Plant materials
The results from a previous study, in which 50 different oilseed rape genotypes were examined under both pot and field experiments, allowed us to categorize the tested genotypes into four groups, based on their NUtE values: Nt-responder, Nt-nonresponder, Nt-efficient, and Nt-inefficient. Nt-responder referred to genotypes with an NUtE value above the mean at high N (0.3 g N kg− 1 dry soil or 180 kg N ha− 1), while genotypes with a NUtE value below the mean were categorized into the Nt-nonresponder group. At the low N supply (0.1 g N kg− 1 dry soil or 0 kg N ha− 1), genotypes displayed a NUtE value above the mean were called Nt-efficient, and Nt-inefficient genotypes were those genotypes with a NUtE value below the mean (He et al. 2017). According to the rank of responses reported previously, we chose 18 genotypes with distinctive NUtE for this study. These included 5 Nt-responder, 5 Nt-nonresponder, 4 Nt-efficient and 4 Nt-inefficient and are described in Table S1.
Experimental design
In this study, a field and a pot experiments were conducted at Yangling district, Shaanxi province, P.R. China (34⁰ 24’ N, 108⁰ 08’ E) from 2016–2018. In the field trail, the soil was with a pH of 7.65, containing 13.7 g kg− 1 organic matter, 1.19 g of total N kg− 1, 24.7 mg of available N kg− 1, 15.7 mg of Olsen-P kg− 1 and 76.9 mg of available K kg− 1. In the pot experiment, the soil had the following properties: 9.21 g kg− 1 organic matter, 0.92 g of total N kg− 1, 22.0 mg of available N kg− 1, 10.7 mg of Olsen-P kg− 1 and 73.6 mg of available K kg− 1, and a pH of 7.5.
Our previous study indicated that the Nt-responder and Nt-nonresponder genotypes were expressed only under high N supply conditions, while the Nt-efficient and Nt-inefficient were expressed under low N supply conditions. Therefore, the 10 high N genotypes were planted with high N level (150 kg N ha− 1 in the field experiment and 0.30 g of N kg− 1 dry soil in the pot experiment), while the 8 low N genotypes were planted with low N level (0 kg N ha− 1 in field experiment and 0.10 g of N kg− 1 dry soil in pot experiment). In the field experiment, the high or low plot of 10 m in length × 2 m wide or 8 m length × 2 m width, consisted of forty or thirty-two rows of oilseed rape with row spacing of 50 cm. Each experiment was arranged in a randomized complete block design with four replicates. In both experiments, sufficient phosphorus as superphosphate (P2O5 135 kg ha− 1 and 0.20 g kg− 1 dry soil) and potassium (K2O 150 kg ha− 1 and 0.30 g kg− 1 dry soil) were supplied.
Observations and measurements
In order to monitor the dynamics of silique development, flowering and fertilization process of the genotypes were categorized into: pre-embryo (1–4 days after flowering), globular (5–8 days after flowering), heart (9–14 days after flowering), torpedo (15–22 days after flowering), and maturation (23–30 days after flowering) stages (Andriotis et al. 2010; Tan et al. 2011; Hehenberger et al. 2012). For accurate monitoring, fully-opened flowers on the main inflorescence of each plant were marked with colored strings each day. In the pot experiment, five marked siliques of each plant at each developmental stage were chosen for the determination of net photosynthetic rate, silique length, width, surface area, EON, biomass and RNA expression levels.
At the flowering stage, we removed the petals from the sampled buds with tweezers, and recorded the stamen and anther number. Then, the pollen grain number and pollen viability were measured according to Lankinen et al. (2018): Pollen grains were sprinkled on a microscope slide in Hoekstra medium with 16% sucrose. The microscope slides were placed in a dark constant temperature incubator with a temperature of 25˚C for 3 h. Pollen germination was terminated by adding 100% glycerol. Pollen grain number and germination rate (pollen viability) were determined under a light microscope (Axioplan 2; Zeiss) as the percentage of germinated pollen grains from 100 pollen grains in a randomly chosen area with the following equation: Pollen viability = the total number of germinated pollen grains / the total number of pollen grains × 100%. The initiation ovule number and abortion rate were determined according to Wang et al. (2011): Ovule abortion rate = the aborted ovule number / the initial ovule number.
Measurement of agronomic traits
At maturation stage, plant height was measured from the base of the stem to the tip of the main inflorescence (Sun et al. 2016). The point of measurement of stem diameter was set at 10 cm from the base of the main stem (Ohashi et al. 2006). First, valid branch height was measured as the height from the base of the stem to the effective primary branches at the bottom of the main stem. Then, the number of first valid branches was measured according to Xu et al. (2014a).
Measurement of yield and N use efficiency
Number of siliques per plant was measured as the number of effective pods on the main inflorescence, branch inflorescence and the whole plant (Shi et al. 2015). Seed weight of each plant was measured by weighing 500 fully developed seeds with four replications; the weight of 500 seeds was then converted to 1,000-seed weight for easy comparison with other studies (Fan et al. 2010). Seed yield per plant was measured as the average dry weight of seeds of the four randomly selected plants from each genotype (Shi et al. 2011). Each of the ground seed and straw samples was weighed, and then digested and determined for N concentration by following the Kjeldahl procedure. Seed and shoot (seed + straw) N accumulations were calculated as the product of dry matter by the respective N concentration. According to He et al. (2017), N utilization efficiency (NUtE) and N uptake efficiency (NUpE) were estimated with the following equations: NUtE = seed yield / shoot N accumulation; NUpE = shoot N accumulation / N supply.
Measurement of siliques indices
At each stage (pre-embryo, globular, heart, torpedo, and maturation), silique net photosynthetic rate was measured on the marked siliques between 09:00 and 11:00, using a Portable Photosynthesis System (Li-6400, LI-COR, Lincoln, NE, USA). Afterwards, the marked siliques were removed from the main inflorescence. Half of each of the sampled siliques was rapidly frozen in liquid nitrogen, and stored at − 80°C for later RNA transcript analysis, and the other half was used for the determination of surface area (Hua et al. 2012) and normal ovule numbers which were counted under a light microscope. The sampled siliques were oven-dried at 105°C for 30 min and then at 70°C until a constant dry weight was reached and then were weighed.
Quantitative RT-PCR analysis
Silique samples of the 18 diverse NUtE genotypes were frozen in liquid nitrogen immediately after collection and stored at -80℃. Approximately 100 mg of tissue was ground in liquid nitrogen and total RNA was extracted using an EZNATM Plant RNA Kit (Omega Bio-Tek Inc., Norcross, GA, USA). The sample was used for cDNA synthesis using TransScript® First-Strand cDNA Synthesis SuperMix (TransGen Biotech, Beijing, China) according to the manufacturer’s instructions. Quantitative PCR analyses were performed in an QuantStudio® Design and Analysis (QuantStudio 5, Life Technologies, CA, USA), using a TransStart Tip Green qPCR SuperMix (TransGen Biotech, China). All of the primers used in the analysis are listed in Table S2. The low NUtE genotypes (Nt-nonresponder and Nt-inefficient) were used as references (Nt-nonresponder for Nt-responder and Nt-inefficient for Nt-efficient, respectively). Data were expressed as the mean of four biological replicates ± SD.
Statistical Analysis
All the data from both the field and pot experiments, were subjected to analysis of variance. Estimates of correlation coefficients and tests of significance, were performed using the SPSS version 17.0. Principal component analysis was performed using the Canoco 5.0 software. When the analysis showed significance, mean comparisons were made according to the least-significant difference test at P ≤ 0.05 (LSD0.05). All the figures were created using Origin 9.0 software, Microsoft Excel and PowerPoint 2016.