Introduction
Phosphorus is an essential nutrient for plant production, and the phosphorus deficiency is one of the most common and serious environmental constraints in tropic regions, reducing maize mean yields. As a result, improving the adaptation and/or tolerance of maize to phosphorus deficiency is an important objective in most regions (
Helentjaris et al., 1986;
Hinsinger and Gilkes, 1996,
Hinsinger, 2001). Plants can actively improve their acquisition of P in several ways. Access to total soil P resources might be improved by increasing the absorbing area of the root system, through increased root length and root fiber number (
Zuber et al., 1968;
Guingo et al., 1998;
Tuberosa et al., 2003;
Zhu et al., 2005).
Great progress has been made on detecting QTLs in rice, cotton,
Brassica napus, and maize in recent years, with QTLs mapped of yield and agronomic and quality traits in tetraploidpotato (
Tuberosa et al., 1998a,
1998b,
2002). QTLs of agronomic and fiber traits in cotton have been detected by AFLP marker (
Wu et al., 2007). QTLs for morphological and physiologic traits related to rice stress tolerance have been studied. QTLs associated with root morphology, crop yield, and stress resistance have been mapped in rice, maize, and soybean (
Chen et al., 2008,
2009,
Chen and Xu, 2011;
Chen et al., 2011). QTLs have also been researched in the maximum root length of maize, total root number of maize, leaf water potential of cotton, osmosis, and osmotic adjustment (
Zhu et al., 2005;
Chen et al., 2008). Marker-assisted selection (MAS) based on QTL has been used in the genetic improvement of yield in maize, common bean, barley, and rice. Moreover, some achievements have been made in molecular marker-assisted breeding (
Tuberosa et al., 1998a;
Yan et al., 2004;
Zhu et al., 2005;
Chen et al., 2009).
QTL mapping provides a means to detect complex genetic characters, such as QTL of plant in response to phosphorus deficiency and allows the identification of molecular markers linked to desirable QTLs that can be directly used to improve PAE and root-related traits through MAS. In maize, the QTLs for root number in Polj17 × F-2 and root volume in B73 × Mo17 (
Kaeppler et al., 2000) have been described. Tuberosa et al. (
2002) reported QTL regions influencing root diameter and root length in hydroponics, while Guingo et al. (
1998) identified the QTL for root weight. Moreover, recently, Guingo et al. (
1998) and Tuberosa et al. (
2002) have described the QTL for root pulling force in hydroponics. The QTLs of root hair length and lateral branch length in hydroponics were studied, and a QTL flanked by npi409-nc007 for root hair length was mapped on Chromosome 5 (
Zhu and Lynch, 2004).
The previous studies in QTLs for root traits were in hydroponics under unnatural environment for plant growth with a small number of QTLs, a short linkage map for QTLs, and a comparatively large distance between markers. Furthermore, the QTL for the same root trait in different environments has not been studied so far.
The genotypic responses to phosphorus deficiency are different and genotype × environment interaction well known in many quantitative trait locus (QTL), which severely limits practices in plant breeding by using marker-assisted selection (MAS) (
Tuberosa et al., 2002,
Tuberosa et al., 2003;
Yan et al., 2004). Only the identification of stable QTL responsible for phosphorus absorption efficiency and root-related traits across P levels, different environments, and different growth stages might be used in MAS.
The objectives of this study were to identify the QTLs for phosphorus absorption efficiency and root-related traits in field conditions and the stable QTL and analyze the common regions of QTLs for multitraits under the four environments including different P levels, different sites, and different growth stages, which may be useful for improving phosphorus efficiency by means of marker-assisted selection.
Materials and methods
Plant materials
The mapping population included 241 F2∶3 families derived from a corresponding number of randomly chosen F2 plants of the cross between inbred 082 (P deficiency tolerant) and Ye107 (P deficiency susceptible), which differed in phosphorus efficiency and root traits. The F2 families were reproduced from October 2006 to February 2007 in Hainan, China. The F2∶3 families were reproduced in March–July, 2007 in Xiema, Beibei, China.
Field experiment
The experiment was designed as a split plot experiment with three replications at Kaixian County (KX), with P as main environment, F2∶3 families along with F1 and both parents lines as vice environment. The field experiment was conducted at a randomized block design with three replications at the South-west University (SU). F2∶3 families along with F1 and both parents lines were sowed. A set of experiments were conducted at Kaixian County (KX) (31°11′N latitude, 98°58′E longitude; 1000 m altitude) and South-west University (SU) (29°48′N latitude, 106°33′E longitude; 150 m altitude) during September to October in 2007. In Kaixian soil, the contents of total N, P, K, and available N, P, K were 0.236 g/kg, 0.395 g/kg, 18.9 g/kg, 14.7 mg/kg, 2.0 mg/kg, and 117 mg/kg, respectively; the organic matter was 2.99 g/kg, and the pH was 8.2. In South-West University soil, the contents of total N, P, K, and available N, P, and K were 0.259 g/kg, 0.602 g/kg, 17.8 g/kg, 14.1 mg/kg, 2.6 mg/kg, 121 mg/kg, respectively, the organic matter was 3.43 g/kg, and the pH was 7.9. Fertilizers were applied before sowing at rates of 120 kg N and 50 kg P per hectare under normal P application (KXNP), but only applied at a rate of 120 kg N under deficient P application at Kaixian (KXDP), while fertilizers were applied before sowing at rates of 120 kg N per hectare at the South-West University (SUDP). The area per split plot was 2.5 m2 with 10 plants. Cultivation was carried out according to standard practices.
Measurement of biologic traits
The plants were harvested at the 21st day after emergence of seedling at Kaixian (KX), while they were collected at the 21st (SUDP1) and 35th (SUDP2) day at the South-West University (SU). The fibrous root number (FN) and taproot length (RL) was recorded. The above-ground biomass weight and the root dry weight (RW) were determined after plants were deactivated at 105°C for 30 min and dried at 80°C for 72 h. The plant weight was the sum of the above-ground biomass weight and the root dry weight.
Analysis of plant phosphorus content
Plants were dried at 60°C for 72 h, ground, and burned to ash at 500°C for 12 h after being weighed. The ash was dissolved by adding 8 mL of 100 mM HCl to each sample. The dissolved samples were analyzed for phosphorus concentration by means of spectroscopic methodology. The phosphorus absorption efficiency (PAE) was calculated by plant weight × plant phosphorus concentration.
Statistical analysis of data
Arithmetic means of three replicates was calculated for each trait of each F
2∶3 family. The transgressive segregation was performed for genotypes, which had traits with values beyond the two parents (i.e., larger than 082 or smaller than Ye107) in four environments. The heritability of traits for the F
2∶3 families was estimated by the following formula:
where
and
are the estimates of genetic variance and environment variance, respectively.
QTL analysis
The procedure of composite interval mapping was used to identify QTLs and estimate their effects. QTL mapping was performed with the software program Windows QTL Cartographer version 2.5. Parameters for forward regression analysis were a window size of 10 cM, a walk speed of 2 cM, five background control markers, and probability thresholds of 0.05 each for the partial
F test for both marker inclusion and exclusion (
Kosambi, 1944). The significance threshold for QTL detection was calculated by 1000 random permutations of the phenotypic data at 5% level, and LOD thresholds were set at 2.48 for all traits. QTL positions were assigned at the point of maximum LOD score in the regions under consideration. Gene action mode of each significant QTL (d/a) was estimated according to the additive (a) and dominant (d) effects, which was classified to four parts of additive (0 to 0.20), partial dominant (0.21 to 0.80), dominant (0.81 to 1.20), and over dominant (>1.20), according to Stuber and Sisco (
1992) and Tuberosa et al. (
1998a).
Results
Variation of phenotypic traits among F2∶3 families
In four environments, the two parental genotypes, 082 and Ye107, differed significantly in PAE, RW, RL, and FN. The former had higher values than the later for these traits (Table 1). All traits were continuously segregated and approximately normally distributed with absolute values of skewness and kurtness less than 1.0, which indicated that all traits were suitable for QTL mapping.
Analysis of variance (ANOVA) was employed to estimate genetic variance (), environment variance (), and subsequently broad-sense heritability (). The for different traits varied from 73.8% to 91.8% (Table 1), and the heritability of the other traits was generally high (>70%).
The analysis of variance for PAE, RW, RL, and FN tested on the F2∶3 families in the four environments, i.e., KXDP, KXNP, SUDP1, and SUDP2, and was summarized in Table 2. The significant variances of genotype and environment indicated that the PAE, RW, RL, and FN might be affected by both the genotypes and environments.
Correlation among traits at the two sites
The correlation coefficient among traits was shown in Table 3. All traits were highly positive correlated (r>0.70).
QTL analysis
In the four environments, KXDP, KXNP, SUDP1, and SUDP2. One QTL was detected to influence PAE, which was located in the interval dupssr15–P1M7/a (bins 6.06) on Chromosome 6 (Table 4 and Fig. 1). The QTL on Chromosome 6 explained 4%-10% of total phenotypic variance of PAE. The alleles from the QTL on Chromosome 6, which contributes to increasing the PAE, were from the higher phosphorus efficiency parental genotype 082(P1) and estimates of the genetic effects presented partial dominance.
In KXNP, KXDP, and SUDP2, there existed one QTL detected to influence PAE and located in the interval P1M3/d–P1M3/g (bins 9.04) on Chromosome 9 (Table 4 and Fig. 1). The QTL on Chromosome 9 explained 8%-11% of total phenotypic variance of PAE. The alleles from the QTL on chromosome 9, which contribute to increase the PAE, were from the higher phosphorus efficiency parental genotype 082(P1) and the estimates of the genetic effects presented over dominance.
In KXNP and KXDP, one QTL was detected to influence RL and located in the interval bnlg2191-umc1572 (bins 6.02) on Chromosome 6 (Table 4 and Fig. 1). The QTL explained 10%-11% of total phenotypic variance RL. The alleles from the QTL, contributing to increasing the RL, were from the higher phosphorus efficiency parental genotype 082(P1) with the estimates of the genetic effects over dominance.
One distinct QTL of PAE was identified in bin 2.03 in KXNP, and three distinct QTLs of RL were identified in bin 2.09, 5.08, and 8.04 in KXDP. One distinct QTL of RL was detected in bin 5.07 in SUDP2, and three distinct QTLs of FN were detected in bins 7.04, 5.07, and 6.06 in KXDP, SUDP1, and KXNP, respectively.
QTL affecting phosphorus absorption efficiency and root weight was detected simultaneously in bin 6.06 in all four environments, while QTL affecting taproot length and fiber number was only detected in one or two environments (Table 4). The results suggested that taproot length and fiber number were more easily affected by the environment than phosphorus absorption efficiency and root weight.
Discussion
In maize (
Zea mays L.), the QTLs affecting root traits were detected on chromosomes bins 1.03, 1.06, 1.08, 2.03, and 2.04 (
Tuberosa et al., 2003). The concentrations of QTLs on Chromosome 1 were found in a previous study (
Tuberosa et al., 2003). This region harbors QTLs for root traits in hydroponics in both Lo964 × Lo1016 (
Tuberosa et al., 2002) and Ac7729 × Ac7643/TZSRW (Tuberosa et al., 2003), QTLs for root traits in both Lo964 × Lo1016 and Polj17 × F-2, and QTL for root volume in B73 × Mo17 (
Kaeppler et al., 2000). In a previous study, the region for QTL on bin 6.06 was for the QTL of root pulling force in hydroponics in Lo964 × Lo1016 (
Tuberosa et al., 2002).
In our study, among QTLs mapped for phosphorus absorption efficiency and root-related traits, one QTL was detected in two environments, one QTL was detected in three environments, and one (bin 6.06) was detected in all four environments. The genomic regions in dupssr15 locus (bin 6.06) for QTL of RW were free from the environment it affects, while others were more affected by environments. The QTLs conferring PAE and RW of Chromosome 6 were relatively stable across environments. The QTL detected at the same marker intervals in four environments indicated that QTLs are not easily affected by environmental factors and that the QTL detected to influence RW was in the interval dupssr15- P1M7/a (bins 6.06) on Chromosome 6 across P levels and two different sites. QTLs affecting phosphorus absorption efficiency and root weight were detected in KXDP, KXNP, SUDP1, and SUDP2, which is the first time for QTLs to be detected in the meantime across P levels and different sites, and the QTLs affecting RW was located in the same region in four environments at the same time, which means the QTLs had high stability in deficient and normal P application. It is so important to improve P absorption in maize that QTL might be considered as the candidate QTLs for phosphorus absorption efficiency and root weight. It is interesting to find the same QTL for trait RW, which suggests that phosphorus utilization efficiency is affected both by phosphorus absorption efficiency and root weight traits, and root weigh and phosphorus absorption efficiency might be controlled by the same gene.
Higher Education Press and Springer-Verlag Berlin Heidelberg
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