New Insights into the Transcriptional Regulation of Genes Involved in the Nitrogen Use Efficiency under Potassium Chlorate in Rice (Oryza sativa L.).

Potassium chlorate (KClO3) has been widely used to evaluate the divergence in nitrogen use efficiency (NUE) between indica and japonica rice subspecies. This study investigated the transcriptional regulation of major genes involved in the NUE in rice treated with KClO3, which acts as an inhibitor of the reducing activity of nitrate reductase (NR) in higher plants. A set of two KClO3 sensitive nitrate reductase (NR) and two nitrate transporter (NRT) introgression rice lines (BC2F7), carrying the indica alleles of NR or NRT, derived from a cross between Saeilmi (japonica, P1) and Milyang23 (indica, P2), were exposed to KClO3 at the seedling stage. The phenotypic responses were recorded 7 days after treatment, and samples for gene expression, physiological, and biochemical analyses were collected at 0 h (control) and 3 h after KClO3 application. The results revealed that Saeilmi (P1, japonica) and Milyang23 (P2, indica) showed distinctive phenotypic responses. In addition, the expression of OsNR2 was differentially regulated between the roots, stem, and leaf tissues, and between introgression lines. When expressed in the roots, OsNR2 was downregulated in all introgression lines. However, in the stem and leaves, OsNR2 was upregulated in the NR introgression lines, but downregulation in the NRT introgression lines. In the same way, the expression patterns of OsNIA1 and OsNIA2 in the roots, stem, and leaves indicated a differential transcriptional regulation by KClO3, with OsNIA2 prevailing over OsNIA1 in the roots. Under the same conditions, the activity of NR was inhibited in the roots and differentially regulated in the stem and leaf tissues. Furthermore, the transcriptional divergence of OsAMT1.3 and OsAMT2.3, OsGLU1 and OsGLU2, between NR and NRT, coupled with the NR activity pattern in the roots, would indicate the prevalence of nitrate (NO3¯) transport over ammonium (NH4+) transport. Moreover, the induction of catalase (CAT) and polyphenol oxidase (PPO) enzyme activities in Saeilmi (P1, KClO3 resistant), and the decrease in Milyang23 (P2, KClO3 sensitive), coupled with the malondialdehyde (MDA) content, indicated the extent of the oxidative stress, and the induction of the adaptive response mechanism, tending to maintain a balanced reduction-oxidation state in response to KClO3. The changes in the chloroplast pigments and proline content propose these compounds as emerging biomarkers for assessing the overall plant health status. These results suggest that the inhibitory potential of KClO3 on the reduction activity of the nitrate reductase (NR), as well as that of the genes encoding the nitrate and ammonium transporters, and glutamate synthase are tissue-specific, which may differentially affect the transport and assimilation of nitrate or ammonium in rice.

RNA-Seq and Electrical Penetration Graph Revealed the Role of Grh1-Mediated Activation of Defense Mechanisms towards Green Rice Leafhopper (Nephotettix cincticeps Uhler) Resistance in Rice (Oryza sativa L.).

The green rice leafhopper (GRH, Nephotettix cincticeps Uhler) is one of the most important insect pests causing serious damage to rice production and yield loss in East Asia. Prior to performing RNA-Seq analysis, we conducted an electrical penetration graph (EPG) test to investigate the feeding behavior of GRH on Ilpum (recurrent parent, GRH-susceptible cultivar), a near-isogenic line (NIL carrying Grh1) compared to the Grh1 donor parent (Shingwang). Then, we conducted a transcriptome-wide analysis of GRH-responsive genes in Ilpum and NIL, which was followed by the validation of RNA-Seq data by qPCR. On the one hand, EPG results showed differential feeding behaviors of GRH between Ilpum and NIL. The phloem-like feeding pattern was detected in Ilpum, whereas the EPG test indicated a xylem-like feeding habit of GRH on NIL. In addition, we observed a high death rate of GRH on NIL (92%) compared to Ilpum (28%) 72 h post infestation, attributed to GRH failure to suck the phloem sap of NIL. On the other hand, RNA-Seq data revealed that Ilpum and NIL GRH-treated plants generated 1,766,347 and 3,676,765 counts per million mapped (CPM) reads, respectively. The alignment of reads indicated that more than 75% of reads were mapped to the reference genome, and 8859 genes and 15,815,400 transcripts were obtained. Of this number, 3424 differentially expressed genes (DEGs, 1605 upregulated in Ilpum and downregulated in NIL; 1819 genes upregulated in NIL and downregulated in Ilpum) were identified. According to the quantile normalization of the fragments per kilobase of transcript per million mapped reads (FPKM) values, followed by the Student's t-test (p < 0.05), we identified 3283 DEGs in Ilpum (1935 upregulated and 1348 downregulated) and 2599 DEGs in NIL (1621 upregulated and 978 downregulated) with at least a log2 (logarithm base 2) twofold change (Log2FC ≥2) in the expression level upon GRH infestation. Upregulated genes in NIL exceeded by 13.3% those recorded in Ilpum. The majority of genes associated with the metabolism of carbohydrates, amino acids, lipids, nucleotides, the activity of coenzymes, the action of phytohormones, protein modification, homeostasis, the transport of solutes, and the uptake of nutrients, among others, were abundantly upregulated in NIL (carrying Grh1). However, a high number of upregulated genes involved in photosynthesis, cellular respiration, secondary metabolism, redox homeostasis, protein biosynthesis, protein translocation, and external stimuli response related genes were found in Ilpum. Therefore, all data suggest that Grh1-mediated resistance against GRH in rice would involve a transcriptome-wide reprogramming, resulting in the activation of bZIP, MYB, NAC, bHLH, WRKY, and GRAS transcription factors, coupled with the induction of the pathogen-pattern triggered immunity (PTI), systemic acquired resistance (SAR), symbiotic signaling pathway, and the activation of genes associated with the response mechanisms against viruses. This comprehensive transcriptome profile of GRH-responsive genes gives new insights into the molecular response mechanisms underlying GRH (insect pest)-rice (plant) interaction.

Genome-wide association study (GWAS) with high-throughput SNP chip DNA markers identified novel genetic factors for mesocotyl elongation and seedling emergence in rice (Oryza sativa L.) using multiple GAPIT models.

This study employed a joint strategy high-density SNP Chip DNA markers and multiple Genome Association and Prediction Integrated Tool (GAPIT) models [(Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), Fixed and random model Circulating Probability Uniform (FarmCPU), General Linear Model (GLM), and Settlement of Mixed Linear Model (MLM) Under Progressively Exclusive Relationship (SUPER)], to investigate novel genetic factors controlling mesocotyl elongation and seedling emergence for direct-seeded rice. Genotype data (230,526 SNP Chip DNA makers) of 117 doubled haploid lines (derived from a cross between 93-11 (Oryza sativa L. ssp. indica) and Milyang352 (O. sativa L. ssp. japonica) were used to perform a Genome-Wide Association Study (GWAS). Results revealed the association between five (5) topmost significant SNP markers, of which number two [AX-155741269, Chr2: 15422406 bp, and AX-155200917, Chr7: 23814085 bp, explaining 37.5% and 13.8% of the phenotypic variance explained (PVE)] are linked to the mesocotyl elongation loci, while three (AX-282097034 and AX-283652873, Chr9: 9882817 bp and 1023383 bp, PVE 64.5%, and 20.2%, respectively, and AX-154356231, Chr1: 17413989 bp, PVE 21.1%) are tightly linked to the loci controlling seedling emergence. The qMEL2-1 and qSEM9-1 are identified as major QTLs explaining 37.5% and 64.5% of the PVE for mesocotyl elongation and seedling emergence, respectively. The AX-282097034 (Chr9: 9882817 bp) was co-detected by four GAPIT models (BLINK, FarmCPU, SUPER, and GLM), while AX-155741269 was co-detected by BLINK and SUPER. Furthermore, a high estimated heritability (Mesocotyl elongation: h2 = 0.955; seedling emergence: h2 = 0.863; shoot length: h2 = 0.707) was observed. Genes harbored by qMEL2-1 and qSEM9-1 have interesting annotated molecular functions that could be investigated through functional studies to uncover their roles during mesocotyl elongation and seedling emergence events in rice. Furthermore, the presence of genes encoding transcription factors, growth- and stress response, or signaling-related genes would suggest that mesocotyl elongation and seedling emergence from deep direct-seeded rice might involve an active signaling cascade and transport of molecules, which could be elucidated through functional analysis. Likewise, genomic selection analysis suggested markers useful for downstream marker-assisted selection (MAS).

Rice (Oryza sativa L.) Grain Size, Shape, and Weight-Related QTLs Identified Using GWAS with Multiple GAPIT Models and High-Density SNP Chip DNA Markers.

This study investigated novel quantitative traits loci (QTLs) associated with the control of grain shape and size as well as grain weight in rice. We employed a joint-strategy multiple GAPIT (Genome Association and Prediction Integrated Tool) models [(Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK)), Fixed and random model Circulating Probability Uniform (FarmCPU), Settlement of MLM Under Progressive Exclusive Relationship (SUPER), and General Linear Model (GLM)]-High-Density SNP Chip DNA Markers (60,461) to conduct a Genome-Wide Association Study (GWAS). GWAS was performed using genotype and grain-related phenotypes of 143 recombinant inbred lines (RILs). Data show that parental lines (Ilpum and Tung Tin Wan Hein 1, TTWH1, Oryza sativa L., ssp. japonica and indica, respectively) exhibited divergent phenotypes for all analyzed grain traits), which was reflected in their derived population. GWAS results revealed the association between seven SNP Chip makers and QTLs for grain length, co-detected by all GAPIT models on chromosomes (Chr) 1-3, 5, 7, and 11, were qGL1-1BFSG (AX-95918134, Chr1: 3,820,526 bp) explains 65.2-72.5% of the phenotypic variance explained (PVE). In addition, qGW1-1BFSG (AX-273945773, Chr1: 5,623,288 bp) for grain width explains 15.5-18.9% of PVE. Furthermore, BLINK or FarmCPU identified three QTLs for grain thickness independently, and explain 74.9% (qGT1Blink, AX-279261704, Chr1: 18,023,142 bp) and 54.9% (qGT2-1Farm, AX-154787777, Chr2: 2,118,477 bp) of the observed PVE. For the grain length-to-width ratio (LWR), the qLWR2BFSG (AX-274833045, Chr2: 10,000,097 bp) explains nearly 15.2-32% of the observed PVE. Likewise, the major QTL for thousand-grain weight (TGW) was detected on Chr6 (qTGW6BFSG, AX-115737727, 28,484,619 bp) and explains 32.8-54% of PVE. The qTGW6BFSG QTL coincides with qGW6-1Blink for grain width and explained 32.8-54% of PVE. Putative candidate genes pooled from major QTLs for each grain trait have interesting annotated functions that require functional studies to elucidate their function in the control of grain size, shape, or weight in rice. Genome selection analysis proposed makers useful for downstream marker-assisted selection based on genetic merit of RILs.

Quality Characteristics of Rice-Based Ice Creams with Different Amylose Contents.

Ice cream consumption has increased over the years. In this study, we investigated the potential of using rice varieties with varying amylose contents for ice cream production. We analyzed the physical and chemical properties and sensory quality characteristics (appearance, taste, texture, chewiness, aroma, and rice flavor) of rice-based ice cream made from five varieties with low and high amylose levels. To make the ice cream, we ground rice into a fine powder and combined it with skim milk powder, butter, sugar, glycerin esters of fatty acids, locust bean gum, and water to form a gelatinized mixture. This mixture was then aged, frozen, and hardened. The ice cream's key quality characteristics, such as viscosity (2170-25,030 cP), hardness (4.27-49.55 N cm-2), and overrun (17.95-46.99%), showed a wide range. Ice cream made from Saemimyeon (high amylose content rice variety) exhibited the highest hardness value (49.55 N cm-2) among the varieties tested, but had relatively low viscosity (4030 cP), overrun (17.95%), and drip-through (0.75 g/min) values. These findings suggest that rice varieties with different amylose contents are suitable for making ice cream and have the potential to expand the rice processing market and increase its value.

Nitric oxide: A core signaling molecule under elevated GHGs (CO2, CH4, N2O, O3)-mediated abiotic stress in plants.

Nitric oxide (NO), an ancient molecule with multiple roles in plants, has gained momentum and continues to govern plant biosciences-related research. NO, known to be involved in diverse physiological and biological processes, is a central molecule mediating cellular redox homeostasis under abiotic and biotic stresses. NO signaling interacts with various signaling networks to govern the adaptive response mechanism towards stress tolerance. Although diverging views question the role of plants in the current greenhouse gases (GHGs) budget, it is widely accepted that plants contribute, in one way or another, to the release of GHGs (carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) and ozone (O3)) to the atmosphere, with CH4 and N2O being the most abundant, and occur simultaneously. Studies support that elevated concentrations of GHGs trigger similar signaling pathways to that observed in commonly studied abiotic stresses. In the process, NO plays a forefront role, in which the nitrogen metabolism is tightly related. Regardless of their beneficial roles in plants at a certain level of accumulation, high concentrations of CO2, CH4, and N2O-mediating stress in plants exacerbate the production of reactive oxygen (ROS) and nitrogen (RNS) species. This review assesses and discusses the current knowledge of NO signaling and its interaction with other signaling pathways, here focusing on the reported calcium (Ca2+) and hormonal signaling, under elevated GHGs along with the associated mechanisms underlying GHGs-induced stress in plants.

Multiple Facets of Nitrogen: From Atmospheric Gas to Indispensable Agricultural Input.

Nitrogen (N) is a gas and the fifth most abundant element naturally found in the atmosphere. N's role in agriculture and plant metabolism has been widely investigated for decades, and extensive information regarding this subject is available. However, the advent of sequencing technology and the advances in plant biotechnology, coupled with the growing interest in functional genomics-related studies and the various environmental challenges, have paved novel paths to rediscovering the fundamentals of N and its dynamics in physiological and biological processes, as well as biochemical reactions under both normal and stress conditions. This work provides a comprehensive review on multiple facets of N and N-containing compounds in plants disseminated in the literature to better appreciate N in its multiple dimensions. Here, some of the ancient but fundamental aspects of N are revived and the advances in our understanding of N in the metabolism of plants is portrayed. It is established that N is indispensable for achieving high plant productivity and fitness. However, the use of N-rich fertilizers in relatively higher amounts negatively affects the environment. Therefore, a paradigm shift is important to shape to the future use of N-rich fertilizers in crop production and their contribution to the current global greenhouse gases (GHGs) budget would help tackle current global environmental challenges toward a sustainable agriculture.

Novel QTL Associated with Aerenchyma-Mediated Radial Oxygen Loss (ROL) in Rice (Oryza sativa L.) under Iron (II) Sulfide.

In rice, high radial oxygen loss (ROL) has been associated with the reduction in the activity of methanogens, therefore reducing the formation of methane (CH4) due to the abundance in application of nitrogen (N)-rich fertilizers. In this study, we evaluated the root growth behavior and ROL rate of a doubled haploid (DH) population (n = 117) and parental lines 93-11 (P1, indica) and Milyang352 (P2, japonica) in response to iron (II) sulfide (FeS). In addition, we performed a linkage mapping and quantitative trait locus (QTL) analysis on the same population for the target traits. The results of the phenotypic evaluation revealed that parental lines had distinctive root growth and ROL patterns, with 93-11 (indica) and Milyang352 (japonica) showing low and high ROL rates, respectively. This was also reflected in their derived population, indicating that 93.2% of the DH lines exhibited a high ROL rate and about 6.8% had a low ROL pattern. Furthermore, the QTL and linkage map analysis detected two QTLs associated with the control of ROL and root area on chromosomes 2 (qROL-2-1, 127 cM, logarithm of the odds (LOD) 3.04, phenotypic variation explained (PVE) 11.61%) and 8 (qRA-8-1, 97 cM, LOD 4.394, PVE 15.95%), respectively. The positive additive effect (2.532) of qROL-2-1 indicates that the allele from 93-11 contributed to the observed phenotypic variation for ROL. The breakthrough is that the qROL-2-1 harbors genes proposed to be involved in stress signaling, defense response mechanisms, and transcriptional regulation, among others. The qPCR results revealed that the majority of genes harbored by the qROL-2-1 recorded a higher transcript accumulation level in Milyang352 over time compared to 93-11. Another set of genes exhibited a high transcript abundance in P1 compared to P2, while a few were differentially regulated between both parents. Therefore, OsTCP7 and OsMYB21, OsARF8 genes encoding transcription factors (TFs), coupled with OsTRX, OsWBC8, and OsLRR2 are suggested to play important roles in the positive regulation of ROL in rice. However, the recorded differential expression of OsDEF7 and OsEXPA, and the decrease in OsNIP2, Oscb5, and OsPLIM2a TF expression between parental lines proposes them as being involved in the control of oxygen flux level in rice roots.

Novel QTL Associated with Shoot Branching Identified in Doubled Haploid Rice (Oryza sativa L.) under Low Nitrogen Cultivation.

Shoot branching is considered as an important trait for the architecture of plants and contributes to their growth and productivity. In cereal crops, such as rice, shoot branching is controlled by many factors, including phytohormones signaling networks, operating either in synergy or antagonizing each other. In rice, shoot branching indicates the ability to produce more tillers that are essential for achieving high productivity and yield potential. In the present study, we evaluated the growth and development, and yield components of a doubled haploid population derived from a cross between 93-11 (P1, indica) and Milyang352 (P2, japonica), grown under normal nitrogen and low nitrogen cultivation open field conditions. The results of the phenotypic evaluation indicated that parental lines 93-11 (P1, a high tillering indica cultivar) and Milyang352 (P2, a low tillering japonica cultivar) showed distinctive phenotypic responses, also reflected in their derived population. In addition, the linkage mapping and quantitative trait locus (QTL) analysis detected three QTLs associated with tiller number on chromosome 2 (qTNN2-1, 130 cM, logarithm of the odds (LOD) 4.14, PVE 14.5%; and qTNL2-1, 134 cM, LOD: 6.05, PVE: 20.5%) and chromosome 4 (qTN4-1, 134 cM, LOD 3.92, PVE 14.5%), with qTNL2-1 having the highest phenotypic variation explained, and the only QTL associated with tiller number under low nitrogen cultivation conditions, using Kompetitive Allele-Specific PCR (KASP) and Fluidigm markers. The additive effect (1.81) of qTNL2-1 indicates that the allele from 93-11 (P1) contributed to the observed phenotypic variation for tiller number under low nitrogen cultivation. The breakthrough is that the majority of the candidate genes harbored by the QTLs qTNL2-1 and qTNN4-1 (here associated with the control of shoot branching under low and normal nitrogen cultivation, respectively), were also proposed to be involved in plant stress signaling or response mechanisms, with regard to their annotations and previous reports. Therefore, put together, these results would suggest that a possible crosstalk exists between the control of plant growth and development and the stress response in rice.

Rapid and Easy High-Molecular-Weight Glutenin Subunit Identification System by Lab-on-a-Chip in Wheat (Triticum aestivum L.).

Lab-on-a-chip technology is an emerging and convenient system to easily and quickly separate proteins of high molecular weight. The current study established a high-molecular-weight glutenin subunit (HMW-GS) identification system using Lab-on-a-chip for three, six, and three of the allelic variations at the Glu-A1, Glu-B1, and Glu-D1 loci, respectively, which are commonly used in wheat breeding programs. The molecular weight of 1Ax1 and 1Ax2* encoded by Glu-A1 locus were of 200 kDa and 192 kDa and positioned below 1Dx subunits. The HMW-GS encoded by Glu-B1 locus were electrophoresed in the following order below 1Ax1 and 1Ax2*: 1Bx13 ≥ 1Bx7 = 1Bx7OE > 1Bx17 > 1By16 > 1By8 = 1By18 > 1By9. 1Dx2 and Dx5 showed around 4-kDa difference in their molecular weights, with 1Dy10 and 1Dy12 having 11-kDa difference, and were clearly differentiated on Lab-on-a-chip. Additionally, some of the HMW-GS, including 1By8, 1By18, and 1Dy10, having different theoretical molecular weights showed similar electrophoretic mobility patterns on Lab-on-a-chip. The relative protein amount of 1Bx7OE was two-fold higher than that of 1Bx7 or 1Dx5 and, therefore, translated a significant increase in the protein amount in 1Bx7OE. Similarly, the relative protein amounts of 8 & 10 and 10 & 18 were higher than each subunit taken alone. Therefore, this study suggests the established HMW-GS identification system using Lab-on-a-chip as a reliable approach for evaluating HMW-GS for wheat breeding programs.