A multiple ion-uptake phenotyping platform reveals shared mechanisms that affect nutrient uptake by maize roots

Nutrient uptake is critical for crop growth and determined by root foraging in soil. Growth and branching of roots lead to effective root placement to acquire nutrients, but relatively less is known about absorption of nutrients at the root surface from the soil solution. This knowledge gap could be alleviated by understanding sources of genetic variation for short-term nutrient uptake on a root length basis. A new modular platform for high-throughput phenotyping of multiple ion uptake kinetics was designed to determine nutrient uptake rates in Zea mays. Using this system, uptake rates were characterized for the crop macronutrients nitrate, ammonium, potassium, phosphate and sulfate among the Nested Association Mapping (NAM) population founder lines. The data revealed that substantial genetic variation exists for multiple ion uptake rates in maize. Interestingly, specific nutrient uptake rates (nutrient uptake rate per length of root) were found to be both heritable and distinct from total uptake and plant size. The specific uptake rates of each nutrient were positively correlated with one another and with specific root respiration (root respiration rate per length of root), indicating that uptake is governed by shared mechanisms. We selected maize lines with high and low specific uptake rates and performed an RNA-seq analysis, which identified key regulatory components involved in nutrient uptake. The high-throughput multiple ion uptake kinetics pipeline will help further our understanding of nutrient uptake, parameterize holistic plant models, and identify breeding targets for crops with more efficient nutrient acquisition. Significance Statement Nutrient uptake is among the most limiting factors for plant growth and yet has not been used as a selection criterion in breeding. This is partly due to the lack of high-throughput phenotyping methods for measuring nutrient uptake. Here we describe a novel high-throughput phenotyping pipeline for quantification of multiple ion uptake rates. Using this new phenotyping system, our results demonstrate that specific ion uptake performance by maize plants is positively correlated among the macronutrients nitrogen, phosphorus, potassium and sulfur, and that substantial variation exists within a genetically diverse population. The findings reveal components of regulatory pathways possibly related with enhanced uptake, and confirm that nutrient uptake itself is a potential target for breeding of nutrient-efficient crops.

. In recent years, advances in root imaging and deep (referred to as specific nutrient uptake rate) (25), with a few ex-40 amples of genotypic variation within the same species (26-28). 41 However, the research field is critically understudied as most 42 phenotyping efforts rely on isotope accumulation, which is a 43

Significance Statement
Nutrient uptake is among the most limiting factors for plant growth and yet has not been used as a selection criterion in breeding. This is partly due to the lack of high-throughput phenotyping methods for measuring nutrient uptake. Here we describe a novel high-throughput phenotyping pipeline for quantification of multiple ion uptake rates. Using this new phenotyping system, our results demonstrate that specific ion uptake performance by maize plants is positively correlated among the macronutrients nitrogen, phosphorus, potassium and sulfur, and that substantial variation exists within a genetically diverse population. The findings reveal components of regulatory pathways possibly related with enhanced uptake, and confirm that nutrient uptake itself is a potential target for breeding of nutrient-efficient crops.
LMY, FBF, RES and MG conceived the research; MG and LMY developed the method; MG, HG, AS and YG assisted with the experimentation; MG, SR, AS and DH analyzed the data; and all authors contributed to the writing of the paper.
The authors declare no conflict of interest. 1 To whom correspondence should be addressed. E-mail: lmyork@noble.org were collected in a collection plate and the ion concentrations 104 were quantified using ion chromatography (Fig. 1F ). The 105 downstream data analysis for calculating specific nutrient up-106 take rates was automated using R scripts ( Fig. 1G and H ) 107 (https://doi.org/10.5281/zenodo.3893945).

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The multiple ion uptake pipeline was used to determine 109 35 uptake parameters for each plant (described in Table S1). 110 Including all plant traits measured, a total of 50 traits were col-111 lected for each plant. These traits were used to determine the 112 nutrient uptake capabilities of each plant in terms of: (i) the 113 total uptake performance of a plant, (ii) the specific ion uptake 114 rate on a root length or mass basis, and (iii) the ion uptake 115 ratio and stoichiometry of the plant. The pipeline is modular 116 and flexible for adoption with different plant species by chang-117 ing vessel volumes, nutrient concentrations, and experiment 118 designs. The phenotyping platform enables exploration of a 119 broad range of questions, including studies of competitive and 120 facilitative interactions between nutrients, influence of abiotic 121 and biotic factors on nutrient uptake, and the use of mutants 122 for genetic confirmation of nutrient uptake properties.

Genetic diversity exists among NAM population founder lines 124
for specific nutrient uptake rates and is highly heritable. Us-125 ing the multiple ion uptake phenotyping pipeline, specific 126 nutrient uptake rates of nitrate, ammonium, phosphate, potas-127 sium, and sulfate were characterized simultaneously for the 128 25 maize NAM population founder lines and the reference 129 line B73. After growth in a common nutrient solution, each 130 line was deprived of the focal macronutrients for 48 hours, 131 and then transferred to the uptake setup. Nutrient uptake 132 performance was characterized in a high and a low multiple ion 133 solution with a 10-fold macronutrient concentration difference 134 to characterize high and low affinity performance (23, 33, 34). 135 We found that genetic diversity exists among the NAM 136 population founders for specific nutrient uptake rates (on a root 137 length basis), with significant genotypic differences for nitrate 138 (P < 0.001, Fig. 2A Fig. 2A and B). Furthermore, 144 significant effects of genotype × concentration were detected 145 for nitrate and sulfate (P < 0.05, Table S2). The founders 146 showed differential nitrate uptake rate capacity between the 147 concentration solutions, with the greatest difference observed 148 for line Ki3, which exhibited a specific uptake rate in the 149 high concentration that was 5.29 times higher than in the low 150 concentration. Line HP301 appeared to have a near maximum 151 specific uptake rate (Imax) in the low concentration as its 152 ratio of uptake between the two nutrient concentrations was  The specific nutrient uptake rates for each macronutrient 156 were found to be highly heritable with a broad-sense heritabil-157 ity between 0.37 and 0.88 (Fig. S2). Therefore, the traits 158 assessed by this pipeline may serve as novel breeding targets 159 with genetic variation that could be harnessed for breeding  To determine if specific nutrient uptake rate in a plant is 169 relative to a particular nutrient concentration, or consistent 170 across a wide concentration range, a regression between the 171 specific nutrient uptake rates by concentration was made. 172 A positive significant relationship was observed between the 173 concentration levels for specific nutrient uptake rates of nitrate 174 (P < 0.05, Fig. S3), with a non-significant trend for sulfate (P 175 = 0.08, Fig. S3). For phosphorus, potassium and ammonium, 176 however, no significant relationship was found between specific 177 uptake rates in the two concentrations (P = ns, Fig. S3). 178 Therefore, measurements in a single nutrient concentration 179 representative of dominant field conditions at the respective 180 growth stage may have predictive power for crop selection. 181 Wide genotypic variation in specific nutrient uptake rate was 182 observed within each nutrient, representing value for screening 183 lines at multiple nutrient concentrations for more detailed 184 characterization when possible. The overall interactions among plant traits were determined 188 using the genetically diverse NAM population founder dataset. 189 A principal component analysis (PCA) for all 50 uptake and 190 plant was conducted, which showed that the first two PCs 191 accounted for more than half (62.3%) of the total variance. 192 The PCA ordination revealed a distinct separation between 193 the specific nutrient uptake and root respiration rates from 194 the total uptake and plant size measures (Fig. 3A). This 195 trait separation indicates independent genetic control and, 196 therefore, distinct breeding targets. As specific nutrient uptake 197 and respiration rate traits are independent of plant size, the 198 ratio of these two traits could be considered as an index of 199 efficiency.

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A correlation matrix of the specific nutrient uptake rate 201 The net uptake rate ratio between nitrate and ammonium in the 1 mM high concentration solution (P < 0.001). A ratio above 1 represents a higher proportion of ammonium uptake compared to nitrate. ANOVA results for all nutrient combinations are shown in Table S2.   Fig. S6). That the correlation between specific nutri-242 ent uptake rate and respiration rate was only observed in the 243 high concentration indicates that high root respiration itself 244 is not causative of increased uptake (P = ns, Fig. 4A and B). 245 When exposed to the high concentration an average increase 246 of 27% in specific root respiration rate was observed across 247 all lines. Lines with a greater uptake capacity likely respired 248 more to facilitate the active transport of nutrients for a higher 249 specific uptake rate (Fig. 4B). For phosphate and ammonium, 250 positive correlations between specific root respiration rates and 251 specific nutrient uptake rates were observed in both nutrient 252 concentration solutions (R = 0.16, 0.24, P < 0.001, Fig. S6). 253 These results indicate that increased respiration may be a 254 cost of increased uptake, but that simultaneously selecting for 255 higher uptake but lower respiration may be possible.

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Lines with high specific nutrient uptake rate have elevated 257 transcript abundance of nutrient responsive genes and 258 metabolism. To elucidate the pathways and differences be-259 tween lines with high and low specific macronutrient uptake 260 rates at the molecular level, a comparative transcriptomic anal-261 ysis was conducted. Two lines with high specific uptake rates 262 (M162W and Ky21), three lines with low specific uptake rates 263 (CML69, CML227 and CML228) and the reference line B73, 264 which showed an intermediate specific uptake rate in both low 265 and high concentration solutions, were selected for RNA-seq 266 ( Fig. 5A and B). The phenotyping experiment described above 267 and most experiments in the literature include a deprivation 268 step generally believed to increase uptake rates by priming 269 the molecular machinery. To understand short-term transcrip-270 tomic responses specific to the high nutrient uptake rate lines, 271 maize seedlings were grown in full nutrient conditions for 12 272 days and then one half of the seedlings were macronutrient 273 deprived for 48 hours, which was the same procedure used 274 for the phenotyping experiment. We hypothesized that both 275 NAM lines with high specific nutrient uptake rates (Ky21 and 276 M162W) under nutrient deprived conditions utilized a con-277 served set of pathways and genes to mediate elevated nutrient 278 uptake that were reduced or missing in NAM lines which were 279  unable to do so (CML69, CML227, CML228 and B73). plant uptake and plant size traits (Fig. 6A and B). Specific ion 340 uptake rates for several macronutrients were found to be highly 341 heritable and variable among the genetically diverse NAM 342 population founder lines. Harnessing this natural variation 343 through identification of underlying genes and mechanisms 344 is of paramount importance to improving nutrient uptake 345 efficiency in crops. Work in maize indicated variation in uptake 346 kinetics even among root classes such as seminal, nodal, and 347 lateral roots, which implies that regulation of transporters and 348 other molecular machinery leads to substantial differences in 349 uptake (39). Allelic variation of a nitrate transporter affecting 350 specific uptake rate in rice demonstrates that a single allele can 351 significantly affect plant resource acquisition (40). Recently, 352 mining natural sequences for more effective RuBisCO alleles 353 led to discovery of variants with six-fold faster reactions than 354 typical plant variants (41), and similar strategies could be 355 used for nutrient uptake. Breeding efforts for yield may have 356 indirectly selected for increased specific nitrogen uptake rate 357 in modern wheat varieties (42) and, therefore, crop selection 358 for specific ion uptake rate directly could possibly accelerate 359 gains in nutrient uptake efficiency and yield.

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The multiple ion phenotyping approach allowed investiga-361 tion of the interaction between nutrients in plant uptake. We 362 uncovered that specific ion uptake rates are positively corre-363 lated among the macronutrients N, P, K, and S and, therefore, 364 are likely governed by shared mechanisms (Fig. 6C ). Only a 365 few studies have measured the uptake rates of more than one 366 nutrient, and even more rarely investigated in the context of 367 discovering shared mechanisms through correlative analysis 368 across lines (26, 32). Nutrient transporters have been shown 369 to exhibit cross-regulation with multiple nutrients at the local 370 and whole plant levels as well as to facilitate uptake of phyto-371 hormones (43, 44). Our RNA-seq analyses identified central 372 regulators of nutrient-signaling networks that have elevated 373 transcript abundance in the high specific nutrient uptake lines. 374 With the current push towards multi-dimensional phe-375 nomics (45-47), conducting nutrient uptake experiments in 376 representative conditions is important to assess the complexity 377 of interplay between nutrients. Adding to this complexity, we 378 also found significant variation in preference for specific nutri-379 ents in particular nutrient combinations among the NAM pop-380 ulation founder lines (Fig. 6D). This illustrates the importance 381 of characterizing cultivars to ensure that they are adapted 382 to the soil environment and fertilizer regimes according to 383 nutrient uptake characteristics. Dissection of these mecha-384 nisms is important to understand the fundamental processes 385 by which all plants forage nutrients from their environment. 386 This study used a hydroponics approach as it has inherent 387 practical advantages over soil in controlling nutrient availabil-388 ity and measurements of uptake rates. It will be important 389 to extend this research to determine how soil physical and 390 chemical properties affect multiple nutrient uptake rates and 391 nutrient preferences. Optimization of above-and below-ground 392 plant traits to the environment and management practices 393 will be integral to improving nutrient uptake and reducing 394 fertilizer losses.

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Nutrient uptake is a substantial carbon expense to the 396 plant and, therefore, understanding how nutrient uptake af-397 fects overall plant efficiencies is vital. We phenotyped the 398 specific root respiration rates amongst the NAM population 399 founder lines as a measure of root activity and metabolic cost. 400 Fig. 6. Mechanisms of uptake performance with regards to plant size, specific uptake rates, uptake of different nutrients, and respiration. Root colors represent the area of root nutrient uptake per nutrient type. Circle colors represent different nutrient types.
The results revealed that specific nutrient uptake rates were 401 positively correlated with specific root respiration rate in the 402 high nutrient concentration solutions (Fig. 6E). As specific 403 root respiration rate was not correlated in the low concentra- precise phenotyping, which will provide mechanistic insights 436 into nutrient uptake and has a great potential for genomic 437 selection that will benefit agriculture. The results revealed 438 that specific ion uptake rates are highly heritable and, there-439 fore, we envision that breeding for targeted environments by

686
The depletion rate of a nutrient from a solution is commonly 687 accepted as equal to the net uptake rate by roots (assuming both 688 influx and efflux). Therefore, the following equation was used 689 to determine the total net influx rates for nitrate, ammonium, 690 potassium, phosphate and sulfate: where In is the net influx into the plant; C 0 is the initial con-