High throughput RNA sequencing of a hybrid maize and its parents shows different mechanisms responsive to nitrogen limitation
© Bi et al.; licensee BioMed Central Ltd. 2014
Received: 16 August 2013
Accepted: 25 January 2014
Published: 28 January 2014
Development of crop varieties with high nitrogen use efficiency (NUE) is crucial for minimizing N loss, reducing environmental pollution and decreasing input cost. Maize is one of the most important crops cultivated worldwide and its productivity is closely linked to the amount of fertilizer used. A survey of the transcriptomes of shoot and root tissues of a maize hybrid line and its two parental inbred lines grown under sufficient and limiting N conditions by mRNA-Seq has been conducted to have a better understanding of how different maize genotypes respond to N limitation.
A different set of genes were found to be N-responsive in the three genotypes. Many biological processes important for N metabolism such as the cellular nitrogen compound metabolic process and the cellular amino acid metabolic process were enriched in the N-responsive gene list from the hybrid shoots but not from the parental lines’ shoots. Coupled to this, sugar, carbohydrate, monosaccharide, glucose, and sorbitol transport pathways were all up-regulated in the hybrid, but not in the parents under N limitation. Expression patterns also differed between shoots and roots, such as the up-regulation of the cytokinin degradation pathway in the shoots of the hybrid and down-regulation of that pathway in the roots. The change of gene expression under N limitation in the hybrid resembled the parent with the higher NUE trait. The transcript abundances of alleles derived from each parent were estimated using polymorphic sites in mapped reads in the hybrid. While there were allele abundance differences, there was no correlation between these and the expression differences seen between the hybrid and the two parents.
Gene expression in two parental inbreds and the corresponding hybrid line in response to N limitation was surveyed using the mRNA-Seq technology. The data showed that the three genotypes respond very differently to N-limiting conditions, and the hybrid clearly has a unique expression pattern compared to its parents. Our results expand our current understanding of N responses and will help move us forward towards effective strategies to improve NUE and enhance crop production.
Nitrogen (N) is the most important inorganic nutrient for plant growth. The production of high-yielding crops is associated with the application of large quantities of N fertilizers . The addition of N fertilizer is typically the single highest input cost for many crops and since its production is energy intensive, this cost is dependent on the price of energy . Incorporation of N into agricultural crops, however, rarely exceeds 40% of the applied N, indicating a serious inefficiency in N utilization [3, 4]. The remaining N from fertilizer is lost to the atmosphere or leached to the groundwater and other freshwater bodies, which is causing serious N pollution and becoming a threat to global ecosystems [3, 4]. Therefore, to minimize the loss of N, reduce environmental pollution and decrease input cost, it is crucial to develop crop varieties with high nitrogen use efficiency (NUE) [5, 6].
While improved agricultural practice is one way to increase NUE , it is also crucial to understand more about the genetics of NUE in order to select better varieties. Several studies have presented evidence that natural variation exists in Arabidopsis for nitrogen metabolism, including nitrogen uptake and nitrogen remobilization (reviewed by [8–10]). Genetic differences in N uptake and/or grain yield per unit of N applied have also been reported in different crops including wheat, rice, maize, sorghum, and barley [11–16].
Maize is one of the most important crops cultivated worldwide and a large amount of fertilizer is used for its production. Genetic variation in maize such as in N-remobilization and post-silking N-uptake, nitrogen metabolism, nitrogen management, and senescence have been reported [17–21]. Although some physiological and phenotypic analyses have been done , the molecular knowledge governing genetic variation among different varieties for NUE is poorly understood. In a previous study, we developed a hydroponic growth system and tested two inbred lines and their hybrid that were different in their NUE at maturity under N limitation . One parent, SRG200, showed a higher NUE than the other parent SRG100. Differences between these genetic lines were found after phenotypic, molecular, and metabolic factors were tested at an early vegetative stage and transcriptional analysis on a small number of selected genes involved in N metabolism was conducted . To have a better understanding of how different maize genotypes respond to N limitation, we used whole transcriptome sequencing (mRNA-Seq) to conduct a survey of the transcriptomes of these SRG100, SRG200, and their hybrid under sufficient and limiting N conditions. The primary objectives of this study were to observe the major differences in gene expression among these three lines responding to N limitation, to distinguish the contribution of each parental line to gene expression in the hybrid line, and to discover whether these differences in expression correlate with the differences in the NUE trait studied.
Transcriptomes of the two inbred parental lines and the hybrid line under sufficient and limiting N conditions
Expressed genes in all the samples
% of total paired reads
# genes (FGS) >0 FPKM (% difference under N limitation)
# genes (FGS) >1 FPKM (% difference under N limitation)
# genes (FGS) >5 FPKM (% difference under N limitation)
Identification of differentially expressed genes in leaves and roots of the three genotypes under limiting N conditions
Significantly differentially expressed (DE) genes identified
# Differentially expressed genes (↓ down-regulated, ↑ up-regulated)
Sufficient N vs. Limiting N
688 (525 ↓, 163 ↑)
Sufficient N vs. Limiting N
322 (188 ↓, 134 ↑)
Sufficient N vs. Limiting N
643 (390 ↓, 253 ↑)
Sufficient N vs. Limiting N
675 (438 ↓, 237 ↑)
Sufficient N vs. Limiting N
585 (339 ↓, 246 ↑)
Sufficient N vs. Limiting N
725 (541 ↓, 184 ↑)
In roots, 18, 26, and 23 GO terms were enriched, respectively, among genes up-regulated in response to N limitation for SRG100, SRG200, and SRG150, with some of these enriched in all three genotypes (Additional file 4). Some GO terms were only enriched in the two parents or in SRG200 and SRG150, and other GO terms were enriched only in SRG150, such as anion transport GO:0006820) and ion transport (GO:0006811) (Additional file 4). 20, 45, and 47 GO terms were enriched respectively in the genes down-regulated in response to N limitation for SRG100, SRG200, and SRG150. The terms photosynthesis (GO:0015979); photosynthesis, light harvesting (GO:0009765); photosynthesis, light reaction (GO:0019684) were down-regulated in all three genotypes, although the number of genes enriched in these groups was different, with the hybrid having the smallest number (Additional file 4). Again, some GO terms were enriched in the two parents such as generation of precursor metabolites and energy (GO:0006091), or in SRG200 and SRG150, such as gene expression (GO:0010467) and cellular macromolecule biosynthetic process (GO:0034645) (Additional file 4). Other GO terms were enriched only in SRG150 such as regulation of gene expression (GO:0010468), regulation of primary metabolic process (GO:0080090), and regulation of nitrogen compound metabolic process (GO:0051171) (Additional file 4).
Assessment of additive expression in the hybrid
Expression in the hybrid under different N conditions and GO terms enriched
d/a < −1
0 > d/a > −1
1 > d/a > 0
d/a > 1
Number of genes
GO terms enriched (with BP, MF, CC)
d/a < −1
expression level outside range of SRG100
0 > d/a > −1
expression level skewed towards SRG100
1 > d/a > 0
expression level skewed towards SRG200
d/a > 1
expression level outside range of SRG200
Identification of allelic expression in the hybrid
In root samples both parental alleles had similar probabilities of exhibiting the more highly expressed allele for genes with differential allele expression. However, the GO terms represented from the sets of parental alleles differ significantly (Additional file 10). The details of these genes are listed in Additional file 11. In leaves, the cellular N compound metabolic process (GO:0034641) was enriched for the hybrid regardless of which parental allele was more highly expressed under sufficient N condition, but was only enriched in the hybrid when the SRG200 allele was more highly expressed under the low N condition (Additional file 10). The hexose metabolic process (GO:0019318) and glucose metabolic process (GO:0006006) were enriched in the hybrid when expressing SRG200 alleles more highly than SRG100 alleles under sufficient N condition (Additional file 10). In the roots, the enriched GO terms were quite different from the ones in the shoots although the cellular N compound metabolic process (GO:0034641) was enriched in the hybrid when the allele from either SRG100 or SRG200 was more highly expressed under sufficient N condition, but only enriched in the hybrid when SRG200 alleles were more highly expressed than SRG100 alleles under low N condition, which was similar in the shoots (Additional file 10).
Transcriptome changes under N limitation for the three genotypes shows different mechanisms to deal with N limitation
Efforts have been directed to understand the mechanisms of how plants respond to N limitation. Many approaches have been used, and one of these is transcriptome profiling . Microarray technology has been used in the past for analyzing genome-scale gene expression . Extensive studies have been performed for Arabidopsis thaliana[29–39]. There have also been studies for various crops such as rice seedlings at an early stage of low N stress  and the model legume Medicago truncatula. Recently, Yang et al.  utilized multiple whole-genome microarray experiments to identify gene expression biomarkers in maize, which can be used to monitor nitrogen status. The microarray technology, however, has a few intrinsic limitations. The dynamic range of microarrays is restricted by factors such as the probe density/availability and the intensities of fluorescent dyes, as well as reduced sensitivity by non-specific cross-hybridization which can mask isoform expression and inflate the expression of rare transcripts . One significant advantage of sequence-based transcriptomics is the potential to precisely quantify the abundance of any transcript, drastically increasing the dynamic range of the experiment . Considering the advantages, we did a survey of the maize transcriptome using the mRNA- Seq technique for two parental inbred lines and the corresponding hybrid line, for which a number of phenotypic, molecular, and metabolic factors were previously studied under sufficient and limiting N conditions .
From our results, it is evident that the dynamic changes in the transcriptome for the three genotypes reflect the differences in their response to growth under limiting N. Between the two parents, SRG200 demonstrated a better strategy to deal with N limitation, and the hybrid was superior to the parents . From the DE genes identified and the GO terms enriched, the different responses are noticeable among the three genotypes (Additional files 3 and 4; Figures 1 and 2). In leaf tissues, the hybrid shows an enhancement in the cellular nitrogen compound metabolic process, the cellular amino acid metabolic process, and transport when the plants were under N stress, and these changes were not seen in the parental lines. Although the hybrid showed a reduction in the cellular carbohydrate metabolic process under N limitation, the genes involved in photosynthesis were not over-represented in the down-regulated gene list, which was different from the SRG100 parental line, suggesting that the photosynthesis rate was not down-regulated as much in the hybrid as in the SRG100 parental line (Additional file 3). As C and N metabolism are closely linked and tightly regulated [45, 46], maintaining an adequate photosynthetic rate would certainly favor an efficient production of reduced C and the subsequent efficient use of N. This result correlates well with our physiological tests in a previous study where SRG200 and SRG150 maintained higher sugar content in leaves than SRG100 . In root tissues, both the hybrid and the SRG200 parent significantly increased transport activity, which was not seen in the SRG100 parental line, and the down-regulation of gene expression associated with primary metabolism was very significant in the hybrid (Additional file 4). It has been well documented that root/shoot ratios would increase when plants are grown under N-limiting conditions  and that there is an interaction between nitrogen and cytokinin . Interestingly, the cytokinin degradation pathway was up-regulated in the shoots and down-regulated in the roots under N limitation only in the hybrid (Figures 1 and 2). Less reduction of root biomass in the hybrid under N limitation was observed from our previous study , and the down-regulation of the cytokinin degradation in the hybrid roots under N limitation might be one of the mechanisms for the hybrid to adapt to N limitation. The limited expression data from our previous study suggested that the three genotypes had different mechanism to cope with N stress . The present transcriptome data supports that former observation as the three genotypes presented a different enriched gene set when they had to deal with N stress.
The change in gene expression in the hybrid resembles one parent with a similar NUE trait under N limitation
From our previous study, we learned that the parental line SRG200 had higher NUE than SRG100 and that heterosis was observed in the hybrid SRG150 . In this study, we found that there was a dynamic reprogramming of the transcriptome and the hybrid gene expression levels were significantly more similar to SRG200 levels than SRG100 levels when the hybrid plants were experiencing N limitation (Table 3, Additional files 8 and 9, Figure 3B). This result demonstrated that the transcriptomic similarity mimicked phenotypic similarity.
One possible explanation for the similarity in changes between gene expression levels of one of the parents, SRG200, and the hybrid would be that some alleles derived from that parent control expression of other genes in the hybrid, particularly under the N limiting condition. Across all genes SRG200 alleles were slightly more likely to be up-regulated than SRG100 alleles but the difference was not statistically significant. Expression level is determined by a combination of cis-acting and trans-acting regulatory sequences. Changes in the expression of the latter, which might be allele specific, would lead to changes in expression of a variety of the regulated genes in a non-allele specific manner. Further investigation is needed to understand how plants sense N limitation and change the inventories of the expression of allele-specific genes and how this correlates with the NUE trait in different genotypes.
Gene expression under N limitation in two parental inbreds and the corresponding hybrid line that responded differently to N limitation was surveyed using the mRNA-Seq technology. The data showed that the three genotypes have different mechanisms to deal with N-limiting conditions. Gene expression levels are correlated with the ability of a particular line to respond to growth under limiting N. There was allele-specific expression in the hybrid with a slight bias to the parent that grew better under limiting N. This study enhances our current understanding of the response to growth under N limitation, and the results of this type of study can be used to develop plants with improved NUE.
Plant materials and growth condition
The plant materials and growth conditions were identical to our previous study . Briefly, seeds of the two elite maize inbred lines, SRG100 and SRG200, and the hybrid line, SRG150, created by crossing the two inbred lines, (Syngenta Biotechnology Inc. NC, USA), were germinated in turface for 2 days, and then transplanted to the hydroponic system in nutrient solution containing 4 mM MgSO4, 5 mM KCl, 5 mM CaCl2, 1 mM KH2PO4, 0.1 mM Fe-EDTA, 0.5 mM MES (pH 6.0), 9 μM MnSO4, 0.7 μM ZnSO4, 0.3 μM CuSO4, 46 μM NaB4O7 and 0.2 μM (NH4)6Mo7O2. Seedlings were transferred to a 35 L container containing 25 L of the nutrient solution; the volume and the pH were adjusted weekly by adding fresh nutrient solution and using phosphoric acid to adjust the pH to 5.5. Two different nitrate (KNO3) concentrations were used; one as sufficient N condition (3 mM) and one as limiting N condition (1 mM) . Plants were grown in a growth cabinet (Conviron, Manitoba, Canada) under long day conditions of 16 hr light (~500 μmol m-2 s-1) at 28°C and 8 hr dark at 23°C. Plants were harvested four weeks later. Leaves (3rd to 5th) and the whole roots were collected separately. Plant harvest was carried out at noon for each sample which was pooled from 2–3 plants. The materials were submerged in RNAlater (Ambion Inc., TX, USA) and stored at −80°C until further analysis.
RNA extraction, quality control, normalization, mRNA Seq library construction and Illumina SBS
mRNA was extracted using mirVana™ miRNA isolation kit (Ambion Inc., TX, USA). Using a Bio-Rad Experion system (Hercules, CA, USA), total RNA integrity was measured. An RNA Quality Index (RQI) value greater than 8 was selected as the cut-off value for the total RNA quality control. The RNA samples that passed the QC process were used in the mRNA-Seq library construction. Following the Illumina manual of Preparing Samples for Sequencing of mRNA (Illumina, San Diego, CA, USA), 5 ug of total RNA for each sample were used in the mRNA-Seq library construction. Sera-mag Magnetic Oligo(dT) beads were used to purify the poly-A containing mRNA molecules. Subsequently the purified mRNA was fragmented into small pieces using divalent cations under elevated temperature, and reverse transcribed into cDNA using SuperScript II (Invitrogen, Carlsbad, CA, USA). The cDNA went through an end repair process, the addition of a single ‘A’ base to the 3′ ends, and ligation of the Illumina paired-end sequencing adapters. The ligation products were fragmented on a 2% agarose TAE gel, and the gel slices containing material in the 200 bp (±15 bp) range were excised. cDNA was purified from the gel slices using QIAquick Gel Extraction Kit (QIAGEN, Valencia, CA). Finally, the size-selected cDNA libraries ligated to the Illumina sequencing adaptors were selectively enriched using 15 cycles of PCR, and validated using a Bio-Rad Experion system. Each final cDNA library was then applied on one lane of the Illumina paired-end flow cell for the cluster generation process and subsequently sequenced using the Illumina next-generation sequencing platform GA II as 2 × 36 or 2 × 40 bp paired-end reads.
Sequenced read processing and alignment
Reads were aligned to the B73 reference genome version 2 (maizesequence.org) using Tophat v1.4.1  and Bowtie v0.12.7 . Before alignment, Bowtie quality control removed 0.1-0.2% of the total reads. A minimum intron length of 5 and a maximum intron length of 5000 were used for alignment. Segment lengths were set to half the read lengths and segment mismatches were set to 1. All other parameters were set to default.
Identification of expressed genes
A reference annotation from Ensembl Genomes (zea_mays.AGPv2.62.gtf) was used to guide transcript assembly by Cufflinks v1.3.0  to obtain fragments per kilobase of exon per million fragments mapped (FPKM) for all genes within the WGS. Fragment bias correction , which corrects for sequence-specific bias, and multi-hit read correction, which divides the value of a multi-mapped read between each map location based on a probabilistic model, were used with Cufflinks. Cuffmerge was used to create a single unified assembly from each of the 12 individual Cufflinks assemblies. Cuffmerge maximizes assembly quality by removing transcripts that are artifacts and merging novel isoforms with known isoforms across all Cufflinks assemblies. A transcript was considered to be expressed if its FPKM value was greater than one and if it was part of the maize Filtered Gene Set (FGS) version 5b.60 (maizesequence.org). The FGS is a list of maize genes in which pseudogenes, transposable element encoding genes, and low-confidence hypothetical models have been removed.
Identification of significantly differentially expressed (DE) genes
Cufflinks  was used to perform pairwise comparisons between samples to find differentially expressed transcripts. Fragment bias correction , multi-hit read correction, and upper-quartile normalization , which causes Cufflinks to divide the number of reads mapped to each gene by 75th quartile of the counts instead of dividing by the total number of mapped reads for normalization, were used with Cufflinks. An FGS transcript was differentially expressed between samples if the FPKM in one sample was greater than one and if p-value after correcting for multiple testing with the Benjamini-Hochberg correction was less than 0.05.
In the equation, F1 is the transcript expression level in SRG150, μ is the average gene expression level in the two inbred parents, P1 is the gene expression level in SRG200. If F1 = P1, then d/a = 1 and the gene shows dominant gene action from the SRG200 allele. Genes with d/a values between −1 < d/a < 0 exhibit hybrid expression levels skewed towards SRG100 levels, and genes with d/a values between 0 < d/a < 1 exhibit hybrid expression levels skewed towards SRG200. Genes with d/a values greater than 1.0 or less than −1.0 have hybrid expression levels outside of the parental range. Genes with d/a values of 0 have expression levels in the hybrid that are additive and favor neither parent. The one sample Wilcoxon test  was used on the d/a estimates to determine if hybrid transcript expression across all genes deviated significantly from expected additive parental levels and to determine the overall direction of bias.
Identification of SNPs
Trinity  was used to create de novo transcriptomes for SRG100 and SRG200. The contigs from the de novo transcriptomes were aligned to the B73 reference genome to find common contigs between the two transcriptomes and to call SNPs between the two transcriptomes. The hybrid mRNA-Seq reads were aligned separately to both transcriptomes and read depths were determined using SamTools  at 67,760 SNPs. SRG100 allele depths were estimated from hybrid reads aligned to the SRG100 transcriptome, and SRG200 allele depths were estimated from hybrid reads aligned to the SRG200 transcriptome. For a read to count towards the allele depth of a given parent, it needed to match the base at the SNP position for the given parent. FGS genes with mean SNP read depths greater than 10 reads per SNP in the gene were used for allelic imbalance analysis. The binomial exact test with an alpha value of 0.05 was used to determine if a gene had preferential expression for the allele of one parent over that of the other parent.
Availability of supporting data
The datasets supporting the results of this article are available in the Sequence Read Archive (SRA). The accession ID is SRP033653, with the following link: http://www.ncbi.nlm.nih.gov/sra/?term=SRP033653.
We would like to thank Mr. Xiaojian Yang for his help with the initial data analysis. This work was supported by the Natural Sciences and Engineering Research Council of Canada and Ontario Research Fund to SJR.
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