Analysis of Gene Regulatory Networks of Maize in Response to Nitrogen

GWAS and Meta-QTL Analysis of Yield-Related Ear Traits in Maize

Maize ear traits are an important component of yield, and the genetic basis of ear traits facilitates further yield improvement. In this study, a panel of 580 maize inbred lines were used as the study material, eight ear-related traits were measured through three years of planting, and whole genome sequencing was performed using the maize 40 K breeding chip based on genotyping by targeted sequencing (GBTS) technology. Five models were used to conduct a genome-wide association study (GWAS) on best linear unbiased estimate (BLUE) of ear traits to find the best model. The FarmCPU (Fixed and random model Circulating Probability Unification) model was the best model for this study; a total of 104 significant single nucleotide polymorphisms (SNPs) were detected, and 10 co-location SNPs were detected simultaneously in more than two environments. Through gene function annotation and prediction, a total of nine genes were identified as potentially associated with ear traits. Moreover, a total of 760 quantitative trait loci (QTL) associated with yield-related traits reported in 37 different articles were collected. Using the collected 760 QTL for meta-QTL analysis, a total of 41 MQTL (meta-QTL) associated with yield-related traits were identified, and 19 MQTL detected yield-related ear trait functional genes and candidate genes that have been reported in maize. Five significant SNPs detected by GWAS were located within these MQTL intervals, and another three significant SNPs were close to MQTL (less than 1 Mb). The results provide a theoretical reference for the analysis of the genetic basis of ear-related traits and the improvement of maize yield.

Single-cell transcriptome analyses reveal cellular and molecular responses to low nitrogen in burley tobacco leaves

Tobacco (Nicotiana tabacum) is cultivated and consumed worldwide. It requires great amounts of nitrogen (N) to achieve the best yield and quality. With a view to sustainable and environmentally friendly agriculture, developing new genotypes with high productivity under low N conditions is an important approach. It is unclear how genes in tobacco are expressed at the cellular level and the precise mechanisms by which cells respond to environmental stress, especially in the case of low N. Here, we characterized the transcriptomes in tobacco leaves grown in normal and low-N conditions by performing scRNA-seq. We identified 10 cell types with 17 transcriptionally distinct cell clusters with the assistance of marker genes and constructed the first single-cell atlas of tobacco leaves. Distinct gene expression patterns of cell clusters were observed under low-N conditions, and the mesophyll cells were the most important responsive cell type and displayed heterogene responses among its three subtypes. Pseudo-time trajectory analysis revealed low-N stress decelerates the differentiation towards mesophyll cells. In combination with scRNA-seq, WGCNA, and bulk RNA-seq results, we found that genes involved in porphyrin metabolism, nitrogen metabolism, carbon fixation, photosynthesis, and photosynthesis-antenna pathway play an essential role in response to low N. Moreover, we identified COL16, GATA24, MYB73, and GLK1 as key TFs in the regulation of N-responsive genes. Collectively, our findings are the first observation of the cellular and molecular responses of tobacco leaves under low N stress and lay the cornerstone for future tobacco scRNA-seq investigations.

Weighted gene co-expression network analysis of nitrogen (N)-responsive genes and the putative role of G-quadruplexes in N use efficiency (NUE) in rice

Rice is an important target to improve crop nitrogen (N) use efficiency (NUE), and the identification and shortlisting of the candidate genes are still in progress. We analyzed data from 16 published N-responsive transcriptomes/microarrays to identify, eight datasets that contained the maximum number of 3020 common genes, referred to as N-responsive genes. These include different classes of transcription factors, transporters, miRNA targets, kinases and events of post-translational modifications. A Weighted gene co-expression network analysis (WGCNA) with all the 3020 N-responsive genes revealed 15 co-expression modules and their annotated biological roles. Protein-protein interaction network analysis of the main module revealed the hub genes and their functional annotation revealed their involvement in the ubiquitin process. Further, the occurrences of G-quadruplex sequences were examined, which are known to play important roles in epigenetic regulation but are hitherto unknown in N-response/NUE. Out of the 3020 N-responsive genes studied, 2298 contained G-quadruplex sequences. We compared these N-responsive genes containing G-quadruplex sequences with the 3601 genes we previously identified as NUE-related (for being both N-responsive and yield-associated). This analysis revealed 389 (17%) NUE-related genes containing G-quadruplex sequences. These genes may be involved in the epigenetic regulation of NUE, while the rest of the 83% (1811) genes may regulate NUE through genetic mechanisms and/or other epigenetic means besides G-quadruplexes. A few potentially important genes/processes identified as associated with NUE were experimentally validated in a pair of rice genotypes contrasting for NUE. The results from the WGCNA and G4 sequence analysis of N-responsive genes helped identify and shortlist six genes as candidates to improve NUE. Further, the hitherto unavailable segregation of genetic and epigenetic gene targets could aid in informed interventions through genetic and epigenetic means of crop improvement.

Exploring the Potential of Heterosis to Improve Nitrogen Use Efficiency in Popcorn Plants

Nitrogen is crucial for plant growth and development, and improving nitrogen use efficiency (NUE) is a viable strategy for reducing dependence on nitrogen inputs and promoting sustainability. While the benefits of heterosis in corn are well known, the physiological mechanisms underlying this phenomenon in popcorn are less understood. We aimed to investigate the effects of heterosis on growth and physiological traits in four popcorn lines and their hybrids under two contrasting nitrogen conditions. We evaluated morpho-agronomic and physiological traits such as leaf pigments, the maximum photochemical efficiency of PSII, and leaf gas exchange. Components associated with NUE were also evaluated. N deprivation caused reductions of up to 65% in terms of plant architecture, 37% in terms of leaf pigments, and 42% in terms of photosynthesis-related traits. Heterosis had significant effects on growth traits, NUE, and foliar pigments, particularly under low soil nitrogen conditions. N-utilization efficiency was found to be the mechanism favoring superior hybrid performance for NUE. Non-additive genetic effects were predominant in controlling the studied traits, indicating that exploring heterosis is the most effective strategy for obtaining superior hybrids to promote NUE. The findings are relevant and beneficial for agro farmers seeking sustainable agricultural practices and improved crop productivity through the optimization of nitrogen utilization.

Insights on Phytohormonal Crosstalk in Plant Response to Nitrogen Stress: A Focus on Plant Root Growth and Development

Nitrogen (N) is a vital mineral component that can restrict the growth and development of plants if supplied inappropriately. In order to benefit their growth and development, plants have complex physiological and structural responses to changes in their nitrogen supply. As higher plants have multiple organs with varying functions and nutritional requirements, they coordinate their responses at the whole-plant level based on local and long-distance signaling pathways. It has been suggested that phytohormones are signaling substances in such pathways. The nitrogen signaling pathway is closely associated with phytohormones such as auxin (AUX), abscisic acid (ABA), cytokinins (CKs), ethylene (ETH), brassinosteroid (BR), strigolactones (SLs), jasmonic acid (JA), and salicylic acid (SA). Recent research has shed light on how nitrogen and phytohormones interact to modulate physiology and morphology. This review provides a summary of the research on how phytohormone signaling affects root system architecture (RSA) in response to nitrogen availability. Overall, this review contributes to identifying recent developments in the interaction between phytohormones and N, as well as serving as a foundation for further study.

Nitrogen-dependent binding of the transcription factor PBF1 contributes to the balance of protein and carbohydrate storage in maize endosperm

Fluctuations in nitrogen (N) availability influence protein and starch levels in maize (Zea mays) seeds, yet the underlying mechanism is not well understood. Here, we report that N limitation impacted the expression of many key genes in N and carbon (C) metabolism in the developing endosperm of maize. Notably, the promoter regions of those genes were enriched for P-box sequences, the binding motif of the transcription factor prolamin-box binding factor 1 (PBF1). Loss of PBF1 altered accumulation of starch and proteins in endosperm. Under different N conditions, PBF1 protein levels remained stable but PBF1 bound different sets of target genes, especially genes related to the biosynthesis and accumulation of N and C storage products. Upon N-starvation, the absence of PBF1 from the promoters of some zein genes coincided with their reduced expression, suggesting that PBF1 promotes zein accumulation in the endosperm. In addition, PBF1 repressed the expression of sugary1 (Su1) and starch branching enzyme 2b (Sbe2b) under normal N supply, suggesting that, under N-deficiency, PBF1 redirects the flow of C skeletons for zein toward the formation of C compounds. Overall, our study demonstrates that PBF1 modulates C and N metabolism during endosperm development in an N-dependent manner.

K. S, Vadivel R, T. K. D, Raj R, Pooniya V, Babu S, Rathore SS, L. M, Tiwari G. Nitrogen use efficiency-a key to enhance crop productivity under a changing climate

Nitrogen (N) is an essential element required for the growth and development of all plants. On a global scale, N is agriculture's most widely used fertilizer nutrient. Studies have shown that crops use only 50% of the applied N effectively, while the rest is lost through various pathways to the surrounding environment. Furthermore, lost N negatively impacts the farmer's return on investment and pollutes the water, soil, and air. Therefore, enhancing nitrogen use efficiency (NUE) is critical in crop improvement programs and agronomic management systems. The major processes responsible for low N use are the volatilization, surface runoff, leaching, and denitrification of N. Improving NUE through agronomic management practices and high-throughput technologies would reduce the need for intensive N application and minimize the negative impact of N on the environment. The harmonization of agronomic, genetic, and biotechnological tools will improve the efficiency of N assimilation in crops and align agricultural systems with global needs to protect environmental functions and resources. Therefore, this review summarizes the literature on nitrogen loss, factors affecting NUE, and agronomic and genetic approaches for improving NUE in various crops and proposes a pathway to bring together agronomic and environmental needs.

THP9 enhances seed protein content and nitrogen-use efficiency in maize

Teosinte, the wild ancestor of maize (Zea mays subsp. mays), has three times the seed protein content of most modern inbreds and hybrids, but the mechanisms that are responsible for this trait are unknown^1,2. Here we use trio binning to create a contiguous haplotype DNA sequence of a teosinte (Zea mays subsp. parviglumis) and, through map-based cloning, identify a major high-protein quantitative trait locus, TEOSINTE HIGH PROTEIN 9 (THP9), on chromosome 9. THP9 encodes an asparagine synthetase 4 enzyme that is highly expressed in teosinte, but not in the B73 inbred, in which a deletion in the tenth intron of THP9-B73 causes incorrect splicing of THP9-B73 transcripts. Transgenic expression of THP9-teosinte in B73 significantly increased the seed protein content. Introgression of THP9-teosinte into modern maize inbreds and hybrids greatly enhanced the accumulation of free amino acids, especially asparagine, throughout the plant, and increased seed protein content without affecting yield. THP9-teosinte seems to increase nitrogen-use efficiency, which is important for promoting a high yield under low-nitrogen conditions.

Nitrate/ammonium-responsive microRNA-mRNA regulatory networks affect root system architecture in Populus × canescens

BACKGROUND

Nitrate (NO₃^-) and ammonium (NH₄⁺) are the primary forms of inorganic nitrogen (N) taken up by plant roots, and a lack of these N sources commonly limits plant growth. To better understand how NO₃^- and NH₄⁺ differentially affect root system architecture, we analyzed the expression profiles of microRNAs and their targets in poplar roots treated with three forms of nitrogen S1 (NO₃^-), S2 (NH₄NO₃, normal), and S3 (NH₄⁺) via RNA sequencing.

RESULTS

The results revealed a total of 709 miRNAs. Among them, 57 significantly differentially expressed miRNAs and 28 differentially expressed miRNA-target pairs showed correlated expression profiles in S1 vs. S2. Thirty-six significantly differentially expressed miRNAs and 12 differentially expressed miRNA-target pairs showed correlated expression profiles in S3 vs. S2. In particular, NFYA3, a target of upregulated ptc-miR169i and ptc-miR169b, was downregulated in S1 vs. S2, while NFYA1, a target of upregulated ptc-miR169b, was downregulated in S3 vs. S2 and probably played an important role in the changes in root morphology observed when the poplar plants were treated with different N forms. Furthermore, the miRNA-target pairs ptc-miR169i/b-D6PKL2, ptc-miR393a-5p-AFB2, ptc-miR6445a-NAC14, ptc-miR172d-AP2, csi-miR396a-5p_R + 1_1ss21GA-EBP1, ath-miR396b-5p_R + 1-TPR4, and ptc-miR166a/b/c-ATHB-8 probably contributed to the changes in root morphology observed when poplar plants were treated with different N forms.

CONCLUSIONS

These results demonstrate that differentially expressed miRNAs and their targets play an important role in the regulation of the poplar root system architecture by different N forms.

A comprehensive transcription factor and DNA-binding motif resource for the construction of gene regulatory networks in Botrytis cinerea and Trichoderma atroviride

Botrytis cinerea and Trichoderma atroviride are two relevant fungi in agricultural systems. To gain insights into these organisms' transcriptional gene regulatory networks (GRNs), we generated a manually curated transcription factor (TF) dataset for each of them, followed by a GRN inference utilizing available sequence motifs describing DNA-binding specificity and global gene expression data. As a proof of concept of the usefulness of this resource to pinpoint key transcriptional regulators, we employed publicly available transcriptomics data and a newly generated dual RNA-seq dataset to build context-specific Botrytis and Trichoderma GRNs under two different biological paradigms: exposure to continuous light and Botrytis-Trichoderma confrontation assays. Network analysis of fungal responses to constant light revealed striking differences in the transcriptional landscape of both fungi. On the other hand, we found that the confrontation of both microorganisms elicited a distinct set of differentially expressed genes with changes in T. atroviride exceeding those in B. cinerea. Using our regulatory network data, we were able to determine, in both fungi, central TFs involved in this interaction response, including TFs controlling a large set of extracellular peptidases in the biocontrol agent T. atroviride. In summary, our work provides a comprehensive catalog of transcription factors and regulatory interactions for both organisms. This catalog can now serve as a basis for generating novel hypotheses on transcriptional regulatory circuits in different experimental contexts.

Morphological, physiological, and transcriptional responses to low nitrogen stress in Populus deltoides Marsh. clones with contrasting nitrogen use efficiency

Background

Nitrogen (N) is one of the main factors limiting the wood yield in poplar cultivation. Understanding the molecular mechanism of N utilization could play a guiding role in improving the nitrogen use efficiency (NUE) of poplar.

Results

In this study, three N-efficient genotypes (A1-A3) and three N-inefficient genotypes (C1-C3) of Populus deltoides were cultured under low N stress (5 μM NH₄NO₃) and normal N supply (750 μM NH₄NO₃). The dry matter mass, leaf morphology, and chlorophyll content of both genotypes decreased under N starvation. The low nitrogen adaptation coefficients of the leaves and stems biomass of group A were significantly higher than those of group C (p < 0.05). Interestingly, N starvation induced fine root growth in group A, but not in group C. Next, a detailed time-course analysis of enzyme activities and gene expression in leaves identified 2062 specifically differentially expressed genes (DEGs) in group A and 1118 in group C. Moreover, the sensitivity to N starvation of group A was weak, and DEGs related to hormone signal transduction and stimulus response played an important role in the low N response this group. Weighted gene co-expression network analysis identified genes related to membranes, catalytic activity, enzymatic activity, and response to stresses that might be critical for poplar’s adaption to N starvation and these genes participated in the negative regulation of various biological processes. Finally, ten influential hub genes and twelve transcription factors were identified in the response to N starvation. Among them, four hub genes were related to programmed cell death and the defense response, and PodelWRKY18, with high connectivity, was involved in plant signal transduction. The expression of hub genes increased gradually with the extension of low N stress time, and the expression changes in group A were more obvious than those in group C.

Conclusions

Under N starvation, group A showed stronger adaptability and better NUE than group C in terms of morphology and physiology. The discovery of hub genes and transcription factors might provide new information for the analysis of the molecular mechanism of NUE and its improvement in poplar.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07991-7.

Low nitrogen availability inhibits the phosphorus starvation response in maize (Zea mays ssp. mays L.)

BACKGROUND

Nitrogen (N) and phosphorus (P) are macronutrients essential for crop growth and productivity. In cultivated fields, N and P levels are rarely sufficient, contributing to the gap between realized and potential production. Fertilizer application increases nutrient availability, but is not available to all farmers, nor are current rates of application sustainable or environmentally desirable. Transcriptomic studies of cereal crops have revealed dramatic responses to either low N or low P single stress treatments. In the field, however, levels of both N and P may be suboptimal. The interaction between N and P starvation responses remains to be fully characterized.

RESULTS

We characterized growth and root and leaf transcriptomes of young maize plants under nutrient replete, low N, low P or combined low NP conditions. We identified 1555 genes to respond to our nutrient treatments, in one or both tissues. A large group of genes, including many classical P starvation response genes, were regulated antagonistically between low N and P conditions. An additional experiment over a range of N availability indicated that a mild reduction in N levels was sufficient to repress the low P induction of P starvation genes. Although expression of P transporter genes was repressed under low N or low NP, we confirmed earlier reports of P hyper accumulation under N limitation.

CONCLUSIONS

Transcriptional responses to low N or P were distinct, with few genes responding in a similar way to the two single stress treatments. In combined NP stress, the low N response dominated, and the P starvation response was largely suppressed. A mild reduction in N availability was sufficient to repress the induction of P starvation associated genes. We conclude that activation of the transcriptional response to P starvation in maize is contingent on N availability.

Transcriptome Analysis for Fraxinus mandshurica Rupr. Seedlings from Different Carbon Sequestration Provenances in Response to Nitrogen Deficiency

To explore the molecular regulatory mechanism of high-carbon (C) sequestration Fraxinus mandshurica Rupr. (F. mandshurica) provenance and the expression profile of F. mandshurica during nitrogen (N) starvation, the foliage and roots of the annual Wuchang (WC) seedlings with greater C amount and Hailin (HL) seedlings with smaller C amount, which were grown in N-deficient nutrition and complete N, were used for RNA-seq and physiological determination, respectively. One thousand and fifty-seven differentially expressed genes (DEGs) between WC and HL and 8173 DEGs related to N deficiency were identified, respectively. The root of F. mandshurica responded to N deficiency more strongly than foliar. The target genes that responded to N deficiency in roots were mainly regulatory genes (transcription factors, hormones and protein kinases), and their response patterns were upregulated. The growth and N concentration in both WC and HL were reduced by the N deficiency, which might result from the decrease of the leaf Nitrate reductase (NR) and glutamine synthetase (GS) enzyme activity and ABA content, although the root-to-shoot ratio; lateral root number; lignin content; endogenous hormones content (GA, IAA and ZR); root GS and glutamate synthetase activity and transcriptional level of most of the regulatory genes were increased. The C sequestration capacity in WC was greater than that in HL, which related to the higher GS enzymes activity and transcriptional levels of regulatory genes and metabolic genes (terpenes, carbohydrates, and lipid energy). However, the C sequestration advantage of WC was significantly reduced by the N deficiency, which was due to the smaller response to N deficiency compared to HL.

Meta-Analysis of Yield-Related and N-Responsive Genes Reveals Chromosomal Hotspots, Key Processes and Candidate Genes for Nitrogen-Use Efficiency in Rice

Nitrogen-use efficiency (NUE) is a function of N-response and yield that is controlled by many genes and phenotypic parameters that are poorly characterized. This study compiled all known yield-related genes in rice and mined them from the N-responsive microarray data to find 1,064 NUE-related genes. Many of them are novel genes hitherto unreported as related to NUE, including 80 transporters, 235 transcription factors (TFs), 44 MicroRNAs (miRNAs), 91 kinases, and 8 phosphatases. They were further shortlisted to 62 NUE-candidate genes following hierarchical methods, including quantitative trait locus (QTL) co-localization, functional evaluation in the literature, and protein-protein interactions (PPIs). They were localized to chromosomes 1, 3, 5, and 9, of which chromosome 1 with 26 genes emerged as a hotspot for NUE spanning 81% of the chromosomes. Further, co-localization of the NUE genes on NUE-QTLs resolved differences in the earlier studies that relied mainly on N-responsive genes regardless of their role in yield. Functional annotations and PPIs for all the 1,064 NUE-related genes and also the shortlisted 62 candidates revealed transcription, redox, phosphorylation, transport, development, metabolism, photosynthesis, water deprivation, and hormonal and stomatal function among the prominent processes. In silico expression analysis confirmed differential expression of the 62 NUE-candidate genes in a tissue/stage-specific manner. Experimental validation in two contrasting genotypes revealed that high NUE rice shows better photosynthetic performance, transpiration efficiency and internal water-use efficiency in comparison to low NUE rice. Feature Selection Analysis independently identified one-third of the common genes at every stage of hierarchical shortlisting, offering 6 priority targets to validate for improving the crop NUE.

Physiological characteristics and RNA sequencing in two root zones with contrasting nitrate assimilation of Populus × canescens

Different root zones have distinct capacities for nitrate (NO3-) uptake in Populus species, but the underlying physiological and microRNA (miRNA) regulatory mechanisms remain largely unknown. To address this question, two root zones of Populus × canescens (Ait.) Smith. with contrasting capacities for NO3- uptake were investigated. The region of 0-40 mm (root zone I) to the root apex displayed net influxes, whereas the region of 40-80 mm (root zone II) exhibited net effluxes. Concentrations of NO3- and ammonium (NH4+) as well as nitrate reductase activity were lower in zone II than in zone I. Forty one upregulated and twenty three downregulated miRNAs, and 576 targets of these miRNAs were identified in zone II in comparison with zone I. Particularly, growth-regulating factor 4 (GRF4), a target of upregulated ptc-miR396g-5p and ptc-miR396f_L + 1R-1, was downregulated in zone II in comparison with zone I, probably contributing to lower NO3- uptake rates and assimilation in zone II. Furthermore, several miRNAs and their targets, members of C2H2 zinc finger family and APETALA2/ethylene-responsive element binding protein family, were found in root zones, which probably play important roles in regulating NO3- uptake. These results indicate that differentially expressed miRNA-target pairs play key roles in regulation of distinct NO3- uptake rates and assimilation in different root zones of poplars.

Genome-Wide Association Study and Identification of Candidate Genes for Nitrogen Use Efficiency in Barley (Hordeum vulgare L.)

Nitrogen (N) fertilizer is largely responsible for barley grain yield potential and quality, yet excessive application leads to environmental pollution and high production costs. Therefore, efficient use of N is fundamental for sustainable agriculture. In the present study, we investigated the performance of 282 barley accessions through hydroponic screening using optimal and low NH4NO3 treatments. Low-N treatment led to an average shoot dry weight reduction of 50%, but there were significant genotypic differences among the accessions. Approximately 20% of the genotypes showed high (>75%) relative shoot dry weight under low-N treatment and were classified as low-N tolerant, whereas 20% were low-N sensitive (≤55%). Low-N tolerant accessions exhibited well-developed root systems with an average increase of 60% in relative root dry weight to facilitate more N absorption. A genome-wide association study (GWAS) identified 66 significant marker trait associations (MTAs) conferring high nitrogen use efficiency, four of which were stable across experiments. These four MTAs were located on chromosomes 1H(1), 3H(1), and 7H(2) and were associated with relative shoot length, relative shoot and root dry weight. Genes corresponding to the significant MTAs were retrieved as candidate genes, including members of the asparagine synthetase gene family, several transcription factor families, protein kinases, and nitrate transporters. Most importantly, the high-affinity nitrate transporter 2.7 (HvNRT2.7) was identified as a promising candidate on 7H for root and shoot dry weight. The identified candidate genes provide new insights into our understanding of the molecular mechanisms driving nitrogen use efficiency in barley and represent potential targets for genetic improvement.

Transcriptome analysis of potato shoots, roots and stolons under nitrogen stress

Potato crop requires high dose of nitrogen (N) to produce high tuber yield. Excessive application of N causes environmental pollution and increases cost of production. Hence, knowledge about genes and regulatory elements is essential to strengthen research on N metabolism in this crop. In this study, we analysed transcriptomes (RNA-seq) in potato tissues (shoot, root and stolon) collected from plants grown in aeroponic culture under controlled conditions with varied N supplies i.e. low N (0.2 milli molar N) and high N (4 milli molar N). High quality data ranging between 3.25 to 4.93 Gb per sample were generated using Illumina NextSeq500 that resulted in 83.60-86.50% mapping of the reads to the reference potato genome. Differentially expressed genes (DEGs) were observed in the tissues based on statistically significance (p ≤ 0.05) and up-regulation with ≥ 2 log2 fold change (FC) and down-regulation with ≤ -2 log2 FC values. In shoots, of total 19730 DEGs, 761 up-regulated and 280 down-regulated significant DEGs were identified. Of total 20736 DEGs in roots, 572 (up-regulated) and 292 (down-regulated) were significant DEGs. In stolons, of total 21494 DEG, 688 and 230 DEGs were significantly up-regulated and down-regulated, respectively. Venn diagram analysis showed tissue specific and common genes. The DEGs were functionally assigned with the GO terms, in which molecular function domain was predominant in all the tissues. Further, DEGs were classified into 24 KEGG pathways, in which 5385, 5572 and 5594 DEGs were annotated in shoots, roots and stolons, respectively. The RT-qPCR analysis validated gene expression of RNA-seq data for selected genes. We identified a few potential DEGs responsive to N deficiency in potato such as glutaredoxin, Myb-like DNA-binding protein, WRKY transcription factor 16 and FLOWERING LOCUS T in shoots; high-affinity nitrate transporter, protein phosphatase-2c, glutaredoxin family protein, malate synthase, CLE7, 2-oxoglutarate-dependent dioxygenase and transcription factor in roots; and glucose-6-phosphate/phosphate translocator 2, BTB/POZ domain-containing protein, F-box family protein and aquaporin TIP1;3 in stolons, and many genes of unknown function. Our study highlights that these potential genes play very crucial roles in N stress tolerance, which could be useful in augmenting research on N metabolism in potato.

Nitrogen Starvation Differentially Influences Transcriptional and Uptake Rate Profiles in Roots of Two Maize Inbred Lines with Different NUE

Nitrogen use efficiency (NUE) of crops is estimated to be less than 50%, with a strong impact on environment and economy. Genotype-dependent ability to cope with N shortage has been only partially explored in maize and, in this context, the comparison of molecular responses of lines with different NUE is of particular interest in order to dissect the key elements underlying NUE. Changes in root transcriptome and NH₄⁺/NO₃^- uptake rates during growth (after 1 and 4 days) without N were studied in high (Lo5) and low (T250) NUE maize inbred lines. Results suggests that only a small set of transcripts were commonly modulated in both lines in response to N starvation. However, in both lines, transcripts linked to anthocyanin biosynthesis and lateral root formation were positively affected. On the contrary, those involved in root elongation were downregulated. The main differences between the two lines reside in the ability to modulate the transcripts involved in the transport, distribution and assimilation of mineral nutrients. With regard to N mineral forms, only the Lo5 line responded to N starvation by increasing the NH₄⁺ fluxes as supported by the upregulation of a transcript putatively involved in its transport.

Plant Networks as Traits and Hypotheses: Moving Beyond Description

Biology relies on the central thesis that the genes in an organism encode molecular mechanisms that combine with stimuli and raw materials from the environment to create a final phenotypic expression representative of the genomic programming. While conceptually simple, the genotype-to-phenotype linkage in a eukaryotic organism relies on the interactions of thousands of genes and an environment with a potentially unknowable level of complexity. Modern biology has moved to the use of networks in systems biology to try to simplify this complexity to decode how an organism's genome works. Previously, biological networks were basic ways to organize, simplify, and analyze data. However, recent advances are allowing networks to move beyond description and become phenotypes or hypotheses in their own right. This review discusses these efforts, like mapping responses across biological scales, including relationships among cellular entities, and the direct use of networks as traits or hypotheses.

The Use of Nitrogen and Its Regulation in Cereals: Structural Genes, Transcription Factors, and the Role of miRNAs

Cereals and, especially, rice, maize, and wheat, are essential commodities, on which human nutrition is based. Expanding population and food demand have required higher production which has been achieved by increasing fertilization, and especially nitrogen supply to cereal crops. In fact, nitrogen is a crucial nutrient for the plant, but excessive use poses serious environmental and health issues. Therefore, increasing nitrogen use efficiency in cereals is of pivotal importance for sustainable agriculture. The main steps in the use of nitrogen are uptake and transport, reduction and assimilation, and translocation and remobilization. Many studies have been carried out on the genes involved in these phases, and on transcription factors regulating these genes. Lately, increasing attention has been paid to miRNAs responding to abiotic stress, including nutrient deficiency. Many miRNAs have been found to regulate transcription factors acting on the expression of specific genes for nitrogen uptake or remobilization. Recent studies on gene regulatory networks have also demonstrated that miRNAs can interact with several nodes in the network, functioning as key regulators in nitrogen metabolism.

Functional Research on Three Presumed Asparagine Synthetase Family Members in Poplar

Asparagine synthetase (AS), a key enzyme in plant nitrogen metabolism, plays an important role in plant nitrogen assimilation and distribution. Asparagine (Asn), the product of asparagine synthetase, is one of the main compounds responsible for organic nitrogen transport and storage in plants. In this study, we performed complementation experiments using an Asn-deficient Escherichia coli strain to demonstrate that three putative asparagine synthetase family members in poplar (Populussimonii× P.nigra) function in Asn synthesis. Quantitative real-time PCR revealed that the three members had high expression levels in different tissues of poplar and were regulated by exogenous nitrogen. PnAS1 and PnAS2 were also affected by diurnal rhythm. Long-term dark treatment resulted in a significant increase in PnAS1 and PnAS3 expression levels. Under long-term light conditions, however, PnAS2 expression decreased significantly in the intermediate region of leaves. Exogenous application of ammonium nitrogen, glutamine, and a glutamine synthetase inhibitor revealed that PnAS3 was more sensitive to exogenous glutamine, while PnAS1 and PnAS2 were more susceptible to exogenous ammonium nitrogen. Our results suggest that the various members of the PnAS gene family have distinct roles in different tissues and are regulated in different ways.

Computational prediction of gene regulatory networks in plant growth and development

Plants integrate a wide range of cellular, developmental, and environmental signals to regulate complex patterns of gene expression. Recent advances in genomic technologies enable differential gene expression analysis at a systems level, allowing for improved inference of the network of regulatory interactions between genes. These gene regulatory networks, or GRNs, are used to visualize the causal regulatory relationships between regulators and their downstream target genes. Accordingly, these GRNs can represent spatial, temporal, and/or environmental regulations and can identify functional genes. This review summarizes recent computational approaches applied to different types of gene expression data to infer GRNs in the context of plant growth and development. Three stages of GRN inference are described: first, data collection and analysis based on the dataset type; second, network inference application based on data availability and proposed hypotheses; and third, validation based on in silico, in vivo, and in planta methods. In addition, this review relates data collection strategies to biological questions, organizes inference algorithms based on statistical methods and data types, discusses experimental design considerations, and provides guidelines for GRN inference with an emphasis on the benefits of integrative approaches, especially when a priori information is limited. Finally, this review concludes that computational frameworks integrating large-scale heterogeneous datasets are needed for a more accurate (e.g. fewer false interactions), detailed (e.g. discrimination between direct versus indirect interactions), and comprehensive (e.g. genetic regulation under various conditions and spatial locations) inference of GRNs.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.