Next Article in Journal
Effects of Different Light Spectra on Final Biomass Production and Nutritional Quality of Two Microgreens
Previous Article in Journal
Evaluation of Fatty Acid Compositions, Antioxidant, and Pharmacological Activities of Pumpkin (Cucurbita moschata) Seed Oil from Aqueous Enzymatic Extraction
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Plants
Volume 10
Issue 8
10.3390/plants10081585
plants-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Dissecting the Genetic Basis of Flowering Time and Height Related-Traits Using Two Doubled Haploid Populations in Maize

by
Lei Du
1,
Hao Zhang
1,
Wangsen Xin
1,
Kejun Ma
1,
Dengxiang Du
1,
Changping Yu
2 and
Yongzhong Liu
1,*
1
National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
2
Maize Breeding Research Institute, Shiyan Academy of Agricultural Sciences, Shiyan 442000, China
*
Author to whom correspondence should be addressed.
Plants 2021, 10(8), 1585; https://doi.org/10.3390/plants10081585
Submission received: 25 June 2021 / Revised: 23 July 2021 / Accepted: 27 July 2021 / Published: 31 July 2021
(This article belongs to the Section Plant Genetics, Genomics and Biotechnology)
Browse Figures
Versions Notes

Abstract

:
In the field, maize flowering time and height traits are closely linked with yield, planting density, lodging resistance, and grain fill. To explore the genetic basis of flowering time and height traits in maize, we investigated six related traits, namely, days to anthesis (AD), days to silking (SD), the anthesis–silking interval (ASI), plant height (PH), ear height (EH), and the EH/PH ratio (ER) in two locations for two years based on two doubled haploid (DH) populations. Based on the two high-density genetic linkage maps, 12 and 22 quantitative trait loci (QTL) were identified, respectively, for flowering time and height-related traits. Of these, ten QTLs had overlapping confidence intervals between the two populations and were integrated into three consensus QTLs (qFT_YZ1a, qHT_YZ5a, and qHT_YZ7a). Of these, qFT_YZ1a, conferring flowering time, is located at 221.1–277.0 Mb on chromosome 1 and explained 10.0–12.5% of the AD and SD variation, and qHT_YZ5a, conferring height traits, is located at 147.4–217.3 Mb on chromosome 5 and explained 11.6–15.3% of the PH and EH variation. These consensus QTLs, in addition to the other repeatedly detected QTLs, provide useful information for further genetic studies and variety improvements in flowering time and height-related traits.

1. Introduction

Maize (Zea mays L.) is an important food and forage crop, and an industrial raw material crop. Flowering time and height traits are important agronomical traits in maize production, and are closely linked to the switch from vegetative growth to reproductive growth [1]. However, the balance of this switch usually breaks down when the breeding process is exposed to an exotic maize germplasm source, especially tropical and sub-tropical material, which generally leads to late flowering and a greater height [2]. Therefore, flowering time and height traits are often among the main issues that must be overcome when using new maize germplasm.
Flowering time-related traits, including days to anthesis (AD), days to silking (SD), and the anthesis–silking interval (ASI), are vital to harvesting date, crop rotation schemes, and adaptation to different environments [3,4]. Previous studies have shown that these traits are highly quantitative traits in maize [5]. Map-based cloning for dissecting quantitative traits and using linked markers for improvement are an effective breeding strategy. To date, many flowering time-related major QTLs detected by QTL mapping have been proposed, such as epc [6], D8idp [7], zfl1 [8], conz1 [9], ZmPR1-4 [10], ZCN8 [11], and eIF-4A [12]. More recently, high-resolution populations and high-density molecular markers have been widely utilized in genetic mapping, and many novel loci for these traits have been found in maize [13,14]. Additionally, a series of genes conferring flowering time have been cloned in maize, and some molecular mechanisms have also been proposed. For example, most flowering time-related genes were confirmed to encode a CCT domain-containing protein and are relative to the photoperiod response [5,15,16,17]. Other molecular mechanisms were also found, for example, the late flowering gene ID1 encodes a zinc finger transcription factor [18]; the early flowering gene dlf1 encodes a leucine zipper protein [19]; and the early flowering gene ZmSOC1 encodes a conserved MADS domain protein [20]. Other genes are regulatory elements for flowering time; for instance, the cis-acting regulatory element Vgt1 influences the transcript expression levels of the downstream gene ZmRap2.7 that is associated with late flowering [21], and the gene ZmMADS1 is a positive transcriptional regulator for early flowering [22]. These quantitative trait loci (QTLs)/genes and mechanisms provide useful information for further genetic studies on flowering time.
Height traits are closely linked with planting density, lodging resistance, and biomass yield [23], and dwarf mutants are considered a decisive factor for the “green revolution” [24]. Height traits including plant height (PH), ear height (EH), and EH/PH ratio (ER) are complex traits that are controlled by multiple genes and environmental factors [25]. Due to easy measurement of height and its high heritability, a large number of these maize QTLs have been identified, most of which are clustered in at least four main regions on the genetic linkage maps: bin 1.02–1.03 [26,27,28], bin 1.04–1.06 [26,29,30,31], bin 3.05–3.07 [27,28,29,31], and bin 5.04–5.06 [30,31,32,33]. In addition, many height-related maize genes have been confirmed, and some of their molecular mechanisms have been also illustrated. Most of these genes are involved in hormone synthesis, for example, dwarf3, dwarf8, and ZmGA3ox2 influencing gibberellin synthesis [24,34,35], and nana plant1 impacting brassinosteroid synthesis [36]. Others are involved in hormone transport, for example, brachytic2 influencing polar auxin transports [37]. Moreover, some are involved in signaling related to hormone synthesis, for example, dwarf9 regulates DELLA proteins of the gibberellin signal transduction pathways [38]. There are also other types of genes that regulate plant height, such as ZmRPH1 encoding a QWRF homolog protein in maize [39]. This useful information will be an important basis for genetic studies and variety improvements in height traits.
The half-tropical inbred line Q1 is an important germplasm source for breeding in the mountains of Southwest China. However, this line leads to late flowering and greater height in an improving variety. The objectives of this study were to exploit early flowering and dwarf alleles that are derived from temperate elite inbred lines Ye478 and Zheng58, and to identify significant QTLs for further genetic study and molecular marker-assisted (MAS) breeding. To achieve these objectives, three flowering time traits (AD, SD, and ASI) and three height traits (PH, EH, and ER) were measured or calculated in two locations for two years based on two double haploid (DH) populations. QTL analysis of these six traits was used to explore the genetic basis and to identify significant QTLs closely linked with these traits. The results will be used to understand the genetic basis of flowering time and height traits, and further provide useful alleles for MAS breeding.

2. Materials and Methods

2.1. Genetic Materials

Two maize DH populations sharing a common parent were constructed as previously described [40]. The common parent Q1 is a half-tropical inbred line that is important for hybrid corn production in the mountains of Southwest China, but shows late flowering and greater height. The other two parents, Ye478 and Zheng58, are elite inbred lines for hybrid corn production, which have been widely planted over the past two decades on the plains of China, and show early flowering and dwarfing. These three parents had no obvious diseases or pests around tasseling and silking (Figure S1). In brief, the common parent Q1 was crossed with two different parents (Ye478 and Zheng58), separately. Then, the F1 hybrids of Q1 × Ye478 (QY) and Q1 × Zheng58 (QZ) were subjected to haploid induction by crossing with the haploid inducer. In the following planting season, the haploid seedlings were doubled by application of 0.06% colchicine. The two DH populations were named QY and QZ and comprised 123 and 163 DH lines, respectively.

2.2. Phenotypic Evaluation and Statistical Analysis

The three parents and DH lines were evaluated as described previously [40] in two locations: the towns of Huangliang (31.30° N, 110.89° E, altitude: 890 m) and Zhenzi (31.45° N, 110.99° E, altitude: 1321 m), located in the city of Yichang, Hubei Province, which are typical maize-growing regions in the southwest mountains of China. The novel aspect of the current work was the new phenotype value of six flowering time and height related traits, as described below. These locations have a milder temperature and higher humidity condition during the corn growing season, and usually have no obvious diseases and pests around the tasseling period (Figure S1). In the town of Huangliang, we evaluated flowering time and height-related traits in the years of 2016 and 2017, and in the town of Zhenzi, we evaluated these traits only in 2017. In the subsequent analysis, we combined the location and year as one variable factor, namely, environment. In each environment, the parents and DH lines were planted in the field in two replicates with a completely randomized block design. Each plot consisted of one row with 10 plants per row. All field management of fertilization, irrigation, pest control, and weed management was the same as that of local fields. In practice, 75 g/m2 of compound fertilizer (including N, P, and K) was applied before sowing, and 20 g/m2 urea was replenished in the elongation period and before tasselling. We sprayed herbicide (acetochlor) once after sowing to prevent weeds and sprayed pesticides once before tasselling for pest control. Tasseling days (AD, days to 50% plants tasseling in each plot) and silking days (SD, days to 50% plants silking in each plot) were investigated, and the anthesis–silking interval (ASI) was also calculated for each plot. Five representative plants in each plot were used for collecting plant height (PH; in cm) and ear height (EH; in cm) data [31] at two weeks after tasseling, when most lines have no obvious diseases and pests. The EH/PH ratio (ER) was calculated for each plot and was transformed using the arcsine method for subsequent analysis.
Analysis of descriptive statistics (e.g., mean, range, skewness, and kurtosis) was conducted in Excel 2010. The variance of phenotypic data was estimated using variance analysis by the aov procedure in R software [41]. The model for variance analysis was Y = μ + βG + γL + (γβ)LG + εLGR, where βG represents the effect of the Gth DH line, γL is the effect of the Lth environment, (γβ)LG is the corresponding interaction effect, and εLGR is the residual effect. All effects were considered to be random. The broad-sense heritability was calculated by H2 = ∂ G 2 /( ∂ G 2 + ∂ G L 2 /l + ∂ e 2 /lr), where ∂ G 2 is genetic variance,   ∂ G L 2 is genotype × environmental variance, ∂ e 2 is error variance, l is the number of environments, and r is the number of replicates in each environment [42]. The best linear unbiased prediction (BLUP) was calculated for each phenotype by the lme4 package [43] in R software across different environments and used for subsequent analysis.

2.3. Linkage Map and QTL Analysis

Two ultra-high density linkage maps of the two DH populations were developed as previously described [40]. In brief, the two DH populations were genotyped using genotyping by sequencing (GBS) technology on an Illumina 4000 platform. A total of 64,553 and 42,792 high-quality SNP and INDEL markers were obtained, respectively. Subsequently, linkage maps were constructed based on the linkage and crossover among these markers. Finally, these two linkage maps included 1101 and 1294 bins, respectively. The total map length was 1479.4 and 1872.1 cM, and the average distances between adjacent bins were 1.36 and 1.44 cM for the QY and QZ genetic linkage maps, respectively.
QTL analysis was performed using the composite interval mapping method (CIM) in Windows QTL Cartographer v2.5 [44]. The BLUP values of phenotype for each trait across the three environments were used for QTL analysis. A significant LOD threshold of a putative QTL was determined by 1000 permutation tests (α  =  0.05) with a step size of 1.0 cM. The LOD thresholds ranged from 2.9 to 3.2, and we used a mean value of 3 to investigate significant QTLs. The confidence interval (CI) of QTLs was defined as the 2 LOD interval flanking the QTL peak. QTLs with overlapping CIs and identical effect directions were assumed to be the same. QTL nomenclature followed the description of [45] with minor modifications: the first letter was “q” for QTL, followed by the trait abbreviation, a letter representing the population from which the QTL was identified (“Y” for the QY population, “Z” for the QZ population), a number indicating the chromosome, and a final letter differentiating QTLs on the same chromosome.

3. Results

3.1. Phenotypic Variation

The descriptive statistics for the six flowering time and height-related traits of the three parents and the DH lines are represented in Table 1. The parent Q1 had a later flowering time and taller height compared with the parents Ye478 and Zheng58. In addition, wide flowering time variations were observed among the DH lines in the two populations. For example, the ranges of AD and SD in the QY population were 74.0–100.0 days and 77.0–105.0 days, respectively, whereas in the QZ population, the ranges were 72.0–99.0 days and 75.0–105.0 days, respectively. Similarly, wide variations in height-related traits were also observed among the DH lines; for example, the PH ranged from 123.0 to 310.0 cm in the QY population and from 140.0 to 305.0 cm in QZ population. The EH ranged from 37.0 to 143.7 cm in the QY population and from 34.3 to 157.0 cm in the QZ population. Additionally, the frequency of phenotypic value in the two DH populations for the six traits followed an approximately normal distribution (Figure 1), indicating that these traits were controlled by QTLs. The phenotype values between PH and EH (p < 0.0001, 0.75–0.80), between EH and ER (p < 0.0001, 0.82–0.86), and between AD and SD (p < 0.0001, 0.90–0.91) were positively correlated in the two populations, whereas there was weaker correlativity between the flowering time and the height-related traits (Figure 1).
The genotypic variance of the AD, ASI, PH, EH, and ER traits was significant in the two populations, demonstrating real genetic differences for these six traits among DH lines in the two populations (Table S1). The difference between environments was not significant except for EH in the QY population, indicating that most of these traits were stable in each environment. The environment and genotype by environment variance were significant in the two DH populations, which could be caused by including differences of humidity, temperature, and rainfall across the environments (Table S1). Heritability for AD, AD, ASI, PH, EH, and ER ranged from 70.7 to 87.2% in the QY population, and ranged from 71.4 to 83.6% in the QZ population (Table S1). The high repeatability and heritability indicates that much of the phenotypic variance was genetically controlled in the populations and suitable for QTL mapping.

3.2. Identification of QTLs for Six Traits

We conducted a QTL analysis of individual DH populations using the corresponding BLUP value across the three environments for each trait. A total of 34 QTLs associated with the six traits were identified (Table 2, Figure 2).
In the QY population, 17 QTLs were detected, with LOD scores ranging from 3.0 to 8.0. These QTLs were distributed on six chromosomes and explained 6.5 to 16.7% of the phenotypic variation. Of these QTLs, there were three, four, and one QTLs conferring the AD, SD, and ASI traits, respectively. Most of these flowering time-related QTLs decreased phenotype value when they were from Ye478, except for qASI_Y5a, and five of them could explain up to 10% of the phenotypic variation. In addition, four, four, and one QTLs were detected as conferring the PH, EH, and ER traits, respectively. All of these height trait-related QTLs also decreased phenotype value when they were derived from the parent Ye478, and four of them could explain up to 10% of the phenotypic variation.
In the QZ population, there also were 17 QTLs detected, with LOD scores ranging from 3.0 to 12.0. These QTLs were distributed on nine chromosomes, except for chromosome 2, and explained 4.4 to 22.0% of the phenotypic variation. Of these QTLs, there were two and two QTLs associated with the AD and SD traits, respectively, and no QTL was detected for ASI. All of these flowering time-related QTLs decreased phenotype value when they were from Zheng58, and two of them could explain up to 10% of the phenotypic variation. In addition, four, six, and three QTLs were identified associated with the PH, EH, and ER traits, respectively. Most of these QTLs decreased the phenotype value when they were from Zheng58, except for qEH_Z6a and qEH_Z7a, and six of them could explain up to 10% of the phenotypic variation.

3.3. Co-Localization of QTLs for Different Traits between the Two DH Populations

To determine the relationship of the six trait-related QTLs detected in different DH populations sharing a common parent Q1, we compared the physical interval corresponding to the two LOD interval for each QTL. Eleven chromosome regions contained overlapped QTLs for more than one trait, which were distributed on chromosome 1, 3, 5, 7, 8, 9, and 10 (Table 2, Figure 2). On chromosome 1, the region of 15.6–33.0 Mb includes two overlapped QTLs (qPH_Y1a and qEH_Y1a); the region of 35.5–172.2 Mb includes three overlapped QTLs (qPH_Z1a, qEH_Z1a, and qER_Z1a); and the region of 221.1–277.0 Mb also includes three overlapped QTLs (qAD_Y1a, qSD_Y1a, and qSD_Z1a). On chromosome 3, the region of 6.7–11.9 Mb includes two QTLs (qEH_Z3a and qER_Z3a). On chromosome 5, the region of 20.3–165.9 Mb includes two QTLs (qAD_Y5a and qSD_Y5a); and the region of 147.4–217.3 Mb includes five QTLs (qPH_Y5a, qEH_Y5a, qER_Y5a, qPH_Z5a, and qEH_Z5a). On the chromosome 7, the region of 87.4–134.7 Mb includes two QTLs (qEH_Y7a and qEH_Z7a). On chromosome 8, the region of 110.5–163.8 Mb includes two QTLs (qAD_Z8a and qSD_Z8a). On chromosome 9, the region of 9.4–108.9 Mb includes two QTLs (qPH_Y9a and qEH_Y9a); and the region of 147.7–155.6 Mb includes two QTLs (qPH_Z9a and qEH_Z9a). On chromosome 10, the region of 14.4–129.5 Mb includes two QTLs (qAD_Y10a and qPH_Z10a). These overlapped chromosome regions could result from pleiotropy or linked genes. Among these genetic hotspots, the regions of 221.1–277.0 Mb on chromosome 1 (for flowering time traits), 147.4–217.3 Mb on chromosome 5 (for height traits), and 87.4–134.7 Mb on chromosome 7 (for height traits) were co-localized QTLs between the two DH populations, indicating that these regions could contribute to effects in different genetic backgrounds. We named these three co-localized genomic regions qFT_YZ1a, qHT_YZ5a, and qHT_YZ7a, respectively, and they will be the focus for further study.

4. Discussion

4.1. Relationship between Flowering Time and Height-Related Traits

Flowering time and height traits are two of the most studied traits in maize. Most studies indicate that these traits are closely correlated [36]. In this study, many correlations between flowering time and height traits were found to be significant, indicating that there could be pleiotropy or linked genes associated with these traits. In many crops, a series of genes have been validated to regulate both flowering time and plant height, for example, the rice genes Ghd7, DTH8, and Hd1 [46,47,48], and the maize gene Dwarf8 [49]. Additionally, some co-localized QTLs for these traits have also been identified, such as in maize [25], barley [50], and rice [51,52]. In our results, we found one significant co-localized genetic locus between flowering time and height traits, located at 14.4–129.5 Mb on chromosome 10 and contributing to AD and PH. These results provide genetic confirmation of the correlations between flowering time and height traits.

4.2. Potential Utilization of the Present QTLs

For any target trait, the QTL/gene that can be repeatedly identified across traits, populations, and environments is desirable for successful implementation of MAS breeding [31]. In the present study, we detected three consensus QTLs. Of these, the flowering time-related QTL qFT_YZ1a could explain 10.0–12.5% of AD and SD variation in both of the populations (Table 2), suggesting it may be a major QTL. The height trait-related QTL qHT_YZ5a contributed to 11.6–15.3% of PH and EH variation in both DH populations, which could also be a major QTL. Furthermore, we also found that these two consensus QTLs could contribute to effects in the three environments of the two populations (Table S2), indicating that they function stably. These consensus and stable and major QTLs may be considered priority candidates for MAS breeding. Another consensus QTL qHT_YZ7a could not be identified in all environments in the QZ population (Table S2), suggesting that environmental conditions and genetic background have a strong effect on its reliability. In addition to these consensus QTLs, other QTLs were detected only in individual populations, but some of them also contribute to a large effect. For example, qAD_Y5a/qSD_Y5a and qAD_Y10a/qSD_Y10a could explain up to 16.7% and 13.5% of AD and SD variation, respectively. qPH_Y9a/qEH_Y9a, qPH_Z9a/qEH_Z9a, qPH_Z1a/qEH_Z1a/qER_Z1a, and qEH_Z3a/qER_Z3a could contribute to more than 10% of PH and EH variation. At all of these loci, the early flowering or dwarf alleles were from the low-value parents Zheng58 or Ye478, indicating that they could improve the late flowering and higher height issues of Q1.
Decreasing height is usually a common target when applying exotic germplasm, especially tropical and sub-tropical germplasm, in breeding programs. However, plant height was positively correlated with grain yield [53], suggesting that we should decrease EH without affecting PH. Additionally, current high-density breeding targets need to similarly reduce ER traits [54]. This means ER may be more important than the PH and EH traits. In our results, the consensus QTL qHT_YZ5a was associated with the ER trait, further indicating its importance in improving height traits. Additionally, the population-specific QTLs qEH_Z3a/qER_Z3a and qER_Z1a could also explain up to 22.0% and 13.8% of ER variation, also suggesting their importance for improving height traits.

4.3. Comparison with QTLs Identified in Previous Studies

In the present study, we identified one flowering time-related consensus QTL qFT_YZ1a, located at 221.1–277.0 Mb on chromosome 1. Within the CI of qFT_YZ1a, the gene id1 has been reported previously, and encodes a zinc finger protein and functions in late flowering [18]. This region also harbors the gene Dwarf8, which is implicated in both flowering time and plant height [49]. Interestingly, the orthologs gene of Dwarf8 in wheat have contributed to the “green revolution” [24]. In addition, we also identified two other repeatedly identified QTLs for flowering time. Of these, qAD_Z8a/qSD_Z8a was located in the genomic region 110.5–163.8 Mb of chromosome 8, where Vgt1 has been identified for late flowering [21], and Zcn8 has been found to be a key photoperiod regulatory gene in maize [11]. The QTL qAD_Y5a/ qSD_Y5a was located in the genomic region 20.3–165.9 Mb of chromosome 5, where, to the best of our knowledge, no gene has been validated as being associated with flowering time.
For height traits, we identified two consensus QTLs between the two populations. Of these, qHT_YZ5a is located at bin 5.04–5.06 and is co-localized with four previously identified QTLs [30,31,32,33]. Additionally, within the CI of qHT_YZ5a, the gene d9 has been validated as conferring dwarf characteristics and late flowering [38], and a major QTL qPH5–1 also has been identified for the PH and EH of testcross performance and RILs per se [33]. In addition, another researcher also detected a dwarf allele in this region [55]. Interestingly, a lodging resistance-related QTL was found in this region, suggesting that lodging could be linked with height traits [56]. Another consensus QTL qHT_YZ7a located in the genomic region 87.4–134.7 Mb on chromosome 7 was significantly associated with only EH in the two DH populations. Within the CI of qHT_YZ7a, a major QTL for PH in normal and stress environments was detected [25]. In addition to these consensus QTLs, there were also four other repeatedly identified QTLs for height traits. Of these, qPH_Y1a/qEH_Y1a spanned the genomic region of 15.6–33.4 Mb on chromosome 1, where the gene ZmRPH1 has been validated to be linked with PH and EH [39], and another similar QTL was also reported previously in this region [29]. The qPH_Z1a/qEH_Z1a/qER_Z1a overlapped with a QTL cluster conferring the PH, EH, and AD traits [57]. Another two repeatedly identified QTLs qPH_Z3a/qEH_Z3a and qPH_Z9a/ qEH_Z9a have not been found to have any major QTLs or genes associated with height traits to the best of our knowledge.

5. Conclusions

Flowering time and height are important agronomic traits in maize breeding. These traits are highly quantitative traits and are influenced by the environment. Thus, it is a challenge to improve them for phenotypic selection. In this study, we detected 34 QTLs conferring flowering time and height-related traits based on two DH populations, and 21 of these overlapped with at least one other QTL. Furthermore, ten QTLs had overlapping confidence intervals between the two DH populations and were integrated into three consensus QTLs. The flowering time-related consensus QTL qFT_YZ1a could explain 10–12.5% of the phenotypic variation for different traits in the two populations. This QTL is also located at a significant region of the previously detected flowering time QTL, which would be a major candidate region for future gene cloning and marker-assisted selection (MAS) breeding for flowering time. In addition, another consensus QTL qHT_YZ5a for height traits could explain 11.6–15.3% of phenotypic variation in different traits and populations. A number of QTLs were found in this region, suggesting that qHT_YZ5a could harbor novel major alleles. These two major consensus QTLs, in addition to other repeatedly detected QTLs, provide new insights for genetic improvement of flowering time and height-related traits.

Supplementary Materials

The following materials are available online at https://www.mdpi.com/article/10.3390/plants10081585/s1, Table S1: Analysis of variance for the six flowering time and height traits of two DH populations over three environments. Table S2: QTLs for the six flowering time and height related traits in the two DH populations and three environments. Figure S1: The performance of three parents around tasseling period.

Author Contributions

L.D. and Y.L. designed the study. Y.L. supervised the study. L.D., H.Z., C.Y., W.X., and K.M. performed the experiments. L.D. and D.D. analyzed the data. L.D. and Y.L. prepared the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Key Research and Development Program of China (2016YFD0101205).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare that they have no conflict of interest.

References

  1. Irish, E.; Nelson, T.M. Identification of multiple stages in the conversion of maize meristems from vegetative to floral development. Development 1991, 112, 891–898. [Google Scholar] [CrossRef]
  2. Hallauer, A.R.; Carena, M.J. Adaptation of tropical maize germplasm to temperate environments. Euphytica 2014, 196, 1–11. [Google Scholar] [CrossRef]
  3. Bendix, C.; Marshall, C.M.; Harmon, F.G. Circadian Clock Genes Universally Control Key Agricultural Traits. Mol. Plant 2015, 8, 1135–1152. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Buckler, E.S.; Holland, J.B.; Bradbury, P.J.; Acharya, C.B.; Brown, P.J.; Browne, C.; Ersoz, E.; Flint-Garcia, S.; Garcia, A.; Glaubitz, J.C.; et al. The Genetic Architecture of Maize Flowering Time. Science 2009, 325, 714–718. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Ducrocq, S.; Giauffret, C.; Madur, D.; Combes, V.; Dumas, F.; Jouanne, S.; Coubriche, D.; Jamin, P.; Moreau, L.; Charcosset, A. Fine Mapping and Haplotype Structure Analysis of a Major Flowering Time Quantitative Trait Locus on Maize Chromosome 10. Genetics 2009, 183, 1555–1563. [Google Scholar] [CrossRef] [Green Version]
  6. Vega, S.H.; Sauer, M.; Orkwiszewski, J.A.; Poethig, R.S. The early phase change Gene in Maize. Plant Cell 2002, 14, 133–147. [Google Scholar] [CrossRef] [Green Version]
  7. Camus-Kulandaivelu, L.; Veyrieras, J.B.; Madur, D.; Combes, V.; Fourmann, M.; Barraud, S.; Dubreuil, P.; Gouesnard, B.; Manicacci, D.; Charcosset, A. Maize adaptation to temperate climate: Relationship between population structure and polymorphism in the Dwarf8 gene. Genetics 2006, 172, 2449–2463. [Google Scholar] [CrossRef] [Green Version]
  8. Bomblies, K.; Doebley, J.F. Pleiotropic Effects of the Duplicate Maize FLORICAULA/LEAFY Genes zfl1 and zfl2 on Traits Under Selection During Maize Domestication. Genetics 2006, 172, 519–531. [Google Scholar] [CrossRef] [Green Version]
  9. Miller, T.A.; Muslin, E.H.; Dorweiler, J.E. A maize CONSTANS-like gene, conz1, exhibits distinct diurnal expression patterns in varied photoperiods. Planta 2008, 227, 1377–1388. [Google Scholar] [CrossRef]
  10. Coles, N.D.; McMullen, M.D.; Balint-Kurti, P.J.; Pratt, R.C.; Holland, J.B. Genetic Control of Photoperiod Sensitivity in Maize Revealed by Joint Multiple Population Analysis. Genetics 2010, 184, 799–812. [Google Scholar] [CrossRef] [Green Version]
  11. Meng, X.; Muszynski, M.G.; Danilevskaya, O.N. The FT-Like ZCN8 Gene Functions as a Floral Activator and Is Involved in Photoperiod Sensitivity in Maize. Plant Cell 2011, 23, 942–960. [Google Scholar] [CrossRef] [Green Version]
  12. Durand, E.; Bouchet, S.; Bertin, P.; Ressayre, A.; Jamin, P.; Charcosset, A.; Dillmann, C.; Tenaillon, M.I. Flowering Time in Maize: Linkage and Epistasis at a Major Effect Locus. Genetics 2012, 190, 1547–1562. [Google Scholar] [CrossRef] [Green Version]
  13. Romay, M.C.; Millard, M.J.; Glaubitz, J.C.; Peiffer, J.A.; Swarts, K.L.; Casstevens, T.M.; Elshire, R.J.; Acharya, C.B.; Mitchell, S.E.; Flint-Garcia, S.A.; et al. Comprehensive genotyping of the USA national maize inbred seed bank. Genome Biol. 2013, 14, R55. [Google Scholar] [CrossRef] [Green Version]
  14. Li, Y.; Li, C.; Bradbury, P.J.; Liu, X.; Lu, F.; Romay, C.M.; Glaubitz, J.C.; Wu, X.; Peng, B.; Shi, Y.; et al. Identification of genetic variants associated with maize flowering time using an extremely large multi-genetic background population. Plant J. 2016, 86, 391–402. [Google Scholar] [CrossRef]
  15. Hung, H.-Y.; Shannon, L.M.; Tian, F.; Bradbury, P.J.; Chen, C.; Flint-Garcia, S.A.; McMullen, M.D.; Ware, D.; Buckler, E.S.; Doebley, J.F.; et al. ZmCCT and the genetic basis of day-length adaptation underlying the postdomestication spread of maize. Proc. Natl. Acad. Sci. USA 2012, 109, E1913–E1921. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Yang, Q.; Li, Z.; Li, W.; Ku, L.; Wang, C.; Ye, J.; Li, K.; Yang, N.; Li, Y.; Zhong, T.; et al. CACTA-like transposable element in ZmCCT attenuated photoperiod sensitivity and accelerated the postdomestication spread of maize. Proc. Natl. Acad. Sci. USA 2013, 110, 16969–16974. [Google Scholar] [CrossRef] [Green Version]
  17. Jin, M.; Liu, X.; Jia, W.; Liu, H.; Li, W.; Peng, Y.; Du, Y.; Wang, Y.; Yin, Y.; Zhang, X.; et al. ZmCOL3, a CCT gene represses flowering in maize by interfering with the circadian clock and activating expression of ZmCCT. J. Integr. Plant Biol. 2018, 60, 465–480. [Google Scholar] [CrossRef] [PubMed]
  18. Colasanti, J.; Yuan, Z.; Sundaresan, V. The indeterminate Gene Encodes a Zinc Finger Protein and Regulates a Leaf-Generated Signal Required for the Transition to Flowering in Maize. Cell 1998, 93, 593–603. [Google Scholar] [CrossRef] [Green Version]
  19. Muszynski, M.G.; Dam, T.; Li, B.; Shirbroun, D.M.; Hou, Z.; Bruggemann, E.; Archibald, R.; Ananiev, E.V.; Danilevskaya, O.N. Delayed flowering1 Encodes a Basic Leucine Zipper Protein That Mediates Floral Inductive Signals at the Shoot Apex in Maize. Plant Physiol. 2006, 142, 1523–1536. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  20. Zhao, S.; Luo, Y.; Zhang, Z.; Xu, M.; Wang, W.; Zhao, Y.; Zhang, L.; Fan, Y.; Wang, L. ZmSOC1, a MADS-Box Transcription Factor from Zea mays, Promotes Flowering in Arabidopsis. Int. J. Mol. Sci. 2014, 15, 19987–20003. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  21. Salvi, S.; Sponza, G.; Morgante, M.; Tomes, D.; Niu, X.; Fengler, K.A.; Meeley, R.; Ananiev, E.V.; Svitashev, S.; Bruggemann, E.; et al. Conserved noncoding genomic sequences associated with a flowering-time quantitative trait locus in maize. Proc. Natl. Acad. Sci. USA 2007, 104, 11376–11381. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Alter, P.; Bircheneder, S.; Zhou, L.Z.; Schlüter, U.; Gahrtz, M.; Sonnewald, U.; Dresselhaus, T. Flowering Time-Regulated Genes in Maize Include the Transcription Factor ZmMADS1. Plant Physiol. 2016, 172, 389–404. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Berke, T.G.; Rocheford, T.R. Quantitative Trait Loci for Flowering, Plant and Ear Height, and Kernel Traits in Maize. Crop Sci. 1995, 35, 1542–1549. [Google Scholar] [CrossRef]
  24. Peng, J.; Richards, D.E.; Hartley, N.M.; Murphy, G.P.; Devos, K.M.; Flintham, J.E.; Beales, J.; Fish, L.J.; Worland, A.J.; Pelica, F.; et al. Green revolution’ genes encode mutant gibberellin response modulators. Nature 1999, 400, 256–261. [Google Scholar] [CrossRef] [PubMed]
  25. Zhang, Y.; Li, Y.; Wang, Y.; Liu, Z.; Liu, C.; Peng, B.; Tan, W.; Wang, D.; Shi, Y.; Sun, B.; et al. Stability of QTL across environments and QTL-by-environment interactions for plant and ear height in maize. Agric. Sci. China 2010, 9, 1400–1412. [Google Scholar] [CrossRef]
  26. Cai, H.; Chu, Q.; Gu, R.; Yuan, L.; Liu, J.; Zhang, X.; Chen, F.; Mi, G.; Zhang, F. Identification of QTLs for plant height, ear height and grain yield in maize (Zea mays L.) in response to nitrogen and phosphorus supply. Plant Breed. 2012, 131, 502–510. [Google Scholar] [CrossRef]
  27. Vanous, A.; Gardner, C.; Blanco, M.; Martin-Schwarze, A.; Lipka, A.E.; Flint-Garcia, S.; Bohn, M.; Edwards, J.; Lubberstedt, T. Association Mapping of Flowering and Height Traits in Germplasm Enhancement of Maize Doubled Haploid (GEM-DH) Lines. Plant Genome 2018, 11, 170083. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Wu, X.; Guo, X.; Wang, A.; Liu, P.; Wu, W.; Zhao, Q.; Zhao, M.; Zhu, Y.; Chen, Z. Quantitative trait loci mapping of plant architecture-related traits using the high-throughput genotyping by sequencing method. Euphytica 2019, 215, 212. [Google Scholar] [CrossRef]
  29. Peiffer, J.A.; Romay, M.C.; Gore, M.A.; Flint-Garcia, S.A.; Zhang, Z.; Millard, M.J.; Gardner, C.A.; McMullen, M.D.; Holland, J.B.; Bradbury, P.J.; et al. The Genetic Architecture Of Maize Height. Genetics 2014, 196, 1337–1356. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  30. Li, X.; Zhou, Z.; Ding, J.; Wu, Y.; Zhou, B.; Wang, R.; Ma, J.; Wang, S.; Zhang, X.; Xia, Z.; et al. Combined Linkage and Association Mapping Reveals QTL and Candidate Genes for Plant and Ear Height in Maize. Front. Plant Sci. 2016, 15, 833. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Zhou, Z.; Zhang, C.; Zhou, Y.; Hao, Z.; Wang, Z.; Zeng, X.; Di, H.; Li, M.; Zhang, D.; Yong, H.; et al. Genetic dissection of maize plant architecture with an ultra-high density bin map based on recombinant inbred lines. BMC Genom. 2016, 3, 178. [Google Scholar] [CrossRef] [Green Version]
  32. Chen, Z.; Wang, B.; Dong, X.; Liu, H.; Ren, L.; Chen, J.; Hauck, A.; Song, W.; Lai, J. An ultra-high density bin-map for rapid QTL mapping for tassel and ear architecture in a large F₂ maize population. BMC Genom. 2014, 15, 433. [Google Scholar] [CrossRef] [Green Version]
  33. Zhou, Z.; Zhang, C.; Lu, X.; Wang, L.; Hao, Z.; Li, M.; Zhang, D.; Yong, H.; Zhu, H.; Weng, J.; et al. Dissecting the Genetic Basis Underlying Combining Ability of Plant Height Related Traits in Maize. Front. Plant Sci. 2018, 9, 1117. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Winkler, R.G.; Helentjaris, T. The maize Dwarf3 gene encodes a cytochrome P450-mediated early step in Gibberellin biosynthesis. Plant Cell 1995, 7, 1307–1317. [Google Scholar] [PubMed] [Green Version]
  35. Teng, F.; Zhai, L.; Liu, R.; Bai, W.; Wang, L.; Huo, D.; Tao, Y.; Zheng, Y.; Zhang, Z. ZmGA3ox2, a candidate gene for a major QTL, qPH3.1, for plant height in maize. Plant J. 2013, 73, 405–416. [Google Scholar] [CrossRef]
  36. Hartwig, T.; Chuck, G.S.; Fujioka, S.; Klempien, A.; Weizbauer, R.; Potluri, D.P.; Choe, S.; Johal, G.S.; Schulz, B. Brassinosteroid control of sex determination in maize. Proc. Natl. Acad. Sci. USA 2011, 108, 19814–19819. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Multani, D.S.; Briggs, S.P.; Chamberlin, M.A.; Blakeslee, J.J.; Murphy, A.S.; Johal, G.S. Loss of an MDR Transporter in Compact Stalks of Maize br2 and Sorghum dw3 Mutants. Science 2003, 302, 81–84. [Google Scholar] [CrossRef] [PubMed]
  38. Lawit, S.J.; Wych, H.M.; Xu, D.; Kundu, S.; Tomes, D.T. Maize DELLA Proteins dwarf plant8 and dwarf plant9 as Modulators of Plant Development. Plant Cell Physiol. 2010, 51, 1854–1868. [Google Scholar] [CrossRef] [Green Version]
  39. Li, W.; Ge, F.; Qiang, Z.; Zhu, L.; Zhang, S.; Chen, L.; Wang, X.; Li, J.; Fu, Y. Maize ZmRPH1 encodes a microtubule-associated protein that controls plant and ear height. Plant Biotechnol. J. 2020, 18, 1345–1347. [Google Scholar] [CrossRef] [Green Version]
  40. Du, L.; Yu, F.; Zhang, H.; Wang, B.; Ma, K.; Yu, C.; Xin, W.; Huang, X.; Liu, Y.; Liu, K. Genetic mapping of quantitative trait loci and a major locus for resistance to grey leaf spot in maize. Theor. Appl. Genet. 2020, 133, 2521–2533. [Google Scholar] [CrossRef] [PubMed]
  41. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2014; Available online: http://www.R-project.org/ (accessed on 10 July 2014).
  42. Knapp, S.J.; Stroup, W.W.; Ross, W.M. Exact Confidence Intervals for Heritability on a Progeny Mean Basis. Crop Sci. 1985, 25, 192–194. [Google Scholar] [CrossRef]
  43. Bates, D.; Mächler, M.; Bolker, B.; Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 2015, 67. [Google Scholar] [CrossRef]
  44. Wang, S.; Basten, C.; Zeng, Z. Windows QTL Cartographer 2.5; Department of Statistics, North Carolina State University: Raleigh, NC, USA, 2012. [Google Scholar]
  45. McCouch, S.; Cho, Y.; Yano, M.; Paul, E.; Blinstrub, M.; Morishima, H.; Kinoshita, T. Report on QTL nomenclature. Rice Genet. Newsl. 1997, 14, 11–13. [Google Scholar]
  46. Wei, X.; Xu, J.; Guo, H.; Jiang, L.; Chen, S.; Yu, C.; Zhou, Z.; Hu, P.; Zhai, H.; Wan, J. DTH8 Suppresses Flowering in Rice, Influencing Plant Height and Yield Potential Simultaneously. Plant Physiol. 2010, 153, 1747–1758. [Google Scholar] [CrossRef] [Green Version]
  47. Weng, X.; Wang, L.; Wang, J.; Hu, Y.; Du, H.; Xu, C.; Xing, Y.; Li, X.; Xiao, J.; Zhang, Q. Grain Number, Plant Height, and Heading Date7 Is a Central Regulator of Growth, Development, and Stress Response. Plant Physiol. 2014, 164, 735–747. [Google Scholar] [CrossRef] [Green Version]
  48. Cai, Y.; Chen, X.; Xie, K.; Xing, Q.; Wu, Y.; Li, J.; Du, C.; Sun, Z.; Guo, Z. Dlf1, a WRKY Transcription Factor, Is Involved in the Control of Flowering Time and Plant Height in Rice. PLoS ONE 2014, 9, e102529. [Google Scholar] [CrossRef] [Green Version]
  49. Thornsberry, J.M.; Goodman, M.M.; Doebley, J.; Kresovich, S.; Nielsen, D.; Buckler, E.S. Dwarf8 polymorphisms associate with variation in flowering time. Nat. Genet. 2001, 28, 286–289. [Google Scholar] [CrossRef]
  50. Wang, J.; Yang, J.; Jia, Q.; Zhu, J.; Shang, Y.; Hua, W.; Zhou, M. A New QTL for Plant Height in Barley (Hordeum vulgare L.) Showing No Negative Effects on Grain Yield. PLoS ONE 2014, 9, e90144. [Google Scholar] [CrossRef]
  51. Yan, W.H.; Wang, P.; Chen, H.X.; Zhou, H.J.; Li, Q.P.; Wang, C.R.; Ding, Z.H.; Zhang, Y.S.; Yu, S.B.; Xing, Y.Z.; et al. A Major QTL, Ghd8, Plays Pleiotropic Roles in Regulating Grain Productivity, Plant Height, and Heading Date in Rice. Mol. Plant 2011, 4, 319–330. [Google Scholar] [CrossRef]
  52. Zhang, Z.H.; Wang, K.; Guo, L.; Zhu, Y.J.; Fan, Y.Y.; Cheng, S.H.; Zhuang, J.Y. Pleiotropism of the Photoperiod-Insensitive Allele of Hd1 on Heading Date, Plant Height and Yield Traits in Rice. PLoS ONE 2012, 7, e52538. [Google Scholar] [CrossRef] [Green Version]
  53. Beavis, W.D.; Grant, D.; Albertsen, M.; Fincher, R. Quantitative trait loci for plant height in four maize populations and their associations with qualitative genetic loci. Theor. Appl. Genet. 1991, 83, 141–145. [Google Scholar] [CrossRef] [PubMed]
  54. Duvick, D.N. Genetic progress in yield of United States maize. Maydica 2007, 50, 193–202. [Google Scholar]
  55. Weng, J.; Xie, C.; Hao, Z.; Wang, J.; Liu, C.; Li, M.; Zhang, D.; Bai, L.; Zhang, S.; Li, X. Genome-Wide Association Study Identifies Candidate Genes That Affect Plant Height in Chinese Elite Maize (Zea mays L.) Inbred Lines. PLoS ONE 2011, 6, e29229. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Farkhari, M.; Krivanek, A.; Xu, Y.; Rong, T.; Naghavi, M.R.; Samadi, B.Y.; Lu, Y. Root-lodging resistance in maize as an example for high-throughput genetic mapping via single nucleotide polymorphism-based selective genotyping. Plant Breed. 2012, 132, 90–98. [Google Scholar] [CrossRef]
  57. Tadesse, E.B.; Olsen, M.; Das, B.; Gowda, M.; Labuschagne, M. Genetic Dissection of Grain Yield and Agronomic Traits in Maize under Optimum and Low-Nitrogen Stressed Environments. Int. J. Mol. Sci. 2020, 21, 543. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Plants 10 01585 g001 550
Figure 1. Distribution plot of phenotypic value and the Pearson correlation coefficient among different traits in the DH lines of the two DH populations: (A) panel represents QY population; (B) panel represents QZ population. On the diagonal are the bar plots of phenotypic distributions for the six traits; below the diagonal is the regression graph, and each sub-graph represents a regression of two corresponding traits on the diagonal; above the diagonal is the Pearson correlation coefficient, and each sub-graph represents a correlation coefficient of two corresponding traits on the diagonal. The “*” and “***” above the correlation coefficient represent significant p-value < 0.05 and 0.001, respectively.
Figure 1. Distribution plot of phenotypic value and the Pearson correlation coefficient among different traits in the DH lines of the two DH populations: (A) panel represents QY population; (B) panel represents QZ population. On the diagonal are the bar plots of phenotypic distributions for the six traits; below the diagonal is the regression graph, and each sub-graph represents a regression of two corresponding traits on the diagonal; above the diagonal is the Pearson correlation coefficient, and each sub-graph represents a correlation coefficient of two corresponding traits on the diagonal. The “*” and “***” above the correlation coefficient represent significant p-value < 0.05 and 0.001, respectively.
Plants 10 01585 g001
Plants 10 01585 g002 550
Figure 2. Distribution of QTLs for the six flowering time and height-related traits on the maize chromosomes. Colored lines depict QTL regions for different traits; the solid lines and hollow lines represent QTLs detected in the QY and QZ population, respectively, and the black spots represent centromeres. The red and blue colors represent flowering time and height traits, respectively, and the colors’ shading is used to distinguish the traits. The horizontal axes indicate the physical location in different chromosomes.
Figure 2. Distribution of QTLs for the six flowering time and height-related traits on the maize chromosomes. Colored lines depict QTL regions for different traits; the solid lines and hollow lines represent QTLs detected in the QY and QZ population, respectively, and the black spots represent centromeres. The red and blue colors represent flowering time and height traits, respectively, and the colors’ shading is used to distinguish the traits. The horizontal axes indicate the physical location in different chromosomes.
Plants 10 01585 g002
Table
Table 1. Phenotypic summary of the two DH populations and their parents combined with the three environments.
Table 1. Phenotypic summary of the two DH populations and their parents combined with the three environments.
TraitsQ1Ye478Zheng58Population QYPopulation QZ
Mean ± SD aRange bMean ± SDSkew. cKurt. dRangeMean ± SDSkew.Kurt.
AD (days)89.1 ± 3.2 80.0 ± 2.181.9 ± 2.174.0–100.087.8 ± 4.6−0.07 −0.17 72.0–99.084.3 ± 4.70.13 −0.47
SD (days)94.0 ± 1.883.5 ± 1.885.2 ± 1.677.0–105.091.3 ± 4.7−0.09 0.02 75.0–105.088.5 ± 5.30.05 −0.19
ASI (days)4.9 ± 1.93.5 ± 0.43.4 ± 1.40–12.03.5 ± 1.90.78 0.66 −2.0–16.04.3 ± 2.30.84 1.60
PH (cm)270.1 ± 8.9174.5 ± 10.7158.6 ± 9.7123.0–310.0206.7 ± 28.20.11 0.43 140.0–305.0208.1 ± 28.40.16 −0.10
EH (cm)120.3 ± 3.260.5 ± 3.850.6 ± 4.337.0–143.775.3 ± 18.10.32 0.12 34.3–157.071.0 ± 19.30.32 0.16
ER (%)44.6 ± 2.634.2 ± 4.131.7 ± 3.219.8–57.936.3 ± 5.30.02 0.29 18.6–54.935.8 ± 6.3−0.13 −0.17
a standard deviation; b minimum value to maximum value; c skewness; d kurtosis. The traits of AD, SD, ASI, PH, EH, and ER represent days to anthesis, days to silking, anthesis–silking interval, plant height, ear height, and EH/PH ratio, respectively. The population QY represents the DH population constructed by Q1 and Ye478, and the population QY represents the DH population constructed by Q1 and Zheng58.
Table
Table 2. QTLs for the six flowering time and height-related traits in the two DH populations.
Table 2. QTLs for the six flowering time and height-related traits in the two DH populations.
Pop.QTL NameChr.Peak
(cM)		LODAdd.R2 (%)2-LOD Interval
(cM)		Range
(Mb)		Trait
QYqPH_Y1a140.24.2−6.78.836.6–50.415.6–33.4PH
qEH_Y1a144.33.2−3.47.041.3–49.622.6–33.0EH
qAD_Y1a1173.96.5−1.012.5165.7–185.4234.3–277.0AD
qSD_Y1a1173.95.3−1.010.7162.4–184.3232.2–272.1SD
qSD_Y3a335.33.5−0.86.828.7–36.14.9–6.5SD
qSD_Y5a562.38.0−2.016.754.1–71.320.3–165.9SD
qAD_Y5a566.54.3−0.88.354.1–71.120.3–165.9AD
qPH_Y5a591.97.2−9.015.374.6–96.0165.9–203.8PH
qEH_Y5a5102.55.6−4.813.391.4–112.9195.8–214.0EH
qER_Y5a5117.33.0−1.07.8106.6–121.4207.7–217.3ER
qASI_Y5a5130.44.11.211.7128.8–140.3218.9–221.1ASI
qPH_Y7a744.33.1−5.86.542.6–50.024.7–45.7PH
qEH_Y7a770.73.3−3.57.763.2–80.6119.5–134.7EH
qEH_Y9a937.75.1−4.512.026.5–48.49.4–21.6EH
qPH_Y9a952.06.0−8.414.043.7–65.616.8–108.9PH
qAD_Y10a1034.54.3−0.88.231.7–44.914.4–129.5AD
qSD_Y10a1056.06.3−1.113.545.1–59.9129.5–142.3SD
QZqER_Z1a190.07.9−1.713.873.8–96.035.5–71.2ER
qEH_Z1a194.26.6−4.611.283.4–107.251.4–85.1EH
qPH_Z1a1109.05.0−5.97.799.7–125.572.9–172.2PH
qSD_Z1a1189.65.0−0.910.0176–197.0221.1–240.4SD
qER_Z1a1239.63.0−1.04.8235.3–250.5279.6–285.5ER
qEH_Z3a360.64.1−3.56.649.6–65.56.7–11.9EH
qER_Z3a360.612.0−2.122.055.6–63.78.5–10.5ER
qAD_Z4a499.86.4−0.811.383.4–104.9158.2–181.5AD
qPH_Z5a5111.77.5−7.412.499.3–123.7147.4–175.0PH
qEH_Z5a5128.06.8−4.711.6116.7–138.5168.6–199.3EH
qEH_Z6a6153.73.02.94.4146.5–160.7166.8–169.7EH
qEH_Z7a768.03.23.15.156.8–78.787.4–126.7EH
qSD_Z8a885.53.8−0.77.379.4–96.5110.5–156.3SD
qAD_Z8a897.83.2−0.65.680.9–99.3112.4–163.8AD
qPH_Z9a997.98.9−9.214.790.0–108.8147.7–155.6PH
qEH_Z9a997.94.2−4.06.889.7–105.9147.7–155.2EH
qPH_Z10a1029.03.1−4.84.823.5–30.317.4–69.0PH
“Pop.” represents the population from which the QTL was detected; “Chr.” is the chromosome; “LOD” is logarithm of odds; “Add.” represents additive effect of QTL; “R2” is phenotypic variation explained by each QTL; “2 LOD interval” represents confidence interval that defines the 2 LOD interval of the QTL; “Range” represents the physical interval of the QTL distributed in the chromosome according to B73 RefGen_v4.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Du, L.; Zhang, H.; Xin, W.; Ma, K.; Du, D.; Yu, C.; Liu, Y. Dissecting the Genetic Basis of Flowering Time and Height Related-Traits Using Two Doubled Haploid Populations in Maize. Plants 2021, 10, 1585. https://doi.org/10.3390/plants10081585

AMA Style

Du L, Zhang H, Xin W, Ma K, Du D, Yu C, Liu Y. Dissecting the Genetic Basis of Flowering Time and Height Related-Traits Using Two Doubled Haploid Populations in Maize. Plants. 2021; 10(8):1585. https://doi.org/10.3390/plants10081585

Chicago/Turabian Style

Du, Lei, Hao Zhang, Wangsen Xin, Kejun Ma, Dengxiang Du, Changping Yu, and Yongzhong Liu. 2021. "Dissecting the Genetic Basis of Flowering Time and Height Related-Traits Using Two Doubled Haploid Populations in Maize" Plants 10, no. 8: 1585. https://doi.org/10.3390/plants10081585

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop