Plant Breeding. 2020;00:1–13. wileyonlinelibrary.com/journal/pbr  |  1© 2020 Blackwell Verlag GmbH

1  | INTRODUC TION

Maize is a globally important food, fodder and energy crop. Brassinosteroids (BRs) and gibberellins (GAs) are two important classes of plant hormones controlling plant developmental processes (Hu et al., 2017). Fluctuations in BRs and GAs biosynthesis and signal transduction, together with other hormones, drive plant growth and development and affect plant responses to environmental stimuli.

BRs are the only steroids among plant hormones. They were first extracted from Brassica napus pollen, 40 years ago (Grove et al., 1979). BRs are ubiquitous in the plant kingdom, and play a critical role in plant growth and development, influencing cell ex-pansion, cell elongation, cell division, cell wall formation (Clouse & Sasse, 1998; Hacham et al., 2011; Sasse, 2003), seed germina-tion (Kim, Warpeha, & Huber, 2019; Steber & McCourt, 2001),

vascular differentiation (Cano-Delgado et al., 2004), stem and root growth (Krishna, 2003), flowering time (Clouse, 2008), se-nescence (Vardhini, Anuradha, Sujatha, & Rao, 2010), leaf archi-tecture (Teresa, Anna, Neeru, & Timothy, 2009), seed yield (Che et al., 2015; Choe et al., 2001), plant height, fertility, maturation, plant architecture, photomorphogenesis, leaf morphogenesis and photosynthesis (Vriet, Russinova, & Reuzeau, 2012). In addition, BRs play a pivotal role in resistance to abiotic and biotic stresses (Anwar et al., 2018; Bajguz & Hayat, 2009). For example, lil1-1, a novel allele of the brassinosteroid-deficient dwarf1 (brd1) gene, can enhance drought tolerance (Castorina et al., 2018). OsGSK1 serves as a negative regulator of BR signalling. Knockout (KO) mutants of OsGSK1 in rice showed enhanced tolerance to cold, heat, salt and drought stresses (Koh et al., 2007). BRs can be manipulated to in-crease yield in two ways: by genetic manipulation of BR biosynthesis

Received: 1 January 2020  |  Revised: 5 June 2020  |  Accepted: 15 June 2020

DOI: 10.1111/pbr.12845

O R I G I N A L A R T I C L E

Genetic variation of seedling traits responded to brassinosteroid and gibberellin inhibitors in maize (Zea mays) doubled haploid lines

Kun Hu1,2  | Ying Xie3 | Chenglai Wu4 | Ursula K. Frei2 | Thomas Lübberstedt2

1Maize Research Institute, State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, Sichuan Agricultural University, Wenjiang, Sichuan, China2Department of Agronomy, Iowa State University, Ames, IA, USA3College of Agronomy, Sichuan Agricultural University, Wenjiang, Sichuan, China4State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, Shandong Agricultural University, Tai'an, Shandong, China

CorrespondenceThomas Lübberstedt, Department of Agronomy, Iowa State University, Ames, IA, USA.Email: thomasl@iastate.edu

Funding informationUSDA’s National Institute of Food and Agriculture, Grant/Award Number: IOW04314 and IOW05520

Communicated by: Roberto Tuberosa

AbstractThe purpose of this study was to examine the genotypic variation in maize doubled haploid (DH) lines response to brassinosteroid and gibberellin inhibitors. Plant re-sponses to hormone inhibitors were determined in growth chamber experiments using germination paper for three different seedling treatments: application of propi-conazole (Pcz), uniconazole (Ucz) or water (control). Mesocotyl length (ML) was more sensitive to hormone inhibitors, especially to the Ucz treatment, than other seed-ling traits. ML was significantly correlated with other traits in the Ucz treatment. All the seedling traits showed moderate-to-high broad sense heritability values, ranging from 0.39 to 0.82. The Euclidian genetic distances of inbred line pairs ranged from 1.27 to 19.94, indicating there was a high level of variability across the maize DH lines used in this study. DH lines with extreme MLs were identified, which can provide valuable breeding resources for improving abiotic stress tolerance, and for further genetic studies.

K E Y W O R D S

brassinosteroid, genetic variation, gibberellins, maize DH lines, mesocotyl length, seedling traits

2  |     HU et al.

and through the signalling pathway by exogenous application of BRs (Vriet et al., 2012). Endogenous BR levels and sensitivity have been modified by genetic engineering in a variety of plant species, such as Arabidopsis thaliana (Baud et al., 2009; Cano-Delgado et al., 2004; Steber & McCourt, 2001; Zhu, Sae-Seaw, & Wang, 2013), rice (Fujii & Saka, 2015; Hao, Yin, & Fei, 2013; Hong et al., 2005; Wu et al., 2008), tomato (Dhaubhadel, Chaudhary, Dobinson, & Krishna, 1999; Hasan, Hayat, & Ahmad, 2011; Vidya Vardhini & Rao, 2002) and cotton (Ming et al., 2007; Shi et al., 2006; Sun, Fokar, Asami, Yoshida, & Allen, 2004; Sun et al., 2005). However, the biosynthesis and sig-nalling pathway of BRs are not very well studied in maize, especially in the seedlings, which warrant further in-depth studies (Hartwig et al., 2011; Makarevitch, Thompson, Muehlbauer, & Springer, 2012).

Gibberellins are a large group of diterpene plant hormones. They were first discovered in the “foolish seedling” rice, in the late 19th century, and are known for their contribution to the “green rev-olution” in the 1960’s (Stowe & Yamaki, 1957). In rice and wheat, plant height can be reduced by defects in the GAs signalling path-way, resulting in higher yield (Peng et al., 1999; Sasaki et al., 2002). However, many GAs biosynthesis/signalling-deficient maize (Zea mays) mutants have pleiotropic phenotypes that are detrimental to the crop yield (Li et al., 2019). Bioactive GAs are biosynthesized by a complex pathway, and have a profound influence on plant growth and development, including seed germination and devel-opment (Yamaguchi, 2008), stem elongation (Zhao et al., 2017), leaf expansion (Li et al., 2012), flower development and fruit set (Liu et al., 2018), root growth (Ubeda-Tomás et al., 2008) and reg-ulation of fertilization (Dorcey, Urbez, Blázquez, Carbonell, & Perez-Amador, 2009). GAs biosynthesis and signalling pathways have been studied in various plant species, such as Arabidopsis (Yamaguchi et al., 2014), rice (Spielmeyer, Ellis, & Chandler, 2002; Tang et al., 2018), maize (White, Proebsting, Hedden, & Rivin, 2000; Zhang, Wang, Zhao, Zhang, & Li, 2019), wheat (Flintham, Börner, Worland, & Gale, 1997; Guo et al., 2018) and tomato (De Jong, Mariani, & Vriezen, 2009). In a previous study, the authors found that GAs played an important role in the promotion of mesocotyl elongation and seed germination under deep-sowing conditions (Pan, Zhong, & Zhao, 2016). GAs significantly increased the elon-gation of the first internode via cell elongation in 'Hong Mang Mai' which is a wheat variety tolerant to deep-seeding conditions (Chen, Higashitani, Suge, Takeda, & Takahashi, 2003; Chen et al., 2001). As physiological mechanism, endogenous GAs synthesis was crucial for mesocotyl elongation and promoted mesocotyl elongation via cell elongation rather than cell division (Zhao et al., 2010). Mesocotyl elongation was more sensitive to GAs under deep seeding than under shallow seeding, and was closely correlated with endogenous GAs levels (Zhao & Wang, 2008). Exogenous GAs can strongly stim-ulate internode elongation in dwarf GA1-deficient mutants of pea, the first internode elongation of wheat and mesocotyl and coleoptile elongation of rice (Cao et al., 2005; Chen et al., 2001; Watanabe, Hase, & Saigusa, 2007; Yang, Davies, & Reid, 1996).

Maize breeders usually focus on increasing grain yield in order to meet the rising food demand. To accelerate the breeding process,

breeders prefer to predict the grain yield at the seeding stage (e.g. using genomic selection) rather than in field trials, which can be expensive. Moreover, uniform seedling establishment is critical for yield stability (Amram et al., 2015). Several traits, including shoot and root lengths and dry weights, have been studied in maize seed-lings, and it has been shown that seedling and adult traits can be correlated (Abdel-Ghani et al., 2012). Furthermore, improvement of early maize seedling vigour is essential for adaptation to various en-vironmental stressors, such as low temperatures in central Europe and drought in Sub-Saharan Africa (Badu-Apraku & Fakorede, 2017; Hund et al., 2004). Deep sowing could help maintain the seeds at a stable temperature and ensure adequate moisture in the seed zone before germination (Zhang et al., 2012). However, the elongated mesocotyl is significantly associated with deep-seeding tolerance in maize because an elongated and vigorous mesocotyl could enhance the seedling's ability to push the coleoptile and plumule towards the soil surface when sown deeply (Niu, Wu, Liu, Wu, & Wang, 2019; Zhang et al., 2012). BRs and GAs control maize seedling elonga-tion by regulating cell elongation, thus, affecting shoot and root lengths, mesocotyl length (ML) and the root: shoot ratio (Hartwig et al., 2012; Pacifici, Polverari, & Sabatini, 2015). In addition, BRs and GAs are related to the seedling's tolerance to stressors, such as low temperatures and drought (Bajguz & Hayat, 2009; Colebrook, Thomas, Phillips, & Hedden, 2014; Krishna, 2003).

In this study, we used propiconazole (Pcz) and uniconazole (Ucz), which are inhibitors involved in biosynthesizing of BR and GAs, re-spectively, to assess the effects of BRs and GAs on maize doubled haploid (DH) lines, from physiological and genetic perspectives (Hartwig et al., 2012; Rademacher, 2000). The aim of this study was to characterize BR and GAs inhibitor responses of five seedling traits using 242 maize DH lines. Our specific objectives were to (a) calcu-late the phenotypic and genotypic coefficients of variance, heritabil-ities and phenotypic correlation coefficients among these five traits, (b) identify sensitivities towards BR and GAs inhibitor treatments and (c) determine the traits and lines with potential utility for plant breeders.

2  | MATERIAL S AND METHODS

2.1 | Plant materials

A panel of maize (Zea mays L.) BC3-derived DH lines was derived from BGEM BC1 DH lines, which were developed for the Germplasm Enhancement of Maize (GEM) project, following previously de-scribed procedures (Brenner, Blanco, Gardner, & Lübberstedt, 2012; Sanchez, Liu, Ibrahim, Blanco, & Lubberstedt, 2018). Briefly, various exotic maize landraces from the GEM project were used as donor parents, and two expired Plant Variety Protection (PVP) lines PHB47 and PHZ51, representing the Stiff Stalk and Non-Stiff Stalk heterotic groups, respectively, were used as recurrent parents. Subsequently, BC1 plants were used to produce BGEM BC1 DH lines, of which 20 BGEM BC1 DH lines were selected based on seedling total root

     |  3HU et al.

length. Nine BGEM BC1 DH lines with PHB47 background were backcrossed twice with PHB47 and 11 BGEM BC1 DH lines with PHZ51 background were backcrossed twice with PHZ51. BC3F1 plants were crossed with the inducer hybrid RWS-9 × RWK-76 to produce haploid seeds, which were identified using the R-nj colour marker (Liu et al., 2016; Roeber, Gordillo, & Geiger, 2005). During summer 2016, putative haploids were planted in the greenhouse and treated with colchicine at the 3–4 leaf developmental stage, following the procedure described by Vanous, Vanous, Frei and Lübberstedt (2017). Treated haploid plants were transplanted to the field (Agronomy Farm, Iowa State University, Ames, IA) and self-pol-linated to produce DH lines.

2.2 | Experimental design and seedling phenotyping

A total of 242 BC3-derived DH lines and recurrent parents, i.e., PHB47 and PHZ51, were used in this study. A paper roll assay was used to germinate seeds, as previously described (Abdel-Ghani, Sanchez, Kumar, & Lübberstedt, 2016). All DH lines were exposed to three independent treatments, either with 80 μM Pcz (BR bio-synthesis inhibitor), 80 μM Ucz (GAs biosynthesis inhibitor), or water (control). Each treatment was applied in three independent experiments completed October 31, 2017, November 14, 2017 and November 29, 2017 using a completely randomized design (CRD). For each treatment, six kernels were used per experiment, and seeds were grown following the procedure described in Hu et al. (2017).

Primary root length (PRL), shoot length (SL) and ML were mea-sured manually using a scaled ruler. PRL (cm) was measured from the root–shoot transition zone to the tip of the primary root. SL (cm) was measured from the first node to the tip of the seedling. ML (cm) was from the root–shoot zone to the first node of the seedlings. At the end of the trials, seedlings were oven dried at 55℃ for 48 hr, and the total dry weight (TDW) was measured (Pace, Gardner, Romay, Ganapathysubramanian, & Lubberstedt, 2015). Total seedling length (TSL) was calculated as a total of PRL, ML and SL. Sensitivity was calculated by dividing the trait values in the Pcz and Ucz treatments with the corresponding values in the treatment with water, for example:

where SMLP is the sensitivity of ML treated with Pcz, ML_P is the ML value when treated with Pcz and ML_W is the ML value when treated with water.

2.3 | Statistical analysis of phenotypic data

Four of six seedlings were selected from each experimental unit (each roll) for trait measurements to eliminate the effects of poorly germi-nated or non-germinated seedlings. Analysis of variance of seedling

traits was performed using the additive model yij = μ + Ei + Gj + εij (Hu et al., 2017), where yij represents the observation from the ijth experimental unit, μ is the overall mean, Ei is the effect of the ith experiment, Gj is the effect of the jth genotype and εij is the experi-mental error.

H2, or the broad sense heritability, was calculated using the fol-lowing formula (Pace et al., 2015):

where �2G and �2

P represent the genotypic and phenotypic variances,

respectively, calculated based on entry means, as follows:

Therefore, the equation for H2 could also be represented as:

where MSG is the mean square of genotype, MSE is the mean square of error and exp is the number of independent experiments (three).

Genotypic coefficient of variance (GCV) was calculated using the following formula (Singh & Chaudhary, 1979):

where �2G is the genotypic variance and x is the mean value for a given

trait.Genetic advance (GA) and genetic advance as percentage of

mean (GAM) were calculated as follows (Shukla et al., 2006):

where k = 2.06 at 5% selection intensity for the traits, �P is the pheno-typic standard deviation (SD), H2 is the broad sense heritability and x is the mean value for a given trait.

2.4 | Multivariate analysis

Means and SDs were calculated for each trait. These data were used to classify DH lines into three different classes, as described in Kumar, Abdel-Ghani, Reyes-Matamoros, Hochholdinger, and Lübberstedt (2012). A polymorphic diversity index was calculated

SMLP=ML_P

ML_W

H2=

�2G

�2P

�2G=

(

MSG−MSE

exp

)

�2P=

(

MSG−MSE

exp

)

+MSE

H2=

(

MSG−MSE

exp

)

(

MSG−MSE

exp

)

+MSE

GCV=

√

�2G

x

GAM=GA

x

4  |     HU et al.

TAB

LE 1

 Su

mm

ary

stat

istic

s fo

r 244

BC

3-D

H li

nes

unde

r the

thre

e tr

eatm

ents

. PH

Z51

and

PHB

47 in

dica

te th

e su

bset

s of

BC

3-D

H li

nes

with

PH

Z51

or P

HB

47 a

s th

e re

curr

ent p

aren

t, re

spec

tivel

y

Trai

tTr

eatm

ent

All

lines

PHZ5

1PH

B47

Min

.M

ax.

Mea

nSD

CV

Min

.M

ax.

Mea

nSD

CV

Min

.M

ax.

Mea

nSD

CV

PRL

Pcz

11.9

841

.83

28.1

04.

270.

1511

.98

41.8

328

.96

3.81

0.13

12.9

334

.78

25.1

34.

440.

18

Ucz

6.13

30.0

320

.23

4.03

0.20

10.9

030

.03

21.2

63.

370.

166.

1326

.03

16.6

14.

080.

25

Wat

er13

.15

47.4

533

.15

5.45

0.16

13.1

547

.45

33.4

15.

520.

1714

.83

41.6

332

.25

5.14

0.16

ML

Pcz

0.83

9.95

4.48

1.56

0.35

0.97

9.95

4.84

1.47

0.30

0.83

8.85

3.26

1.18

0.36

Ucz

0.35

6.70

2.78

1.29

0.46

0.90

6.70

3.22

1.09

0.34

0.35

3.13

1.25

0.56

0.45

Wat

er3.

4722

.60

11.9

82.

590.

223.

4722

.60

12.3

22.

620.

217.

0318

.50

10.8

12.

100.

19

SLPc

z1.

1511

.80

5.03

1.63

0.32

1.15

9.07

4.70

1.40

0.30

3.20

11.8

06.

141.

840.

30

Ucz

1.43

6.03

3.72

0.68

0.18

1.60

6.03

3.83

0.66

0.17

1.43

4.60

3.35

0.60

0.18

Wat

er1.

4715

.55

5.58

2.06

0.37

1.47

12.2

54.

801.

190.

252.

9015

.55

8.28

2.15

0.26

TDW

Pcz

0.09

0.32

0.20

0.03

0.17

0.10

0.32

0.21

0.03

0.16

0.09

0.32

0.19

0.03

0.18

Ucz

0.10

0.33

0.21

0.03

0.16

0.10

0.30

0.21

0.03

0.16

0.12

0.33

0.21

0.03

0.16

Wat

er0.

110.

300.

200.

030.

170.

110.

300.

200.

030.

160.

110.

300.

180.

030.

18

TSL

Pcz

15.7

854

.30

37.6

35.

220.

1415

.78

54.3

038

.53

4.90

0.13

19.9

748

.17

34.5

35.

100.

15

Ucz

10.0

738

.53

26.7

45.

170.

1915

.43

38.5

328

.32

4.17

0.15

10.0

731

.87

21.2

14.

480.

21

Wat

er23

.08

66.2

050

.72

6.96

0.14

23.0

864

.73

50.5

37.

040.

1429

.90

66.2

051

.36

6.66

0.13

Abb

revi

atio

ns: D

H, d

oubl

ed h

aplo

id; M

L, m

esoc

otyl

leng

th; P

RL, p

rimar

y ro

ot le

ngth

; SD

, sta

ndar

d de

viat

ion;

SL,

sho

ot le

ngth

; TD

W, t

otal

dry

wei

ght;

TSL,

Tot

al s

eedl

ing

leng

th.

     |  5HU et al.

from the frequency data, from the low-, medium- and high-perform-ing categories for each trait, to evaluate the Shannon-Weaver di-versity index (H′) for each seedling trait. H′ was calculated using the following formula (Hutcheson, 1970):

where Pi is the ratio of individuals in the ith category of an n–category character and n is the number of phenotypic categories.

Best linear unbiased prediction (BLUP) was used to adjust means for each trait. Phenotypic correlation coefficients were calculated using the IBM SPSS 22.0 software.

The BLUP value of each trait was normalized for cluster analysis by Z-scores in IBM SPSS 22.0, to avoid effects of scaling differences. JMP 13 software (SAS Institute Inc.) was used for cluster analysis.

3  | RESULTS

3.1 | Phenotypic descriptive statistics and distribution

Considerable variation and diversity were observed for all traits in the BC3-DH panel in all three treatments (Pcz, Ucz and water). All trait values were higher in the water treatment than in the Pcz and Ucz treatments, except TDW (Table 1). Mixed model analysis revealed significant differences (p = .01) among the DH lines for all traits, in pairwise comparisons of the three different treatments. Significant differences (p = .05) were found between DH lines with PHB47 and PHZ51 backgrounds, except for TSL in water treatment (Table S1). All trait values displayed wide ranges, with PRL ranging from 12.0 to 41.8, 6.1 to 30.0 and 13.2 to 47.5 cm in the Pcz, Ucz and water treatments, respectively, and ML from 0.83 to 9.95, 0.35 to 6.70 and 3.47 to 22.60 cm in the three treatments, respectively (Table 1). ML and SL displayed very high CV values, ranging from 0.22 to 0.46 and from 0.18 to 0.37, respectively, for the three differ-ent treatments. TSL exhibited extremely low CV values of 0.14, 0.19 and 0.14 in the Pcz, Ucz and water treatments, respectively, indicat-ing that total root lengths were very stable.

Most lines fell into the medium category (ranging from 0.63 to 0.76) for all traits (Table 2). The H′ value for all traits ranged from 0.72 to 0.91. ML exhibited very high H′ values, ranging from 0.81 to 0.89 for the three different treatments, whereas SL presented lower values, ranging from 0.74 to 0.82. All other seedling traits exhibited H′ values greater than 0.72 in the three different treatments.

3.2 | Sensitivity of DH lines to BR and GAs inhibitors

Sensitivity was calculated as the ratio of seedling traits under Pcz or Ucz with those in the water treatment. For all maize DH lines

studied, PRL, ML and SL values were lower in the Pcz and Ucz treat-ments than in the water treatment (Figure 1). Overall, the sensitivity to Ucz was higher than that to Pcz, and this difference was signifi-cant (Table S2). ML had the highest sensitivity to the Ucz treatment, and SL had the lowest sensitivity to the Pcz treatment. Sensitivities of PRL, ML and SL were different between the PHB47 and PHZ51 groups, with higher sensitivity observed in the PHB47 group for these traits. All differences between the two groups were signifi-cant (Table S2).

Doubled haploid lines K054N, K161S and PHB47 were highly sen-sitive to Pcz and Ucz treatments, while DH lines K084N and K108N showed low sensitivity to these treatments (Table 3). Majority of high-performing lines were from the PHB47 background. The high sensitivity of ML ranged from 0.20 to 0.24 and from 0.07 to 0.09 in the Pcz and Ucz treatments respectively. Low-performing lines were obtained from the PHZ51 background, except K146S (0.54). The low sensitivity of ML ranged from 0.51 to 0.60 and from 0.38 to 0.52 in the Pcz and Ucz treatments, respectively.

3.3 | Heritability, genetic coefficient of variance and genetic advance estimates

The H2 estimates ranged widely, with values between 0.41 and 0.70, 0.39 and 0.79 and 0.44 and 0.82 in the Pcz, Ucz and water

H�=−

n∑

i=1

PilnPi

TA B L E 2   Frequency distribution and Shannon-Weaver diversity index (H′) for seedling traits under Pcz, Ucz and water treatments

Trait Treatment

Frequencya 

H′Small Medium High

PRL Pcz 0.12 0.76 0.12 0.72

Ucz 0.16 0.69 0.15 0.84

Water 0.20 0.63 0.17 0.91

ML Pcz 0.16 0.69 0.15 0.84

Ucz 0.18 0.65 0.17 0.89

Water 0.15 0.70 0.15 0.81

SL Pcz 0.14 0.72 0.14 0.79

Ucz 0.14 0.70 0.16 0.82

Water 0.10 0.75 0.15 0.74

TDW Pcz 0.16 0.72 0.12 0.78

Ucz 0.16 0.71 0.13 0.80

Water 0.14 0.72 0.14 0.79

TSL Pcz 0.13 0.74 0.13 0.76

Ucz 0.18 0.67 0.16 0.87

Water 0.18 0.67 0.15 0.86

Abbreviations: ML, mesocotyl length; PRL, primary root length; SD, standard deviation; SL, shoot length; TDW, total dry weight; TSL, Total seedling length.aSmall is the proportion of low performing lines with non-favourable root characteristics [≤x − SD], medium is the proportion of lines with medium performance [≥x − SD] to [≤x + SD] and high is the proportion of line with high performance [≥x + SD].

6  |     HU et al.

treatments respectively (Table 4). H2 estimates were the lowest under treatment with Pcz, whereas the highest values were ob-served in the water treatment. In general, H2 estimates were higher for ML than for other traits, and heritability of PRL was the lowest in the three different experiments. The GCV value of TSL was the lowest (0.08), while that of ML was the highest (0.41) in the water treatment. The GCV values in the lines treated with Pcz (0.20) and Ucz (0.21) were higher than those under treatment with water (0.18). The GA estimates for PRL (3.64 cm) and TSL (5.66 cm) were higher than those for other traits, and GAM of ML in the Ucz treatment (74%) was higher than that for other traits (Table 4).

3.4 | Correlation of phenotypic seedling traits

Significant positive trait correlations were observed, with correlation coefficients ranging from 0.13 to 0.96 (Table 5). A positive correlation was observed between PRL and TSL, with correlation coefficients of 0.91, 0.96 and 0.84 in the Pcz, Ucz and water treatments, respec-tively. The correlation coefficients between ML and TSL in Pcz, Ucz and water treatments were .64, .76 and .47, respectively. A weak negative correlation was found between SL and TDW in the Pcz and water treatments (r = −.14 and −.29), but it was not significant in the Ucz treatment. Significant correlations were detected between

TSL and other traits in all three treatments, except between TSL and TDW in water treatment.

3.5 | Genetic distance analysis

Genetic distance was calculated based on all seedling-related traits, as Euclidean distance (Figure 2). All DH lines were divided into two main groups. The first group contained 202 lines, named, Group 1, including PHZ51, with higher ML, whereas the second group con-tained 42 DH lines, named, Group 2 including PHB47, with lower ML. The first group was further divided into two subgroups. The sec-ond subgroup (including recurrent parent PHZ51) contained 93 DH lines named group 1–2, and exhibited the highest PRL and ML in the three treatments (Table 6). In general, the two main groups consisted of two sets of maize inbred lines with PHB47 or PHZ51 as the recur-rent parent. However, some DH lines were assigned to the other re-current parent group. For instance, K163N with PHZ51 background was assigned to the PHB47 group, and 14 BC3-derived DH lines with PHB47 background were assigned to the PHZ51 group. Genetic dis-tances ranged from 1.27 to 19.94. The mean genetic distance of all BC3-derived DH lines was 6.95, that of PHB47-based DH lines to PHB47 was 7.54 and of PHZ51-based DH lines to PHZ51 was 5.29. K055N and K161S exhibited the largest genetic distance, while the

F I G U R E 1   Mean sensitivity of PRL, ML, SL and TDW to brassinosteroid and gibberellin inhibitors. ML, mesocotyl length; PRL, primary root length; SL, shoot length; TDW, total dry weight; TSL, total seedling length

     |  7HU et al.

lowest genetic distance was obtained between K096N and K121N, from the group 1–2.

4  | DISCUSSION

4.1 | Reliability of data and consistency with previous studies

Paper roll assays can efficiently determine maize seedling traits, and they have been extensively used to study root traits. These assays are less laborious and require less time and space than hydroponics for hormone inhibitor studies. A previous study indicated that seed-ling traits can be significantly correlated with agronomic traits, such as silking, anthesis–silking interval and grain yield (Hu et al., 2017).

Trait heritabilities have profound significance in designing op-timal strategies for selecting traits of interest and calculating ex-pected genetic gain. Heritabilities in this study ranged from 0.39 to 0.82, indicating that these seedling traits can be reliably evaluated. Heritabilities relating to mesocotyl were much higher than those for other traits, indicating that there was greater genetic variation in ML in our experimental population. Heritability values for PRL were around 0.40 in the Pcz, Ucz and water treatments, which is slightly lower than values reported in previous studies (Kumar et al., 2012; Pace et al., 2015; Sanchez et al., 2018) involving other populations.

This difference might be due to maize seedling growth in darkness for eight days in our treatment.

4.2 | Performance of seedling traits in different treatments and subgroups

Plant hormones are small molecules, ubiquitous in higher plants. They are essential for regulating plant growth and development, and in the plants’ responses to biotic and abiotic stress. Substantial ge-netic variation was observed for various seedling traits in different hormone inhibitor and water treatments. Ucz had a stronger effect on PRL, ML and SL than Pcz, particularly on ML. These findings are consistent with those of a previous study which reported greater ML sensitivity to Ucz than to Pcz (Hu et al., 2017). Sensitivities of PRL, ML and SL were different between the two recurrent parent groups. The PHZ51 group was more tolerant than the PHB47 group, and all low-performing lines were from the PHZ51 group, except for K146S.

4.3 | Dendrogram, diversity index and correlations

The BC3-DH lines were clustered into two groups, according to re-current parent backgrounds. However, one BC3-derived DH line with genetic background of PHZ51 was assigned to the PHB47 group,

TA B L E 3   Ten highest and lowest performing lines based on sensitivity of mesocotyl length to Pcz and Ucz treatments

Category Line SML_P Line SML_U

High-performing line K256S 0.20 K114S 0.07

K054N 0.21 K136S 0.08

K231S 0.22 K137S 0.08

K254S 0.23 K115S 0.08

K090N 0.23 K248S 0.08

K112S 0.24 K054N 0.09

K111S 0.24 PHB47 0.09

PHB47 0.24 K161S 0.09

K138S 0.24 K247S 0.09

K161S 0.24 K135S 0.09

Low-performing line K091N 0.51 K026N 0.38

K071N 0.51 K060N 0.39

K076N 0.51 K237N 0.40

K074N 0.52 K180N 0.40

K146S 0.54 K108N 0.42

K084N 0.54 K101N 0.43

K235N 0.55 K087N 0.45

K080N 0.55 K084N 0.48

K173N 0.59 K106N 0.49

K108N 0.60 K221N 0.52

Note: SML_P indicates sensitivity of mesocotyl length to Pcz treatment.SML_U indicates sensitivity of mesocotyl length to Ucz treatment.

8  |     HU et al.

and 14 lines with genetic background of PHB47 were clustered into the PHZ51 group. Although these lines have higher similarity with their recurrent parents, their seedling traits showed a higher similar-ity with the other group. However, different results can be expected when using DNA markers to group these DH lines.

High H′ values were observed for seedling attributes, indicating a wide range of variation in these seedling traits (Kumar et al., 2012). ML

exhibited the highest H′ values, and explained most variation among the DH lines in this study. Thus, ML was the most important trait for explaining phenotypic variation, especially in the Ucz treatment group.

4.4 | Sensitivity of seedling traits to different treatments

Mean sensitivity of PRL, ML and SL was below 1.0 for all 242 maize DH lines, however, the mean sensitivity for TDW was around 1.0. It may be because BR and GAs regulate cell elongation, rather than cell number, at the seedling stage. Seedlings in the inhibitor treat-ments were found to be stockier than in the water treatment (Hu et al., 2017). For Pcz/Ucz treatments, sensitivity of PRL, ML and SL was ranked in the following order: ML > PRL > SL. This is consistent with previous research (Hartwig et al., 2012). This indicates tissue-specific sensitivity towards Pcz and Ucz. SL was measured from the first node to the tip of the seedling, which is mainly composed of the coleoptile. Its main role is support of juvenile leaves during soil pen-etration, originates directly from the proembryo and not from the apical meristem like true leaves. Tissue-specific sensitivity of Pcz/Ucz in the primary root, mesocotyl and shoot alludes to differential BR/GAs biosynthesis and/or signal transduction for different maize tissues.

All the sensitivities of PRL, ML and SL are normally distributed for Pcz and Ucz treatments. Sensitivity of PRL, ML and SL of PHZ51 was significantly lower than for PHB47. Meanwhile sensitivities of PRL, ML and SL for PHZ51 background were significantly lower than those for PHB47 background in the Pcz and Ucz treatments. This result illustrates that lines with PHZ51 background were more toler-ant to Pcz and Ucz treatments. The abovementioned results suggest that genetic diversity between these maize lines influences their re-sponse to Pcz and Ucz. A previous study indicates that A619 (NSS) was more resistant to Pcz than B73 (BSS) (Hartwig et al., 2012). PHZ51 belongs to the NSS heterotic group, PHB47 to the BSS heterotic group. Whether increased resistance to Pcz and Ucz is a feature of the NSS heterotic group compared to the BSS heterotic group needs further experimental verification.

Sensitivities of PRL, ML and SL in the Pcz treatment were sig-nificantly lower than those in the Ucz treatment, indicating that Ucz (i.e. GAs inhibitor) exerts a stronger effect than Pcz (i.e. BR inhibi-tor). However, Ucz did not have a strong effect on the sensitivity of TDW. ML was found to be more sensitive than PRL and SL in both Pcz and Ucz treatments, which is consistent with previous results (Hu et al., 2017). Therefore, we can conclude that ML of BC3-DH lines with PHB47 background in the Ucz treatment shows the high-est sensitivity.

4.5 | Application in genetics and breeding of maize

With global climate change, droughts become more frequent and severe (Dai, 2011; Vicente-Serrano, Quiring, Peña-Gallardo, Yuan,

TA B L E 4   Heritability, genetic coefficient of variation, genetic advance and genetic advance as percentage of mean of seedling traits in the three treatments

Trait Treatment H2 GCV GA GAM

PRL Pcz 0.41 0.10 3.64 0.13

Ucz 0.39 0.12 3.16 0.16

Water 0.44 0.09 4.13 0.12

ML Pcz 0.70 0.29 2.26 0.50

Ucz 0.79 0.41 2.07 0.74

Water 0.64 0.17 3.40 0.28

SL Pcz 0.58 0.24 1.92 0.38

Ucz 0.59 0.14 0.83 0.22

Water 0.82 0.33 3.42 0.61

TDW Pcz 0.70 0.14 0.05 0.24

Ucz 0.70 0.14 0.05 0.24

Water 0.67 0.13 0.05 0.23

TSL Pcz 0.49 0.10 5.28 0.14

Ucz 0.50 0.13 5.26 0.20

Water 0.53 0.08 6.44 0.13

Abbreviations: ML, mesocotyl length; PRL, primary root length; SL, shoot length; TDW, total dry weight; TSL, Total seedling length.

TA B L E 5   Pearson correlation coefficients of five seedling traits in Pcz, Ucz and water treatments

Trait Treatment ML SL TDW TSL

PRL Pcz 0.44** −0.07 0.17** 0.91**

Ucz 0.59** 0.44** 0.11 0.96**

Water 0.10 0.15* 0.09 0.84**

ML Pcz −0.10 0.19** 0.64**

Ucz 0.33** 0.16* 0.76**

Water −0.15* 0.09 0.47**

SL Pcz −0.14* 0.23**

Ucz 0.07 0.56**

Water −0.29** 0.43**

TDW Pcz 0.16*

Ucz 0.13*

Water −0.01

Abbreviations: ML, mesocotyl length; ns, non-significant; PRL, primary root length; SL, shoot length; TDW, total dry weight; TSL, Total seedling length.**Significant at p = .01. *Significant at p = .05.

     |  9HU et al.

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& Domínguez-Castro, 2020). Deep sowing is an effective meas-ure to ensure that seeds absorb water from the deep soil layer and emerge normally in arid and semi-arid regions. It also prevents dam-age from the surface application of harmful chemicals (Niu, Hao, Wu, & Wang, 2020). Mesocotyl elongation acts as the single crucial re-sponse to make germplasm tolerant to deep sowing (Troyer, 1997; Zhao et al., 2010). ML correlates closely with the deep-sowing ger-mination rate. Mesocotyl elongation is significantly induced by deep sowing. Successful breaking and emergence of seeds from the deep soil depend on mesocotyl elongation.

In this study, substantial differences were observed in ML of the BC3-DH lines in the three treatments. In addition, ML exhib-ited a high level of heritability, suggesting its suitability as a selec-tion organ to evaluate stress and deep-sowing tolerance during the early seedling stage. For example, ML of 14 of the 242 DH lines was greater than 15 cm. These DH lines could provide valuable breeding resources for improving abiotic stress tolerance, which can be used for deep sowing, and to improve the tolerance of inbred maize lines to low temperature and drought. DH lines K060N and K058N, de-rived from the ELOTES OCCIDENT DGO236 (PI 484828) accession in PHZ51 background, exhibited ML of 8.8 and 18.9 cm, respectively, in the water treatment. DH lines K090N and K080N were derived from the same donor germplasm, i.e. Arizona-LIB 16 (PI 485359), in the PHZ51 background. However, while the ML sensitivity of the DH line K090N was high in the Pcz treatment that of the DH line K080N was low. This isogenic pair of lines may aid in understand-ing the mechanisms underlying mesocotyl growth and development. It will facilitate breeding maize cultivars with long mesocotyls and deep-sowing tolerance.

Modern maize varieties have been selected for productivity at high planting density and for reduced shade-avoidance response (Fellner, Ford, & Van Volkenburgh, 2006; Niu et al., 2020). When crops grow under shade conditions, responses include increased growth of the hypocotyl and stem, as well as leaf hyponasty and peti-ole extension, and involve the action of multiple hormones, including auxin, ethylene, brassinosteriods and GAs (Colebrook et al., 2014). Modern maize shows a generally reduced sensitivity to hormones. Some DH lines in our study had elongated mesocotyl in the water

treatment, but showed no response to Pcz and Ucz. These DH lines are not susceptible to hormone deficiency. This may be desirable to increase crop yields.

PHB47 and PHZ51 are two expired PVP inbred lines, represent-ing the Stiff Stalk and Non-Stiff Stalk heterotic groups, respectively, and were used as recurrent parents. Fourteen various exotic maize landraces from the GEM project were used as donor parents. These isogenic lines exceeded the performance of PHB47 and PHZ51. For instance, K138S was derived from a cross between PHB47 and CON PUNT CUZ13(Ames 28653). The mesocotyl of K138S was substan-tially longer (16.31 cm) than that of PHB47 (9.88 cm). These results indicate that Ames 28653 carries one or more chromosome seg-ments increasing ML. The abovementioned results suggest that the population used in our study might be used to improve other phe-notypes, relevant for modern maize breeding to improve PVP inbred lines PHB47 and PHZ51, or more recent elite germplasm.

ACKNOWLEDG EMENTSThe authors would like to thank USDA's National Institute of Food and Agriculture (Project numbers: IOW04314 and IOW05520), the RF Baker Center for Plant Breeding, the Plant Sciences Institute at Iowa State University for supporting this work and China Scholarship Council for Kun Hu's funding.

CONFLIC T OF INTERE S TThe authors declare that they have no conflict of interest. This arti-cle does not contain any studies involving animals or human partici-pants performed by any of the authors.

AUTHOR CONTRIBUTIONSKH and TL conceived the study, designed the experiments, discussed the results and finalized the manuscript. KH, YX, CW and UF per-formed the experiments. KH analysed the data. UF provided the DH line seeds. TL edited the manuscript. All authors read and approved the final manuscript. All authors have no conflicts on the rights.

ORCIDKun Hu https://orcid.org/0000-0002-5655-274X

Treatment Group Count PRL ML SL TDW TSL

Pcz Group 1-1 109 27.91 4.18 5.02 0.20 37.17

Group 1-2 93 29.27 5.39 4.55 0.21 39.28

Group 2 42 26.02 3.29 6.10 0.19 35.31

Ucz Group 1-1 109 20.33 2.62 3.88 0.21 26.88

Group 1-2 93 21.21 3.64 3.66 0.22 28.53

Group 2 42 17.63 1.22 3.40 0.21 22.18

Water Group 1-1 109 33.86 11.63 5.15 0.19 49.71

Group 1-2 93 33.39 12.92 4.61 0.21 51.04

Group 2 42 33.21 10.72 8.79 0.18 52.30

Abbreviations: ML, mesocotyl length; PRL, primary root length; SL, shoot length; TDW, total dry weight; TSL, Total seedling length.

TA B L E 6   Mean trait values in the three treatments in cluster analysis

     |  11HU et al.

R E FE R E N C E SAbdel-Ghani, A. H., Kumar, B., Reyes-Matamoros, J., Gonzalez-Portilla,

P. J., Jansen, C., Martin, J. P. S., … Lübberstedt, T. (2012). Genotypic variation and relationships between seedling and adult plant traits in maize (Zea mays L.) inbred lines grown under contrasting nitrogen levels. Euphytica, 189(1), 123–133. https://doi.org/10.1007/s1068 1-012-0759-0

Abdel-Ghani, A., Sanchez, D., Kumar, B., & Lübberstedt, B. (2016). Paper roll culture and assessment of root parameters. Bio-Protocol, 6, e1926.

Amram, A., Fadida-Myers, A., Golan, G., Nashef, K., Ben-David, R., & Peleg, Z. (2015). Effect of GA-sensitivity on wheat early vigor and yield components under deep sowing. Frontiers in Plant Science, 6, 487. https://doi.org/10.3389/fpls.2015.00487

Anwar, A., Liu, Y., Dong, R., Bai, L., Yu, X., & Li, Y. (2018). The physiological and molecular mechanism of brassinosteroid in response to stress: A review. Biological Research, 51(1), 46. https://doi.org/10.1186/s4065 9-018-0195-2

Badu-Apraku, B., & Fakorede, M. A. B. (2017). Improvement of early and extra-early maize for combined tolerance to drought and heat stress in sub-Saharan Africa. In B. Badu-Apraku & M. A. B. Fakorede (Eds.), Advances in Genetic Enhancement of Early and Extra-Early Maize for Sub-Saharan Africa (pp. 311–358). Cham, Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-64852 -1

Bajguz, A., & Hayat, S. (2009). Effects of brassinosteroids on the plant re-sponses to environmental stresses. Plant Physiology and Biochemistry, 47(1), 1–8. https://doi.org/10.1016/j.plaphy.2008.10.002

Baud, S., Dichow, N. R., Kelemen, Z., d’Andréa, S., To, A., Berger, N., … Miquel, M. (2009). Regulation of HSD1 in seeds of Arabidopsis thaliana. Plant and Cell Physiology, 50(8), 1463–1478. https://doi.org/10.1093/pcp/pcp092

Brenner, E. A., Blanco, M., Gardner, C., & Lübberstedt, T. (2012). Genotypic and phenotypic characterization of isogenic doubled haploid exotic introgression lines in maize. Molecular Breeding, 30(2), 1001–1016. https://doi.org/10.1007/s1103 2-011-9684-5

Cano-Delgado, A., Yin, Y., Yu, C., Vafeados, D., Mora-Garcia, S., Cheng, J. C., … Chory, J. (2004). BRL1 and BRL3 are novel brassinosteroid receptors that function in vascular differentiation in Arabidopsis. Development, 131(21), 5341–5351. https://doi.org/10.1242/dev.01403

Cao, L., Yuan, S., Zhou, H., Zhan, X., Wu, W., Gao, J., & Cheng, S. (2005). Effect of different hormones on mesocotyl length in Oryza sativa L. Acta Agronomica Sinica., 31(8), 1098–1100.

Castorina, G., Persico, M., Zilio, M., Sangiorgio, S., Carabelli, L., & Consonni, G. (2018). The maize lilliputian1 (lil1) gene, encoding a brassinosteroid cytochrome P450 C-6 oxidase, is involved in plant growth and drought response. Annals of Botany, 122(2), 227–238. https://doi.org/10.1093/aob/mcy047

Che, R., Tong, H., Shi, B., Liu, Y., Fang, S., Liu, D., … Wang, H. (2015). Control of grain size and rice yield by GL2-mediated brassinosteroid responses. Nature Plants, 2(1), 1–8.

Chen, L., Higashitani, A., Suge, H., Takeda, K., & Takahashi, H. (2003). Spiral growth and cell wall properties of the gibberellin-treated first internodes in the seedlings of a wheat cultivar tolerant to deep-sow-ing conditions. Physiologia Plantarum, 118(1), 147–155. https://doi.org/10.1034/j.1399-3054.2003.00093.x

Chen, L., Nishizawa, T., Higashitani, A., Suge, H., Wakui, Y., Takeda, K., & Takahashi, H. (2001). A variety of wheat tolerant to deep-seed-ing conditions: Elongation of the first internode depends on the re-sponse to gibberellin and potassium. Plant, Cell & Environment, 24(4), 469–476. https://doi.org/10.1046/j.1365-3040.2001.00688.x

Choe, S., Fujioka, S., Noguchi, T., Takatsuto, S., Yoshida, S., & Feldmann, K. A. (2001). Overexpression of DWARF4 in the brassinosteroid bio-synthetic pathway results in increased vegetative growth and seed

yield in Arabidopsis. The Plant Journal, 26(6), 573–582. https://doi.org/10.1046/j.1365-313x.2001.01055.x

Clouse, S. D. (2008). The molecular intersection of brassinosteroid-regu-lated growth and flowering in Arabidopsis. Proceedings of the National Academy of Sciences, 105(21), 7345-7346. https://doi.org/10.1073/pnas.08035 52105

Clouse, S. D., & Sasse, J. M. (1998). Brassinosteroids: Essential reg-ulators of plant growth and development. Annual Review of Plant Biology, 49(1), 427–451. https://doi.org/10.1146/annur ev.arpla nt.49.1.427

Colebrook, E. H., Thomas, S. G., Phillips, A. L., & Hedden, P. (2014). The role of gibberellin signalling in plant responses to abiotic stress. Journal of Experimental Biology, 217(1), 67–75. https://doi.org/10.1242/jeb.089938

Dai, A. (2011). Drought under global warming: A review. Wires Climate Change, 2(1), 45–65. https://doi.org/10.1002/wcc.81

De Jong, M., Mariani, C., & Vriezen, W. H. (2009). The role of auxin and gibberellin in tomato fruit set. Journal of Experimental Botany, 60(5), 1523–1532. https://doi.org/10.1093/jxb/erp094

Dhaubhadel, S., Chaudhary, S., Dobinson, K. F., & Krishna, P. (1999). Treatment with 24-epibrassinolide, a brassinosteroid, increases the basic thermotolerance of Brassica napus and tomato seedlings. Plant Molecular Biology, 40(2), 333–342. https://doi.org/10.1023/a:10062 83015582

Dorcey, E., Urbez, C., Blázquez, M. A., Carbonell, J., & Perez-Amador, M. A. (2009). Fertilization-dependent auxin response in ovules triggers fruit development through the modulation of gibberellin metabo-lism in Arabidopsis. The Plant Journal, 58(2), 318–332. https://doi.org/10.1111/j.1365-313X.2008.03781.x

Fellner, M., Ford, E. D., & Van Volkenburgh, E. (2006). Development of erect leaves in a modern maize hybrid is associated with re-duced responsiveness to auxin and light of young seedlings in vitro. Plant Signaling & Behavior, 1(4), 201–211. https://doi.org/10.4161/psb.1.4.3106

Flintham, J., Börner, A., Worland, A., & Gale, M. (1997). Optimizing wheat grain yield: Effects of Rht (gibberellin-insensitive) dwarfing genes. The Journal of Agricultural Science, 128(1), 11–25.

Fujii, S., & Saka, H. (2015). Distribution of assimilates to each organ in rice plants exposed to a low temperature at the ripening stage, and the effect of brassinolide on the distribution. Plant Production Science, 4(2), 136–144. https://doi.org/10.1626/pps.4.136

Grove, M. D., Spencer, G. F., Rohwedder, W. K., Mandava, N., Worley, J. F., Warthen, J. D., … Cook, J. C. (1979). Brassinolide, a plant growth-promoting steroid isolated from Brassica napus pollen. Nature, 281(5728), 216. https://doi.org/10.1038/281216a0

Guo, G., Liu, X., Sun, F., Cao, J., Huo, N. A., Wuda, B., … Yao, Y. (2018). Wheat miR9678 affects seed germination by generating phased siR-NAs and modulating abscisic acid/gibberellin signaling. The Plant Cell, 30(4), 796–814. https://doi.org/10.1105/tpc.17.00842

Hacham, Y., Holland, N., Butterfield, C., Ubeda-Tomas, S., Bennett, M. J., Chory, J., & Savaldi-Goldstein, S. (2011). Brassinosteroid perception in the epidermis controls root meristem size. Development, 138(5), 839–848. https://doi.org/10.1242/dev.061804

Hao, J., Yin, Y., & Fei, S. Z. (2013). Brassinosteroid signaling network: Implications on yield and stress tolerance. Plant Cell Reports, 32(7), 1017–1030. https://doi.org/10.1007/s0029 9-013-1438-x

Hartwig, T., Chuck, G. S., Fujioka, S., Klempien, A., Weizbauer, R., Potluri, D. P. V., … Schulz, B. (2011). Brassinosteroid control of sex deter-mination in maize. Proceedings of the National Academy of Sciences, 108(49), 19814–19819. https://doi.org/10.1073/pnas.11083 59108

Hartwig, T., Corvalan, C., Best, N. B., Budka, J. S., Zhu, J.-Y., Choe, S., & Schulz, B. (2012). Propiconazole Is a Specific and Accessible Brassinosteroid (BR) Biosynthesis Inhibitor for Arabidopsis and Maize. PLoS One, 7(5), e36625. https://doi.org/10.1371/journ al.pone.0036625

12  |     HU et al.

Hasan, S. A., Hayat, S., & Ahmad, A. (2011). Brassinosteroids protect photosynthetic machinery against the cadmium induced oxidative stress in two tomato cultivars. Chemosphere, 84(10), 1446–1451. https://doi.org/10.1016/j.chemo sphere.2011.04.047

Hong, Z., Ueguchi-Tanaka, M., Fujioka, S., Takatsuto, S., Yoshida, S., Hasegawa, Y., … Matsuoka, M. (2005). The Rice brassinosteroid-de-ficient dwarf2 mutant, defective in the rice homolog of Arabidopsis DIMINUTO/DWARF1, is rescued by the endogenously accumulated alternative bioactive brassinosteroid, dolichosterone. The Plant Cell, 17(8), 2243–2254. https://doi.org/10.1105/tpc.105.030973

Hu, S., Sanchez, D. L., Wang, C., Lipka, A. E., Yin, Y., Gardner, C. A. C., & Lubberstedt, T. (2017). Brassinosteroid and gibberellin control of seedling traits in maize (Zea mays L.). Plant Science, 263, 132–141. https://doi.org/10.1016/j.plant sci.2017.07.011

Hund, A., Fracheboud, Y., Soldati, A., Frascaroli, E., Salvi, S., & Stamp, P. (2004). QTL controlling root and shoot traits of maize seedlings under cold stress. Theoretical and Applied Genetics, 109(3), 618–629. https://doi.org/10.1007/s0012 2-004-1665-1

Hutcheson, K. (1970). A test for comparing diversities based on the Shannon formula. Journal of Theoretical Biology, 29(1), 151–154. https://doi.org/10.1016/0022-5193(70)90124 -4

Kim, S. Y., Warpeha, K. M., & Huber, S. C. (2019). The brassinosteroid re-ceptor kinase, BRI1, plays a role in seed germination and the release of dormancy by cold stratification. Journal of Plant Physiology, 241, 153031. https://doi.org/10.1016/j.jplph.2019.153031

Koh, S., Lee, S.-C., Kim, M.-K., Koh, J. H., Lee, S., An, G., … Kim, S.-R. (2007). T-DNA tagged knockout mutation of rice OsGSK1, an or-thologue of Arabidopsis BIN2, with enhanced tolerance to various abiotic stresses. Plant Molecular Biology, 65(4), 453–466. https://doi.org/10.1007/s1110 3-007-9213-4

Krishna, P. (2003). Brassinosteroid-Mediated Stress Responses. Journal of Plant Growth Regulation, 22(4), 289–297. https://doi.org/10.1007/s0034 4-003-0058-z

Kumar, B., Abdel-Ghani, A. H., Reyes-Matamoros, J., Hochholdinger, F., & Lübberstedt, T. (2012). Genotypic variation for root architecture traits in seedlings of maize (Zea mays L.) inbred lines. Plant Breeding, 131(4), 465–478. https://doi.org/10.1111/j.1439-0523.2012.01980.x

Li, J., Sima, W., Ouyang, B. O., Wang, T., Ziaf, K., Luo, Z., … Ye, Z. (2012). Tomato SlDREB gene restricts leaf expansion and internode elonga-tion by downregulating key genes for gibberellin biosynthesis. Journal of Experimental Botany, 63(18), 6407–6420. https://doi.org/10.1093/jxb/ers295

Li, W., Ge, F., Qiang, Z., Zhu, L., Zhang, S., Chen, L., … Fu, Y. (2019). Maize ZmRPH1 encodes a microtubule-associated protein that controls plant and ear height. Plant Biotechnology Journal, 18(6), 1345–1347. https://doi.org/10.1111/pbi.13292

Liu, S., Zhang, Y., Feng, Q., Qin, L., Pan, C., Lamin-Samu, A. T., & Lu, G. (2018). Tomato AUXIN RESPONSE FACTOR 5 regulates fruit set and devel-opment via the mediation of auxin and gibberellin signaling. Scientific Reports, 8(1), 2971. https://doi.org/10.1038/s4159 8-018-21315 -y

Liu, Z., Wang, Y., Ren, J., Mei, M., Frei, U. K., Trampe, B., & Lübberstedt, T. (2016). Maize doubled haploids. Plant Breeding Reviews, 40, 123.

Luo, M., Xiao, Y., Li, X., Lu, X., Deng, W., Li, D., … Pei, Y. (2007). GhDET2, a steroid 5α-reductase, plays an important role in cotton fiber cell initiation and elongation. The Plant Journal, 51(3), 419–430. https://doi.org/10.1111/j.1365-313X.2007.03144.x

Makarevitch, I., Thompson, A., Muehlbauer, G. J., & Springer, N. M. (2012). Brd1 gene in maize encodes a brassinosteroid C-6 oxidase. PLoS One, 7(1), e30798. https://doi.org/10.1371/journ al.pone.0030798

Niu, L., Hao, R., Wu, X., & Wang, W. (2020). Maize mesocotyl: Role in response to stress and deep-sowing tolerance. Plant Breeding, 139, 466–473. https://doi.org/10.1111/pbr.12804

Niu, L., Wu, Z., Liu, H., Wu, X., & Wang, W. (2019). 2-DE-based pro-teomic analysis of protein changes associated with etiolated

mesocotyl growth in Zea mays. BMC Genomics, 20(1), 758. https://doi.org/10.1186/s1286 4-019-6109-z

Pace, J., Gardner, C., Romay, C., Ganapathysubramanian, B., & Lubberstedt, T. (2015). Genome-wide association analysis of seed-ling root development in maize (Zea mays L.). BMC Genomics, 16, 47. https://doi.org/10.1186/s1286 4-015-1226-9

Pacifici, E., Polverari, L., & Sabatini, S. (2015). Plant hormone cross-talk: The pivot of root growth. Journal of Experimental Botany, 66(4), 1113–1121. https://doi.org/10.1093/jxb/eru534

Pan, B., Zhong, T., & Zhao, G. (2016). Promoting deep-sowing germin-ability of corn (Zea mays) by seed soaking with gibberellic acid. Archives of Agronomy and Soil Science, 63(9), 1314–1323. https://doi.org/10.1080/03650 340.2016.1268256

Peng, J., Richards, D. E., Hartley, N. M., Murphy, G. P., Devos, K. M., Flintham, J. E., … Pelica, F. (1999). ‘Green revolution’genes en-code mutant gibberellin response modulators. Nature, 400(6741), 256–261.

Rademacher, W. (2000). GROWTH RETARDANTS: effects on gibberellin biosynthesis and other metabolic pathways. Annual Review of Plant Physiology and Plant Molecular Biology, 51(1), 501–531. https://doi.org/10.1146/annur ev.arpla nt.51.1.501

Roeber, F., Gordillo, G., & Geiger, H. (2005). In vivo haploid induction in maize. Performance of new inducers and significance of doubled haploid lines in hybrid breeding [Zea mays L.]. Maydica (Italy), 50(3-4), 275–283.

Sanchez, D. L., Liu, S., Ibrahim, R., Blanco, M., & Lubberstedt, T. (2018). Genome-wide association studies of doubled haploid exotic in-trogression lines for root system architecture traits in maize (Zea mays L.). Plant Science, 268, 30–38. https://doi.org/10.1016/j.plant sci.2017.12.004

Sasaki, A., Ashikari, M., Ueguchi-Tanaka, M., Itoh, H., Nishimura, A., Swapan, D., … Matsuoka, M. (2002). Green revolution: A mutant gib-berellin-synthesis gene in rice. Nature, 416(6882), 701. https://doi.org/10.1038/416701a

Sasse, J. M. (2003). Physiological actions of brassinosteroids: An up-date. Journal of Plant Growth Regulation, 22(4), 276–288. https://doi.org/10.1007/s0034 4-003-0062-3

Shi, Y.-H., Zhu, S.-W., Mao, X.-Z., Feng, J.-X., Qin, Y.-M., Zhang, L., … Zhu, Y.-X. (2006). Transcriptome profiling, molecular biological, and phys-iological studies reveal a major role for ethylene in cotton fiber cell elongation. The Plant Cell, 18(3), 651–664. https://doi.org/10.1105/tpc.105.040303

Shukla, S., Bhargava, A., Chatterjee, A., Srivastava, J., Singh, N., & Singh, S. P. (2006). Mineral profile and variability in vegetable amaranth (Amaranthus tricolor). Plant Foods for Human Nutrition, 61(1), 23–28. https://doi.org/10.1007/s1113 0-006-0004-x

Singh, R. K., & Chaudhary, B. D. (1979). Biometrical methods in quan-titative genetic analysis. Biometrical Methods in Quantitative Genetic Analysis.

Spielmeyer, W., Ellis, M. H., & Chandler, P. M. (2002). Semidwarf (sd-1), "green revolution" rice, contains a defective gibberellin 20-oxidase gene. Proceedings of the National Academy of Sciences of the United States of America, 99(13), 9043–9048. https://doi.org/10.1073/pnas.13226 6399

Steber, C. M., & McCourt, P. (2001). A role for brassinosteroids in germi-nation in Arabidopsis. Plant Physiology, 125(2), 763–769. https://doi.org/10.1104/pp.125.2.763

Stowe, B. B., & Yamaki, T. (1957). The history and physiological action of the gibberellins. Annual Review of Plant Physiology, 8(1), 181–216. https://doi.org/10.1146/annur ev.pp.08.060157.001145

Sun, Y., Fokar, M., Asami, T., Yoshida, S., & Allen, R. D. (2004). Characterization of the brassinosteroid insensitive 1 genes of cotton. Plant Molecular Biology, 54(2), 221–232. https://doi.org/10.1023/B:PLAN.00000 28788.96381.47

     |  13HU et al.

Sun, Y., Veerabomma, S., Abdel-Mageed, H. A., Fokar, M., Asami, T., Yoshida, S., & Allen, R. D. (2005). Brassinosteroid regulates fiber de-velopment on cultured cotton ovules. Plant and Cell Physiology, 46(8), 1384–1391. https://doi.org/10.1093/pcp/pci150

Tang, Y., Liu, H., Guo, S., Wang, B., Li, Z., Chong, K., & Xu, Y. (2018). OsmiR396d affects gibberellin and brassinosteroid signaling to reg-ulate plant architecture in rice. Plant Physiology, 176(1), 946–959. https://doi.org/10.1104/pp.17.00964

Teresa, C., Anna, T., Neeru, G., & Timothy, N. (2009). VH1/BRL2 recep-tor-like kinase interacts with vascular-specific adaptor proteins VIT and VIK to influence leaf venation. The Plant Journal, 57(6), 1000–1014. https://doi.org/10.1111/j.1365-313X.2008.03742.x

Troyer, A. F. (1997). The location of genes governing long first internode of corn. Genetics, 145(4), 1149–1154.

Ubeda-Tomás, S., Swarup, R., Coates, J., Swarup, K., Laplaze, L., Beemster, G. T. S., … Bennett, M. J. (2008). Root growth in Arabidopsis requires gibberellin/DELLA signalling in the endodermis. Nature Cell Biology, 10(5), 625. https://doi.org/10.1038/ncb1726

Vanous, K., Vanous, A., Frei, U. K., & Lübberstedt, T. (2017). Generation of maize (Zea mays ) doubled haploids via traditional methods. Current Protocols in Plant Biology, 2, 147–157. https://doi.org/10.1002/cppb.20050

Vardhini, B. V., Anuradha, S., Sujatha, E., & Rao, S. S. R. (2010). Role of brassinosteroids in alleviating various abiotic and biotic stresses–A review. Plant Stress, 4(1), 55–61.

Vicente-Serrano, S. M., Quiring, S. M., Peña-Gallardo, M., Yuan, S., & Domínguez-Castro, F. (2020). A review of environmental droughts: Increased risk under global warming? Earth-Science Reviews, 201, 102953. https://doi.org/10.1016/j.earsc irev.2019.102953

Vidya Vardhini, B., & Rao, S. S. R. (2002). Acceleration of ripening of to-mato pericarp discs by brassinosteroids. Phytochemistry, 61(7), 843–847. https://doi.org/10.1016/S0031 -9422(02)00223 -6

Vriet, C., Russinova, E., & Reuzeau, C. (2012). Boosting crop yields with plant steroids. The Plant Cell, 24(3), 842–857. https://doi.org/10.1105/tpc.111.094912

Watanabe, H., Hase, S., & Saigusa, M. (2007). Effects of the combined application of ethephon and gibberellin on growth of rice (Oryza sa-tiva L.) seedlings. Plant Production Science, 10(4), 468–472. https://doi.org/10.1626/pps.10.468

White, C. N., Proebsting, W. M., Hedden, P., & Rivin, C. J. (2000). Gibberellins and seed development in maize. I. Evidence that gibber-ellin/abscisic acid balance governs germination versus maturation pathways. Plant Physiology, 122(4), 1081–1088.

Wu, C.-Y., Trieu, A., Radhakrishnan, P., Kwok, S. F., Harris, S., Zhang, K. E., … Pennell, R. I. (2008). Brassinosteroids regulate grain filling in rice. The Plant Cell, 20(8), 2130–2145. https://doi.org/10.1105/tpc.107.055087

Yamaguchi, N., Winter, C. M., Wu, M.-F., Kanno, Y., Yamaguchi, A., Seo, M., & Wagner, D. (2014). Gibberellin acts positively then negatively to

control onset of flower formation in Arabidopsis. Science, 344(6184), 638–641.

Yamaguchi, S. (2008). Gibberellin metabolism and its regulation. Annual Review of Plant Biology, 59(1), 225–251. https://doi.org/10.1146/annur ev.arpla nt.59.032607.092804

Yang, T., Davies, P. J., & Reid, J. B. (1996). Genetic dissection of the rel-ative roles of auxin and gibberellin in the regulation of stem elonga-tion in intact light-grown peas. Plant Physiology, 110(3), 1029–1034. https://doi.org/10.1104/pp.110.3.1029

Zhang, H., Ma, P., Zhao, Z., Zhao, G., Tian, B., Wang, J., & Wang, G. (2012). Mapping QTL controlling maize deep-seeding tolerance-related traits and confirmation of a major QTL for mesocotyl length. Theoretical and Applied Genetics, 124(1), 223–232. https://doi.org/10.1007/s0012 2-011-1700-y

Zhang, X., Wang, B., Zhao, Y., Zhang, J., & Li, Z. (2019). Auxin and GA signaling play important roles in the maize response to phosphate deficiency. Plant Science, 283, 177–188. https://doi.org/10.1016/j.plant sci.2019.02.011

Zhao, B., Li, H., Li, J., Wang, B., Dai, C., Wang, J., & Liu, K. (2017). Brassica napus DS-3, encoding a DELLA protein, negatively regulates stem elongation through gibberellin signaling pathway. Theoretical and Applied Genetics, 130(4), 727–741. https://doi.org/10.1007/s0012 2-016-2846-4

Zhao, G., Fu, J., Wang, G., Ma, P., Wu, L., & Wang, J. (2010). Gibberellin-induced mesocotyl elongation in deep-sowing tolerant maize inbred line 3681–4. Plant Breeding, 129(1), 87–91. https://doi.org/10.1111/j.1439-0523.2009.01658.x

Zhao, G., & Wang, J. (2008). Effect of gibberellin and uniconazole on mesocotyl elongation of dark-grown maize under different seed-ing depths. Plant Production Science, 11(4), 423–429. https://doi.org/10.1626/pps.11.423

Zhu, J. Y., Sae-Seaw, J., & Wang, Z. Y. (2013). Brassinosteroid signal-ling. Development, 140(8), 1615–1620. https://doi.org/10.1242/dev.060590

SUPPORTING INFORMATIONAdditional supporting information may be found online in the Supporting Information section.

How to cite this article: Hu K, Xie Y, Wu C, Frei UK, Lübberstedt T. Genetic variation of seedling traits responded to brassinosteroid and gibberellin inhibitors in maize (Zea mays) doubled haploid lines. Plant Breed. 2020;00:1–13. https://doi.org/10.1111/pbr.12845