Transcriptome analysis reveals Nitrogen deficiency induced alterations in leaf and root of three cultivars of potato (Solanum tuberosum L.)

How lignin biosynthesis responds to nitrogen in plants: a scoping review

Nitrogen (N) plays a critical role in the functioning of key amino acids and synthetic enzymes responsible for the various stages of lignin biosynthesis. However, the precise mechanisms through which N influences lignin biosynthesis have not been fully elucidated. This scoping review explores how lignin biosynthesis responds to N in plants. A systematic search of the literature in several databases was conducted using relevant keywords. Only 44 of the 1842 selected studies contained a range of plant species, experimental conditions, and research approaches. Lignin content, structure, and biosynthetic pathways in response to N are discussed, and possible response mechanisms of lignin under low N are proposed. Among the selected studies, 64.52% of the studies reter to lignin content found a negative correlation between N availability and lignin content. Usually, high N decreases the lignin content, delays cell lignification, increases p-hydroxyphenyl propane (H) monomer content, and regulates lignin synthesis through the expression of key genes (PAL, 4CL, CCR, CAD, COMT, LAC, and POD) encoding miRNAs and transcription factors (e.g., MYB, bHLH). N deficiency enhances lignin synthesis through the accumulation of phenylpropanoids, phenolics, and soluble carbohydrates, and indirect changes in phytohormones, secondary metabolites, etc. This review provides new insights and important references for future studies on the regulation of lignin biosynthesis.

Transcriptome Profiling Reveals the Gene Network Responding to Low Nitrogen Stress in Wheat

As one of the essential nutrients for plants, nitrogen (N) has a major impact on the yield and quality of wheat worldwide. Due to chemical fertilizer pollution, it has become increasingly important to improve crop yield by increasing N use efficiency (NUE). Therefore, understanding the response mechanisms to low N (LN) stress is essential for the regulation of NUE in wheat. In this study, LN stress significantly accelerated wheat root growth, but inhibited shoot growth. Further transcriptome analysis showed that 8468 differentially expressed genes (DEGs) responded to LN stress. The roots and shoots displayed opposite response patterns, of which the majority of DEGs in roots were up-regulated (66.15%; 2955/4467), but the majority of DEGs in shoots were down-regulated (71.62%; 3274/4565). GO and KEGG analyses showed that nitrate reductase activity, nitrate assimilation, and N metabolism were significantly enriched in both the roots and shoots. Transcription factor (TF) and protein kinase analysis showed that genes such as MYB-related (38/38 genes) may function in a tissue-specific manner to respond to LN stress. Moreover, 20 out of 107 N signaling homologous genes were differentially expressed in wheat. A total of 47 transcriptome datasets were used for weighted gene co-expression network analysis (17,840 genes), and five TFs were identified as the potential hub regulatory genes involved in the response to LN stress in wheat. Our findings provide insight into the functional mechanisms in response to LN stress and five candidate regulatory genes in wheat. These results will provide a basis for further research on promoting NUE in wheat.

Genome-material costs and functional trade-offs in the autopolyploid Solidago gigantea (giant goldenrod) series

PREMISE

Increased genome-material costs of N and P atoms inherent to organisms with larger genomes have been proposed to limit growth under nutrient scarcities and to promote growth under nutrient enrichments. Such responsiveness may reflect a nutrient-dependent diploid versus polyploid advantage that could have vast ecological and evolutionary implications, but direct evidence that material costs increase with ploidy level and/or influence cytotype-dependent growth, metabolic, and/or resource-use trade-offs is limited.

METHODS

We grew diploid, autotetraploid, and autohexaploid Solidago gigantea plants with one of four ambient or enriched N:P ratios and measured traits related to material costs, primary and secondary metabolism, and resource-use.

RESULTS

Relative to diploids, polyploids invested more N and P into cells, and tetraploids grew more with N enrichments, suggesting that material costs increase with ploidy level. Polyploids also generally exhibited strategies that could minimize material-cost constraints over both long (reduced monoploid genome size) and short (more extreme transcriptome downsizing, reduced photosynthesis rates and terpene concentrations, enhanced N-use efficiencies) evolutionary time periods. Furthermore, polyploids had lower transpiration rates but higher water-use efficiencies than diploids, both of which were more pronounced under nutrient-limiting conditions.

CONCLUSIONS

N and P material costs increase with ploidy level, but material-cost constraints might be lessened by resource allocation/investment mechanisms that can also alter ecological dynamics and selection. Our results enhance mechanistic understanding of how global increases in nutrients might provide a release from material-cost constraints in polyploids that could impact ploidy (or genome-size)-specific performances, cytogeographic patterning, and multispecies community structuring.

An Integrated Analysis of Metabolome, Transcriptome, and Physiology Revealed the Molecular and Physiological Response of Citrus sinensis Roots to Prolonged Nitrogen Deficiency

Citrus sinensis seedlings were supplied with a nutrient solution containing 15 (control) or 0 (nitrogen (N) deficiency) mM N for 10 weeks. Extensive metabolic and gene reprogramming occurred in 0 mM N-treated roots (RN0) to cope with N deficiency, including: (a) enhancing the ability to keep phosphate homeostasis by elevating the abundances of metabolites containing phosphorus and the compartmentation of phosphate in plastids, and/or downregulating low-phosphate-inducible genes; (b) improving the ability to keep N homeostasis by lowering the levels of metabolites containing N but not phosphorus, upregulating N compound degradation, the root/shoot ratio, and the expression of genes involved in N uptake, and resulting in transitions from N-rich alkaloids to carbon (C)-rich phenylpropanoids and phenolic compounds (excluding indole alkaloids) and from N-rich amino acids to C-rich carbohydrates and organic acids; (c) upregulating the ability to maintain energy homeostasis by increasing energy production (tricarboxylic acid cycle, glycolysis/gluconeogenesis, oxidative phosphorylation, and ATP biosynthetic process) and decreasing energy utilization for amino acid and protein biosynthesis and new root building; (d) elevating the transmembrane transport of metabolites, thus enhancing the remobilization and recycling of useful compounds; and (e) activating protein processing in the endoplasmic reticulum. RN0 had a higher ability to detoxify reactive oxygen species and aldehydes, thus protecting RN0 against oxidative injury and delaying root senescence.

Short-term transcriptomic analysis at organ scale reveals candidate genes involved in low N responses in NUE-contrasting tomato genotypes

BACKGROUND

Understanding the complex regulatory network underlying plant nitrogen (N) responses associated with high Nitrogen Use Efficiency (NUE) is one of the main challenges for sustainable cropping systems. Nitrate (NO₃ ^-), acting as both an N source and a signal molecule, provokes very fast transcriptome reprogramming, allowing plants to adapt to its availability. These changes are genotype- and tissue-specific; thus, the comparison between contrasting genotypes is crucial to uncovering high NUE mechanisms.

METHODS

Here, we compared, for the first time, the spatio-temporal transcriptome changes in both root and shoot of two NUE contrasting tomato genotypes, Regina Ostuni (high-NUE) and UC82 (low-NUE), in response to short-term (within 24 h) low (LN) and high (HN) NO₃ ^- resupply.

RESULTS

Using time-series transcriptome data (0, 8, and 24 h), we identified 395 and 482 N-responsive genes differentially expressed (DEGs) between RO and UC82 in shoot and root, respectively. Protein kinase signaling plant hormone signal transduction, and phenylpropanoid biosynthesis were the main enriched metabolic pathways in shoot and root, respectively, and were upregulated in RO compared to UC82. Interestingly, several N transporters belonging to NRT and NPF families, such as NRT2.3, NRT2.4, NPF1.2, and NPF8.3, were found differentially expressed between RO and UC82 genotypes, which might explain the contrasting NUE performances. Transcription factors (TFs) belonging to several families, such as ERF, LOB, GLK, NFYB, ARF, Zinc-finger, and MYB, were differentially expressed between genotypes in response to LN. A complementary Weighted Gene Co-expression Network Analysis (WGCNA) allowed the identification of LN-responsive co-expression modules in RO shoot and root. The regulatory network analysis revealed candidate genes that might have key functions in short-term LN regulation. In particular, an asparagine synthetase (ASNS), a CBL-interacting serine/threonine-protein kinase 1 (CIPK1), a cytokinin riboside 5'-monophosphate phosphoribohydrolase (LOG8), a glycosyltransferase (UGT73C4), and an ERF2 were identified in the shoot, while an LRR receptor-like serine/threonine-protein kinase (FEI1) and two TFs NF-YB5 and LOB37 were identified in the root.

DISCUSSION

Our results revealed potential candidate genes that independently and/or concurrently may regulate short-term low-N response, suggesting a key role played by cytokinin and ROS balancing in early LN regulation mechanisms adopted by the N-use efficient genotype RO.

Comparative Transcriptomic Analysis Reveals the Negative Response Mechanism of Peanut Root Morphology and Nitrate Assimilation to Nitrogen Deficiency

Root architecture plays a fundamental role in crop yield, which is sensitive to nitrogen fertilizer. Although it is well studied that nitrogen fertilizer significantly promotes peanut (Arachis hypogaea L.) growth and yield, less information was available on how its root development responds to nitrogen deficiency. In this study, the growth and development of roots were inhibited, as indicated by the significantly decreased root dry weight and length and the lateral root number, especially under 10 days of nitrogen deficiency treatment. The activities and the expression of the genes related to nitrogen assimilation enzymes including nitrate reductase, glutamine synthetase, glutamate dehydrogenase, and glutamine oxoglutarate aminotransferase and the genes encoding the nitrate transporters were significantly decreased under 10 days of nitrogen deficiency treatment, which may lead to a decrease in nitrate content, as indicated by the significantly decreased nitrogen balance index. Transcriptome sequencing revealed a total of 293 (119 up- and 174 downregulated) and 2271 (1165 up- and 1106 downregulated) differentially expressed genes (DEGs) identified after five and ten days of nitrogen deficiency treatments, respectively. Bioinformatic analysis showed that these DEGs were mainly involved in nitrate transportation and assimilation, phytohormone signal transduction, and the lignin biosynthesis pathway. Furthermore, a putative schematic diagram of nitrogen deficiency inhibiting root growth was established, which gives us a better understanding of nitrogen metabolism in peanut roots and a theoretical basis for improving nitrogen use efficiency.

Crop germplasm: Current challenges, physiological-molecular perspective, and advance strategies towards development of climate-resilient crops

Germplasm is a long-term resource management mission and investment for civilization. An estimated ∼7.4 million accessions are held in 1750 plant germplasm centres around the world; yet, only 2% of these assets have been utilized as plant genetic resources (PGRs). According to recent studies, the current food yield trajectory will be insufficient to feed the world's population in 2050. Additionally, possible negative effects in terms of crop failure because of climate change are already being experienced across the world. Therefore, it is necessary to reconciliation of research advancement and innovation of practices for further exploration of the potential of crop germplasm especially for the complex traits associated with yield such as water- and nitrogen use efficiency. In this review, we tried to address current challenges, research gaps, physiological and molecular aspects of two broad spectrum complex traits such as water- and nitrogen-use efficiency, and advanced integrated strategies that could provide a platform for combined stress management for climate-smart crop development. Additionally, recent development in technologies that are directly related to germplasm characterization was highlighted for further molecular utilization towards the development of elite varieties.

Mapping of Candidate Genes in Response to Low Nitrogen in Rice Seedlings

Nitrogen is not only a macronutrient essential for crop growth and development, but also one of the most critical nutrients in farmland ecosystem. Insufficient nitrogen supply will lead to crop yield reduction, while excessive application of nitrogen fertilizer will cause agricultural and eco-environment damage. Therefore, mining low-nitrogen tolerant rice genes and improving nitrogen use efficiency are of great significance to the sustainable development of agriculture. This study was conducted by Genome-wide association study on a basis of two root morphological traits (root length and root diameter) and 788,396 SNPs of a natural population of 295 rice varieties. The transcriptome of low-nitrogen tolerant variety (Longjing 31) and low-nitrogen sensitive variety (Songjing 10) were sequenced between low and high nitrogen treatments. A total of 35 QTLs containing 493 genes were mapped. 3085 differential expressed genes were identified. Among these 493 genes, 174 genes showed different haplotype patterns. There were significant phenotype differences among different haplotypes of 58 genes with haplotype differences. These 58 genes were hypothesized as candidate genes for low nitrogen tolerance related to root morphology. Finally, six genes (Os07g0471300, Os11g0230400, Os11g0229300, Os11g0229400, Os11g0618300 and Os11g0229333) which expressed differentially in Longjing 31 were defined as more valuable candidate genes for low-nitrogen tolerance. The results revealed the response characteristics of rice to low-nitrogen, and provided insights into regulatory mechanisms of rice to nitrogen deficiency.

Screening of differentially expressed microRNAs and target genes in two potato varieties under nitrogen stress

BACKGROUND

A reasonable supply of nitrogen (N) fertilizer is essential for obtaining high-quality, high-level, and stable potato yields, and an improvement in the N utilization efficiency can effectively reduce N fertilizer use. It is important to use accurate, straightforward, and efficient transgenic breeding techniques for the identification of genes that can improve nitrogen use efficiency, thus enabling us to achieve the ultimate goal of breeding N-efficient potato varieties. In recent years, some of the mechanisms of miRNAs have been elucidated via the analysis of the correlation between the expression levels of potato miRNA target genes and regulated genes under conditions of stress, but the role of miRNAs in the inhibition/expression of key genes regulating N metabolism under N stress is still unclear. Our study aimed to identify the role played by specific enzymes and miRNAs in the responses of plants to N stress.

RESULTS

The roots and leaves of the N-efficient potato variety, Yanshu4 ("Y"), and N-inefficient potato variety, Atlantic ("D"), were collected at the seedling and budding stages after they were exposed to different N fertilizer treatments. The miRNAs expressed differentially under the two types of N stress and their corresponding target genes were first predicted using miRNA and degradome analysis. Then, quantitative polymerase chain reaction (qRT-PCR) was performed to verify the expression of differential miRNAs that were closely related to N metabolism. Finally, the shearing relationship between stu-miR396-5p and its target gene StNiR was determined by analyzing luciferase activity levels. The results showed that NiR activity increased significantly with an increase in the applied N levels from the seedling stage to the budding stage, and NiR responded significantly to different N treatments. miRNA sequencing enabled us to predict 48 families with conserved miRNAs that were mainly involved in N metabolism, carbon metabolism, and amino acid biosynthesis. The differences in the expression of the following miRNAs were identified via screening (high expression levels and P < 0.05): stu-miR396-5p, stu-miR408b-3p_R-1, stu-miR3627-3p, stu-miR482a-3p, stu-miR8036-3p, stu-miR482a-5p, stu-miR827-5p, stu-miR156a_L-1, stu-miR827-3p, stu-miR172b-5p, stu-miR6022-p3_7, stu-miR398a-5p, and stu-miR166c-5p_L-3. Degradome analysis showed that most miRNAs had many-to-many relationships with target genes. The main target genes involved in N metabolism were NiR, NiR1, NRT2.5, and NRT2.7. qRT-PCR analysis showed that there were significant differences in the expression levels of stu-miR396-5p, stu-miR8036-3p, and stu-miR482a-3p in the leaves and roots of the Yanshu4 and Atlantic varieties at the seedling and budding stages under conditions that involved no N and excessive N application; the expression of these miRNAs was induced in response to N stress. The correlation between the differential expression of stu-miR396-5p and its corresponding target gene NiR was further verified by determining the luciferase activity level and was found to be strongly negative.

CONCLUSION

The activity of NiR was significantly positively correlated with N application from the seedling to the budding stage. Differential miRNAs and target genes showed a many-to-many relationship with each other. The expression of stu-miR396-5p, stu-miR482a-3p, and stu-miR8036-3p in the roots and leaves of the Yanshu4 and Atlantic varieties at the seedling and budding stages was notably different under two types of N stress. Under two types of N stress, stu-miR396-5p was down-regulated in Yanshu4 in the seedling-stage and shoot-stage roots, and up-regulated in seedling-stage roots and shoot-stage leaves; stu-miR482a-3p was up-regulated in the seedling and shoot stages. The expression of stu-miR8036-3p was up-regulated in the leaves and roots at the seedling and budding stages, and down-regulated in roots under both types of N stress. The gene expressing the key enzyme involved in N metabolism, StNiR, and the stu-miR396-5p luciferase assay reporter gene had a strong regulatory relationship with each other. This study provides candidate miRNAs related to nitrogen metabolism and highlights that differential miRNAs play a key role in nitrogen stress in potato, providing insights for future research on miRNAs and their target genes in nitrogen metabolic pathways and breeding nitrogen-efficient potatoes.

Comparison of single-trait and multi-trait genomic predictions on agronomic and disease resistance traits in spring wheat

This study performed comprehensive analyses on the predictive abilities of single-trait and two multi-trait models in three populations. Our results demonstrated the superiority of multi-traits over single-trait models across seven agronomic and four to seven disease resistance traits of different genetic architecture. The predictive ability of multi-trait and single-trait prediction models has not been investigated on diverse traits evaluated under organic and conventional management systems. Here, we compared the predictive abilities of 25% of a testing set that has not been evaluated for a single trait (ST), not evaluated for multi-traits (MT1), and evaluated for some traits but not others (MT2) in three spring wheat populations genotyped either with the wheat 90K single nucleotide polymorphisms array or DArTseq. Analyses were performed on seven agronomic traits evaluated under conventional and organic management systems, four to seven disease resistance traits, and all agronomic and disease resistance traits simultaneously. The average prediction accuracies of the ST, MT1, and MT2 models varied from 0.03 to 0.78 (mean 0.41), from 0.05 to 0.82 (mean 0.47), and from 0.05 to 0.92 (mean 0.67), respectively. The predictive ability of the MT2 model was significantly greater than the ST model in all traits and populations except common bunt with the MT1 model being intermediate between them. The MT2 model increased prediction accuracies over the ST and MT1 models in all traits by 9.0-82.4% (mean 37.3%) and 2.9-82.5% (mean 25.7%), respectively, except common bunt that showed up to 7.7% smaller accuracies in two populations. A joint analysis of all agronomic and disease resistance traits further improved accuracies within the MT1 and MT2 models on average by 21.4% and 17.4%, respectively, as compared to either the agronomic or disease resistance traits, demonstrating the high potential of the multi-traits models in improving prediction accuracies.

Identification of Spring Wheat with Superior Agronomic Performance under Contrasting Nitrogen Managements Using Linear Phenotypic Selection Indices

Both the Linear Phenotypic Selection Index (LPSI) and the Restrictive Linear Phenotypic Selection Index (RLPSI) have been widely used to select parents and progenies, but the effect of economic weights on the selection parameters (the expected genetic gain, response to selection, and the correlation between the indices and genetic merits) have not been investigated in detail. Here, we (i) assessed combinations of 2304 economic weights using four traits (maturity, plant height, grain yield and grain protein content) recorded under four organically (low nitrogen) and five conventionally (high nitrogen) managed environments, (ii) compared single-trait and multi-trait selection indices (LPSI vs. RLPSI by imposing restrictions to the expected genetic gain of either yield or grain protein content), and (iii) selected a subset of about 10% spring wheat cultivars that performed very well under organic and/or conventional management systems. The multi-trait selection indices, with and without imposing restrictions, were superior to single trait selection. However, the selection parameters differed quite a lot depending on the economic weights, which suggests the need for optimizing the weights. Twenty-two of the 196 cultivars that showed superior performance under organic and/or conventional management systems were consistently selected using all five of the selected economic weights, and at least two of the selection scenarios. The selected cultivars belonged to the Canada Western Red Spring (16 cultivars), the Canada Northern Hard Red (3), and the Canada Prairie Spring Red (3), and required 83–93 days to maturity, were 72–100 cm tall, and produced from 4.0 to 6.2 t ha⁻¹ grain yield with 14.6–17.7% GPC. The selected cultivars would be highly useful, not only as potential trait donors for breeding under an organic management system, but also for other studies, including nitrogen use efficiency.

Transcriptome analysis reveals multiple effects of nitrogen accumulation and metabolism in the roots, shoots, and leaves of potato (Solanum tuberosum L.)

BACKGROUND

Nitrogen (N) is a major element and fundamental constituent of grain yield. N fertilizer plays an essential role in the roots, shoots, and leaves of crop plants. Here, we obtained two N-sensitive potato cultivars.

RESULTS

The plants were cultivated in the pots using N-deficient and N-sufficient conditions. Crop height, leaf chlorophyll content, dry matter, and N-accumulation significantly decreased under N-deficient conditions. Furthermore, we performed a comprehensive analysis of the phenotype and transcriptome, GO terms, and KEGG pathways. We used WGCNA of co-expressed genes, and 116 differentially expressed hub genes involved in photosynthesis, nitrogen metabolism, and secondary metabolites to generate 23 modules. Among those modules, six NRT gene families, four pigment genes, two auxin-related genes, and two energy-related genes were selected for qRT-PCR validation.

CONCLUSIONS

Overall, our study demonstrates the co-expressed genes and potential pathways associated with N transport and accumulation in potato cultivars' roots, shoots, and leaves under N-deficient conditions. Therefore, this study provides new ideas to conduct further research on improving nitrogen use efficiency in potatoes.

Germplasm, Breeding, and Genomics in Potato Improvement of Biotic and Abiotic Stresses Tolerance

Potato is one of the most important food crops in the world. Late blight, viruses, soil and tuber-borne diseases, insect-pests mainly aphids, whiteflies, and potato tuber moths are the major biotic stresses affecting potato production. Potato is an irrigated and highly fertilizer-responsive crop, and therefore, heat, drought, and nutrient stresses are the key abiotic stresses. The genus Solanum is a reservoir of genetic diversity, however, a little fraction of total diversity has been utilized in potato breeding. The conventional breeding has contributed significantly to the development of potato varieties. In recent years, a tremendous progress has been achieved in the sequencing technologies from short-reads to long-reads sequence data, genomes of Solanum species (i.e., pan-genomics), bioinformatics and multi-omics platforms such as genomics, transcriptomics, proteomics, metabolomics, ionomics, and phenomics. As such, genome editing has been extensively explored as a next-generation breeding tool. With the available high-throughput genotyping facilities and tetraploid allele calling softwares, genomic selection would be a reality in potato in the near future. This mini-review covers an update on germplasm, breeding, and genomics in potato improvement for biotic and abiotic stress tolerance.

Genome-based prediction of agronomic traits in spring wheat under conventional and organic management systems

Using phenotype data of three spring wheat populations evaluated at 6-15 environments under two management systems, we found moderate to very high prediction accuracies across seven traits. The phenotype data collected under an organic management system effectively predicted the performance of lines in the conventional management and vice versa. There is growing interest in developing wheat cultivars specifically for organic agriculture, but we are not aware of the effect of organic management on the predictive ability of genomic selection (GS). Here, we evaluated within populations prediction accuracies of four GS models, four combinations of training and testing sets, three reaction norm models, and three random cross-validations (CV) schemes in three populations phenotyped under organic and conventional management systems. Our study was based on a total of 578 recombinant inbred lines and varieties from three spring wheat populations, which were evaluated for seven traits at 3-9 conventionally and 3-6 organically managed field environments and genotyped either with the wheat 90 K SNP array or DArTseq. We predicted the management systems (CV0_M) or environments (CV0), a subset of lines that have been evaluated in either management (CV2_M) or some environments (CV2), and the performance of newly developed lines in either management (CV1_M) or environments (CV1). The average prediction accuracies of the model that incorporated genotype × environment interactions with CV0 and CV2 schemes varied from 0.69 to 0.97. In the CV1 and CV1M schemes, prediction accuracies ranged from - 0.12 to 0.77 depending on the reaction norm models, the traits, and populations. In most cases, grain protein showed the highest prediction accuracies. The phenotype data collected under the organic management effectively predicted the performance of lines under conventional management and vice versa. This is the first comprehensive GS study that investigated the effect of the organic management system in wheat.

Physical mapping of QTL associated with agronomic and end-use quality traits in spring wheat under conventional and organic management systems

Using phenotypic data of four biparental spring wheat populations evaluated at multiple environments under two management systems, we discovered 152 QTL and 22 QTL hotspots, of which two QTL accounted for up to 37% and 58% of the phenotypic variance, consistently detected in all environments, and fell within genomic regions harboring known genes. Identification of the physical positions of quantitative trait loci (QTL) would be highly useful for developing functional markers and comparing QTL results across multiple independent studies. The objectives of the present study were to map and characterize QTL associated with nine agronomic and end-use quality traits (tillering ability, plant height, lodging, grain yield, grain protein content, thousand kernel weight, test weight, sedimentation volume, and falling number) in hard red spring wheat recombinant inbred lines (RILs) using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. We evaluated a total of 698 RILs from four populations derived from crosses involving seven parents at 3-8 conventionally (high N) and organically (low N) managed field environments. Using the phenotypic data combined across all environments per management, and the physical map between 1058 and 6526 markers per population, we identified 152 QTL associated with the nine traits, of which 29 had moderate and 2 with major effects. Forty-nine of the 152 QTL mapped across 22 QTL hotspot regions with each region coincident to 2-6 traits. Some of the QTL hotspots were physically located close to known genes. QSv.dms-1A and QPht.dms-4B.1 individually explained up to 37% and 58% of the variation in sedimentation volume and plant height, respectively, and had very large LOD scores that varied from 19.0 to 35.7 and from 16.7 to 55.9, respectively. We consistently detected both QTL in the combined and all individual environments, laying solid ground for further characterization and possibly for cloning.

Genome-wide identification, structural and gene expression analysis of the nitrate transporters (NRTs) family in potato (Solanum tuberosum L.)

Nitrogen (N2) is the most important source of mineral N for plant growth, which was mainly transported by nitrate transporters (NRTs). However, little is known about the NRT gene family in potato. In this study, StNRT gene family members were identified in potato. In addition, we performed StNRT subfamily classification, gene structure and distribution analysis, and conserved domain prediction using various bioinformatics tools. Totally, 39 StNRT gene members were identified in potato genome, including 33, 4 and 2 member belong to NRT1, NRT2, and NRT3, respectively. These 39 StNRT genes were randomly distributed on all chromosomes. The collinearity results show that StNRT members in potato are closely related to Solanum lycopersicum and Solanum melongena. For the expression, different members of StNRT play different roles in leaves and roots. Especially under sufficient nitrogen conditions, different members have a clear distribution in different tissues. These results provide valuable information for identifying the members of the StNRT family in potato and could provide functional characterization of StNRT genes in further research.

Transcriptome sequencing of wild soybean revealed gene expression dynamics under low nitrogen stress

Nitrogen is one of the essential elements for plant growth. Wild soybeans (Glycine soja) have strong abilities to survive in harsh and barren environments, and hence become ideal plant model for studying plant adaptability to low nitrogen (LN) conditions. In this study, we analyzed and compared the transcriptomes of wild soybean subjected to LN treatments. We totally identified 1095 (681 up and 414 down) and 5490 (2998 up and 2492 down) differentially expressed genes (DEGs) in the aerial parts (leaf and stem, LS) and roots, respectively. Gene ontology classification analysis revealed that the categories related to LN stress (including oxidation reduction, transcriptional regulation, membrane, and protein phosphorylation) were highly enriched among DEGs. In addition, a total of 784 transcription factor (TF) and 84 transporter protein (TP) genes were determined in LS DEGs, of which some TF genes (NAC1, NAC35, ZFP1, CIM1, and WRKY25) and TP genes like NRT2.5 (nitrate transporter) and ABCC12 (ABC transporter) were widely upregulated under LN stress. Nevertheless, a total of 3859 TF and 370 TP genes were identified in root DEGs, of which some TF genes (NAC6, NAC14, MYB29, MYB92, bZIP62, bZIP72, WRKY60, WRKY58) and TP genes like NRT2.4 and HAK5 (potassium transporter) were upregulated under LN stress. These findings suggest that the identified DEGs may play vital roles in plant responses to LN stress, providing important genetic resources for further functional dissection of plant molecular mechanisms to LN stress.

Physical Mapping of QTL in Four Spring Wheat Populations under Conventional and Organic Management Systems. I. Earliness

In previous studies, we reported quantitative trait loci (QTL) associated with the heading, flowering, and maturity time in four hard red spring wheat recombinant inbred line (RIL) populations but the results are scattered in population-specific genetic maps, which is challenging to exploit efficiently in breeding. Here, we mapped and characterized QTL associated with these three earliness traits using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. Our data consisted of (i) 6526 single nucleotide polymorphisms (SNPs) and two traits evaluated at five conventionally managed environments in the 'Cutler' × 'AC Barrie' population; (ii) 3158 SNPs and two traits evaluated across three organic and seven conventional managements in the 'Attila' × 'CDC Go' population; (iii) 5731 SilicoDArT and SNP markers and the three traits evaluated at four conventional and organic management systems in the 'Peace' × 'Carberry' population; and (iv) 1058 SNPs and two traits evaluated across two conventionally and organically managed environments in the 'Peace' × 'CDC Stanley' population. Using composite interval mapping, the phenotypic data across all environments, and the IWGSC RefSeq v2.0 physical maps, we identified a total of 44 QTL associated with days to heading (11), flowering (10), and maturity (23). Fifteen of the 44 QTL were common to both conventional and organic management systems, and the remaining QTL were specific to either the conventional (21) or organic (8) management systems. Some QTL harbor known genes, including the Vrn-A1, Vrn-B1, Rht-A1, and Rht-B1 that regulate photoperiodism, flowering time, and plant height in wheat, which lays a solid basis for cloning and further characterization.

A comparison of shared patterns of differential gene expression and gene ontologies in response to water-stress in roots and leaves of four diverse genotypes of Lolium and Festuca spp. temperate pasture grasses

Ryegrasses (Lolium spp.) and fescues (Festuca spp.) are closely related and widely cultivated perennial forage grasses. As such, resilience in the face of abiotic stresses is an important component of their traits. We have compared patterns of differentially expressed genes (DEGs) in roots and leaves of two perennial ryegrass genotypes and a single genotype of each of a festulolium (predominantly Italian ryegrass) and meadow fescue with the onset of water stress, focussing on overall patterns of DEGs and gene ontology terms (GOs) shared by all four genotypes. Plants were established in a growing medium of vermiculite watered with nutrient solution. Leaf and root material were sampled at 35% (saturation) and, as the medium dried, at 15%, 5% and 1% estimated water contents (EWCs) and RNA extracted. Differential gene expression was evaluated comparing the EWC sampling points from RNAseq data using a combination of analysis methods. For all genotypes, the greatest numbers of DEGs were identified in the 35/1 and 5/1 comparisons in both leaves and roots. In total, 566 leaf and 643 root DEGs were common to all 4 genotypes, though a third of these leaf DEGs were not regulated in the same up/down direction in all 4 genotypes. For roots, the equivalent figure was 1% of the DEGs. GO terms shared by all four genotypes were often enriched by both up- and down-regulated DEGs in the leaf, whereas generally, only by either up- or down-regulated DEGs in the root. Overall, up-regulated leaf DEGs tended to be more genotype-specific than down-regulated leaf DEGs or root DEGs and were also associated with fewer GOs. On average, only 5–15% of the DEGs enriching common GO terms were shared by all 4 genotypes, suggesting considerable variation in DEGs between related genotypes in enacting similar biological processes.

Targeting Nitrogen Metabolism and Transport Processes to Improve Plant Nitrogen Use Efficiency

In agricultural cropping systems, relatively large amounts of nitrogen (N) are applied for plant growth and development, and to achieve high yields. However, with increasing N application, plant N use efficiency generally decreases, which results in losses of N into the environment and subsequently detrimental consequences for both ecosystems and human health. A strategy for reducing N input and environmental losses while maintaining or increasing plant performance is the development of crops that effectively obtain, distribute, and utilize the available N. Generally, N is acquired from the soil in the inorganic forms of nitrate or ammonium and assimilated in roots or leaves as amino acids. The amino acids may be used within the source organs, but they are also the principal N compounds transported from source to sink in support of metabolism and growth. N uptake, synthesis of amino acids, and their partitioning within sources and toward sinks, as well as N utilization within sinks represent potential bottlenecks in the effective use of N for vegetative and reproductive growth. This review addresses recent discoveries in N metabolism and transport and their relevance for improving N use efficiency under high and low N conditions.

Physiological and Transcriptomic Responses to Nitrogen Deficiency in Neolamarckia cadamba

Nitrogen (N) is one of the abundant and essential elements for plant growth and development, and N deficiency (ND) affects plants at both physiological and transcriptomic levels. Neolamarckia cadamba is a fast-growing woody plant from the Rubiaceae family. However, the physiological and molecular impacts of ND on this species have not been well investigated. Here, we studied how N. cadamba responds to ND under hydroponic conditions. In a physiological aspect, ND led to a reduction in biomass, chlorophyll content, and photosynthetic capacity. ND also impaired the assimilation of N as the activities of glutamine synthetase (GS) and nitrate reductase (NR) were decreased in the root. Interestingly, the lignin content of stem increased progressively during the ND stress. The main transcription factors, the transcription factors that are important to N regulation has been found to be upregulated, including Nodule inception-like protein 7 (NLP7), TGACG motif-binding factor 1 (TGA1), basic helix-loop-helix protein 45 (BHLH45), NAM, ATAF1,2, CUC2 (NAC) transcription factor 43 (NAC43), and basic leucine zipper pattern 44 (bZIP44). The expression of N transporters, such as nitrate transporter 2.4 (NRT2.4), ammonium transporter 3 (AMT3), and amino acid transporter protein 3 (AAP3), was also upregulated. In addition, phosphorus- and calcium-related genes such as phosphate starvation response 2 (PHR2) and cyclic nucleotide-gated ion channel 15 (CNGC15) were expressed more abundantly in response to ND stress. Our results reveal the physiological and molecular mechanisms by which woody plants respond to ND.

Genome-wide identification, structural and gene expression analysis of the nitrate transporters (NRTs) family in potato (Solanum tuberosum L.)

Nitrogen (N2) is the most important source of mineral N for plant growth, which was mainly transported by nitrate transporters (NRTs). However, little is known about the NRT gene family in potato. In this study, StNRT gene family members were identified in potato. In addition, we performed StNRT subfamily classification, gene structure and distribution analysis, and conserved domain prediction using various bioinformatics tools. Totally, 39 StNRT gene members were identified in potato genome, including 33, 4 and 2 member belong to NRT1, NRT2, and NRT3, respectively. These 39 StNRT genes were randomly distributed on all chromosomes. The collinearity results show that StNRT members in potato are closely related to Solanum lycopersicum and Solanum melongena. For the expression, different members of StNRT play different roles in leaves and roots. Especially under sufficient nitrogen conditions, different members have a clear distribution in different tissues. These results provide valuable information for identifying the members of the StNRT family in potato and could provide functional characterization of StNRT genes in further research.