Previous PageTable Of ContentsNext Page

Identification of quantitative trait loci for flowering time using SSR markers in maize under water-stressed conditions

Shihuang Zhang and Xinhai Li

Institute of Crop Breeding and Cultivation, Chinese Academy of Agricultural Sciences, Beijing 100081, China Email cshzhang@public.bta.net.cn

Abstract

Characterization of the quantitative trait loci (QTL) involved in flowering time will be helpful for selection in maize breeding. In this study, three flowering traits of 234 F2:3 families, derived from the cross X178B73, were evaluated under well-watered and water-stressed regimes in Linfen city of Shanxi province, China. The Simple Sequence Repeat (SSR) marker map was used to identify QTL conferring flowering traits. Correlation analysis showed that anthesis silking interval (ASI) was significantly correlated with female flowering trait (FFT). With composite interval mapping, 9, 7 and 6 QTLs were identified for male flowering trait (MFT), FFT and ASI under water-stressed regime, respectively, and individual QTL could account for 2.88%- 31.65% of phenotypic variation. Some QTLs for MFT were found to overlap with those for FFT and ASI. The QTL adjacent to nc134 on chromosome 9 was consistently mapped for MFT, FTT and ASI under two water regimes, and the QTL near phi053 on chromosome 3 was mapped both for MFT and FFT.

Media summary

QTLs identified for drought tolerance at flowering stage will facilitate germplasm improvement for drought tolerance in China.

Key words

Zea mays L, drought tolerance, SSR markers, Quantitative trait locus (QTL), flowering time, linkage map

Introduction

Water availability is one of the major limiting factors for plant growth. Maize, one of the staple food and feed crops in the world, is particularly sensitive to water stress at flowering stage. In China, 70% of maize acreage is grown under drought conditions, and there is about 30% yield loss annually. With development of molecular markers, it is possible to identify major QTLs regulating specific drought responses, and further to establish a marker-aided selection (MAS) approach, providing an efficient way to improve drought tolerance in maize (Veldboom et al. 1996). To date, many QTLs for flowering time in maize, identified under drought-stressed conditions, were mainly investigated by RFLP markers (Ribaut et al. 1996; Sari-gorla et al. 1999). RFLP makers were rarely used in maize breeding because of high cost and labor requirement. The emergence of SSR marker techniques provide an alternative approach for establishing MAS with its cheaper price and ease of handling. Only part of the QTLs (no more than 12) of one complex trait can be detected in a given mapping population because of the limitation of polymorphic markers between two parents (Hyne and Kearsey 1995). The comprehensive genetic basis on drought tolerance during flowering time in maize can be obtained by analyzing populations with different genetic backgrounds. The objective of this paper was to locate QTLs associated with drought tolerance by use of a SSR linkage map and to analyze their genetic effects in Chinese maize germplasm.

Materials and methods

Plant materials and plot design

An F2 population of 234 plants derived from the cross, X178 B73, was used to construct the genetic linkage map. The 234 corresponding F2:3 families was evaluated for drought response in Linfen city, Shanxi province during the dry summer season in 2002. The phenotyping experiment was arranged in a complete block design with two replicates each under well-watered (WW) and severe-stressed (SS) regimes. The plot consisted of one 4m-row with 0.60m spacing between plots. Water was applied by furrow irrigation. All the treatments received the first irrigation 20 days after planting. After this period, irrigation was applied every 20 days to the WW regime, while SS regime obtained irrigation only at 65 days. Both treatments were irrigated at 90 days after planting to ensure adequate development of the kernels that had been set.

Flowering and ASI scoring

Male flowering time (MFT) and female flowering time (FFT) were recorded as the number of days from emergence to anther extrusion from the tassel or to visible silks of 50% of the plants per plot. Anthesis- silking interval (ASI) was calculated as the difference between FFT and MFT of each plot.

DNA extraction and SSR marker assay

Leaf tissues of each F2 plant were collected and ground to fine powder within liquid nitrogen. DNA extraction, PCR reaction, gel electrophoresis and silver staining method, were performed following the protocol adapted by CIMMYT Applied Molecular Genetics Laboratory (2001). The SSR markers showing polymorphism between the parents were used to assay 234 F2 individuals from the cross X178 B73.

Statistical and QTL analyses

The means of MFT, FFT and ASI for parents and F2:3 families were calculated across each water regime, and simple Pearson correlation coefficients were calculated between the traits. A linkage map was constructed using Mapmaker 3.0 with the LOD threshold of 3.0. The procedure of composite interval mapping was used to identify QTLs and estimate their effects. QTLs for each trait were searched using WinqtlCart2.0 with the LOD threshold of 2.5 (Wang et al. 2003). The gene action of QTL was determined with the dominance ratio (DR=∣d/a∣)defined by Stuber et al.(1987) (additive for DR<0.2, partial dominance for 0.2≤DR<0.8, dominance for 0.8≤DR<1.2, overdominance for DR≥1.2).

Results

Flowering and ASI data analysis

The parental line X178 flowered a little earlier than B73, and both were delayed in silking under the water- stressed regime with increased ASI (Table1). In the F2:3 population, MFT ranged from 54.0 to 64.5 days and from 54.0 to 65.0 days under WW and SS regimes, respectively, and showed a normal frequency distribution. FFT in the F2:3 population ranged from 55.0 to 65.5 days and 56.0 to 67.0 days under two water regimes, respectively, and also showed a normal frequency distribution (Figure 1). Across two water regimes, there were positive correlations between MFT and FFT and between ASI and FFT, and the magnitude of the linear correlations decreased under SS (Table 2). The linear correlations between ASI and MFT were very low, almost zero under SS regime.

Table 1 Mean and range of flowering time for X178 (P1), B73 (P2) and the F2:3 progenies of maize

Parameters

MFT

FFT

ASI

WW

SS

WW

SS

WW

SS

Mean (P1)

60.0

60.0

61.0

63.0

1.0

3.0

Mean (P2)

63.00.5

62.50.5

64.50.5

65.50.5

1.0

3.0

Mean (F2:3)

59.840.09

60.050.09

61.320.11

61.910.11

1.480.05

1.860.06

Range (F2:3)

54.0-64.5

54.0-65.0

55.0-65.5

56.0-67.0

-1.0-4.5

-1.0-5.0

Figure 1 Distribution of means of flowering time in F2:3 population under WW and SS regimes

Table 2 Correlation coefficients between FFT and MFT and ASI under WW and SS regimes

Item

WW regime

SS regime

 

MFT

FFT

ASI

MFT

FFT

ASI

MFT

1.00

0.88**

0.18**

1.00

0.86**

0.09

FFT

 

1.00

0.62**

 

1.00

0.59**

ASI

   

1.00

   

1.00

** significant at P = 0.01

SSR marker linkage map

One hundred and thirty-seven SSR markers (36.9%) from total 371 markers were polymorphic between the two parental lines, and were further used to genotype the 234 F2 individuals. At 137 loci, 39 markers (28.5%) showed a distorted segregation from the expected ratio (1:2:1), and the parental genomes were 49.1% from X178 and 50.9% from B73. After running Mapmaker software at LOD 3.0, 121 SSR markers were assigned to 10 linkage groups, while 16 markers remained unlinked. The linkage map covered 1379.5 cM on total ten chromosomes of maize with an average interval of 11.4cM, and the marker order in the map was in agreement with their bins on the chromosomes (Maize DB, 2002).

QTL mapping

QTLs detected with an LOD threshold of 2.5 for three flowering traits were presented in Table 3. For MFT, 6 QTLs were identified on chromosomes 1, 3, 4, 8 and 9 under WW regime, which accounted for about 49% of total phenotypic variation. Under SS regime, 9 QTLs were detected, and 3 of them were also detected under WW regime. The qMFT6 on chromosome 9, adjacent to nc134, was consistently identified across two water regimes with the highest R2 explaining 22.4% and 26.9% of the phenotypic variation, respectively, and displaying additive gene effects.

Six QTLs for FFT were identified under WW and SS regimes, and contributed 48.1% and 57.3% of the total phenotypic variation, respectively. Four QTLs were commonly identified across two water regimes, and the qFFT6 on chromosome 9, adjacent to nc134, was found to be the major QTL, which was also identified in expression of MFT under two water regimes.

Four QTLs of ASI were identified on chromosomes 1 and 9 under WW regime, explaining 34.1% of phenotypic variation, while 6 QTLs were found under SS condition, explaining 50.9% of phenotypic variation. Four QTLs on chromosomes 1 and 3 were detected only under drought conditions, adjacent to bnlg176, phi265454, bnlg1144 and umc1320, respectively.

Some QTLs located in the same region of chromosomes were associated with different traits. The region close to nc134 on chromosome 9 consistently mapped QTLs for MFT, FFT and ASI under both water regimes with the allele from B73 contributing to an increase of the trait values. The region adjacent to phi053 on chromosome 3 mapped QTLs of both MFT and FFT with allele from X178 increasing the trait value. The region located in the interval phi328175-phi260485 on chromosome 7 mapped QTLs involved in drought tolerance for MFT and FFT with the allele from B73 increasing the trait value. The molecular markers linked to these consensus QTLs involved in drought responses could be very efficient in establishing a MAS approach for germplasm improvement for drought tolerance in maize.

Acknowledgement

The research was supported by International Joint Research Project (2003-Q03) and National High- technology Program (2001AA211111).

Table 3. QTLs involved in expression of flowering traits in maize under WW or SS regimes

Trait

Regime

Locus

Chr.

Marker

Position

LOD

Additive effect (a)

Dominant effect (d)

d/a

Gene action

R2 (%)

   

qMFT1

1

phi011

1.33

2.7

-0.43

0.10

0.22

PD

3.72

   

qMFT2

3

phi053

0.68

3.6

0.52

-0.36

0.69

PD

4.82

 

WW

qMFT3

3

bnlg1601

0.71

3.6

0.55

-0.34

0.63

PD

5.33

   

qMFT4

4

bnlg2291

0.94

4.2

-0.45

0.06

0.14

A

6.46

   

qMFT5

8

umc1933

1.30

2.5

-0.03

0.43

12.58

OD

3.24

MFT

 

qMFT6

9

nc134

0.74

13.7

-0.87

-0.13

0.15

A

22.45

   

qMFT7

1

umc1917

0.69

2.5

0.47

-0.65

1.37

OD

5.54

   

qMFT8

2

umc1516

0.90

4.1

-0.36

-0.17

0.47

PD

5.15

   

qMFT2

3

phi053

0.68

6.8

0.68

-0.21

0.31

PD

8.49

   

qMFT9

3

phi073

0.81

4.2

0.58

-0.14

0.24

PD

6.43

 

SS

qMFT4

4

bnlg2291

0.96

4.8

-0.50

0.15

0.29

PD

6.35

   

qMFT10

5

umc1647

0.64

2.6

0.51

-0.40

0.79

PD

3.33

   

qMFT11

6

bnlg1538

0.37

2.6

-0.33

-0.07

0.23

PD

2.99

   

qMFT12

7

phi328175

1.04

4.0

-0.65

0.22

0.34

PD

8.42

   

qMFT6

9

nc134

0.71

18.4

-0.95

-0.17

0.18

A

26.89

   

qFFT1

1

phi265454

1.91

2.5

0.53

-0.39

0.73

PD

3.40

   

qFFT2

3

phi053

0.68

3.1

0.61

-0.48

0.80

D

3.99

   

qFFT3

3

bnlg1601

0.73

3.0

0.64

-0.47

0.74

PD

4.46

 

WW

qFFT4

5

umc1647

0.66

3.8

0.70

-0.68

0.98

D

5.57

   

qFFT5

5

mmc0081

0.76

3.8

0.71

-0.59

0.84

D

5.77

FFT

 

qFFT6

9

nc134

0.71

16.5

-1.20

-0.12

0.10

A

25.92

   

qFFT1

1

phi265454

1.91

4.9

0.71

-0.22

0.30

PD

5.80

   

qFFT2

3

phi053

0.68

3.5

0.54

-0.07

0.13

A

4.04

 

SS

qFFT3

3

bnlg1601

0.73

3.1

0.53

-0.03

0.06

A

4.03

   

qFFT7

7

phi328175

0.96

4.8

-0.82

0.23

0.28

PD

8.85

   

qFFT6

9

nc134

0.69

22.1

-1.23

-0.44

0.36

PD

31.65

   

qFFT8

10

bnlg1360

0.61

2.5

0.51

-0.19

0.36

PD

2.88

   

qASI1

1

phi109275

0.47

3.4

-0.29

-0.02

0.05

A

5.59

 

WW

qASI2

1

umc1917

0.63

2.8

-0.32

-0.05

0.17

A

6.31

   

qASI3

9

umc1037

0.55

5.9

-0.32

-0.07

0.21

PD

11.07

ASI

 

qASI4

9

nc134

0.67

6.3

-0.33

-0.11

0.34

PD

11.16

   

qASI5

1

bnlg176

0.42

4.9

-0.45

0.13

0.29

PD

8.96

   

qASI2

1

umc1917

0.63

5.8

-0.56

0.20

0.36

PD

11.81

   

qASI6

1

phi265454

1.83

5.0

0.43

-0.08

0.18

A

9.67

 

SS

qASI7

3

bnlg1144

0.25

3.5

-0.38

0.20

0.53

PD

5.03

   

qASI8

3

umc1320

1.65

2.9

0.21

0.08

0.35

PD

4.82

   

qASI4

9

nc134

0.72

7.1

-0.30

-0.18

0.61

PD

10.63

References

CIMMYT (2001). Applied Molecular Genetics Laboratory, Laboratory protocols. CIMMYT, Mexico, D.F.

Hyne V and Kearsey MJ (1995). QTL analysis: Further uses of marker regression. Theor Appl Genet 91, 471-476.

Ribaut JM, Hoisington DA, Deutsch JA, Jiang C, Gpnzalez-de-Leon D (1996). Identification of quantitative trait loci under drought conditions in tropical maize, I. Flowering parameters and the anthesis-silking interval. Theor Appl Genet 92, 905-914.

Sari-Gorla M, Krajewski P, Fonzo ND, Villa M, Frova C (1999). Genetic analysis of drought tolerance in maize by molecular markers. I. Plant height and flowering .Theor Appl Genet 99, 289-295.

Stuber CW, Edwards MD, Wendel JF (1987). Molecular marker-facilitated investigation of quantitative trait loci in maize. Factors influencing yield and its component traits. Crop Sci 27, 639-648.

Veldboom LR and Lee M (1996). Genetic mapping of quantitative trait loci in maize in stress and nonstress environments: 1. Plant height and flowering. Crop Sci 36, 1320-1327

Wang SC, Basten CJ, Zeng ZB (2003). WinQtlCart V2.0, Program in Statistical Genetics, North Carolina state University, Raleigh, NC.

Previous PageTop Of PageNext Page