environments. Within the two subspecies of rice, JAPONICA, and INDICA, the cold tolerance potential of its accessions is highly variable and depends on their genetic background. Yet, cold stress tolerance response mechanisms are complex and not well understood. This study utilized 370 accessions from the Rice Diversity Panel 1 (RDP1) to investigate and correlate four cold stress tolerance response phenotypes: membrane damage, seedling survivability, and catalase and anthocyanin antioxidative activity. Most JAPONICA accessions, and admixed accessions within JAPONICA, had lower membrane damage, higher antioxidative activity, and overall, higher seedling survivability compared to INDICA accessions. Genome-wide association study (GWAS) mapping was done using the four traits to find novel quantitative trait loci (QTL), and to validate and fine-map previously identified QTL. A total of 20 QTL associated to two or more traits were uncovered by our study. Gene Ontology (GO) term enrichment analyses satisfying four layers of filtering retrieved three potential pathways: signal transduction, maintenance of plasma membrane and cell wall integrity, and nucleic acids metabolism as general mechanisms of cold stress tolerance responses involving antioxidant activity.

Selection of transcripts related to low-temperature tolerance using RNA sequencing from F2 plants between japonica and indica rice (Oryza sativa L.) cultivars

At low temperatures (18°C), seedlings of an indica rice (Oryza sativa L.) cultivar Kasalath showed symptoms of chlorosis, although the leaves of a japonica cultivar Arroz da Terra remained green. In this study, transcripts related to the chlorophyll content of rice seedlings grown at 18°C were investigated using RNA-sequencing (RNA-Seq) data for F2 crosses between cultivars Arroz da Terra and Kasalath, as well as their parental cultivars. Differential expression analysis revealed that gene ontology terms related to 'photosynthesis' were significantly enriched in lowly expressed genes at 18°C than at 25°C in Kasalath. However, the gene ontology terms related to 'response to stress' were significantly enriched in highly expressed genes at 18°C than at 25°C in Kasalath. When the F2 plants were grown at 18°C, their chlorophyll contents varied. Transcripts with expression levels related to chlorophyll content were statistically selected using RNA-Seq data from 21 F2 plants. In regression models, frequently selected genes included four photosynthetic and two stress-responsive genes. The expression values of four photosynthetic and two stress-responsive genes in high-frequency selected genes were significantly correlated with chlorophyll content not only in plants analysed using RNA-Seq but also in 95 F2 plants.

Assessing alfalfa (Medicago sativa L.) tolerance to salinity at seedling stage and screening of the salinity tolerance traits

Salt is among the most harmful agents that negatively influences crop yield. Alfalfa is an important perennial forage crop that exhibits wide cultivar variations in salt tolerance. Developing salt-tolerant alfalfa plants is a promising way to utilize salinized land. A comprehensive method was developed to achieve reliable and effective evaluation of alfalfa salt resistance. This included principal components, membership functions and cluster and stepwise regression analyses. These were used to analyse the salt tolerance coefficients of 14 traits and to evaluate 20 diverse alfalfa cultivars at the seedling stage. The various morphological root parameters of six alfalfa cultivars with contrasting salt tolerance were also tested by a scanning apparatus. According to the comprehensive evaluation value (D value), one highly salt-tolerant, two salt-tolerant, four moderately salt-tolerant and 13 salt-sensitive alfalfa cultivars were screened. A mathematical equation for the evaluation of alfalfa salt tolerance was established: D' = -0.126 + 0.667SFW + 0.377SDW + 1.089K⁺ /Na⁺  + 0.172SFW/RFW (R²  = 0.988; average forecast accuracy of 96.95%), where four indices were closely related to the salt tolerance: shoot fresh weight, ratio of shoot fresh weight to root fresh weight, shoot dry weight and ratio of K⁺ to Na⁺ in the shoot. We also found that SSA correlated strongly with SFW, SDW, K⁺ /Na⁺ , D values, while SRV correlated obviously with SFW, SFW/RFW and D values after 150 mm NaCl treatment. In conclusion, the SFW, K⁺ /Na⁺ , SDW, SFW/RFW, SSA and SRV could be used as indicators of salt tolerance in alfalfa seedlings grown under 150 mm NaCl treatment.

Assessment of the vigor of rice seeds by near-infrared hyperspectral imaging combined with transfer learning

Rice seed vigor plays a significant role in determining the quality and quantity of rice production. Thus, the quick and non-destructive identification of seed vigor is not only beneficial to fully obtain the state of rice seeds but also the intelligent development of agriculture by instant monitoring. Thus, herein, near-infrared hyperspectral imaging technology, as an information acquisition tool, was introduced combined with a deep learning algorithm to identify the rice seed vigor. Both the spectral images and average spectra of the rice seeds were sent to discriminant models including deep learning models and traditional machine learning models, and the highest accuracy of vigor identification reached 99.5018% using the self-built model. The parameters of the established deep learning models were frozen to be feature extractor for transfer learning. The identification results whose highest number also reached almost 98% indicated the possibility of applying transfer learning to improve the universality of the models. Moreover, by visualizing the output of convolutional layers, the progress and mechanism of spectral image feature extraction in the established deep learning model was explored. Overall, the self-built deep learning models combined with near-infrared hyperspectral images in the determination of rice seed vigor have potential to efficiently perform this task.

Parallel reaction monitoring revealed tolerance to drought proteins in weedy rice (Oryza sativa f. spontanea)

Drought is a complicated abiotic stress factor with severe effects on rice growth and production. Weedy rice is a valuable genetic resource that possesses a strong capacity for drought tolerance, cold tolerance, and salt tolerance, and is an excellent material for studying rice tolerance. Here, according to comprehensive tolerance to drought index D, accession WR16 was selected based on strong drought tolerance among 133 studied weedy red rice germplasms. WR16 was compared with Oryza sativa ssp. Japonica. cv. IAPAR-9, a reference genotype originating from Brazil. In addition, accession WR24 was classified as moderately tolerant to drought accessions. Transcriptomic and proteomic analyses were combined to identify 38 co-upregulated proteins related to drought tolerance, and targeted parallel reaction monitoring (PRM) was used to precisely quantify and verify nine proteins in the complex backgrounds. Result showed that six proteins were significantly (Fisher's exact P value < 0.05) related to drought tolerance in accessions WR16 and WR24. Among them, OS09T0478300-01, OS09T0530300-01, and OS01T0800500-01 formed a combined defense system to respond to drought stress in weedy rice. Results of these studies provide comprehensive information for precisely identifying and verifying tolerance to drought proteins and lay a solid theoretical foundation for research on drought tolerance mechanisms.

Transcriptomic Profiling of Young Cotyledons Response to Chilling Stress in Two Contrasting Cotton (Gossypium hirsutum L.) Genotypes at the Seedling Stage

Young cotyledons of cotton seedlings are most susceptible to chilling stress. To gain insight into the potential mechanism of cold tolerance of young cotton cotyledons, we conducted physiological and comparative transcriptome analysis of two varieties with contrasting phenotypes. The evaluation of chilling injury of young cotyledons among 74 cotton varieties revealed that H559 was the most tolerant and YM21 was the most sensitive. The physiological analysis found that the ROS scavenging ability was lower, and cell membrane damage was more severe in the cotyledons of YM21 than that of H559 under chilling stress. RNA-seq analysis identified a total of 44,998 expressed genes and 19,982 differentially expressed genes (DEGs) in young cotyledons of the two varieties under chilling stress. Weighted gene coexpression network analysis (WGCNA) of all DEGs revealed four significant modules with close correlation with specific samples. The GO-term enrichment analysis found that lots of genes in H559-specific modules were involved in plant resistance to abiotic stress. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that pathways such as plant hormone signal transduction, MAPK signaling, and plant–pathogen interaction were related to chilling stress response. A total of 574 transcription factors and 936 hub genes in these modules were identified. Twenty hub genes were selected for qRT-PCR verification, revealing the reliability and accuracy of transcriptome data. These findings will lay a foundation for future research on the molecular mechanism of cold tolerance in cotyledons of cotton.

Integrated RNA-Seq Analysis and Meta-QTLs Mapping Provide Insights into Cold Stress Response in Rice Seedling Roots

Rice (Oryza sativa L.) is a widely cultivated food crop around the world, especially in Asia. However, rice seedlings often suffer from cold stress, which affects their growth and yield. Here, RNA-seq analysis and Meta-QTLs mapping were performed to understand the molecular mechanisms underlying cold tolerance in the roots of 14-day-old seedlings of rice (RPY geng, cold-tolerant genotype). A total of 4779 of the differentially expressed genes (DEGs) were identified, including 2457 up-regulated and 2322 down-regulated DEGs. The GO, COG, KEEG, and Mapman enrichment results of DEGs revealed that DEGs are mainly involved in carbohydrate transport and metabolism, signal transduction mechanisms (plant hormone signal transduction), biosynthesis, transport and catabolism of secondary metabolites (phenylpropanoid biosynthesis), defense mechanisms, and large enzyme families mechanisms. Notably, the AP2/ERF-ERF, NAC, WRKY, MYB, C2H2, and bHLH transcription factors participated in rice’s cold–stress response and tolerance. On the other hand, we mapped the identified DEGs to 44 published cold–stress-related genes and 41 cold-tolerant Meta-QTLs regions. Of them, 12 DEGs were the published cold–stress-related genes and 418 DEGs fell into the cold-tolerant Meta-QTLs regions. In this study, the identified DEGs and the putative molecular regulatory network can provide insights for understanding the mechanism of cold stress tolerance in rice. In addition, DEGs in KEGG term-enriched terms or cold-tolerant Meta-QTLs will help to secure key candidate genes for further functional studies on the molecular mechanism of cold stress response in rice.