GWAS reveals two novel loci for photosynthesis-related traits in soybean

Genome-wide association study and candidate gene identification for agronomic traits in 182 upward-growing fruits of C. frutescens and C. annuum

Pepper agronomic traits serve as pivotal indicators for characterizing germplasm attributes and correlations. It is important to study differential genotypic variation through phenotypic differences of target traits. Whole genome resequencing was used to sequence the whole genome among different individuals of species with known reference genomes and annotations, and based on this, differential analyses of individuals or populations were carried out to identify SNPs for agronomic traits related to pepper. This study conducted a genome-wide association study encompassing 26 key agronomic traits in 182 upward-growing fruits of C. frutescens and C. annuum. The population structure (phylogenetics, population structure, population principal component analysis, genetic relationship) and linkage disequilibrium analysis were realized to ensure the accuracy and reliability of GWAS results, and the optimal statistical model was determined. A total of 929 SNPs significantly associated with 26 agronomic traits, were identified, alongside the detection of 519 candidate genes within 100 kb region adjacent to these SNPs. Additionally, through gene annotation and expression pattern scrutiny, genes such as GAUT1, COP10, and DDB1 correlated with fruit traits in Capsicum frutescens and Capsicum annuum were validated via qRT-PCR. In the CH20 (Capsicum annuum) and YB-4 (Capsicum frutescens) cultivars, GAUT1 and COP10 were cloned with cDNA lengths of 1065 bp and 561 bp, respectively, exhibiting only a small number of single nucleotide variations and nucleotide deletions. This validation provides a robust reference for molecular marker-assisted breeding of pepper agronomic traits, offering both genetic resources and theoretical foundations for future endeavors in molecular marker-assisted breeding for pepper.

Genetic dissection of ten photosynthesis-related traits based on InDel- and SNP-GWAS in soybean

KEY MESSAGE

A total of 416 InDels and 112 SNPs were significantly associated with soybean photosynthesis-related traits. GmIWS1 and GmCDC48 might be related to chlorophyll fluorescence and gas-exchange parameters, respectively. Photosynthesis is one of the main factors determining crop yield. A better understanding of the genetic architecture for photosynthesis is of great significance for soybean yield improvement. Our previous studies identified 5,410,112 single nucleotide polymorphisms (SNPs) from the resequencing data of 219 natural soybean accessions. Here, we identified 634,106 insertions and deletions (InDels) from these 219 accessions and used these InDel variations to perform principal component and linkage disequilibrium analysis of this population. The genome-wide association study (GWAS) were conducted on six chlorophyll fluorescence parameters (chlorophyll content, light energy absorbed per reaction center, quantum yield for electron transport, probability that a trapped exciton moves an electron into the electron transport chain beyond primary quinone acceptor, maximum quantum yield of photosystem II primary photochemistry in the dark-adapted state, performance index on absorption basis) and four gas-exchange parameters (intercellular carbon dioxide concentration, stomatal conductance, net photosynthesis rate, transpiration rate) and revealed 416 significant InDels and 112 significant SNPs. Based on GWAS results, GmIWS1 (encoding a transcription elongation factor) and GmCDC48 (encoding a cell division cycle protein) with the highest expression in the mapping region were determined as the candidate genes responsible for chlorophyll fluorescence and gas-exchange parameters, respectively. Further identification of favorable haplotypes with higher photosynthesis, seed weight and seed yield were carried out for GmIWS1 and GmCDC48. Overall, this study revealed the natural variations and candidate genes underlying the photosynthesis-related traits based on abundant phenotypic and genetic data, providing valuable insights into the genetic mechanisms controlling photosynthesis and yield in soybean.

Genome-wide association and RNA-seq analyses reveal a potential gene related to linolenic acid in soybean seeds

Linolenic acid (LA) has poor oxidative stability since it is a polyunsaturated fatty acid. Soybean oil has a high LA content and thus has poor oxidative stability. To identify candidate genes that affect the linolenic acid (LA) content in soybean seeds, a genome-wide association study (GWAS) was performed with 1,060 soybean cultivars collected in China between 2019-2021 and which LA content was measured using matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF IMS). A candidate gene, GmWRI14, encoding an APETALA2 (AP2)-type transcription factor, was detected by GWAS in cultivars from all three study years. Multiple sequence alignments showed that GmWRI14 belongs to the plant WRI1 family. The fatty acid contents of different soybean lines were evaluated in transgenic lines with a copy of GmWRI14, control lines without GmWRI14, and the gmwri14 mutant. MALDI-TOF IMS revealed that GmWRI14 transgenic soybeans had a lower LA content with a significant effect on seed size and shape, whereas gmwri14 mutants had a higher LA content. compared to control. The RNA-seq results showed that GmWRI14 suppresses GmFAD3s (GmFAD3B and GmFAD3C) and GmbZIP54 expression in soybean seeds, leading to decreased LA content. Based on the RNA-seq data, yeast one-hybrid (Y1H) and qRT-PCR were performed to confirm the transcriptional regulation of FAD3s by GmWRI14. Our results suggest that FAD3 is indirectly regulated by GmWRI14, representing a new molecular mechanism of fatty acid biosynthesis, in which GmWRI14 regulates LA content in soybean seeds.

Exploration of chlorophyll fluorescence characteristics gene regulatory in rice (Oryza sativa L.): a genome-wide association study

Chlorophyll content and fluorescence parameters are crucial indicators to evaluate the light use efficiency in rice; however, the correlations among these parameters and the underlying genetic mechanisms remain poorly understood. Here, to clarify these issues, we conducted a genome-wide association study (GWAS) on 225 rice accessions. In the phenotypic and Mendelian randomization (MR) analysis, a weak negative correlation was observed between the chlorophyll content and actual quantum yield of photosystem II (Φ I I ). The phenotypic diversity observed in SPAD, N P Q t , Φ N P Q , and F v / F m among accessions was affected by genetic background. Furthermore, the GWAS identified 78 SNPs and 17 candidate genes significantly associated with SPAD, N P Q t , Φ I I , Φ N P Q , q L and q P . Combining GWAS on 225 rice accessions with transcriptome analysis of two varieties exhibiting distinct fluorescence characteristics revealed two potential candidate genes (Os03g0583000 from Φ I I & q P traits and Os06g0587200 from N P Q t trait), which are respectively associated with peroxisomes, and protein kinase catalytic domains might involve in regulating the chlorophyll content and chlorophyll fluorescence. This study provides novel insights into the correlation among chlorophyll content and fluorescence parameters and the genetic mechanisms in rice, and offers valuable information for the breeding of rice with enhanced photosynthetic efficiency.

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

GmFtsH25 overexpression increases soybean seed yield by enhancing photosynthesis and photosynthates

Increasing plant photosynthetic capacity is a promising approach to boost yields, but it is particularly challenging in C₃ crops, such as soybean (Glycine max (L.) Merr.). Here, we identified GmFtsH25, encoding a member of the filamentation temperature-sensitive protein H protease family, as a major gene involved in soybean photosynthesis, using linkage mapping and a genome-wide association study. Overexpressing GmFtsH25 resulted in more grana thylakoid stacks in chloroplasts and increased photosynthetic efficiency and starch content, while knocking out GmFtsH25 produced the opposite phenotypes. GmFtsH25 interacted with photosystem I light harvesting complex 2 (GmLHCa2), and this interaction may contribute to the observed enhanced photosynthesis. GmFtsH25 overexpression lines had superior yield traits, such as yield per plant, compared to the wild type and knockout lines. Additionally, we identified an elite haplotype of GmFtsH25, generated by natural mutations, which appears to have been selected during soybean domestication. Our study sheds light on the molecular mechanism by which GmFtsH25 modulates photosynthesis and provides a promising strategy for improving the yields of soybean and other crops.

Genetic control of tolerance to drought stress in soybean

BACKGROUND

Drought stress limits the production of soybean [Glycine max (L.) Merr.], which is the most grown high-value legume crop worldwide. Breeding for drought tolerance is a difficult endeavor and understanding the genetic basis of drought tolerance in soybean is therefore crucial for harnessing the genomic regions involved in the tolerance mechanisms. A genome-wide association study (GWAS) analysis was applied in a soybean germplasm collection (the EUCLEG collection) of 359 accessions relevant for breeding in Europe, to identify genomic regions and candidate genes involved in the response to short duration and long duration drought stress (SDS and LDS respectively) in soybean.

RESULTS

The phenotypic response to drought was stronger in the long duration drought (LDS) than in the short duration drought (SDS) experiment. Over the four traits considered (canopy wilting, leaf senescence, maximum absolute growth rate and maximum plant height) the variation was in the range of 8.4-25.2% in the SDS, and 14.7-29.7% in the LDS experiments. The GWAS analysis identified a total of 17 and 22 significant marker-trait associations for four traits in the SDS and LDS experiments, respectively. In the genomic regions delimited by these markers we identified a total of 12 and 16 genes with putative functions that are of particular relevance for drought stress responses including stomatal movement, root formation, photosynthesis, ABA signaling, cellular protection and cellular repair mechanisms. Some of these genomic regions co-localized with previously known QTLs for drought tolerance traits including water use efficiency, chlorophyll content and photosynthesis.

CONCLUSION

Our results indicate that the mechanism of slow wilting in the SDS might be associated with the characteristics of the root system, whereas in the LDS, slow wilting could be due to low stomatal conductance and transpiration rates enabling a high WUE. Drought-induced leaf senescence was found to be associated to ABA and ROS responses. The QTLs related to WUE contributed to growth rate and canopy height maintenance under drought stress. Co-localization of several previously known QTLs for multiple agronomic traits with the SNPs identified in this study, highlights the importance of the identified genomic regions for the improvement of agronomic performance in addition to drought tolerance in the EUCLEG collection.

A soybean sodium/hydrogen exchanger GmNHX6 confers plant alkaline salt tolerance by regulating Na+/K+ homeostasis

Alkaline soil has a high pH due to carbonate salts and usually causes more detrimental effects on crop growth than saline soil. Sodium hydrogen exchangers (NHXs) are pivotal regulators of cellular Na⁺/K⁺ and pH homeostasis, which is essential for salt tolerance; however, their role in alkaline salt tolerance is largely unknown. Therefore, in this study, we investigated the function of a soybean NHX gene, GmNHX6, in plant response to alkaline salt stress. GmNHX6 encodes a Golgi-localized sodium/hydrogen exchanger, and its transcript abundance is more upregulated in alkaline salt tolerant soybean variety in response to NaHCO₃ stress. Ectopic expression of GmNHX6 in Arabidopsis enhanced alkaline salt tolerance by maintaining high K⁺ content and low Na⁺/K⁺ ratio. Overexpression of GmNHX6 also improved soybean tolerance to alkaline salt stress. A single nucleotide polymorphism in the promoter region of NHX6 is associated with the alkaline salt tolerance in soybean germplasm. A superior promoter of GmNHX6 was isolated from an alkaline salt tolerant soybean variety, which showed stronger activity than the promoter from an alkaline salt sensitive soybean variety in response to alkali stress, by luciferase transient expression assays. Our results suggested soybean NHX6 gene plays an important role in plant tolerance to alkaline salt stress.

Analysis of Physiological Variations and Genetic Architecture for Photosynthetic Capacity of Japanese Soybean Germplasm

The culmination of conventional yield improving parameters has widened the margin between food demand and crop yield, leaving the potential yield productivity to be bridged by the manipulation of photosynthetic processes in plants. Efficient strategies to assess photosynthetic capacity in crops need to be developed to identify suitable targets that have the potential to improve photosynthetic efficiencies. Here, we assessed the photosynthetic capacity of the Japanese soybean mini core collection (GmJMC) using a newly developed high-throughput photosynthesis measurement system "MIC-100" to analyze physiological mechanisms and genetic architecture underpinning photosynthesis. K-means clustering of light-saturated photosynthesis (A_sat ) classified GmJMC accessions into four distinct clusters with Cluster2 comprised of highly photosynthesizing accessions. Genome-wide association analysis based on the variation of A_sat revealed a significant association with a single nucleotide polymorphism (SNP) on chromosome 17. Among the candidate genes related to photosynthesis in the genomic region, variation in expression of a gene encoding G protein alpha subunit 1 (GPA1) showed a strong correlation (r = 0.72, p < 0.01) with that of A_sat . Among GmJMC accessions, GmJMC47 was characterized by the highest A_sat , stomatal conductance (g_s ), stomatal density (S_Density ), electron transfer rate (ETR), and light use efficiency of photosystem II (Fv'/Fm') and the lowest non-photochemical quenching [NPQ(t)], indicating that GmJMC47 has greater CO₂ supply and efficient light-harvesting systems. These results provide strong evidence that exploration of plant germplasm is a useful strategy to unlock the potential of resource use efficiencies for photosynthesis.

High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean (Glycine max) nested association mapping population

Photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500-2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R2 from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.

Novel target sites for soybean yield enhancement by photosynthesis

Photosynthesis plays an important role in plant growth and development. Increasing photosynthetic rate is a main objective of improving crop productivity. Chlorophyll fluorescence is an effective method for quickly evaluating photosynthesis. In this study, four representative chlorophyll fluorescence parameters, that is, maximum quantum efficiency of photosystem II, quantum efficiency of PSII, photochemical quenching, and non-photochemical quenching, of 219 diverse soybean accessions were measured across three environments. The underlying genetic architecture was analyzed by genome-wide association study. Forty-eight SNPs were detected to associate with the four traits and explained 10.43-20.41% of the phenotypic variation. Nine candidate genes in the stable QTLs were predicted. Great differences in the expression levels of the candidate genes existed between the high photosynthetic efficiency accessions and low photosynthetic efficiency accessions. In all, we uncover 17 QTLs associated with photosynthesis-related traits and nine genes that may participate in the regulation of photosynthesis, which can provide references for revealing the genetic mechanism of photosynthesis. These QTLs and candidate genes will provide new targets for crop yield improvement through increasing photosynthesis.

Genome-Wide Association Study Identifies Candidate Genes Related to the Linoleic Acid Content in Soybean Seeds

Soybean (Glycine max (L.) Merrill) oil is a complex mixture of five fatty acids (palmitic, stearic, oleic, linoleic, and linolenic). The high content of linoleic acid (LA) contributes to the oil having poor oxidative stability. Therefore, soybean seed with a lower LA content is desirable. To investigate the genetic architecture of LA, we performed a genome-wide association study (GWAS) using 510 soybean cultivars collected from China. The phenotypic identification results showed that the content of LA varied from 36.22% to 72.18%. The GWAS analysis showed that there were 37 genes related to oleic acid content, with a contribution rate of 7%. The candidate gene Glyma.04G116500.1 (GmWRI14) on chromosome 4 was detected in three consecutive years. The GmWRI14 showed a negative correlation with the LA content and the correlation coefficient was -0.912. To test whether GmWRI14 can lead to a lower LA content in soybean, we introduced GmWRI14 into the soybean genome. Matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF IMS) showed that the overexpression of GmWRI14 leads to a lower LA content in soybean seeds. Meanwhile, RNA-seq verified that GmWRI14-overexpressed soybean lines showed a lower accumulation of GmFAD2-1A and GmFAD2-1B than control lines. Our results indicate that the down-regulation of the FAD2 gene triggered by the transcription factor GmWRI14 is the underlying mechanism reducing the LA level of seed. Our results provide novel insights into the genetic architecture of LA and pinpoint potential candidate genes for further in-depth studies.

Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods

In conjunction with big data analysis methods, plant omics technologies have provided scientists with cost-effective and promising tools for discovering genetic architectures of complex agronomic traits using large breeding populations. In recent years, there has been significant progress in plant phenomics and genomics approaches for generating reliable large datasets. However, selecting an appropriate data integration and analysis method to improve the efficiency of phenome-phenome and phenome-genome association studies is still a bottleneck. This study proposes a hyperspectral wide association study (HypWAS) approach as a phenome-phenome association analysis through a hierarchical data integration strategy to estimate the prediction power of hyperspectral reflectance bands in predicting soybean seed yield. Using HypWAS, five important hyperspectral reflectance bands in visible, red-edge, and near-infrared regions were identified significantly associated with seed yield. The phenome-genome association analysis of each tested hyperspectral reflectance band was performed using two conventional genome-wide association studies (GWAS) methods and a machine learning mediated GWAS based on the support vector regression (SVR) method. Using SVR-mediated GWAS, more relevant QTL with the physiological background of the tested hyperspectral reflectance bands were detected, supported by the functional annotation of candidate gene analyses. The results of this study have indicated the advantages of using hierarchical data integration strategy and advanced mathematical methods coupled with phenome-phenome and phenome-genome association analyses for a better understanding of the biology and genetic backgrounds of hyperspectral reflectance bands affecting soybean yield formation. The identified yield-related hyperspectral reflectance bands using HypWAS can be used as indirect selection criteria for selecting superior genotypes with improved yield genetic gains in large breeding populations.

Genome-Wide Association Study for Ultraviolet-B Resistance in Soybean (Glycine max L.)

The depletion of the stratospheric ozone layer is a major environmental issue and has increased the dosage of ultraviolet-B (UV-B) radiation reaching the Earth’s surface. Organisms are negatively affected by enhanced UV-B radiation, and especially in crop plants this may lead to severe yield losses. Soybean (Glycine max L.), a major legume crop, is sensitive to UV-B radiation, and therefore, it is required to breed the UV-B-resistant soybean cultivar. In this study, 688 soybean germplasms were phenotyped for two categories, Damage of Leaf Chlorosis (DLC) and Damage of Leaf Shape (DLS), after supplementary UV-B irradiation for 14 days. About 5% of the germplasms showed strong UV-B resistance, and GCS731 was the most resistant genotype. Their phenotypic distributions showed similar patterns to the normal, suggesting UV-B resistance as a quantitative trait governed by polygenes. A total of 688 soybean germplasms were genotyped using the Axiom^® Soya 180K SNP array, and a genome-wide association study (GWAS) was conducted to identify SNPs significantly associated with the two traits, DLC and DLS. Five peaks on chromosomes 2, 6, 10, and 11 were significantly associated with either DLC or DLS, and the five adjacent genes were selected as candidate genes responsible for UV-B resistance. Among those candidate genes, Glyma.02g017500 and Glyma.06g103200 encode cryptochrome (CRY) and cryptochrome 1 (CRY1), respectively, and are known to play a role in DNA repair during photoreactivation. Real-time quantitative RT-PCR (qRT-PCR) results revealed that CRY1 was expressed significantly higher in the UV-B-resistant soybean compared to the susceptible soybean after 6 h of UV-B irradiation. This study is the first GWAS report on UV-B resistance in soybean, and the results will provide valuable information for breeding UV-B-resistant soybeans in preparation for climate change.

Genome-wide association mapping for protein, oil and water-soluble protein contents in soybean

As a globally important legume crop, soybean provides excellent sources of protein and oil for human and livestock nutrition. Improving seed protein and oil contents has always been an important objective in soybean breeding. Water-soluble protein plays a significant role in the processing and efficacy of soybean protein. Here, a genome-wide association study (GWAS) of seed compositions (protein, oil, and water-soluble protein contents) was conducted using 211 diverse soybean accessions genotyped with a 355 K SoySNP array. Three, four, and five QTLs were identified related to the protein, oil, and water-soluble protein contents, respectively. Furthermore, five QTLs (qPC-15-1, qOC-8-1, qOC-12-1, qOC-20-1 and qWSPC-8-1) were detected in multiple environments. Analysis of the favorable alleles for oil and water-soluble protein contents showed that qOC-8-1 (qWSPC-8-1) exerted inverse effects on oil and water-soluble protein synthesis. Relative expression analysis suggested that Glyma.15G049200 in qPC-15-1 affects protein synthesis and Glyma.08G107800 in qOC-8-1 and qWSPC-8-1 might be involved in oil and water-soluble protein synthesis, producing opposite effects. The candidate genes and significant SNPs detected in the present study will allow a deeper understanding of the genetic basis for the regulation of protein, oil and water-soluble protein contents and provide important information that could be utilized in marker-assisted selection for soybean quality improvement.

Alterations in stomatal response to fluctuating light increase biomass and yield of rice under drought conditions

The acceleration of stomatal closure upon high to low light transition could improve plant water use efficiency and drought tolerance. Herein, using genome-wide association study, we showed that the genetic variation in OsNHX1 was strongly associated with the changes in τ_cl , the time constant of stomatal closure, in 206 rice accessions. OsNHX1 overexpression in rice resulted in a decrease in τ_cl , and an increase in biomass, grain yield under drought. Conversely, OsNHX1 knockout by CRISPR/CAS9 shows opposite trends for these traits. We further found three haplotypes spanning the OsNHX1 promoter and CDS regions. Two among them, HapII and HapIII, were found to be associated with a high and low τ_cl , respectively. A near-isogenic line (NIL, S464) was developed through replacing the genomic region harboring HapII (~10 kb) from MH63 (recipient) rice cultivar by the same sized genomic region containing Hap III from 02428 (donor). Compared with MH63, S464 shows a reduction by 35% in τ_cl and an increase by 40% in the grain yield under drought. However, under normal conditions, S464 maintains closely similar grain yield as MH63. The global distribution of the two OsNHX1 haplotypes is associated with the local precipitation. Taken together, the natural variation in OsNHX1 could be utilized to manipulate the stomatal dynamics for an improved rice drought tolerance.

Rice Cultivar Takanari Has Higher Photosynthetic Performance Under Fluctuating Light Than Koshihikari, Especially Under Limited Nitrogen Supply and Elevated CO2

Plants in the field experience dynamic changes of sunlight rather than steady-state irradiation. Therefore, increasing the photosynthetic rate of an individual leaf under fluctuating light is essential for improving crop productivity. The high-yielding indica rice (Oryza sativa L.) cultivar Takanari is considered a potential donor of photosynthesis genes because of its higher steady-state photosynthesis at both atmospheric and elevated CO₂ concentrations than those of several Japanese commercial cultivars, including Koshihikari. Photosynthetic induction after a sudden increase in light intensity is faster in Takanari than in Koshihikari, but whether the daily carbon gain of Takanari outperforms that of Koshihikari under fluctuating light in the field is unclear. Here we report that Takanari has higher non-steady-state photosynthesis, especially under low nitrogen (N) supply, than Koshihikari. In a pot experiment, Takanari had greater leaf carbon gain during the initial 10 min after a sudden increase in irradiation and higher daily CO₂ assimilation under simulated natural fluctuating light, at both atmospheric (400 ppm) and elevated (800 ppm) CO₂ concentrations. The electron transport rate during a day under field conditions with low N supply was also higher in Takanari than in Koshihikari. Although the advantages of Takanari were diminished under high N supply, photosynthetic N use efficiency was consistently higher in Takanari than in Koshihikari, under both low and high N supply. This study demonstrates that Takanari is a promising donor parent to use in breeding programs aimed at increasing CO₂ assimilation in a wide range of environments, including future higher CO₂ concentrations.