1 Running head: Reduced root branching improves drought … · 2015/6/15 · 60 of architectural,...

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Running head: Reduced root branching improves drought tolerance 1

Jonathan Lynch 2

Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802 3

USA 4

Telephone 814-863-2256 5

email: [email protected] 6

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Plant Physiology Preview. Published on June 15, 2015, as DOI:10.1104/pp.15.00187

Copyright 2015 by the American Society of Plant Biologists

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Reduced lateral root branching density improves drought tolerance in maize 8

Ai Zhan1,2, Hannah Schneider2, Jonathan P. Lynch2* 9

1State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest 10

A&F University, Yangling, Shaanxi, 712100, China 11

2Department of Plant Science, The Pennsylvania State University, University Park, PA, 16802 12

USA 13

Summary: Maize genotypes with reduced lateral root branching density have superior water 14

capture, growth, and yield under drought. 15

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Financial sources: This research was supported by the Howard G. Buffett Foundation and 17

the Agriculture and Food Research Initiative of the USDA National Institute of Food and 18

Agriculture competitive grant number 2014-67013-2157 to JPL. 19

* Corresponding author. Email: [email protected], Tel.: +1 8148632256 20

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Abstract 22

An emerging paradigm is that root traits that reduce the metabolic costs of soil exploration 23

improve the acquisition of limiting soil resources. Here we test the hypothesis that reduced 24

lateral root branching density will improve drought tolerance in maize (Zea mays) by reducing 25

the metabolic costs of soil exploration, permitting greater axial root elongation, greater rooting 26

depth, and thereby greater water acquisition from drying soil. Maize recombinant inbred lines 27

with contrasting lateral root number and length (FL: few but long; MS: many but short) were 28

grown under water stress in greenhouse mesocosms, in field rainout shelters, and in a 29

second field environment with natural drought. Under water stress in mesocosms, lines with 30

the FL phenotype had substantially less lateral root respiration per unit axial root length, 31

deeper rooting, greater leaf relative water content, greater stomatal conductance, and 50% 32

greater shoot biomass than lines with the MS phenotype. Under water stress in the two field 33

sites, lines with the FL phenotype had deeper rooting, much lighter stem water δ18O signature 34

signifying deeper water capture, 51 to 67% greater shoot biomass at flowering, and 144% 35

greater yield than lines with the MS phenotype. These results entirely support the hypothesis 36

that reduced lateral root branching density improves drought tolerance. The FL lateral root 37

phenotype merits consideration as a selection target to improve the drought tolerance of 38

maize and possibly other cereal crops. 39

Keywords: Lateral root branching; water stress; respiration; rooting depth; maize 40

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Introduction 42

Suboptimal water availability is a primary limitation to crop productivity in both developed and 43

developing countries (Lynch, 2007; Lobell et al., 2014). Climate change as well as decreased 44

freshwater availability are likely to increase the frequency and severity of crop water stress in 45

the future, causing significant yield loss (Tebaldi and Lobell, 2008; Brisson et al., 2010; IPCC, 46

2014). This will be a major obstacle to sustaining an increased human population, which is 47

projected to reach 9.6 billion by 2050 (Lee, 2011). Therefore, the identification and 48

understanding of traits improving crop drought tolerance have been the focus of the 49

development of more drought-tolerant crops and cropping systems. 50

Root architecture regulates water and nutrient acquisition by positioning root foraging activity 51

in specific soil domains in time and space (Lynch, 1995; Gregory, 2006; Lynch, 2011). 52

Genotypic variation for root traits and their functional implications for soil resource acquisition 53

and improved yields under nutrient and water stress conditions have been reported in many 54

crops. In the case of phosphorus (P), the most immobile macronutrient, whose availability is 55

therefore greatest in the topsoil, the ‘topsoil foraging’ ideotype appears to be particularly 56

important for genotypic adaptation to low phosphorus soils (Lynch and Brown, 2001; Lynch, 57

2011; Richardson et al., 2011). For superior acquisition of water and nitrate, which are highly 58

mobile in the soil, the ‘steep, cheap, and deep (SCD)’ ideotype has been proposed, consisting 59

of architectural, anatomical, and physiological traits accelerating subsoil exploration (Lynch, 60

2013; Lynch and Wojciechowski, 2015). One element of the SCD ideotype is a low density of 61

lateral roots per length of axial root and greater lateral root length of crown roots, as traits that 62

would reduce inter-root competition, improve the metabolic efficiency of soil exploration, and 63

accelerate the elongation of axial roots. 64

Lateral roots originate from a small number of differentiated cells situated in the subapical 65

zone of the axial root. The development of lateral roots has been studied in detail in the model 66

plant Arabidopsis thaliana (Nibau et al., 2008; Péret et al., 2009). Multiple genes, ABA, and 67

auxin are important in pre-branch site formation, lateral root initiation, and lateral root 68

emergence (Swarup et al., 2008; Zhao et al., 2014). For example, in the pre-branch site 69



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formation stage, the position of lateral root primordium was demarked by auxin response DR5 70

driven luciferase, which expression was dependent on AUXIN RESPONSE FACTOR 6, 7, 8, 71

and 19, and on auxin repressor protein IAA8, 19, and 28 (Moreno-Risueno et al., 2010; De 72

Rybel et al., 2010). A newly discovered adaptive mechanism termed lateral root 73

hydropatterning was also involved in regulating pre-branch sites (Bao et al., 2014). In addition, 74

transcription factors such as LBD 16, 18, and 29 which belong to the LBD/ASL family, 75

positively regulate lateral root formation (De Smet et al., 2010). In cereals, a number of genes 76

and growth regulators that regulate lateral root formation have been reported, including the 77

rice crl1 mutants in rice which reduced lateral root number by 70% (Inukai et al., 2005), and in 78

maize, lateral root initiation is inhibited when auxin transport is disrupted by the rum1 mutation 79

(Woll et al., 2005). 80

Lateral roots typically comprise the major portion of root systems, accounting for 81

approximately 90% of the total root length (Pierret et al., 2006; Zobel et al., 2007). The 82

formation of lateral roots increases the sink strength of the root system, promoting the 83

development of greater root length and thereby greater soil resource acquisition (Varney and 84

Canny, 1993; Postma et al., 2014). However, root construction and maintenance requires 85

metabolic investment, which can exceed 50% of daily photosynthesis (Lambers et al., 2002). 86

Thus, the metabolic costs of the construction and maintenance for additional lateral roots, 87

either calculated in units of carbon or in terms of other limiting resources, may reduce the 88

growth of other roots, like axial roots (Borch et al., 1999; Borch et al., 2003; Lynch and Ho, 89

2005; Walk et al., 2006), potentially slowing axial root elongation into deep soil strata. This is 90

especially important for the acquisition of water, whose availability is greater in deeper soil 91

strata in most soils. A plant that is able to access water in deep soil domains at reduced 92

metabolic cost will have superior productivity, because it will have more metabolic resources 93

available for further resource acquisition, growth, and reproduction. Evidence in support of 94

this hypothesis comes from empirical and modeling studies for maize under water and 95

edaphic stress (Lilley and Kirkegaard, 2011; Jaramillo et al., 2013; Uga et al., 2013; Chimungu 96

et al., 2014a; Lynch, 2014; Saengwilai et al., 2014a; Chimungu et al., 2014b; Saengwilai et al., 97

2014b). In addition, increased lateral root branching places roots closer together, which may 98



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increase competition for water among roots of the same plant, effectively reducing the uptake 99

efficiency per unit root length (Postma et al., 2014). The frequency and length of lateral 100

branching determines the balance between the capture of mobile and immobile resources. 101

Mobile resources are captured more efficiently by fewer but longer laterals capable of 102

exploring larger volumes of soil with greater spatial dispersion among roots. Results from the 103

functional-structural plant model SimRoot indicate that the optimal lateral root branching 104

density for N capture is less than that for P capture in maize (Postma et al., 2014). Previous 105

research showed that reduced lateral root branching density improves N capture under N 106

deficiency (Zhan and Lynch, 2015). The few/long (FL) lateral root phenotype is therefore an 107

element of the SCD ideotype for efficient water capture, because sparse lateral branching 108

should conserve internal resources, reduce competition for water among neighboring lateral 109

roots, and explore a greater volume of soil than the many/short (MS) lateral root phenotype. 110

The objectives of this research were to test the hypotheses that: (1) reduced lateral root 111

branching density decreases the respiration of maize roots; (2) maize genotypes with few but 112

long lateral roots have greater rooting depth under water stress conditions, resulting in greater 113

water acquisition, and improving both plant growth and yield. To test these hypotheses we 114

compared the performance of maize recombinant inbred lines (RILs) sharing a common 115

genetic background but having contrasting lateral root branching phenotypes under water 116

stress in greenhouse mesocosms and two field environments. 117

Results 118

Lateral root branching and root length 119

Most genotypes selected for this study displayed stable lateral root branching density 120

phenotypes, except MO327. In two replications of the Pennsylvania (PA) field site in water 121

stress (WS) conditions, MO327 displayed the MS (i.e. Many/Short) lateral root phenotype, 122

rather than the FL (i.e. Few/Long) lateral root phenotype. For purposes of this study, MO327 123

was classified as the FL phenotype in all figures and statistics, which did not substantially 124

affect statistical analyses (Table S1). 125



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In greenhouse mesocosms (GH), water stress (WS) significantly decreased lateral root 126

branching density in crown and primary roots (Fig. 1). Compared with FL (i.e. Few/Long 127

lateral root phenotype) lines, MS (i.e. Many/Short lateral root phenotype) lines had 128

significantly greater lateral root branching density in crown roots, but no significant difference 129

was found in primary and seminal roots. In the two field sites, lateral root branching density of 130

crown roots in MS lines was significantly greater than that of in FL lines in both WS and WW 131

(well watered) conditions (Fig1B-C). Water stress significantly decreased lateral root 132

branching density in crown roots, although no difference was found in primary and seminal 133

roots. 134

Under WS In greenhouse mesocosms, the average axial root lengths of crown, primary, and 135

seminal roots of the FL lines were greater, by 34%, 73%, and 71%, respectively, compared to 136

the MS lines (Fig. 2). Total root length of FL and MS lines had equivalent value in either WS or 137

WW, but WS significantly decreased total root length in both FL and MS lines (Fig. 2). 138

Lateral root branching effects on respiration and rooting depth 139

Water availability and genotype had significant effects on specific root respiration and root 140

respiration of lateral roots per unit axial root length (Table 1). Water stress decreased specific 141

root respiration in the mesocosms by 37%. Under WS conditions in mesocosms, specific root 142

respiration of FL lines was 47% less than MS lines (Table 1). Specific root respiration was 143

positively correlated with lateral root branching density of crown roots under water stress (R2 = 144

0.86, p = 0.0005, Fig. 3). Root respiration of axial and lateral roots per unit axial root length 145

was significantly affected by water treatment (Table 1). Root respiration of axial root per unit 146

axial root length showed no significant difference among genotypes in either WS or WW, but 147

root respiration of axial roots per unit axial root length in WS was 37% less than that in WW. 148

Root respiration of lateral roots per unit axial root length in WS was 43% less than in WW 149

(Table 1). Under WS, root respiration of lateral roots per unit axial root length in FL lines had 150

141% less respiration than MS lines. Root respiration of lateral roots per unit axial root length 151

was positively correlated with the lateral root branching density of crown roots under WS (R2 = 152

0.95, p < 0.0001, Fig, 3). 153



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Water stress decreased root length density in the GH, and in the field in Arizona (AZ) and PA, 154

and the FL lines had greater root length density in deep soil layers than MS lines (Fig. 4). 155

Under WS in AZ, and PA, FL lines had significantly greater D95 (D95 is the depth above which 156

95% of total root length is located in the soil profile) than MS lines (Table S2). FL lines under 157

water stress had a D95 value of 118cm, 54cm, and 55cm in GH, AZ, and PA compared to 88cm, 158

43cm, and 45cm in MS lines, respectively. Lateral root branching density of crown roots was 159

negatively correlated with D95 under WS in all three environments (Fig. 5). 160

Lateral root branching effects on leaf relative water content and δ18O uptake 161

Water treatment and genotype had a significant impact on leaf relative water content (LRWC) 162

in PA and mesocosms (Tables S2). Under nonstressed conditions, LRWC in the GH and AZ 163

was not significantly different between FL and MS lines. Under water stress, the LRWC of FL 164

lines in GH and PA were significantly greater, by 8% and 13%, than the MS lines. Under WS, 165

LRWC was positively correlated with rooting depth in GH (R2 = 0.80, p = 0.0017) and PA (R2 = 166

0.92, p = 0.0001,Fig. 6). 167

Under WS conditions, analysis of soil water isotopic signature (δ18O) in both AZ and PA 168

showed progressively lighter isotope signature of water with increasing depth (Fig. 7). In AZ, 169

the majority of change in this signature was found in the top three soil layers (0-10 cm, 10-20 170

cm, and 20-30 cm) (approximately 1.97‰), while in PA, this change was mainly found in the 171

top two soil layers, 0-10 cm, and 10-20 cm (approximately 4.19‰). No significant difference 172

was found in the deepest three soil layers, which were aggregated as ‘deep water’ for 173

subsequent analyses. The values of stem water δ18O of the eight genotypes varied by 3.25‰ 174

in AZ and 3.45‰ in PA (Table 2). The FL lines in AZ and PA had a 46% and 44% lighter stem 175

water signature, respectively, than the MS lines. Soil water δ18O values were used in an 176

isotopic mixing model to determine water sources contributing to the δ18O signature for stem 177

water, assuming that any water acquired below 30 cm depth was ‘deep water’. Under WS in 178

AZ and PA, the FL lines mainly absorbed ‘deep water’, averaging 66% and 66% of stem water, 179

respectively, while the MS lines had greater reliance on the two most shallow soil layers 180

(Table 2). Lateral root branching density of crown roots was negatively correlated with the 181



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δ18O signature for stem water in AZ (R2 = 0.83, p = 0.0011), and PA (R2 = 0.54, p = 0.0224) 182

(Fig 8). 183

Lateral root branching effects on plant growth and yield 184

In all three environments, WS significantly decreased CO2 exchange rate and stomatal 185

conductance (Fig. 9). Under WS, FL lines had significantly greater leaf CO2 assimilation than 186

MS lines, by 58% in GH, 42% in AZ, and 79% in PA. Stomatal conductance in GH, AZ, and PA 187

were 84%, 73%, and 65% greater in FL lines than in MS lines, respectively, under WS 188

conditions (Fig. 9). 189

Relative shoot dry weight in GH, AZ, and PA were significantly influenced by water treatment 190

and in the two field sites were influenced by genotype (Tables S2). Under WS, the FL lines 191

had 50%, 51%, and 67% greater relative shoot dry weight at 42 days after planting in the GH, 192

and at anthesis in AZ and PA, respectively, than MS lines (Fig. 10). Relative shoot dry weight 193

was negatively correlated with lateral root branching density of crown roots (GH: R2 = 0.86, p 194

= 0.0006; AZ: R2 = 0.51, p = 0.0279; PA: R2 = 0.45, p = 0.0402, Fig. 11A). In PA, the lateral 195

root branching density of crown roots was negatively correlated with yield (R2 = 0.50, p = 196

0.0307, Fig. 11B). Under WS, compared to MS, FL lines improved yield by 144% (Fig. 11B). 197

Discussion 198

We hypothesized that reduced lateral root branching density would decrease the metabolic 199

cost of soil exploration, thereby improving water acquisition, plant growth and yield under 200

water stress. Our results from greenhouse mesocosms and two field environments entirely 201

support the hypothesis that under water stress, root phenotypes with few but long lateral roots 202

have less specific root respiration, greater rooting depth, greater acquisition of deep soil water, 203

improved plant water status, leaf photosynthesis, stomatal conductance, and hence greater 204

plant growth and yield. These results support the inclusion of this lateral root phenotype in the 205

SCD ideotype for optimal acquisition of water and N (Lynch, 2013). 206

In order to impose terminal drought by progressive reduction of soil water content, we used 207

greenhouse mesocosms, reduced irrigation in AZ, and automated rainout shelters in PA. The 208



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combination of results from three distinct environments is noteworthy. Mesocosms are 209

simplified, controlled environments, yet permit detailed analysis of root distribution by depth 210

and intact root respiration as entire root systems can be excavated. The field environments 211

include variable environmental factors such as temperature, rainfall, soil biota, and soil 212

physical properties that may affect results, and the two field environments had contrasting soil 213

physical properties. The fact that results from these contrasting water stress environments are 214

in agreement with each other suggests that potentially confounding factors of any given 215

environment are not driving the results. In addition, we used RILs which share a common 216

genetic background (i.e. all lines descend from the same two parents), without artificially 217

induced mutations or transformation events. Each RIL is a distinct genotype, and comparison 218

of several RILs allows the analysis of a phenotype in distinct genomes, thereby minimizing the 219

risk of confounding effects from pleiotropy, epistasis, or other genetic interactions (Zhu and 220

Lynch, 2004). RILs are particularly valuable in the analysis of phenotypic traits governed by 221

multiple genes as is the case for lateral rooting in maize (Zhu et al., 2005b; Burton et al., 222

2014). 223

We have proposed that reduced lateral root branching density may be a useful adaptation to 224

drought by reducing the metabolic costs of soil exploration (Lynch, 2013). The metabolic costs 225

of soil exploration by root systems are substantial, and can exceed 50% of daily 226

photosynthesis (Lambers et al., 2002). The fewer roots are initiated, the fewer carbon and 227

other resources need to be invested in root growth and maintenance, which could save 228

photosynthate and improve the growth of shoots, other roots, and may enhance reproduction 229

(Lynch, 2007). Root respiration associated with growth, maintenance, and ion uptake are 230

major components of root metabolic costs (Lambers et al., 2002; Lynch and Ho, 2005). In the 231

present study, decreasing lateral root branching of crown roots from 11 to 3 branch cm-1 was 232

associated with 58% reduction of specific root respiration and 71% reduction of lateral root 233

respiration per unit axial root length (Fig. 3). Empirical and modeling results indicate that the 234

optimal density of lateral branching of maize roots decreases at low N availability (Postma et 235

al., 2014; Zhan and Lynch, 2015). In the present study, results from mesocosms and one field 236

site show that reduced lateral root branching density increases rooting depth and improves 237



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plant water status and stomatal conductance (the lack of effect of lateral root branching 238

density on LRWC and stomatal conductance in AZ was due to rainfall at the time of sampling) 239

under drought conditions. Reduced lateral branching directly reduces the respiratory costs 240

associated with sustaining more lateral roots, thereby permitting the axial root to elongate 241

faster. An indirect benefit of reduced lateral branching is that for mobile resources like water 242

and nitrate, greater spatial dispersion of lateral roots increases the soil volume explored per 243

unit of root cost, and reduces resource competition among roots of the same plant, which 244

improves the metabolic efficiency of soil exploration (Postma et al., 2014). This has practical 245

implications, since in many rainfed or drought environments, the topsoil dries before the 246

subsoil, and, as drought progress, roots must exploit increasingly deeper soil strata to capture 247

water. Therefore genotypes with deep root systems would have the capability to capture 248

water from deep soil strata and resist water stress (Lopes and Reynolds, 2010; Wasson et al., 249

2012; Lynch and Wojciechowski, 2015). 250

Reduced lateral root branching density is important for drought tolerance because this 251

phenotype determines the balance between the capture of mobile and immobile resources 252

(Lynch, 2013). Greater lateral root branching increases the rate at which a soil domain is 253

depleted of resources, especially for immobile resources like P. For example, results from a 254

recent modeling study showed that a greater density of lateral branches in the topsoil can 255

improve P uptake from low P soil in wheat by 142% (Heppell et al., 2015). However, for highly 256

mobile resources, like N and water, depletion zones are larger and the greater lateral root 257

branching creates overlapping resource depletion zones around roots of the same plant, 258

thereby decrease resource capture efficiency (Ge et al., 2000). Therefore, lateral root 259

phenotypes to optimize mobile resources should be long and dispersed along the axial roots. 260

Results from the structural-functional simulation model SimRoot have shown that the optimal 261

density of lateral branching of maize roots at low N availability is less than that at low P 262

availability (Postma et al., 2014), a result later confirmed at low N in field and mesocosm 263

studies (Zhan and Lynch, 2015). Here we show that reduced lateral root branching density 264

improves plant water capture under water stress (Table 2, Fig. 6). 265

An additional benefit to reducing root cost is that extra resources from reduced root metabolic 266



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demand can contribute to growth and yield (Lynch, 2014), which are competing sinks for 267

current photosynthate. In the present mesocosm study, decreasing lateral branching of crown 268

roots from 11 to 3 branches cm-1 was associated with a 11% increase of relative shoot 269

biomass (Fig 11A). In the field experiments, decreasing lateral branching of crown roots from 270

11 to 4 branches cm-1 in AZ, and from 12 to 5 branch cm-1 in PA was associated with 40% and 271

37% increase of relative shoot biomass, respectively (Fig. 11A). Simulation results indicate 272

that without root maintenance respiration, maize plants had up to 72% greater growth under 273

limiting nutrient supply (Postma and Lynch, 2010; Postma and Lynch, 2011). Therefore 274

reduced root carbon demand in FL genotypes may be beneficial by increasing carbohydrate 275

availability (Fig. 11A). These results support the hypothesis that genotypes with less costly 276

root tissue could develop the extensive, deep root systems required to fully utilize soil water 277

resources in drying soil without as much yield penalty. 278

Hydrogen and oxygen stable isotope analysis provides an effective approach for studying root 279

water uptake. Normally, natural discrimination by evaporation against heavy isotopes 280

increases the concentration of heavy isotopes of oxygen in water at the soil surface (Durand 281

et al., 2007). Under dry conditions, this results in a relative enrichment in heavy isotopes of 282

elements of water (D and 18O) in the topsoil while deeper soil strata maintain the average 283

isotopic composition of regional precipitation (Durand et al., 2007, Fig. 7). No hydrogen and 284

oxygen isotope fractionation occurs during soil water uptake by root systems (Ehleringer and 285

Dawson, 1992), so the water absorbed by plant roots can be considered as the mixture of 286

water acquired from different soil depths. In the present study, stem water δ18O signatures 287

showed that the FL phenotype had lighter isotope signatures and greater dependency on 288

deep soil water than the MS phenotype (Table 2). The difference in the depths of root water 289

acquisition between the FL and MS genotypes could be attributed to their rooting depth (Table 290

S2, Figs. 4,5). 291

Studies have shown that lateral root formation for embryonic (seminal and primary roots) and 292

post-embryonic (nodal roots, including crown and brace roots) is controlled by multiple 293

pathways or different sensitivities to signals in lateral root formation (Hochholdinger and Feix, 294

1998; Hochholdinger et al., 2001). In maize, the lrt1 mutant is deficient in the initiation of 295



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lateral roots in the primary roots, seminal roots, and the crown roots emerging from the 296

coleoptilar node, however crown roots from subsequent nodes have normal lateral root 297

formation (Hochholdinger and Feix, 1998). In addition, slr1 and slr2 maize mutants display 298

reduced elongation of lateral roots from roots of the embryonic root system and normal lateral 299

root formation from roots in the post-embryonic root system (Hochholdinger et al., 2001). In 300

the present study, primary and seminal roots did not show the same lateral root branching 301

phenotypes as the crown roots, and phenotypes for branching densities were intermediate, 302

rather than in distinct groups of MS or FL (Fig. 1). These results are evidence that lateral 303

branching density for the embryonic and postembryonic root system is under distinct genetic 304

control. However, during vegetative growth of the plant, the crown roots capture the majority 305

of the soil resources (Lynch, 2013). The SCD ideotype proposes an increased lateral 306

branching density of seminal roots to optimize P and ammonium capture during seedling 307

establishment and a decreased lateral root branching density of crown roots to improve 308

capture of nitrate and water during vegetative growth (Lynch, 2013). Results from this study 309

support the SCD ideotype. The FL lateral branching phenotype on crown roots improved plant 310

water status, plant growth, and yield in WS conditions. The genotypes selected for this study 311

did not have clear MS or FL lateral branching phenotypes for primary and seminal roots, 312

which had intermediate branching densities. To further examine the SCD ideotype for primary 313

and seminal roots, additional studies should be conducted using genotypes contrasting for FL 314

and MS of primary and seminal roots. 315

Lateral branching is a heritable trait (Zhu et al., 2005b) and genetically controlled (Doebley et 316

al., 1995; Takeda et al., 2003). Genotypes selected for this study generally displayed stable 317

lateral root branching density phenotypes regardless of treatment or environment. One 318

exception to this was one genotype, MO327, in two replications of the PA field site in WS 319

conditions, which displayed the MS phenotype, rather than the FL phenotype. For purposes of 320

this study, all figures and statistics were performed with MO327 classified as the FL 321

phenotype, which minimally impacts statistics (Supplementary Table S1). Although genotypes 322

remained stable in terms of phenotypic classes for lateral root branching density throughout 323

the experiment, shifts of lateral branching density were observed in the data. For example, in 324



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WS conditions in PA the average lateral root branching density (branch cm-1) was 5 for FL and 325

9.8 for MS, whereas in AZ the average lateral root branching density (branch cm-1) was 6.3 for 326

FL and 11 for MS. This plasticity response may reflect varying soil and environmental 327

conditions at the field sites, which is to be expected as previous studies have shown that 328

genetic variation exists for plasticity in root traits (Zhu et al., 2010). 329

Root depth is one of the most important traits for plant resistance to water stress (Wasson et 330

al., 2012; Lynch and Wojciechowski, 2015). Modeling studies indicate that selection for 331

deeper, more effective roots could significantly improve capture of water and nitrogen in 332

wheat (Manschadi et al., 2006; Asseng and Turner, 2007; Lilley and Kirkegaard, 2011). In rice, 333

maximum root length, root depth, and basal thickness are correlated with yield under water 334

stress (Champoux et al., 1995; Li et al., 2005). When introduced into a shallow-rooting rice 335

cultivar, DRO1 improved yield under drought conditions by increasing rooting depth (Uga et 336

al., 2013). Root depth also has been positively correlated with yield in soybean (Cortes and 337

Sinclair, 1986). Our results in greenhouse mesocosms and two field experiments clearly show 338

that the FL phenotype increases rooting depth (Fig. 4 and Fig. 5), improves water capture 339

from deep soil (Table 2, Fig. 6, and Fig. 8), and improves plant water status, growth and yield 340

(Fig. 6, Fig. 10, and Fig. 11). Although the present study focuses on maize, we suggest that 341

the phenotype of few long lateral roots would improve water capture in other species, like 342

sorghum which has a root system architecture similar to that of maize (Lynch, 2013). Other 343

poaceae species have the same basic root structure as maize and may also benefit from this 344

phenotype, like wheat, rice, and barley, although greater density of nodal roots in tillering 345

species may change the relationship of lateral root branching density and resource capture. 346

Our results are entirely supportive of inclusion of reduced lateral root branching as a 347

component of the SCD ideotype (Lynch, 2013) for improved capture of N (Zhan and Lynch, 348

2015) and water (this paper) when those resources limit growth. The SCD ideotype applies to 349

both water and N capture, since both of these soil resources are often localized in deep soil 350

strata under limiting conditions. 351

Plant breeders rarely select for root traits because they are challenging to phenotype, many 352

traditional metrics of root phenotypes are actually phene aggregates with low heritability, and 353



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root phenotypes often display plasticity in response to soil conditions (Tuberosa et al., 2002; 354

Malamy, 2005; York et al., 2013; Lynch, 2014). As shown here and in previous literature, 355

genotypic differences in lateral root number and length exist in maize (Zhu et al., 2005b; 356

Trachsel et al., 2011; Lynch, 2013; Burton et al., 2014). Previous studies indicate that lateral 357

branching is a heritable trait (Zhu et al., 2005b) and genes affecting lateral branching have 358

been identified in several species, including maize (Doebley et al., 1995) and rice (Takeda et 359

al., 2003), making lateral branching and length a feasible target for plant breeding. Our results 360

from three distinct environments, greenhouse mesocosms and two field sites, are entirely 361

consistent with the hypothesis that the few/long lateral root phenotype increases rooting depth 362

by reducing root metabolic costs, resulting in greater water acquisition from deep soil strata, 363

and improved plant growth and yield under water stress. We suggest that lateral root number 364

and length deserves consideration as a root phenotype to improve drought tolerance in crop 365

breeding programs. 366

Materials and Methods 367

Greenhouse mesocosm experiment 368

Plant materials 369

Eight recombinant inbred lines (RILs) of maize (Zea mays L.), genotypes MO067, MO079, 370

MO086, MO134, MO295, MO321, MO327, and MO362 from the intermated B73 × MO17 371

population (IBM) were obtained from Dr. Shawn Kaeppler (University of Wisconsin, Madison, 372

WI, USA) (Genetics Cooperation Stock Center, Urbana, IL, USA). Our previous screening for 373

lateral root branching and length in this population indicated that RILs MO067, MO079, 374

MO086, and MO327 had few but long lateral roots (FL phenotype), and RILs MO134, MO295, 375

MO321, and MO362 had many but short lateral roots (MS phenotype) (Trachsel et al., 2011; 376

Trachsel et al., 2013a). Thus, in the present study we consider RILs MO067, MO079, MO086, 377

and MO327 to have the FL phenotype, and RILs MO134, MO295, MO321, and MO362 to 378

have the MS phenotype. 379

Experimental design 380



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The greenhouse experiment was a randomized complete block design, the factors were two 381

water treatments (well watered: WW, and water stress: WS) and eight RILs (MO067, MO079, 382

MO086, MO134, MO295, MO321, MO327, and MO362), with four replicates. 383

Growth conditions 384

Plants were grown from March 19 to April 30, 2014 in a greenhouse located on the campus of 385

The Pennsylvania State University in University Park, PA, USA (40°48′ N, 77°51′ W) under 386

constant conditions (14/10 h at 28/24°C day/night, 40-70% relative humility). Seeds of 8 387

genotypes were surface-sterilized in 0.05% NaOCl for 30 min and imbibed for 24 h in aerated 388

1 mM CaSO4, then were placed in darkness at 28 ± 1°C in a germination chamber for two 389

days. Three seedlings of similar size were transplanted to mesocosms consisting of 390

polyvinylchloride (PVC) cylinders 15.7 cm in diameter and 155 cm in height, with plastic liners 391

made of 4 mil (0.116 mm) transparent hi-density polyethylene film, which was used to 392

facilitate root sampling, then thinned to one seedling per mesocosm five days later after 393

planting. The growth medium consisted of (by volume) 50% medium size (0.5–0.3 mm) 394

commercial grade sand (Quikrete Companies Inc., Harrisburg, PA, USA), 35% horticultural 395

size #3 vermiculite, 5% perlite (Whittemore Companies Inc., Lawrence, MA, USA), and 10% 396

topsoil. The topsoil was collected from the Russell E. Larson Agricultural Research Center in 397

Rock Springs, PA (Fine, mixed, semiactive, mesic Typic Hapludalf, pH=6.7, silt loam). To 398

ensure a consistent bulk density, a uniform volume (29 L) of the soil mixture was used in each 399

mesocosm. Mineral nutrients were provided by mixing the media with 70g per column of 400

OSMOCOTE PLUS fertilizer consisting of (in %): N (15), P (9), K (12), S (2.3), B (0.02) Cu 401

(0.05), Fe (0.68), Mn (0.06), Mo (0.02), and Zn (0.05) (Scotts-Sierra Horticultural Products 402

Company, Marysville, Ohio, USA). Two days before planting, each cylinder was irrigated with 403

4.5 L of deionized water. In the first four days, plants received 100 ml of deionized water every 404

day. And then 200ml of deionized water was irrigated in the WW treatment every 2 d, and WS 405

treatment received no further irrigation. Additional light was provided with 400 W metal-halide 406

bulbs (Energy Technics, York, PA, USA) for 14 hours per day to a maximum illumination of 407

1200 μmol photos m-2 s-1. Average daytime temperature in the greenhouse was 408

approximately 28 °C. 409



18

Root respiration and root harvest 410

Three days before harvesting, the ‘head space’ approach of sampling air flow over the soil 411

surface was used in this study to measure the intact root respiration. In short, a PVC plate 412

was placed on top of the pot to seal off the root system from the shoot. An air pump provided 413

a stable flow of air through the ‘head space’ compartment of the pot. The airflow rate was 414

1200 µmol s-1. The measurements were conducted in early morning with a Li-6400 portable 415

Infrared Gas Analyzer (Li-Cor Biosciences, Lincoln, NE, USA). Intact root respiration was 416

measured for a short time (ca.5 min, Fan et al., 2003; Zhu et al., 2005a). In the present study, 417

we assumed that the amount of natural soil and the respiration of microbes was the same in 418

all cylinders (Bouma et al., 1997a; Bouma et al., 1997b), and used the intact root system plus 419

media respiration as a proxy for total root respiration. The intact root system respiration 420

values were divided by the total root length obtained by WinRhizo scanning (described below) 421

to obtain the specific root respiration per unit of root length (µmol CO2 m-1 root length s-1). 422

At harvest (30 April 2014), the plastic sleeve was removed from the supporting PVC cylinder, 423

cut open, and roots were separated from the soil by vigorous rinsing at low pressure with 424

water. Root respiration of axial and lateral roots were measured. Three representative 10cm 425

root segments from the third crown root were excised 20 cm from the base. Lateral roots of 426

axial roots were removed with a Teflon blade (Electron Microscopy Sciences, Hatfield, PA, 427

USA). Excised axial and lateral root samples were patted dry and placed in a 40 ml custom 428

chamber connected to the Li-6400 IRGA (LI-COR, Lincoln, NE, USA), separately. The 429

temperature of the chamber was maintained at 26 ± 1°C by using a water bath while 430

respiration was measured. Carbon dioxide evolution from the root segments was recorded 431

every 5 seconds for 180 seconds. Axial root length of crown and seminal roots was collected 432

from three representative root samples representing the average growth of each root class. 433

Root number in each whorl of crown roots and seminal roots were counted manually. Average 434

axial root length of crown roots was calculated by using a weighted average from all roots. 435

Roots from each 20 cm soil layer were collected, and lateral root number from three 436

representative roots was obtained by scanning with image analysis software (WinRhizo Pro, 437

Régent Instruments, Québec, Canada) as described below. Total root length of each plant 438



19

was the sum of root length in each layer. 439

Plant measurements and shoot dry weight 440

One day before harvesting, leaf relative water content (LRWC) was measured. To measure 441

LRWC, four fresh leaf discs (1 inch in diameter) were collected from the third fully expanded 442

leaf and weighed immediately to determine fresh weight (FW). After which the discs were 443

immediately hydrated to full turgidity by soaking them in distilled water for 8 h. After 8 h, the 444

discs were patted dry and weighed again to determine turgid weight (TW). The discs were 445

then dried at 70 °C for 72 h, and dry weight determined (DW). Leaf RWC was calculated 446

according to the equation: LRWC (%) = 100× (FW – DW) / (TW – DW). 447

The CO2 exchange rate and stomatal conductance of the third fully expanded leaf was 448

measured with a Li-6400 portable photosynthesis system (Li-Cor Biosciences, Lincoln, NE, 449

USA) using a red-blue light at a photosynthetically active radiation intensity of 1200 μmol 450

photons m-2 s-1, CO2 concentration of 400 ppm, and leaf temperature of 25°C. The 451

measurements were conducted between 9 am and 11 am. At harvest, shoots were collected 452

and dried at 70 °C until constant weight for biomass determination. 453

Field studies 454

Field conditions, experimental design, and plant materials 455

Field experiments were carried out from April to July 2014 at the Apache Root Biology Center, 456

Willcox, AZ, USA (AZ) (32°2′0" N, 109°41′30" W) and from May to August 2014 at the Russell 457

Larson Research and Education Center of the Pennsylvania State University in Rock Springs, 458

PA, USA (PA) (40°42′37" N, 77°57′07" W). The soils at the experimental sites were a Grabe 459

loam (coarse-loamy, mixed, thermic Typic Torrifluvent) in AZ and a Hagerstown silt loam (fine, 460

mixed, mesic Typic Hapludalf) in PA. 461

The two experiments were arranged in a split-plot design replicated four times with two water 462

treatments (WS and WW). The main plots were composed of two moisture regimes and the 463

subplots were eight genotypes (RILs MO067, MO079, MO086, MO134, MO295, MO321, 464



20

MO327, and MO362) in each experiment. In AZ, the experiments were planted in five 6 m row 465

plot with 25 cm distance between plants, and 75 cm wide between rows. The WS treatment 466

was initiated starting 40 days after planting by withholding water application in AZ. In PA, each 467

subplot consisted of three rows, each row was 3 m long, 25 cm between plants and 75 cm 468

between rows. The drought treatment was initiated 30 days after planting using an automated 469

rainout shelter in PA. The shelters (10 by 30 m) were covered with a clear greenhouse plastic 470

film (0.184 mm) and were automatically triggered by rainfall to cover the plots, excluding 471

natural precipitation. Adjacent non-sheltered control plots were rainfed, to maintain the soil 472

moisture close to field capacity throughout the growing season, drip-irrigation was applied 473

when necessary. Soil water content in AZ and PA were monitored using soil moisture probes 474

(PR2, Dynamax Inc., Houston, TX, USA) and TRIME FM system (IMKO Mocromodultechnik 475

GmbH, Ettlingen, Germany), respectively, both in WS and WW treatments. At each location, 476

the recommended fertilizer rate was applied before planting. Pest control and irrigation were 477

carried out as needed. 478

Shoot and roots were evaluated 10 weeks after planting at AZ and 12 weeks after planting at 479

PA (anthesis stage). Three representative, adjacent plants were randomly selected in the 480

same row for shoot dry weight per replicate, and dried at 70 °C for 72 h before being weighed. 481

Roots were excavated by removing a soil cylinder ca. 40 cm diameter and 25 cm depth with 482

the plant base as the horizontal center of the soil cylinder. The excavated root crowns were 483

cleaned by vigorous rinsing at low pressure with water. The clean roots were subsequently 484

used to measure lateral root number. All nodal roots emerging belowground were classified 485

as crown roots. Three 5 cm root segments were taken 5 cm from the base of each whorl of 486

crown, primary and seminal roots, and lateral root number of corresponding roots was based 487

on counts. 488

Plant measurements 489

Two days before harvest, CO2 exchange rate and stomatal conductance of the ear leaf was 490

measured with a Li-6400 portable photosynthesis system (Li-Cor Biosciences, Lincoln, NE, 491

USA) using a red-blue light at PAR intensity of 1800 μmol photons m-2 s-1, constant CO2 492



21

concentration of 400 ppm, and leaf temperature of 28 °C. The measurements were conducted 493

between 9:00 and 11:00 am. In both field experiments, LRWC was measured as described 494

above, except that nine fresh leaf discs were collected from the ear leaf for three 495

representative plants per plot (three fresh leaf discs per plant). At physiological maturity, grain 496

yield was collected in PA. Yield was not collected in AZ because of uneven anthesis of these 497

RILs in response to the temperature and photoperiod regime at this location. 498

Shoots and roots were evaluated and excavated 10 weeks after planting at AZ and 12 weeks 499

after planting at PA (anthesis stage). Three representative, adjacent plants were randomly 500

selected in the same row for shoot dry weight per replicate, and dried at 70 °C for 72 h before 501

being weighed. 502

Root harvest and rooting depth 503

Roots were excavated by removing a soil cylinder ca. 40 cm diameter and 25 cm depth with 504

the plant base as the horizontal center of the soil cylinder. The excavated root crowns were 505

cleaned by vigorous rinsing at low pressure with water. The clean roots were subsequently 506

used to measure lateral root number. All nodal roots emerging belowground were classified 507

as crown roots. Three representative 5 cm root segments were taken 5 cm from the base of 508

each whorl of crown, primary and seminal roots, and lateral root number of corresponding 509

roots was based on counts. 510

In both field sites, soil cores were collected at flowering to determine root distribution in the 511

soil profile. A soil coring tube (Giddings Machine Co., Windsor, CO, USA) 5.1 cm in diameter 512

and 60 cm long was used for sampling, the core was taken within a planting row midway 513

between two plants. Soil core was subdivided into 10 cm segments and roots were extracted 514

from each segment. Extracted root samples were scanned using a flatbed scanner (Epson, 515

Perfection V700 Photo, Epson America, Inc. USA) at a resolution of 23.6 pixel mm-1 (600 dpi) 516

and analyzed using image processing software WinRhizo Pro (Regent Instruments, Québec, 517

Canada). Percentages of root length at each depth were calculated in each soil core. Depth 518

above which 95% (D95) of root length is located was calculated by linear interpolation between 519

the cumulative root lengths (Trachsel et al., 2013b). 520



22

Soil and plant sampling of δ18O analysis 521

In both AZ and PA, soil samples for δ18O analysis were collected adjacent to plants in the WS 522

treatment at flowering stage using a 5 cm diameter soil core. Soil cores were taken to the 523

maximum achievable depth of 60 cm. The cores were separated into 10 cm increments: 10, 524

20, 30, 40, 50, and 60 cm. In each replicate three cores were collected from different positions 525

and mixed as one sample for each depth. The maize stems were collected at the same time, 526

approximately 8-10 cm of the stem was collected just above ground level and the epidermis 527

was immediately removed. Soil and maize stem samples were put in a snap vials, sealed with 528

parafilm to prevent evaporation, and refrigerated immediately. Cryogenic vacuum distillation 529

(Ehleringer and Osmond, 1989) was used to extract soil water and crop stem water. In 530

cryogenic vacuum distillation, two glass tubes were attached to a vacuum pump. The sample 531

was placed in one tube and frozen by submerging the tube in liquid nitrogen, and then both 532

tubes were evacuated by vacuum pump to create a closed U-shape configuration. After that, 533

the tube containing the sample was heated to 100°C, while the collection tube was still 534

immersed in liquid nitrogen to collect evaporated water. Samples were weighed and oven 535

dried after extraction to ensure the extraction time was sufficient to vaporize all the water in 536

the samples. The water samples were analyzed using a PICARRO L2130-i δD/δ18O Ultra 537

High Precision Isotopic Water Analyzer (PICARRO Inc, CA, USA). Results were expressed as 538

parts per thousand deviations from the Vienna Standard Mean Ocean Water (VSMOW). To 539

determine the percent contribution of soil water from different depths to the signature of water 540

within the plant tissue, an isotopic mixing model was used (Phillips et al., 2005). IsoSource 541

Version 1.3.1 (Phillips and Gregg, 2003) was used to evaluate the relative contribution of each 542

soil layer to tissue water signature. The fractional increment was set at 1%, and tolerance at 543

0.1. 544

Statistical analysis 545

The experimental data were statistically analyzed by ANOVA, and Tukey’s Honest Significant 546

Difference method (α = 0.05) was used for multiple comparisons with SAS 8.0 software (SAS 547

Stat. Inst. Cary, NC, USA). Linear regression analysis and Pearson correlation coefficients 548



23

were calculated using Sigmaplot software (SigmaPlot 10.0, Systat Software Inc., CA, USA). 549

Acknowledgements 550

We thank the China Scholarship Council for support of Ai Zhan, and Jennifer Yang, Robert 551

Snyder and Johan Prinsloo for technical support. 552



24

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728



33

Table 1. Root respiration of eight maize genotypes under two water treatments. 729

Specific root respiration per unit root length (ηmol CO2 cm-1 RL s-1), root respiration of axial roots per unit axial root length (axial root 730

respiration) (ηmol CO2 cm-1ARL s-1), root respiration of lateral roots per unit axial root length (lateral root respiration) (ηmol CO2 cm-1 731

ARL s-1) of eight maize recombinant inbred lines (RILs) with contrasting lateral root branching density (FL: few but long lateral roots; 732

MS: many but short lateral roots) under well watered (WW) and water stress (WS) conditions in greenhouse mesocosms. Data are 733

means (n=4). The same letters within each column are not significantly different at α = 0.05 (Tukey’s Honest Significant Difference 734

method). ANOVA table (in the lower part of the table) for above parameters as influenced by soil moisture regime (T), genotype (G), 735

and phenotype (P) with associated F-values and probabilities (NS, not significant; *, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001) are shown. 736

Classification based on LRBD RILs

Specific root respiration (ηmol CO2 cm-1 RL s-1)

Axial root respiration(ηmol CO2 cm-1ARL s-1)

Lateral root respiration (ηmol CO2 cm-1 ARL s-1)

WS WW WS WW WS WW

FL 67 164.44 bc 292.63 a 10.24 ab 17.82 a 3.50 b 14.11 a

79 157.81 c 296.45 a 9.27 b 17.72 a 4.03 b 12.13 a

86 149.62 c 253.62 a 12.76 ab 17.34 a 5.27 b 14.11 a

327 159.31 c 241.37 a 11.21 ab 18.70 a 5.31 b 13.03 a

MS 134 233.19 ab 259.49 a 9.79 ab 19.71 a 11.35 a 13.59 a

295 237.43 a 243.42 a 13.53 ab 21.55 a 12.10 a 15.56 a

321 236.21 a 279.96 a 15.37 a 18.15 a 12.24 a 11.26 a

362 221.95 ab 268.77 a 10.50 ab 14.93 a 7.92 ab 14.45 a

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34

ANOVA

Treatment (T) 71.76***

3.42**

9.45**

57.61***

1.67NS

1.35NS

89.69***

5.32***

27.37***

Genotype (G)

Phenotype (P)

G × T 5.46*** 0.97NS 5.02***

P × T 21.24*** 0.16NS 21.64***

737

738

739

740


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35

Table 2. Stem water isotopic signature (δ18O) of eight maize genotypes and proportional water use by depth. 741

Means of δ18O of stem water (n = 4 ± SE) measured for eight maize genotypes contrasting in lateral root branching density (LRBD; FL: 742

few but long lateral roots; MS: many but short lateral roots) and proportional water use by depth from different soil layers (‘deep’ is the 743

aggregate of three deep soil layers) under water stress conditions at anthesis in Arizona (AZ) and Pennsylvania (PA). 744

Classification based on LRBD RILs

δ18O of stem water Proportional water use by depth (%)

AZ PA AZ PA

10 cm 20 cm deep 10 cm 20 cm deep

FL 67 -7.66 ± 0.17 -9.69 ± 0.11 10.20 10.20 61.15 9.65 25.58 64.78

79 -7.89 ± 0.21 -9.94 ± 0.51 9.28 8.90 65.58 8.18 25.83 66.00

86 -7.62 ± 0.13 -9.76 ± 0.35 10.98 10.70 59.28 9.18 25.60 65.28

327 -8.46 ± 0.36 -9.91 ± 0.40 5.60 5.15 80.10 8.23 24.43 67.33

MS 134 -5.39 ± 0.23 -6.49 ± 0.26 26.85 41.60 11.20 56.38 27.03 16.65

295 -5.21 ± 0.22 -6.98 ± 0.0.27 36.45 35.80 9.15 41.68 41.43 23.90

321 -5.59 ± 0.21 -7.01 ± 0.37 29.88 28.80 14.70 47.55 32.60 19.85

362 -5.44 ± 0.25 -6.87 ± 0.11 30.65 33.03 12.85 48.53 32.15 19.33


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36

745



37

Figure Legends 746

Figure 1. Lateral root branching density in greenhouse mesocosms (A), in the field in 747

Arizona (B) and Pennsylvania (C) under well watered (WW) and water stress (WS) 748

conditions. Bars show means of four replicates of the four genotypes in each phenotype 749

class in WW or WS ± SE. Bars with the same letters are not significantly different within 750

the same panel (α = 0.05). 751

Figure 2. Average axial root length of crown, primary, and seminal roots (A), and total root 752

length (B) in greenhouse mesocosms under well watered (WW) and water stress (WS) 753

conditions. Bars show means of four replicates of the four genotypes in each phenotype 754

class in WW or WS ± SE. Bars with the same letters are not significantly different within 755

the same panel (α = 0.05). 756

Figure 3. Correlation between lateral root branching density of crown roots and specific 757

root respiration per unit root length (A), and root respiration per unit axial root length (B) 758

under water stress in greenhouse mesocosms. Each point is the mean of four replicates of 759

each genotype. 760

Figure 4. Root length density by soil depth of maize RILs in greenhouse mesocosms (A), 761

and in the field in Arizona (B) and Pennsylvania (C) under water stress (WS, circles) and 762

well watered (WW, triangles) conditions. The data shown are the mean of four replicates 763

of the four genotypes in each phenotype class in WS or WW ± SE. The average value of 764

D95 for four FL (dash arrow) and four MS (solid arrow) genotypes under WS are shown in 765

each panel. 766

Figure 5. Correlation between lateral root branching density of crown roots and rooting 767

depth (D95) in greenhouse mesocosms (A), in the field in Arizona (B) and Pennsylvania 768

(C) under water stress. Each point is the mean of four replicates of each genotype. 769

Figure 6. Correlation between D95 and leaf relative water content in greenhouse 770

mesocosms (GH), in the field in Arizona (AZ) , and Pennsylvania (PA) under water stress 771



38

conditions. Each point is the mean of four replicates of each genotype. 772

Figure 7. Mean oxygen isotope composition (δ18O) of soil water along the soil profile in 773

the field in Arizona (A) and Pennsylvania (B) under water stress conditions. Values are the 774

means ± SE of four observation points. Bars with the same letters are not significantly 775

different within the same panel (α = 0.05). 776

Figure 8. Correlation between lateral root branching density and stem water isotopic 777

signature (δ18O) in the field in Arizona (AZ) and Pennsylvania (PA) under water stress 778

conditions. Each point is the means of four replicates of each genotype. 779

Figure 9. CO2 exchange rate (A-C) and stomatal conductance (D-F) of FL and MS 780

phenotypes in greenhouse mesocosms (A and D), in the field in Arizona (B and E) and 781

Pennsylvania (C and F) under well watered (WW) and water stress (WS) conditions. Bars 782

show means of four replicates of the four genotypes in each phenotype class in WW or 783

WS ± SE. Bars with the same letters are not significantly different within the same panel (α 784

= 0.05). 785

Figure 10. Relative shoot dry weight (% of greatest shoot dry weight within each location) 786

of FL and MS phenotypes in greenhouse mesocosms (GH), in the field in Arizona (AZ), 787

and Pennsylvania (PA) under water stress (WS) and well watered (WW) conditions. Bars 788

show means of four replicates of the four genotypes in each phenotype class in WW or 789

WS ± SE. 790

Figure 11. Correlation between lateral root branching density of crown roots and A: 791

relative shoot dry weight (% relative to greatest shoot dry weight within each location) in 792

greenhouse mesocosms, in the field in Arizona (AZ) and Pennsylvania (PA), B: relative 793

yield (% relative to greatest yield) in PA under water stress conditions. Each point is the 794

mean of four replicates of each genotype.795



39

796

























1

Supplementary Table S1. Analysis of the effect of plasticity of MO327 genotype of results in water stress (WS) conditions 1

at the PA field site (LRBD: lateral root branching density , LRWC: leaf relative water content). A) All replications of 2

genotype MO327 classified as FL; B) All replications of MO327 classified as MS; C) MO327 classified as MS for replicates 3

2 and 3 and FL for replicates 1 and 4; D) MO327 removed from dataset. 4

5

6

Relative SDW (%)

Relative Yield (%)

CO2 exchange rate (μmol CO2 m-2 s-

1)

Stomatal conductance (mol H2O m-2

s-1)

LRWC (%)

Crown LRBD

(branches cm-1)

Primary LRBD

(branches cm-1)

Seminal LRBC

(branches cm-1)

D95 (cm)

MS FL MS FL MS FL MS FL MS FL MS FL MS FL MS FL MS FL A 31 52.4 19.2 47.4 15.2 27.9 0.1 0.2 77.1 86.6 10 5 6.2 8.2 5.7 4.6 45.1 55.3B 34.8 51.8 24.2 46.7 17.2 27.2 0.1 0.2 79.1 86.8 9.8 6.1 5.6 6.9 5.5 4.7 46.9 54.9C 28.4 42.9 14.6 32.4 16.5 27.2 0.1 0.2 78.3 86.6 10 5.4 6.9 6.1 5.8 4.3 46.1 55.1D 31 52.4 19.2 47.4 15.2 27.9 0.1 0.2 77.1 86.6 10 5 6.2 8.2 5.7 4.6 45.1 55.3


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2

Supplementary Table S2. Summary of analysis of variance for rooting depth (D95), leaf relative water content (LRWC) 7

(%), shoot dry weight (SDW) and yield (Y) as influenced by soil moisture regimes (treatment (T)), genotypes (G), and 8

lateral root phenotypes (P) in greenhouse mesocosms (GH), Arizona (AZ), and Pennsylvania (PA). The associated F-9

values and probabilities (NS, not significant; *, P<0.05; **, P<0.01; ***, P<0.001) are shown. 10

Source of variation

GH AZ PA

D95 LRWC SDW D95 LRWC SDW D95 LRWC SDW Y

Treatment (T) 0.42NS 65.01*** 1949*** 9.70** 8.22** 18.59*** 57.84*** 432.96*** 469.97*** 118.53***

Genotype (G) 24.98*** 4.16** 2.26* 13.55*** 1.50NS 2.21* 5.95*** 7.71*** 7.52*** 2.57*

Phenotype (P) 95.58*** 22.21*** 1.61NS 86.50*** 1.06NS 17.94*** 39.50*** 57.08*** 17.76*** 8.71**

G × T 10.68*** 5.89*** 4.72*** 4.50*** 2.43* 2.15* 4.33*** 9.55*** 5.60*** 1.62NS

P × T 30.59*** 34.64*** 9.52** 26.15*** 5.05* 4.71* 27.62*** 69.88*** 13.50*** 8.24**

11 https://plantphysiol.orgD

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http://scholar.google.com/scholar?as_q=Root cortical aerenchyma enhances the growth of maize on soils with suboptimal availability of nitrogen, phosphorus, and potassium&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Postma&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Plant Physiol%5BTitle%5D%29 AND 166%5BVolume%5D AND 581%5BPagination%5D AND Saengwilai P%2C Tian X%2C Lynch JP%5BAuthor%5D&dopt=abstract

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Swarup K, Benkova E, Swarup R, Casimiro I, Peret B, Yang Y, Parry G, Nielsen E, De Smet I, Vanneste S, et al (2008) The auxininflux carrier LAX3 promotes lateral root emergence. Nat Cell Biol 10: 946-954


Takeda T, Suwa Y, Suzuki M, Kitano H, Ueguchi-tanaka M, Ashikari M (2003) The OsTB1 gene negatively regulates lateralbranching in rice. Plant J 33: 513-520


Tebaldi C, Lobell DB (2008) Towards probabilistic projections of climate change impacts on global crop yields. Geophys Res Lett35: L08705


Trachsel S, Kaeppler SM, Brown KM, Lynch JP (2013) Maize root growth angles become steeper under low N conditions. F CropRes 140: 18-31


Trachsel S, Kaeppler SM, Brown KM, Lynch JP (2011) Shovelomics?: High throughput phenotyping of maize (Zea mays L.) rootarchitecture in the field. Plant Soil 341: 75-87


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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Nat Cell Biol%5BTitle%5D%29 AND 10%5BVolume%5D AND 946%5BPagination%5D AND Swarup K%2C Benkova E%2C Swarup R%2C Casimiro I%2C Peret B%2C Yang Y%2C Parry G%2C Nielsen E%2C De Smet I%2C Vanneste S%2C et al%5BAuthor%5D&dopt=abstract

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Towards probabilistic projections of climate change impacts on global crop yields%2E%5BTitle%5D%29 AND Tebaldi C%2C Lobell DB%5BAuthor%5D&dopt=abstract

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Front Plant Sci%5BTitle%5D%29 AND 4%5BVolume%5D AND 1%5BPagination%5D AND York LM%2C Nord EA%2C Lynch JP%5BAuthor%5D&dopt=abstract

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Zhu J, Kaeppler SM, Lynch JP (2005b) Mapping of QTL for lateral root branching and length in maize (Zea mays L.) underdifferential phosphorus supply. Theor Appl Genet 111: 688-695


Zhu J, Zhang C, Lynch JP (2010) The utility of phenotypic plasticity of root hair length for phosphorus acquisition. Funct Plant Biol37: 313-322


Zobel R, Kinraide T, Baligar V (2007) Fine root diameters can change in response to changes in nutrient concentrations. Plant Soil297: 243-254



http://www.ncbi.nlm.nih.gov/pubmed?term=%28Funct Plant Biol%5BTitle%5D%29 AND 31%5BVolume%5D AND 949%5BPagination%5D AND Zhu J%2C Lynch JP%5BAuthor%5D&dopt=abstract

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http://scholar.google.com/scholar?as_q=Mapping of QTL for lateral root branching and length in maize (Zea mays L&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

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http://www.ncbi.nlm.nih.gov/pubmed?term=%28Funct Plant Biol%5BTitle%5D%29 AND 37%5BVolume%5D AND 313%5BPagination%5D AND Zhu J%2C Zhang C%2C Lynch JP%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Zhu J, Zhang C, Lynch JP (2010) The utility of phenotypic plasticity of root hair length for phosphorus acquisition. Funct Plant Biol 37: 313-322


http://scholar.google.com/scholar?as_q=The utility of phenotypic plasticity of root hair length for phosphorus acquisition&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=The utility of phenotypic plasticity of root hair length for phosphorus acquisition&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Zhu&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=%28Plant Soil%5BTitle%5D%29 AND 297%5BVolume%5D AND 243%5BPagination%5D AND Zobel R%2C Kinraide T%2C Baligar V%5BAuthor%5D&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Zobel R, Kinraide T, Baligar V (2007) Fine root diameters can change in response to changes in nutrient concentrations. Plant Soil 297: 243-254

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Zobel&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Fine root diameters can change in response to changes in nutrient concentrations&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

http://scholar.google.com/scholar?as_q=Fine root diameters can change in response to changes in nutrient concentrations&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Zobel&as_ylo=2007&as_allsubj=all&hl=en&c2coff=1


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