QTL and QTL x environment effects on agronomic and nitrogen acquisition traits in rice

Empowering rice breeding with NextGen genomics tools for rapid enhancement nitrogen use efficiency

As rice has no physiological capacity of fixing nitrogen in the soil, its production had always been reliant on the external application of nitrogen (N) to ensure enhanced productivity. In the light of improving nitrogen use efficiency (NUE) in rice, several advanced agronomic strategies have been proposed. However, the soared increase of the prices of N fertilizers and subsequent environmental downfalls caused by the excessive use of N fertilizers, reinforces the prerequisite adaptation of other sustainable, affordable, and globally acceptable strategies. An appropriate alternative approach would be to develop rice cultivars with better NUE. Conventional breeding techniques, however, have had only sporadic success in improving NUE, and hence, this paper proposes a new schema that employs the wholesome benefits of the recent advancements in omics technologies. The suggested approach promotes multidisciplinary research, since such cooperation enables the synthesis of many viewpoints, approaches, and data that result in a comprehensive understanding of NUE in rice. Such collaboration also encourages innovation that leads to developing rice varieties that use nitrogen more effectively, facilitate smart technology transfer, and promotes the adoption of NUE practices by farmers and stakeholders to minimize ecological impact and contribute to a sustainable agricultural future.

QTL Mapping of Agronomic and Physiological Traits at the Seedling and Maturity Stages under Different Nitrogen Treatments in Barley

Nitrogen (N) stress seriously constrains barley (Hordeum vulgare L.) production globally by influencing its growth and development. In this study, we used a recombinant inbred line (RIL) population of 121 crosses between the variety Baudin and the wild barley accession CN4027 to detect QTL for 27 traits at the seedling stage in hydroponic culture trials and 12 traits at the maturity stage in field trials both under two N treatments, aiming to uncover favorable alleles for N tolerance in wild barley. In total, eight stable QTL and seven QTL clusters were detected. Among them, the stable QTL Qtgw.sau-2H located in a 0.46 cM interval on the chromosome arm 2HL was a novel QTL specific for low N. Notably, Clusters C4 and C7 contained QTL for traits at both the seedling and maturity stages. In addition, four stable QTLs in Cluster C4 were identified. Furthermore, a gene (HORVU2Hr1G080990.1) related to grain protein in the interval of Qtgw.sau-2H was predicted. Correlation analysis and QTL mapping showed that different N treatments significantly affected agronomic and physiological traits at the seedling and maturity stages. These results provide valuable information for understanding N tolerance as well as breeding and utilizing the loci of interest in barley.

Comprehensive QTL analyses of nitrogen use efficiency in indica rice

Nitrogen-use efficiency (NUE) in rice is a complex quantitative trait involved in multiple biological processes and agronomic traits; however, the genetic basis and regulatory network of NUE remain largely unknown. We constructed a high-resolution microarray-based genetic map for 261 recombinant inbred lines derived from two indica parents. Using 2,345 bin markers, comprehensive analyses of quantitative trait loci (QTLs) of seven key agronomic traits under two different N levels were performed. A total of 11 non-redundant QTLs for effective panicle number (EPN), 7 for grain number per panicle, 13 for thousand-grain weight, 2 for seed-setting percentage, 15 for plant height, 12 for panicle length, and 6 for grain yield per plant were identified. The QTL regions were as small as 512 kb on average, and more than half spanned an interval smaller than 100 kb. Using this advantage, we identified possible candidate genes of two major EPN-related QTLs. One QTL detected under both N levels possibly encodes a DELLA protein SLR1, which is known to regulate NUE, although the natural variations of this protein have not been reported. The other QTL detected only under a high N level could encode the transcription factor OsbZIP59. We also predicted the possible candidate genes for another three of the NUE-related QTLs. Our results provide a reference for improving NUE-related QTL cloning and promote our understanding of NUE regulation in indica rice.

Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship

The phenomenal increase in the use of nitrogenous fertilizers coupled with poor nitrogen use efficiency is among the most important threats to the environment, economic, and social health. During the last 2 decades, a number of genomic regions associated with nitrogen use efficiency (NUE) and related traits have been reported by different research groups, but none of the stable and major effect QTL have been utilized in the marker-assisted introgression/pyramiding program. Compiling the data available in the literature could be very useful in identifying stable and major effect genomic regions associated with the root and NUE-related trait improving the rice grain yield. In the present study, we performed meta-QTL analysis on 1,330 QTL from 29 studies published in the past 2 decades. A total of 76 MQTL with a stable effect over different genetic backgrounds and environments were identified. The significant reduction in the confidence interval of the MQTL compared to the initial QTL resulted in the identification of annotated and putative candidate genes related to the traits considered in the present study. A hot spot region associated with correlated traits on chr 1, 4, and 8 and candidate genes associated with nitrate transporters, nitrogen content, and ammonium uptake on chromosomes 2, 4, 6, and 8 have been identified. The identified MQTL, putative candidate genes, and their orthologues were validated on our previous studies conducted on rice and wheat. The research-based interventions such as improving nitrogen use efficiency via identification of major genomic regions and candidate genes can be a plausible, simple, and low-cost solution to address the challenges of the crop improvement program.

Candidate Gene Analysis for Nitrogen Absorption and Utilization in Japonica Rice at the Seedling Stage Based on a Genome-Wide Association Study

Over-application of nitrogen (N) fertilizer in fields has had a negative impact on both environment and human health. Domesticated rice varieties with high N use efficiency (NUE) reduce fertilizer requirements, enabling sustainable agriculture. Genome-wide association study (GWAS) analysis of N absorption and utilization traits under low and high N conditions was performed to obtain 12 quantitative trait loci (QTLs) based on genotypic data including 151,202 single-nucleotide polymorphisms (SNPs) developed by re-sequencing 267 japonica rice varieties. Eighteen candidate genes were obtained by integrating GWAS and transcriptome analyses; among them, the functions of OsNRT2.4, OsAMT1.2, and OsAlaAT genes in N transport and assimilation have been identified, and OsJAZ12 and OsJAZ13 also play important roles in rice adaptation to abiotic stresses. A NUE-related candidate gene, OsNAC68, was identified by quantitative real-time PCR (qRT-PCR) analyses. OsNAC68 encodes a NAC transcription factor and has been shown to be a positive regulator of the drought stress response in rice. Overexpression of OsNAC68 significantly increased rice NUE and grain yield under deficient N conditions, but the difference was not significant under sufficient N conditions. NUE and grain yield significantly decreased under both N supply conditions in the osbnac68 mutant. This study provides crucial insights into the genetic basis of N absorption and utilization in rice, and a NUE-related gene, OsNAC68, was cloned to provide important resources for rice breeding with high NUE and grain yield.

QTL Mapping and Favorable Allele Mining of Nitrogen Deficiency Tolerance Using an Interconnected Breeding Population in Rice

Nitrogen is one of the most important nutrients for rice growth and development. Breeding of nitrogen deficiency tolerance (NDT) variety is considered to be the most economic measure to solve the constrain of low nitrogen stress on grain yield in rice. An interconnected breeding (IB) population of 497 lines developed using Huanghuazhan (HHZ) as the recurrent parent and eight elite lines as the donor parents were tested for five traits including grain yield, biomass, harvest index, thousand grain weight, and spikelet fertility under two nitrogen treatments in three growing seasons. Association analysis using 7,388 bins generated by sequencing identified a total of 14, 14, and 12 QTLs for the five traits under low nitrogen (LN), normal nitrogen (NN), and LN/NN conditions, respectively, across three seasons. Favorable alleles were dissected for the 40 QTLs at the 10 NDT regions, and OM1723 was considered as the most important parent with the highest frequency of favorable alleles contributing to NDT-related traits. Six superior lines all showed significantly higher GY in LN environments and similar GY under NN environments except for H10. Substitution mapping using near-isogenic introgression lines delimited the qTGW2-1, which was identified on chromosome 2 under LN, NN, and LN/NN conditions into two QTLs, which were located in the two regions of about 200 and 350 kb with different favorable alleles. The bins 16, 1301, 1465, 1486, 3464, and 6249 harbored the QTLs for NDT detected in this study, and the QTLs/genes previously identified for NDT or nitrogen use efficiency (NUE) could be used for enhancing NDT and NUE by marker-assisted selection (MAS).

Biochemical and Genetic Approaches Improving Nitrogen Use Efficiency in Cereal Crops: A Review

Nitrogen is an essential nutrient required in large quantities for the proper growth and development of plants. Nitrogen is the most limiting macronutrient for crop production in most of the world's agricultural areas. The dynamic nature of nitrogen and its tendency to lose soil and environment systems create a unique and challenging environment for its proper management. Exploiting genetic diversity, developing nutrient efficient novel varieties with better agronomy and crop management practices combined with improved crop genetics have been significant factors behind increased crop production. In this review, we highlight the various biochemical, genetic factors and the regulatory mechanisms controlling the plant nitrogen economy necessary for reducing fertilizer cost and improving nitrogen use efficiency while maintaining an acceptable grain yield.

A major pleiotropic QTL identified for yield components and nitrogen content in rice (Oryza sativa L.) under differential nitrogen field conditions

To identify the genomic regions for yield and NUE of rice genotypes and lines with promising yield under low N, a recombinant inbred population (RIL) developed between BPT5204 (a mega variety known for its quality) and PTB1 (variety with high NUE) was evaluated for consecutive wet and dry seasons under low nitrogen (LN) and recommended nitrogen (RN) field conditions. A set of 291 RILs were characterized for 24 traits related to leaf, agro-morphological, yield, N content and nitrogen use efficiency indices. More than 50 RILs were found promising with grain yield >10 g under LN. Parental polymorphism survey with 297 SSRs and selective genotyping revealed five genomic regions associated with yield under LN, which were further saturated with polymorphic SSRs. Thirteen promising SSRs were identified out of 144 marker trait associations under LN using single marker analysis. Composite interval mapping showed 37 QTL under LN with five pleiotropic QTL. A major stable pleiotropic (RM13201—RM13209) from PTB1 spanning 825.4 kb region associated with straw N % (SNP) in both treatments across seasons and yield and yield related traits in WS appears to be promising for the MAS. Another major QTL (RM13181-RM13201) was found to be associated with only relative trait parameters of biomass, grain and grain nitrogen. These two major pleiotropic QTL (RM13201-RM13209 and RM13181-RM13201) on chromosome 2 were characterized for their positive allele effect and could be deployed for the development of rice varieties with NUE.

Comparative Transcriptomics of Rice Genotypes with Contrasting Responses to Nitrogen Stress Reveals Genes Influencing Nitrogen Uptake through the Regulation of Root Architecture

The indiscriminate use of nitrogenous fertilizers continues unabated for commercial crop production, resulting in air and water pollution. The development of rice varieties with enhanced nitrogen use efficiency (NUE) will require a thorough understanding of the molecular basis of a plant’s response to low nitrogen (N) availability. The global expression profiles of root tissues collected from low and high N treatments at different time points in two rice genotypes, Pokkali and Bengal, with contrasting responses to N stress and contrasting root architectures were examined. Overall, the number of differentially expressed genes (DEGs) in Pokkali (indica) was higher than in Bengal (japonica) during low N and early N recovery treatments. Most low N DEGs in both genotypes were downregulated whereas early N recovery DEGs were upregulated. Of these, 148 Pokkali-specific DEGs might contribute to Pokkali’s advantage under N stress. These DEGs included transcription factors and transporters and were involved in stress responses, growth and development, regulation, and metabolism. Many DEGs are co-localized with quantitative trait loci (QTL) related to root growth and development, chlorate-resistance, and NUE. Our findings suggest that the superior growth performance of Pokkali under low N conditions could be due to the genetic differences in a diverse set of genes influencing N uptake through the regulation of root architecture.

QTLs identification for nitrogen and phosphorus uptake-related traits using ultra-high density SNP linkage

To understand the genetic basis of nitrogen and phosphorus uptake in the cultivated rice, quantitative trait loci (QTL) analysis for 7 nitrogen and phosphorus uptake-related traits including above-ground biomass (AGB), leaf colour value (SPAD) in heading stage, grain nitrogen concentration (GNC), grain nitrogen content of the plant, total nitrogen content (TNC), grain phosphorus concentration, total phosphorus content (TPC) were conducted using SNP markers in a F2 population derived from a cross between GH128 and W6827. A total of 21 QTLs for nitrogen and phosphorus uptake-related traits distributed in 16 regions along 6 chromosomes were detected using a high density genetic map consisting of 1582 bin markers, with QTLs maximum explaining 8.19% of the phenotypic variation. Nine QTLs (42.9% of total QTLs) were detected on chromosome 2. Among them, two QTL clusters including AGB, TNC, TPC and GNC were also detected in the region bin 140 and bin 146 on the chromosome 2. The distance between the two clusters was only 4.1 cM. The presence of QTL clusters has important significance and could be useful in molecular marker assisted breeding. These genomic regions might be deployed for the simultaneous improving the use efficiency of nitrogen and phosphorus in rice breeding.

Natural variation in Arabidopsis shoot branching plasticity in response to nitrate supply affects fitness

The capacity of organisms to tune their development in response to environmental cues is pervasive in nature. This phenotypic plasticity is particularly striking in plants, enabled by their modular and continuous development. A good example is the activation of lateral shoot branches in Arabidopsis, which develop from axillary meristems at the base of leaves. The activity and elongation of lateral shoots depends on the integration of many signals both external (e.g. light, nutrient supply) and internal (e.g. the phytohormones auxin, strigolactone and cytokinin). Here, we characterise natural variation in plasticity of shoot branching in response to nitrate supply using two diverse panels of Arabidopsis lines. We find extensive variation in nitrate sensitivity across these lines, suggesting a genetic basis for variation in branching plasticity. High plasticity is associated with extreme branching phenotypes such that lines with the most branches on high nitrate have the fewest under nitrate deficient conditions. Conversely, low plasticity is associated with a constitutively moderate level of branching. Furthermore, variation in plasticity is associated with alternative life histories with the low plasticity lines flowering significantly earlier than high plasticity lines. In Arabidopsis, branching is highly correlated with fruit yield, and thus low plasticity lines produce more fruit than high plasticity lines under nitrate deficient conditions, whereas highly plastic lines produce more fruit under high nitrate conditions. Low and high plasticity, associated with early and late flowering respectively, can therefore be interpreted alternative escape vs mitigate strategies to low N environments. The genetic architecture of these traits appears to be highly complex, with only a small proportion of the estimated genetic variance detected in association mapping.

Identification of Quantitative Trait Loci Associated with Nutrient Use Efficiency Traits, Using SNP Markers in an Early Backcross Population of Rice (Oryza sativa L.)

The development of rice cultivars with nutrient use efficiency (NuUE) is highly crucial for sustaining global rice production in Asia and Africa. However, this requires a better understanding of the genetics of NuUE-related traits and their relationship to grain yield. In this study, simultaneous efforts were made to develop nutrient use efficient rice cultivars and to map quantitative trait loci (QTLs) governing NuUE-related traits in rice. A total of 230 BC₁F₅ introgression lines (ILs) were developed from a single early backcross population involving Weed Tolerant Rice 1, as the recipient parent, and Hao-an-nong, as the donor parent. The ILs were cultivated in field conditions with a different combination of fertilizer schedule under six nutrient conditions: minus nitrogen (–N), minus phosphorus (–P), (–NP), minus nitrogen phosphorus and potassium (–NPK), 75% of recommended nitrogen (75N), and NPK. Analysis of variance revealed that significant differences (p < 0.01) were noted among ILs and treatments for all traits. A high-density linkage map was constructed by using 704 high-quality single nucleotide polymorphism (SNP) markers. A total of 49 main-effect QTLs were identified on all chromosomes, except on chromosome 7, 11 and 12, which are showing 20.25% to 34.68% of phenotypic variation. With further analysis of these QTLs, we refined them to four top hotspot QTLs (QTL harbor-I to IV) located on chromosomes 3, 5, 9, and 11. However, we identified four novel putative QTLs for agronomic efficiency (AE) and 22 QTLs for partial factor productivity (PFP) under –P and 75N conditions. These interval regions of QTLs, several transporters and genes are located that were involved in nutrient uptake from soil to plant organs and tolerance to biotic and abiotic stresses. Further, the validation of these potential QTLs, genes may provide remarkable value for marker-aided selection and pyramiding of multiple QTLs, which would provide supporting evidence for the enhancement of grain yield and cloning of NuUE tolerance-responsive genes in rice.

RDWN6XB, a major quantitative trait locus positively enhances root system architecture under nitrogen deficiency in rice

BACKGROUND

Nitrogen (N) is a major input cost in rice production, in addition to causing severe pollution to agricultural and ecological environments. Root dry weight has been considered the most important component related to crop yields than the other root traits. Therefore, development of rice varieties/lines with low input of N fertilizer and higher root traits are essential for sustainable rice production.

RESULTS

In this context, a main effect quantitative trait locus qRDWN6^XB on the long arm of chromosome 6 which positively confers tolerance to N deficiency in the Indica rice variety XieqingzaoB, was identified using a chromosomal segment substitution line (CSSL) population. qRDWN6^XB was determined to be located near marker InD90 on chromosome 6 based on association analysis of phenotype data from three N levels and 120 polymorphic molecular markers. The target chromosomal segment substitution line CSSL45, which has the higher root dry weight (RDW) than indica cultivar Zhonghui9308 and carry qRDWN6^XB, was selected for further study. A BC₅F_2:3 population derived from a cross between CSSL45 and Zhonghui9308 was constructed. To fine-map qRDWN6^XB, we used the homozygous recombinant plants and ultimately this locus was narrowed to a 52.3-kb between markers ND-4 and RM19771, which contains nine candidate genes in this region. One of these genes, LOC_Os06g15910 as a potassium transporter was considered a strong candidate gene for the RDWN6^XB locus.

CONCLUSIONS

The identification of qRDWN6^XB provides a new genetic resource for breeding rice varieties and a starting point to improve grain yield despite the decreased input of N fertilizers. The newly developed and tightly linked InDel marker ND-4 will be useful to improve the root system architecture under low N by marker-assisted selection (MAS) in rice breeding programs.

A follow-up study for biomass yield QTLs in rice

The biomass yield (plant weight) of rice fluctuates from year to year. In a previous study, we demonstrated that six quantitative trait loci (QTLs) contribute to the variation in the plant weight of recombinant inbred lines (RILs) of high-yielding Japanese rice cultivars. However, it remains unclear whether the effects of those QTLs are stable over multiple years. Therefore, we evaluated the effect of the alleles on the plant weight of RILs over multiple years, including a change of fertilization level (i.e., in different environments). Even though the biomass yields of all RILs fluctuated among environments, RILs that were selected on the basis of the genotypes of the detected QTLs had a stable rank order of plant weight that corresponded to their genotypes. This multiple-environment experiment reveals the highly significant contribution of both genotypic and environmental variances to the observed variance in plant weight. A marginally significant QTL–environment interaction was detected at only one of the six QTLs, with a subtle contribution. These results support the idea that the biomass yield of rice can be improved through QTL-based allele selection.

Molecular Genetics and Breeding for Nutrient Use Efficiency in Rice

In the coming decades, rice production needs to be carried out sustainably to keep the balance between profitability margins and essential resource input costs. Many fertilizers, such as N, depend primarily on fossil fuels, whereas P comes from rock phosphates. How long these reserves will last and sustain agriculture remains to be seen. Therefore, current agricultural food production under such conditions remains an enormous and colossal challenge. Researchers have been trying to identify nutrient use-efficient varieties over the past few decades with limited success. The concept of nutrient use efficiency is being revisited to understand the molecular genetic basis, while much of it is not entirely understood yet. However, significant achievements have recently been observed at the molecular level in nitrogen and phosphorus use efficiency. Breeding teams are trying to incorporate these valuable QTLs and genes into their rice breeding programs. In this review, we seek to identify the achievements and the progress made so far in the fields of genetics, molecular breeding and biotechnology, especially for nutrient use efficiency in rice.

Improving nitrogen use efficiency in plants: effective phenotyping in conjunction with agronomic and genetic approaches

For global sustainable food production and environmental benefits, there is an urgent need to improve N use efficiency (NUE) in crop plants. Excessive and inefficient use of N fertiliser results in increased crop production costs and environmental pollution. Therefore, cost-effective strategies such as proper management of the timing and quantity of N fertiliser application, and breeding for better varieties are needed to improve NUE in crops. However, for these efforts to be feasible, high-throughput and reliable phenotyping techniques would be very useful for monitoring N status in planta, as well as to facilitate faster decisions during breeding and selection processes. This review provides an insight into contemporary approaches to phenotyping NUE-related traits and associated challenges. We discuss recent and advanced, sensor- and image-based phenotyping techniques that use a variety of equipment, tools and platforms. The review also elaborates on how high-throughput phenotyping will accelerate efforts for screening large populations of diverse genotypes in controlled environment and field conditions to identify novel genotypes with improved NUE.

Transcriptome Analysis of Two Rice Varieties Contrasting for Nitrogen Use Efficiency under Chronic N Starvation Reveals Differences in Chloroplast and Starch Metabolism-Related Genes

The nitrogen use efficiency (NUE) of crop plants is limited and enhancing it in rice, a major cereal crop, would be beneficial for farmers and the environment alike. Here we report the genome-wide transcriptome analysis of two rice genotypes, IR 64 (IR64) and Nagina 22 (N22) under optimal (N+) and chronic starvation (N−) of nitrogen (N) from 15-day-old root and shoot tissues. The two genotypes were found to be contrasting in their response to N−; IR64 root architecture and root dry weight remained almost equivalent to that under N+ conditions, while N22 showed high foraging ability but a substantial reduction in biomass under N−. Similarly, the photosynthetic pigments showed a drastic reduction in N22 under low N, while IR64 was more resilient. Nitrate reductase showed significantly low specific activity under N− in both genotypes. Glutamate synthase (GOGAT) and citrate synthase CS activity were highly reduced in N22 but not in IR64. Transcriptome analysis of these genotypes revealed nearly double the number of genes to be differentially expressed (DEGs) in roots (1016) compared to shoots (571). The response of the two genotypes to N starvation was distinctly different reflecting their morphological/biochemical response with just two and eight common DEGs in the root and shoot tissues. There were a total of 385 nitrogen-responsive DEGs (106 in shoots and 279 in roots) between the two genotypes. Fifty-two of the 89 DEGs identified as specific to N22 root tissues were also found to be differentially expressed between the two genotypes under N−. Most of these DEGs belonged to starch and chloroplast metabolism, followed by membrane and signaling proteins. Physical mapping of DEGs revealed 95 DEGs in roots and 76 in shoots to be present in quantitative trait loci (QTL) known for NUE.

Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.)

Nitrogen (N) availability is a major factor limiting crop growth and development. Identification of quantitative trait loci (QTL) for N uptake (NUP) and N use efficiency (NUE) can provide useful information regarding the genetic basis of these traits and their associated effects on yield production. In this study, a set of high throughput genotyped chromosome segment substitution lines (CSSLs) derived from a cross between recipient 9311 and donor Nipponbare were used to identify QTL for rice NUP and NUE. Using high throughput sequencing, each CSSL were genotyped and an ultra-high-quality physical map was constructed. A total of 13 QTL, seven for NUP and six for NUE, were identified in plants under hydroponic culture with all nutrients supplied in sufficient quantities. The proportion of phenotypic variation explained by these QTL for NUP and NUE ranged from 3.16-13.99% and 3.76-12.34%, respectively. We also identified several QTL for biomass yield (BY) and grain yield (GY), which were responsible for 3.21-45.54% and 6.28-7.31%, respectively, of observed phenotypic variation. GY were significantly positively correlated with NUP and NUE, with NUP more closely correlated than NUE. Our results contribute information to NUP and NUE improvement in rice.

Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields.

SNP-SNP Interaction Analysis on Soybean Oil Content under Multi-Environments

Soybean oil content is one of main quality traits. In this study, we used the multifactor dimensionality reduction (MDR) method and a soybean high-density genetic map including 5,308 markers to identify stable single nucleotide polymorphism (SNP)—SNP interactions controlling oil content in soybean across 23 environments. In total, 36,442,756 SNP-SNP interaction pairs were detected, 1865 of all interaction pairs associated with soybean oil content were identified under multiple environments by the Bonferroni correction with p <3.55×10⁻¹¹. Two and 1863 SNP-SNP interaction pairs detected stable across 12 and 11 environments, respectively, which account around 50% of total environments. Epistasis values and contribution rates of stable interaction (the SNP interaction pairs were detected in more than 2 environments) pairs were detected by the two way ANOVA test, the available interaction pairs were ranged 0.01 to 0.89 and from 0.01 to 0.85, respectively. Some of one side of the interaction pairs were identified with previously research as a major QTL without epistasis effects. The results of this study provide insights into the genetic architecture of soybean oil content and can serve as a basis for marker-assisted selection breeding.

Mapping QTLs and association of differentially expressed gene transcripts for multiple agronomic traits under different nitrogen levels in sorghum

BACKGROUND

Sorghum is an important C4 crop which relies on applied Nitrogen fertilizers (N) for optimal yields, of which substantial amounts are lost into the atmosphere. Understanding the genetic variation of sorghum in response to limited nitrogen supply is important for elucidating the underlying genetic mechanisms of nitrogen utilization.

RESULTS

A bi-parental mapping population consisting of 131 recombinant inbred lines (RILs) was used to map quantitative trait loci (QTLs) influencing different agronomic traits evaluated under normal N (100 kg.ha(-1) fertilizer) and low N (0 kg.ha(-1) fertilizer) conditions. A linkage map spanning 1614 cM was developed using 642 polymorphic single nucleotide polymorphisms (SNPs) detected in the population using Genotyping-By-Sequencing (GBS) technology. Composite interval mapping detected a total of 38 QTLs for 11 agronomic traits tested under different nitrogen levels. The phenotypic variation explained by individual QTL ranged from 6.2 to 50.8%. Illumina RNA sequencing data generated on seedling root tissues revealed 726 differentially expressed gene (DEG) transcripts between parents, of which 108 were mapped close to the QTL regions.

CONCLUSIONS

Co-localized regions affecting multiple traits were detected on chromosomes 1, 5, 6, 7 and 9. These potentially pleiotropic regions were coincident with the genomic regions of cloned QTLs, including genes associated with flowering time, Ma3 on chromosome 1 and Ma1 on chromosome 6, gene associated with plant height, Dw2 on chromosome 6. In these regions, RNA sequencing data showed differential expression of transcripts related to nitrogen metabolism (Ferredoxin-nitrate reductase), glycolysis (Phosphofructo-2-kinase), seed storage proteins, plant hormone metabolism and membrane transport. The differentially expressed transcripts underlying the pleiotropic QTL regions could be potential targets for improving sorghum performance under limited N fertilizer through marker assisted selection.

Genetic approaches to enhancing nitrogen-use efficiency (NUE) in cereals: challenges and future directions

Over 100million tonnes of nitrogen (N) fertiliser are applied globally each year to maintain high yields in agricultural crops. The rising price of N fertilisers has made them a major cost for farmers. Inefficient use of N fertiliser leads to substantial environmental problems through contamination of air and water resources and can be a significant economic cost. Consequently, there is considerable need to improve the way N fertiliser is used in farming systems. The efficiency with which crops use applied N fertiliser - the nitrogen-use efficiency (NUE) - is currently quite low for cereals. This is the case in both high yielding environments and lower yielding environments characteristic of cereal growing regions of Australia. Multiple studies have attempted to identify the genetic basis of NUE, but the utility of the results is limited because of the complex nature of the trait and the magnitude of genotype by environment interaction. Transgenic approaches have been applied to improve plant NUE but with limited success, due, in part, to a combination of the complexity of the trait but also due to lack of accurate phenotyping methods. This review documents these two approaches and suggests future directions in improving cereal NUE with a focus on the Australian cereal industry.

Metabolic and co-expression network-based analyses associated with nitrate response in rice

BACKGROUND

Understanding gene expression and metabolic re-programming that occur in response to limiting nitrogen (N) conditions in crop plants is crucial for the ongoing progress towards the development of varieties with improved nitrogen use efficiency (NUE). To unravel new details on the molecular and metabolic responses to N availability in a major food crop, we conducted analyses on a weighted gene co-expression network and metabolic profile data obtained from leaves and roots of rice plants adapted to sufficient and limiting N as well as after shifting them to limiting (reduction) and sufficient (induction) N conditions.

RESULTS

A gene co-expression network representing clusters of rice genes with similar expression patterns across four nitrogen conditions and two tissue types was generated. The resulting 18 clusters were analyzed for enrichment of significant gene ontology (GO) terms. Four clusters exhibited significant correlation with limiting and reducing nitrate treatments. Among the identified enriched GO terms, those related to nucleoside/nucleotide, purine and ATP binding, defense response, sugar/carbohydrate binding, protein kinase activities, cell-death and cell wall enzymatic activity are enriched. Although a subset of functional categories are more broadly associated with the response of rice organs to limiting N and N reduction, our analyses suggest that N reduction elicits a response distinguishable from that to adaptation to limiting N, particularly in leaves. This observation is further supported by metabolic profiling which shows that several compounds in leaves change proportionally to the nitrate level (i.e. higher in sufficient N vs. limiting N) and respond with even higher levels when the nitrate level is reduced. Notably, these compounds are directly involved in N assimilation, transport, and storage (glutamine, asparagine, glutamate and allantoin) and extend to most amino acids. Based on these data, we hypothesize that plants respond by rapidly mobilizing stored vacuolar nitrate when N deficit is perceived, and that the response likely involves phosphorylation signal cascades and transcriptional regulation.

CONCLUSIONS

The co-expression network analysis and metabolic profiling performed in rice pinpoint the relevance of signal transduction components and regulation of N mobilization in response to limiting N conditions and deepen our understanding of N responses and N use in crops.

Approaches towards nitrogen- and phosphorus-efficient rice

BACKGROUND AND AIMS

Food production has to increase to meet the demand of a growing population. In light of the high energy costs and increasingly scarce resources, future agricultural systems have to be more productive and more efficient in terms of inputs such as fertilizer and water. The development of rice varieties with high yield under low-nutrient conditions has therefore become a breeding priority. The rapid progress made in sequencing and molecular-marker technology is now beginning to change the way breeding is done, providing new opportunities.

SCOPE

Nitrogen (N) and phosphorus (P) are applied to agricultural systems in large quantities and a deficiency of either nutrient leads to yield losses and triggers complex molecular and physiological responses. The underlying genes are now being identified and studied in detail, and an increasing number of quantitative trait loci (QTLs) related to N and P uptake and utilization are being reported. Here, we provide an overview of the different aspects related to N and P in rice production systems, and apply a breeder's perspective on the potential of relevant genes and pathways for breeding applications.

MAIN POINTS

For the development of nutrient-efficient rice, a holistic approach should be followed combining optimized fertilizer management with enhanced nutrient uptake via a vigorous root system, leading to increased grain filling and yield. Despite an increasing number of N- and P-related genes and QTLs being reported, very few are actively used in molecular breeding programmes. The complex regulation of N- and P-related pathways challenges breeders and the research community to identify large-effect genes/QTLs. For this it will be important to focus more on the analysis of tolerant genotypes rather than model plants, since tolerance pathways may employ a different set of genes.

A statistical procedure to map high-order epistasis for complex traits

Genetic interactions or epistasis have been thought to play a pivotal role in shaping the formation, development and evolution of life. Previous work focused on lower-order interactions between a pair of genes, but it is obviously inadequate to explain a complex network of genetic interactions and pathways. We review and assess a statistical model for characterizing high-order epistasis among more than two genes or quantitative trait loci (QTLs) that control a complex trait. The model includes a series of start-of-the-art standard procedures for estimating and testing the nature and magnitude of QTL interactions. Results from simulation studies and real data analysis warrant the statistical properties of the model and its usefulness in practice. High-order epistatic mapping will provide a routine procedure for charting a detailed picture of the genetic regulation mechanisms underlying the phenotypic variation of complex traits.