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Mapping QTL conferring resistance to iron deficiency chlorosis in mungbean [Vigna radiata (L.) Wilczek]
Field Crops Research 137 (2012) 230–236
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Mapping QTL conferring resistance to iron deficiency chlorosis in mungbean [Vigna radiata (L.) Wilczek] Prayoon Prathet a,b,1 , Prakit Somta b,1 , Peerasak Srinives b,∗ a b
Center of Advanced Studies for Agriculture and Food, KU Institute for Advanced Studies, Kasetsart University (CASAF, NRU-KU, Thailand), Bangkok 10900, Thailand Department of Agronomy, Faculty of Agriculture at Kamphaeng Saen, Kasetsart University, Kamphaeng Saen, Nakhon Pathom 73140, Thailand
a r t i c l e
i n f o
Article history: Received 15 June 2012 Received in revised form 25 July 2012 Accepted 1 August 2012 Keywords: Mungbean Calcareous soil Iron deficiency Leaf chlorosis SSR Quantitative trait loci (QTL)
a b s t r a c t Foliar chlorosis caused by iron deficiency of plants grown on calcareous soil results in substantial crop yield loss and is an important in crop production problem. The objective of this study was to identify the quantitative trait locus (QTL) controlling resistance to iron deficiency chlorosis (IDC) in mungbean. An RIL population of 122 F8 lines developed from the cross between a susceptible cultivar, “Kamphaeng Saen 2” and a resistant line, “NM10-12” was genetically analyzed with simple sequence repeat (SSR) and amplified fragment length polymorphism (AFLP) markers. The population was evaluated for IDC resistance in an iron deficient field by visually scoring and SPAD measurements in 2010 and 2011. Segregation of the visual scores and SPAD values of the RILs in both years suggested quantitative inheritance of the resistance to IDC. Visual score and SPAD value from each year and combined data were used for QTL analysis. Single marker analysis revealed that 12 DNA markers from 3 linkage groups (LG) associated with the resistance. Four SSR and two AFLP markers on LG 3 associated with the resistance in all cases. Composite interval mapping identified two QTLs, qIDC3.1 and qIDC2.1, controlling the resistance. qIDC3.1 on LG 3 was identified from visual scores and SPAD values to account for 12.12% and 41.67% of the total variation depending on traits measured and years. qIDC2.1 on LG 2 was detected only from visual score data in 2010 and explained 45.66% of the total variation. The qIDC3.1 was the same as qIR which was the major QTL previously reported for IDC in mungbean grown in hydroponic conditions. The SSR markers CEDG084 and CEDC031 flanked and closely linked to the qIDC are useful for marker-assisted selection for mungbean resistance to IDC. © 2012 Elsevier B.V. All rights reserved.
1. Introduction It is estimated that about 800 million ha of the World’s land is salt-affected and salt constitutes a major portion of the problem soils that affect agricultural production (FAO, 2005). Calcareous soil is characterized by its having a pH between 7.5 and 8.5, calcium carbonate concentration of 10–14 g kg−1 in the soil surface to a depth of 15 cm, and DTPA-Fe concentration between 10 and 20 mg/kg. In the calcareous soil, the availability of Fe3+ is decreased substantially as the results of precipitation of inorganic Fe-III. The soil causes iron deficiency chlorosis (IDC) where interveinal leaf tissue is yellowish or necrotic while the veins remain green, resulting in limited growth, development and production. Breeding for IDC resistance is an important objective in breeding program of several crops. Mungbean [Vigna radiata (L.) Wilczek] is a socio-economically important legume in South and Southeast Asia with the annual
∗ Corresponding author. Tel.: +66 34 281267; fax: +66 34 281267. E-mail address: [email protected] (P. Srinives). 1 These authors contributed equally to this research. 0378-4290/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.fcr.2012.08.002
planting area of about 6 million ha. It is mainly cultivated in China, Bangladesh, India, Myanmar, Pakistan, Sri Lanka, Thailand, the Philippines, and Viet Nam. In Thailand and the Philippines, planting area of mungbean is greater than any other legume crops. Seed of mungbean is an inexpensive source of dietary proteins and amino acids for common people and vegetarians in the region. Sprout produced from mungbean seed is popularly consumed in Eastern and Western cuisines as a vegetable for minerals and vitamins. Thailand is a major producer and exporter of mungbean seeds and products with the main production in the lower North and upper Central regions. In these regions high pH soil appears in patches across several hundred thousand hectares, yield losses due to IDC have been observed in most high yielding mungbean varieties (Nopparat et al., 1997). As a result, average yield of mungbean in Thailand is only about 750 kg/ha, although yield potential of the cultivars released in Thailand is between 1.8 and 2.5 ton/ha. Although foliar application of iron chelate on mungbean can alleviate IDC, it is not practical or economic for small-farm holders. There are only a few reports on genetic control of IDC in mungbean. Nopparat et al. (1997) reported that resistance to IDC is controlled by the inhibitory action of two genes, but a single
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dominant gene action is also possible. By using bulk segregant analysis technique in a recombinant inbred line population, Sommanus (2000) identified two amplified fragment length polymorphism (AFLP) makers, E-CAG/M-TAC and E-CGT/M-CTG, associated with the IDC resistance. Later, by studying in a hydroponic condition Srinives et al. (2010) reported that resistance to IDC is controlled by a single dominant gene, designated as IR, with modifying genes. The authors confirmed an association between the AFLP markers reported by Sommanus (2000) and the IR gene, and also identified two new AFLP markers, E-ACT/M-CTA and E-ACC/M-CTG, associated with the IR gene. The QTL controlling the resistance, designated as qIR, was located between the two markers and explained as high as 76% of the variation in IDC. However, these markers are not highly effective for marker-assisted selection (MAS) because they are relatively far from the qIR (3.1 and 10 cM, respectively) and are a dominant (Srinives et al., 2010). In legume crops, genetics of the resistance to IDC has been well studied in soybean (Glycine max (L.) Merr.) (Charlson et al., 2005; Cianzio and Fehr, 1980, 1982; Lin et al., 1997, 2000; O’Rourke et al., 2007, 2009; Wang et al., 2008). Cianzio and Fehr (1980) showed that resistance to IDC is controlled by a single major gene with modifiers. Later, Lin et al. (1997) associated located a major QTL on chromosome 3 of soybean for the IDC resistance. Although several candidate genes were found associated with IDC (Mamidi et al., 2012; O’Rourke et al., 2007, 2009), Peiffer et al. (2012) identified two genes, Glyma03g28610 and Glyma03g28630, with the positions coincide with the QTL region for IDC resistance on chromosome 3 identified by Lin et al. (1997), and found that Glyma03g28610 has a 12-bp deletion within a predicted dimerization domain. The authors hypothesized that the deletion may hinder the FIT/bHLH heterodimer which induce other iron acquisition genes. The objectives of this study were to locate the QTL(s) controlling resistance to IDC under field condition and to determine if results confirm the QTL identified earlier by Srinives et al. (2010). DNA markers developed from sequences within and/or nearby the bHLH gene from common bean [Phaseolus vulgaris (L.)] and soybean were also analyzed to test for their association with the IDC resistance in mungbean.
231
7.92, 2.1% organic matter, 17.83 mg/kg of available P, 97.01 mg/kg of exchangeable K, 15,883 mg/kg of exchangeable Ca, 499.63 mg/kg of exchangeable Mg, 0.99 mg/kg of extractable Fe, 13.62 mg/kg of extractable Mn, 1.63 mg/kg of extractable Cu, and 0.47 mg/kg of extractable Zn. In the dry season (March) of 2010 and 2011, the 122 RILs and their parents were sown in a randomized complete block design (RCBD) with two and three replications, respectively. Dry season plantings helped avoid interference from rains that often causes reduction in soil pH and increasing iron availability during RIL evaluation. In each block, each entry was sown in a single row 2.5 m long with 12.5 cm intra-row spacing (ca. 20 plants/row) and 50 cm inter-row spacing. In both experiments, IDC was evaluated by two methods, viz., visual scoring and soil-plant analysis development (SPAD) measurement at 3 weeks after planting. For visual score, plants were evaluated in rows based on leaf chlorosis symptoms. Scoring system was the same as reported by Srinives et al. (2010), viz., 1 (no yellowing), 2 (slight yellowing), 3 (moderate yellowing), 4 (intense yellowing coverage), and 5 (severe yellowing with some necrosis). Scoring was conducted by a panel of two trained staff. For SPAD measurement, 5 plants from each RIL were determined using a MINOLTA SPAD-502 meter (MINOLTA, Tokyo). Each plant was measured on 4 spots (2 each on the left and right of the midrib) on the terminal leaflet of the youngest fully expanded trifoliate leaf of the plant. The measurement was done immediately after visual scoring. The average SPAD reading from 5 plants was used to characterize IDC symptom of a RIL. 2.3. Estimation of heritability of IDC Narrow-sense heritability (h2 ) was estimated based on the property that RILs are theoretically a population of pure lines. Thus only additive genetic variation (a2 ) and interaction between the additive genes contribute to total genetic variation (g2 ), while dominant genetic variation (d2 ) can be negligible. Analysis of variance for SPAD value and visual score were performed on the RIL data using R-program version 2.10.0 (R Development Core Team, 2008). The heritability for both traits were estimated from the formula h2 = g2 /[g2 + (e2 /r)]; where e2 is the experimental error variance and r is the number of replications in each season.
2. Materials and methods 2.1. Plant materials A recombinant inbred line (RIL) population was used in this study. The population was developed from a cross between resistant line “NM10-12-1” and susceptible cultivar “Kamphaeng Saen 2” (KPS2), using KPS2 as the female parent. The parental mungbeans used in this study are the same as those used by Nopparat et al. (1997), Sommanus (2000) and Srinives et al. (2010), although the population or generation used is different. An F1 seed from the cross was grown, self-fertilized and generations advanced as F2 derived lines by single seed descent method. Finally, a population of 122 F8 RILs was obtained. Genomic DNA of the parents and RILs were extracted from young leaves following the method described by Lodhi et al. (1994). DNA was quantified against lambda DNA on 1.5% agarose gel stained with ethidium bromide. 2.2. Evaluation for resistance to iron deficiency chlorosis Field evaluation for resistance to IDC was carried out in an experimental field of Nakhon Sawan Field Crops Research Center, Nakhon Sawan province, Thailand where alkaline soil is uniformly prevailing (Srinives et al., 2010). The soil in this field had pH of
2.4. SSR marker analysis A total of 1191 SSR primer pairs from various legume crops were screened for polymorphism between the parents. Among them, 530 were from mungbean (Seehalak et al., 2009; Somta et al., 2008, 2009; Tangphatsornruang et al., 2009), 332 from azuki bean [Vigna angularis (Ohwi) Ohwi & Ohashi] (Wang et al., 2004), 152 from common bean (Phaseolus vulgaris L.) (Blair et al., 2003; Buso et al., 2006; Gaitán-Solís et al., 2002; Guerra-Sanz, 2004), and 177 from cowpea [Vigna unguiculata (L.) Walp.] (Kongjaimun et al., 2012; Li et al., 2001; Xu et al., 2010). Polymerase chain reaction (PCR) amplification was performed in a 10 l reaction volumes containing 2 ng genomic DNA, 1× Taq buffer with (NH4 )2 SO4 , 1.5 mM MgCl2 , 2 mM dNTPs, 5 pmol of each forward and reverse primers and 1 U Taq DNA polymerase (Fermentas). The DNA was amplified in a GeneAmp® PCR System 9700 thermocycler (Applied Biosystems). Thermal cycling was programmed as follow: 94 ◦ C for 2 min followed by 35 cycles of 94 ◦ C for 30 s, 47–60 ◦ C (depending on primers) for 30 s, 72 ◦ C for 1 min, and 72 ◦ C for 10 min. The PCR products were mixed with 10 l of formamide containing 10 mM EDTA, 0.02% bromophenol blue and xylene-cyanol, denatured at 94 ◦ C for 2 min. Then 1.5–2 l of the final product was loaded onto 5% polyacrylamide gel and visualized by silver staining.
P. Prathet et al. / Field Crops Research 137 (2012) 230–236
To confirm the AFLP markers associated with the resistance reported earlier by Sommanus (2000) and Srinives et al. (2010), four AFLP primer combinations reported by them were screened for polymorphism between the parents, and then analyzed in the RIL population using the same procedure. 2.6. Marker development from soybean and common bean bHLH gene Apart from the DNA markers mentioned above, more markers were developed and used for DNA analysis. Since it has been shown in soybean that the null function of the Glyma03g28610 (a basic helix–loop–helix (bHLH) gene) is responsible for susceptibility to iron deficiency (Peiffer et al., 2012), we hypothesized that bHLH might also be involved in iron deficiency resistance in mungbean. Due to unavailability of mungbean genome sequence, we used a comparative mapping approach to test this hypothesis. Glyma03g28610 was searched for SSRs, and primer pairs were designed to detect them. Glyma03g28610 was also compared to common bean genome sequence assembly (Phaseolus vulgaris v0.9; http://www.phytozome.net) to identify bHLH using BLAST. Once identified, a primer pair was designed targeting to an intron in the bHLH gene. SSRs were also searched from the bHLH gene and the DNA sequences surrounding the gene using the SSRIT program (http://www.gramene.org/microsat/ssr.html). All the SSRs were identified by SSRIT, while all primers were designed by Primer3 (http://www.frodo.wi.mit.edu). Marker analysis was performed as described in the SSR analysis. 2.7. Linkage map and QTL analyses A genetic linkage map was constructed using JoinMap version 3.0 software. A minimum LOD threshold of 3.0 and maximum recombination frequency of 0.50 were applied for grouping the markers into a linkage group. Map distance in centimorgan (cM) was calculated using Kosambi mapping function (Kosambi, 1944). Linkage groups were named following Chankaew et al. (2011) based on common markers. For QTL analysis, single regression analysis was performed to determine significant association between a DNA marker and visual score or SPAD value at P = 0.01 using R-program 10.2.0 (R Development Core Team, 2008). Software WinQTL Cartographer version 2.5 (Wang et al., 2010) was used to locate QTLs associated with the resistance by composite interval mapping (CIM). Walking speed was set at 1 cM. Significant threshold for the QTL was computed by 3000 run of a permutation test at P = 0.001. 3. Results 3.1. IDC response in RILs In the dry season of 2010, KPS2 showed high susceptibility to iron deficiency with the visual score of 5.0 and SPAD value of 4.10, while NM10-12 showed resistance to iron deficiency with the visual score of 2.20 and SPAD value of 38.50. The RILs showed different responses with the visual scores ranged from 1 to 5 and the average of 3.53, while the SPAD values varied from 1.49 to 41.66 with the average of 18.86. In the 2011 season, the results from the parents and RIL were similar to those of the 2010 season. KPS2 had the visual score of 4.80 and SPAD value of 13.8, while NM10-12 had the visual score of 1.30 and SPAD value of 35.70. The visual scores in the RIL population ranged from 1 to 5 with the average of 2.29, while the SPAD values varied from 11.39 to 42.82 with the average of 29.59 (Fig. 1). When the data from 2 years were combined, KPS2
(a)
NM10-12
50
2010
45
2011
KPS2
Combined
40
Number of lines
2.5. AFLP marker analysis
35 30 25
KPS2
NM10-12
20
NM10-12
KPS2
15 10 5 0 1.0-1.5 1.6-2.0 2.1-2.5 2.6-3.0 3.1-3.5 3.6-4.0 4.1-4.5 4.6-5.0
Visual score
(b) 50 Number of lines
232
2010
45
2011
40
Combined
35
NM10-12
KPS2
30 25
NM10-12
KPS2 KPS2
20
NM10-12
15 10 5 0 0-5.0
5.1-10 10.1-15 15.1-20 20.1-25 25.1-30 30.1-35 35.1-40 40.1-45
SPAD value
Fig. 1. Frequency distribution of visual score and SPAD value for response to iron deficiency in RIL population of the mungbean cross between KPS2 and NM1012, evaluated in a calcareous field at Nakhon Sawan Field Crops Research Center, Thailand in 2010 (a) and 2011 (b).
showed a visual score of 4.90 and SPAD value of 8.95, while NM1012 had a visual score of 1.75 and SPAD value of 37.10. In the RILs, a visual score varied between 1.0 and 5.0 with an average of 2.99 and SPAD value ranged from 7.0 to 39.45 with an average of 23.48. There was a high negative correlation between visual score and SPAD value for IDC in 2010 (r = −0.91, P < 0.0001), 2011 (r = −0.83, P < 0.0001) and combined data (r = −0.95, P < 0.0001). Frequency distribution of visual score and SPAD value in each year and combined data showed continuous distribution, suggesting that resistance to IDC in NM10-12 is quantitatively inherited. However, in 2010 visual score of the population skewed toward KPS2, while in 2011 visual score and SPAD value skewed toward NM10-12. 3.2. Heritability of resistance to IDC Analysis of variance (ANOVA) was performed on for visual score and SPAD value in the RIL population to estimate narrow-sense heritability. Results of the ANOVA are shown (Table 1). The h2 estimated for visual score and SPAD value in the 2010 season were 86.04% and 91.96%, respectively, while those in the 2011 season were 54.44% and 88.04%, respectively. The results indicated the importance of genetic factor(s) controlling resistance to IDC in mungbean. 3.3. Marker development and linkage map construction We have developed an SSR marker from the soybean sequence of Glyma03g28610. In silico search using Glyma03g28610 identified Phvulv091030676m.g (scaffold00144: 118332–120552) as a bHLH
P. Prathet et al. / Field Crops Research 137 (2012) 230–236
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Table 1 Analysis of variance of visual score and SPAD value in RIL population of the mungbean cross KPS2 × NM10-12 evaluated for iron deficiency chlorosis at Nakhon Sawan Field Crops Research Center, Thailand in 2010 and 2011. Year 2010
Year 2011
df
Visual score MS
SOV Rep Line Error Total
2.67*** 3.66*** 0.27
1 121 121 243
CV (%) ***
14.82
SPAD value MS
df
981.61*** 308.29*** 12.92
2 121 242 365
Visual score MS
SPAD value MS
9.78*** 3.53*** 1.04
19.05
838.10*** 150.60*** 17.00
41.95
14.67
Significant at the 0.001 probability level.
Table 2 SSR markers associated with resistance to iron deficiency chlorosis based on the data from RIL population of the mungbean cross KPS2 × NM10-12 as detected by single regression analysis at P < 0.01. Marker (LG)
cp03715 (2) CEDG100 (2) cp02662 (2) VR169 (3) E-ACT/M-CTA175 (3) CEDG159 (3) CEDC031(3) CEDG084 (3) E-CAG/M-TAC100 (3) VR-SSR011 (11) CEDG044 (11) VR303 (11) CEDG013 (11) a b c
Year 2010
Year 2011
Combined data
Visual score
SPAD value
Visual score
SPAD value
Visual score
SPAD value
R2 (%)a
Pb
R2 (%)
P
R2 (%)
P
R2 (%)
R2 (%)
P
R2 (%)
7.31 6.58 5.64 9.29 39.58 31.04 59.59 55.30 25.59 Ns Ns Ns Ns
0.0063 0.0043 0.0023 0.0006 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
Nsc Ns Ns <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
Ns Ns Ns 11.35 39.55 37.77 61.60 58.62 28.78 7.05 7.39 8.83 9.16
0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0023 0.0008 0.0009 0.0006
Ns Ns 5.43 9.98 31.57 36.68 51.79 50.65 35.17 Ns Ns Ns 5.91
7.16 5.94 3.90 12.45 40.63 38.42 66.17 62.57 33.93 Ns 4.54 Ns 6.35
0.0082 0.0068 0.0054 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
6.94 Ns 3.44 11.75 41.94 42.88 69.09 66.51 35.61 Ns Ns Ns 5.47
13.41 31.91 37.08 54.05 50.55 35.00 Ns Ns Ns Ns
P
0.0098 0.0003 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
0.0060
0.0079 0.0041
P 0.0094 0.0089 0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
0.0082
Coefficient of the determination. Probability. Non-significant difference.
gene for common bean. Phvulv091030676m.g has a full genomic sequence length of 2221 bp and contains two introns. One intron length polymorphism (ILP) primer pair was designed to target the intron of Phvulv091030676m.g, and 12 pairs were designed to amplify SSRs in and around this gene (Suppl. Table S1). Of the 1203 SSR markers screened for polymorphism between KPS2 and NM10-12-1, 860 (71.49%) were able to amplify the parents and only 62 (7.21%) of these showed polymorphism. In the case of AFLP markers, 4 primer combinations produced 8 polymorphic loci. Linkage map analysis assigned 54 polymorphic markers into 12 linkage groups (LG) with a total genetic distance of 991.98 cM (Suppl. Fig. S1), while 16 markers were unlinked. The shortest linkage group was 23.66 cM, the longest linkage group was 139.45 cM, and the average total distance per linkage was 82.66 cM. Number of markers per LG was between 2 and 8 (LG 3) with an average of 4.5. 3.4. QTL controlling IDC resistance Single marker analysis in the RIL population using both visual score and SPAD value data from each year, and combined data showed that 12 markers from LGs 2, 3 and 11 associated with IDC resistance (P < 0.001) (Table 2). All the significant markers on LG3 were associated with both visual score and SPAD value, while all except one of the markers on LG3 were associated with visual score only. In the 2010 evaluation, the coefficient of determination (R2 ) of these markers for visual score data ranged from 5.64% (cp02662) to 58.89% (CEDC031), while for the SPAD value data varied between 13.41% (VR116) and 62.67% (CEDC031). In 2011 evaluation, R2 of these markers for visual score data ranged from 7.05% (VR-SSR011) to 61.60% (CEDC031), while for the SPAD value data varied from
5.43% (cp02662) to 51.79% (CEDC031). When combined data were used, R2 of these markers for visual score were between 3.90% (cp02662) and 66.17% (CEDC031), while for the SPAD value were 3.44% (cp02662) to 69.09% (CEDC031). Six markers on LG 3, namely VR169, E-ACT/M-CTA175, CEDG159, CEDC031, CEDG084, and ECAG/M-TAC100 showed highly significant association with visual score and SPAD value data, in all cases. Markers CEDC031 and VR169 showed highest and lowest R2 , respectively (Table 2). Composite interval mapping was conducted in the RIL population to locate QTLs for IDC onto the linkage map. For the visual score, permutation tests (3000 runs at P = 0.001) for the data in 2010 and 2011 of the RIL population revealed that LOD score thresholds for the QTL were 5.3 and 6.9, respectively. In both years, CIM identified one major QTL for the visual score locating at 126.9 cM on LG3 between markers CEDC031 and CEDG084 (Table 3; Fig. 2). The QTL was designated as qIDC-SCORE3.1. The qIDC-SCORE3.1 explained 41.467% and 36.72% of the visual score variation in the 2010 and 2011, respectively. Additive effects of the qIDC-SCORE3.1 were 1.25 and 0.98, respectively. However, in 2010, CIM detected another QTL, qIDC-SCORE2.1, locating at 35.7 cM on LG2 between markers CEDG100 and cp02662. The QTL accounted for 45.66% of the total score variation, and had additive effects of 0.45 (Table 3). In case of SPAD value, a 3000-run permutation test at P = 0.001 for the year 2010 and 2011 data gave LOD score thresholds for QTL of 9.6 and 4.7 in that order. CIM consistently identified a major QTL, designated as qIDC-SPAD3.1, for both SPAD data sets (Table 3; Fig. 2). qIDC-SPAD3.1 was located on LG3 between markers CEDC031 and CEDG084 at 126.9 and 127.9 cM using the 2010 and 2011 data in that order. The qIDC-SPAD explained 35.56 and 13.31% of the variation in SPAD values 2010 and 2011, respectively. Additive effects of the qIDC-SPAD were −10.13 and −5.45, respectively.
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Table 3 Quantitative trait loci conditioning resistance to iron deficiency based on the data from RIL population of the mungbean cross KPS2 × NM10-12 as detected by composite interval mapping. Trait
Year
QTL name
LGa
Marker interval
Positionb
LOD score
PVEc (%)
Visual score
2010 2011 Combined
qIDC-SCORE2.1 qIDC-SCORE3.1 qIDC-SCORE3.1 qIDC-SCORE3.1
2 3 3 3
CEDG100–cp02662 CEDC031–CEDG084 CEDC031–CEDG084 CEDC031–CEDG084
35.7 126.9 126.9 126.9
8.41 18.0 32.5 44.3
45.66 41.67 36.72 23.14
0.45 1.25 0.98 1.04
2010 2011 Combined
qIDC-SPAD3.1 qIDC-SPAD3.1 qIDC-SPAD3.1
3 3 3
CEDC031–CEDG084 CEDC031–CEDG084 CEDC031–CEDG084
126.9 127.9 126.9
34.8 29.9 46.9
35.56 13.31 12.14
−10.13 −5.45 −7.93
SPAD value
a b c
Additive effect
Linkage group. Position on the linkage group (centimorgan; cM). Percentage of phenotypic variance explained by the QTL.
(a)
Visual score 2010
Visual score 2011
Combined visual score
SPAD value 2010
SPAD value 2011
Combined SPAD value
48 44 40
LOD score
36 32 28 24 20 16 12 8 4
cM
Visual score 2010
Visual score 2011
Combined visual score
SPAD value 2010
SPAD value 2011
Combined SPAD value
139.5 E-CAG/M-TAC100
10
CEDG184 126.0 CEDC031
(b)
CEDG159 112.0
Linkage group 3
E-ACT/M-CTA175 98.0
84.0
70.0
56.0
42.0
VR169
28.0
cp00361
14.0
0
0
LOD score
8
6
4
2
cM 75.8 CEDG244
60.0 CEDG225
66.0 CEDG108
54.0
48.0
42.0 cp02662
36.0
30.0 CEDG100
cp03715 24.0
18.0
12.0
BM220
6.0
0
0
Linkage group 2 Fig. 2. Position of the QTL controlling iron deficiency resistance and LOD score plotted for composite interval mapping (CIM) on linkage groups 3 (a) and 2 (b) in the RIL population of the cross between KPS2 and NM10-12 as evaluated by visual score and SPAD measurement. The lines parallel to the linkage maps represent LOD threshold.
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Combined data from 2 years were also used for locating the QTL. LOD score threshold determined by permutation test for combined visual score and combined SPAD value were 7.68 and 5.87 in that order. In both traits, CIM detected a single QTL at 126.9 cM on LG3 (Table 3; Fig. 2). qIDC-SCORE3.1 accounted for 23.14% of the total trait variation, while qIDC-SPAD3.1 explained 12.14% of the total trait variation. These QTLs had additive effects of 1.04 and −7.93 in that order. Since the qIDC-SCORE3.1 and qIDC-SPAD3.1 were identified using data from different years, they are very likely the same QTL. We named this QTL as qIDC3.1, and named qIDC-SCORE2.1 as qIDC2.1. 4. Discussion Iron deficiency chlorosis is a world-wide problem in crop production. Plant breeders have long been interested in improving cultivars with resistance to IDC. In Thailand, popular high-yielding mungbean cultivars such as Kamphaeng Saen 1 and KPS2 are susceptible to IDC. Mutation breeding of KPS2 using gamma ray resulted in a high-yielding and IDC resistance cultivar Chai Nat 72 (Anonymous, 2001). Breeding progress to improve resistance to IDC in these varieties by backcrossing or other methods is limited by difficulty in IDC evaluation, although several resistance sources are available and the genetics of the resistance is simple (Srinives et al., 2010). In this study, although QTL mapping reveals QTLs qIDC2.1 and qIDC3.1 controlling the IDC resistance, only qIDC3.1 was consistently detected and confirmed as the major QTL for IDC. qIDC3.1 was found in the dry season in both years with similar or same location and effect. Thus this QTL is robust and considered as the major QTL for IDC resistance in mungbean. qIDC2.1 appears to be a modifier for IDC resistance, and is sensitive to the environment. Although it was found only visual score in 2010, the LOD peak of this QTL almost reached the threshold in 2011 (Table 3; Fig. 2b). Similarly, LOD peaks of this genomic region detected using SPAD values from 2010 and combined data were not far from the threshold (Fig. 2b). The low penetrance or expressivity of this QTL may in part accounts for the low heritability (54.44%) of visual score in 2011. Nonetheless, it is worth noting that results from single marker analysis suggested the presence of other minor QTL(s) for visual score and SPAD value on LG11 in year 2010 (Table 2). These results are in agreement with the report of Srinives et al. (2010) that IDC resistance in mungbean NM10-12 is controlled by a single gene or one major QTL with modifiers. Similarly, it is also reported in soybean that a single gene or single major QTL with modifiers confer resistance to IDC (Cianzio and Fehr, 1980; Lin et al., 1997). In addition, two AFLP markers flanking to QTL for IDC resistance in mungbean under hydroponic condition reported by Srinives et al. (2010) also flank to the QTL found in the present study. This indicates that those QTLs are the same and the mechanisms of the resistance to IDC under hydroponic and field conditions are common. In soybean, a major QTL identified for resistance to IDC under field condition (Lin et al., 1997) is the same QTL as for the resistance under hydroponic condition (Peiffer et al., 2012). Although the heritability of SPAD values in both 2010 and 2011 were as high as 86.04% and 91.96%, respectively, the percentage of variance explained by the QTLs for this trait was lower than 40%. This indicated that additional QTL(s) conditioning IDC in mungbean, if any exists, were undetectable in the present study. It is mainly due to low saturation of the markers and genome coverage resulting from low polymorphism between the parents used. It is worth noting that the linkage map constructed in this study lacks LG7 and LG8 (Suppl. Fig. S1). Low polymorphism in both cultivated × cultivated and cultivated × wild mapping populations of mungbean has been reported (Chankaew et al., 2011; Sompong et al., 2012).
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In contrast to the grass family (Poaceae or Gramineae) which uses “strategy II”, all other plants use “strategy I” to cope with iron-deficiency soil to reduce and acquire Fe2+ (Marschner et al., 1986) for which they acidify the surrounding soil to promote solubilizing unavailable ferric iron by pumping protons into the plasma membrane using an H+ -ATPase. A ferric-chelate reductase (FRO2) reduces chelated Fe3+ into available Fe2+ which is then transported into roots by an iron-regulated transporter (IRT1) (Walker and Connolly, 2008). Gene expression studies of response to iron deficiency in Arabidopsis (Arabidopsis thaliana) revealed that when iron concentration is low in cell an unknown factor triggers the response which activates three transcription factors; Fe-deficiency-induced transcription factor (FIT), basic helix–loop–helix 038 (bHLH038) and bHLH039 (Bauer et al., 2007; Lingam et al., 2011; Wang et al., 2007). Results reported by Yuan et al. (2008) suggest that under the iron deficiency conditions FIT regulates the expression of FRO2 and IRT1 by binding to bHLH. Through fine mapping using nearisogenic lines and gene expression analysis in soybean, Peiffer et al. (2012) identified Glyma03g28610 coding for bHLH as the candidate gene controlling IDC resistance. The authors demonstrated that resistance varieties possess functional bHLH encoded by the Glyma03g28610, while susceptible varieties have defective bHLH encoded by the same locus containing a 12-bp deletion. Since the inheritance of IDC resistance in soybean and mungbean are similar, it is possible that a gene coding bHLH is also responsible for IDC resistance in mungbean. High genome conservation among soybean, mungbean and common bean has been demonstrated (Choi et al., 2004). We tested whether the gene coding for bHLH also controls IDC in mungbean using comparative gene mapping. A genic SSR from Glyma03g28610 failed to amplify DNA of the mungbean parents. Bioinformatics analysis identified Phvulv091030676m.g as the gene for bHLH in common bean. Twelve SSR and one ILP markers in and/or around Phvulv091030676m.g were developed and screened for polymorphism in the parents, but all of them failed to amplify and the ILP showed monomorphism. However, involvement of the gene for bHLH in the IDC resistance in mungbean still cannot be ruled out. It is worth investigating the association between sequence variation of bHLH encoded gene and IDC in the resistance and susceptible mungbeans when the whole genome sequence of mungbean becomes available. This can aid identification of the causal mutation leading to IDC susceptibility in mungbean, and hence enable the functional marker(s) to be developed for marker-assisted selection. Initially, SSR markers CEDC031 and CEDG084 which are closely linked to the resistance gene may be used for MAS of the IDC resistance mungbean. 5. Conclusion This study identified and confirmed QTL for iron deficiency chlorosis in mungbean grown in the calcareous soil using genetic linkage map of RIL population derived from a cross between “Kamphaengsaen 2” and “NM10-12”. A major QTL with similar or same location was identified across 2 years in both visual score and soil-plant analysis development measured for iron deficiency chlorosis, supporting previous findings that iron deficiency chlorosis in mungbean is controlled by a single gene and modifier(s). The QTL identified in this study is the same locus identified for iron deficiency chlorosis in mungbean grown under hydroponic condition. Thus the mechanism of the resistance in the field and hydroponic conditions are the same. Acknowledgements This research was supported by Thailand’s National Science and Technology Development Agency (NSTDA). A part of this research was also funded by Center of Advanced Studies for Agriculture and
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Food, Institute for Advanced Studies, Kasetsart University under the National Research University Program of Office of the Higher Education Commission, Ministry of Education, Thailand. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.fcr.2012.08.002. References Anonymous, 2001. Crop cultivars of Thailand Department of Agriculture. Department of Agriculture, Ministry of Agriculture and Cooperatives, Thailand (in Thai). Bauer, P., Ling, H.Q., Guerinot, M.L., 2007. FIT, the FER-like iron deficiency induced transcription factor in Arabidopsis. Plant Physiol. Biochem. 45, 260–261. Blair, M.W., Pedraza, F., Buendia, H.F., Gaitán-Solís, E., Beebe, S.E., Gepts, P., Thome, J., 2003. Development of a genome-wide anchored microsatellite map of common bean (Phaseolus vulgaris L.). Theor. Appl. Genet. 107, 1362–1374. Buso, G.S.C., Amaral, Z.P.S., Brondani, R.P.V., Ferreira, M.E., 2006. Microsatellite markers for the common bean Phaseolus vulgaris. Mol. Ecol. Notes 6, 252–254. Chankaew, S., Somta, P., Sorajjapinun, W., Srinives, P., 2011. Quantitative trait loci mapping of Cercospora leaf spot resistance in mungbean, Vigna radiata (L.) Wilczek. Mol. Breed. 28, 255–264. Charlson, D.V., Bailey, T.B., Cianzio, S.R., Shoemaker, R.C., 2005. Molecular marker Satt481 is associated with iron-deficiency chlorosis resistance in a soybean breeding population. Crop Sci. 1, 2394–2399. Choi, H.K., Mun, J.H., Kim, D.J., Zhu, H., Baek, J.M., Mudge, J., Roe, B., Ellis, N., Doyle, J., Kiss, G.B., Young, N.D., Cook, D.R., 2004. Estimating genome conservation between crop and model legume species. Proc. Natl. Acad. Sci. U.S.A. 101, 15289–15294. Cianzio, S.R., Fehr, W.R., 1980. Genetic control of iron deficiency chlorosis in soybeans. Iowa State J. Res. 54, 367–375. Cianzio, S.R., Fehr, W.R., 1982. Variation in the inheritance of resistance to iron deficiency chlorosis in soybeans. Crop Sci. 22, 433–434. FAO, 2005. Global Network on Integrated Soil Management for Sustainable Use of Salt-Affected Soils. FAO and Plant Nutrition Management Service, Rome, Italy. Gaitán-Solís, E., Duque, M.C., Edwards, K.J., Thome, J., 2002. Microsatellite repeats in common bean (Phaseolus vulgaris): isolation, characterization, and cross-species amplification in Phaseolus ssp. Crop Sci. 42, 2128–2136. Guerra-Sanz, J.M., 2004. New SSR markers of Phaseolus vulgaris from sequence databases. Plant Breed. 123, 87–89. Kongjaimun, A., Kaga, A., Tomooka, N., Somta, P., Shimizu, T., Shu, Y., Isemura, T., Vaughan, D.A., Srinives, P., 2012. An SSR-based linkage map of yardlong bean (Vigna unguiculata (L.) Walp. subsp. unguiculata Sesquipedalis Group) and QTL analysis of pod length. Genome 55, 81–92. Kosambi, D.D., 1944. The estimation of map distances from recombination values. Ann. Eugen. 12, 172–175. Li, C.D., Fatokun, C.A., Ubi, B., Singh, B.B., Scoles, G.J., 2001. Determining genetic similarities and relationships among cowpea breeding lines and cultivars by microsatellite markers. Crop Sci. 41, 189–197. Lin, S., Cianzio, S., Shoemaker, R., 1997. Mapping genetics loci for iron deficiency chlorosis in soybean. Mol. Breed. 3, 219–229. Lin, S., Cianzio, S., Shoemaker, R., 2000. Molecular characterization of iron deficiency chlorosis in soybean. J. Plant Nutr. 23, 1929–1939. Lingam, S., Mohrbacher, J., Brumbarova, T., Potuschak, T., Fink-Straube, C., Blondet, E., Genschik, P., Bauer, P., 2011. Interaction between the bHLH transcription factor FIT and ETHYLENE INSENSITIVE3/ETHYLENE INSENSITIVE3-LIKE1 reveals molecular linkage between the regulation of iron acquisition and ethylene signaling in Arabidopsis. Plant Cell 23, 1815–1829. Lodhi, M.A., Ye, G.N., Weeden, N.F., Reisch, B.I., 1994. A simple and efficient method for DNA extraction from grapevine cultivars and Vitis species. Plant Mol. Biol. Rep. 12, 6–13.
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Field Crops Research journal homepage: www.elsevier.com/locate/fcr
Mapping QTL conferring resistance to iron deficiency chlorosis in mungbean [Vigna radiata (L.) Wilczek] Prayoon Prathet a,b,1 , Prakit Somta b,1 , Peerasak Srinives b,∗ a b
Center of Advanced Studies for Agriculture and Food, KU Institute for Advanced Studies, Kasetsart University (CASAF, NRU-KU, Thailand), Bangkok 10900, Thailand Department of Agronomy, Faculty of Agriculture at Kamphaeng Saen, Kasetsart University, Kamphaeng Saen, Nakhon Pathom 73140, Thailand
a r t i c l e
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Article history: Received 15 June 2012 Received in revised form 25 July 2012 Accepted 1 August 2012 Keywords: Mungbean Calcareous soil Iron deficiency Leaf chlorosis SSR Quantitative trait loci (QTL)
a b s t r a c t Foliar chlorosis caused by iron deficiency of plants grown on calcareous soil results in substantial crop yield loss and is an important in crop production problem. The objective of this study was to identify the quantitative trait locus (QTL) controlling resistance to iron deficiency chlorosis (IDC) in mungbean. An RIL population of 122 F8 lines developed from the cross between a susceptible cultivar, “Kamphaeng Saen 2” and a resistant line, “NM10-12” was genetically analyzed with simple sequence repeat (SSR) and amplified fragment length polymorphism (AFLP) markers. The population was evaluated for IDC resistance in an iron deficient field by visually scoring and SPAD measurements in 2010 and 2011. Segregation of the visual scores and SPAD values of the RILs in both years suggested quantitative inheritance of the resistance to IDC. Visual score and SPAD value from each year and combined data were used for QTL analysis. Single marker analysis revealed that 12 DNA markers from 3 linkage groups (LG) associated with the resistance. Four SSR and two AFLP markers on LG 3 associated with the resistance in all cases. Composite interval mapping identified two QTLs, qIDC3.1 and qIDC2.1, controlling the resistance. qIDC3.1 on LG 3 was identified from visual scores and SPAD values to account for 12.12% and 41.67% of the total variation depending on traits measured and years. qIDC2.1 on LG 2 was detected only from visual score data in 2010 and explained 45.66% of the total variation. The qIDC3.1 was the same as qIR which was the major QTL previously reported for IDC in mungbean grown in hydroponic conditions. The SSR markers CEDG084 and CEDC031 flanked and closely linked to the qIDC are useful for marker-assisted selection for mungbean resistance to IDC. © 2012 Elsevier B.V. All rights reserved.
1. Introduction It is estimated that about 800 million ha of the World’s land is salt-affected and salt constitutes a major portion of the problem soils that affect agricultural production (FAO, 2005). Calcareous soil is characterized by its having a pH between 7.5 and 8.5, calcium carbonate concentration of 10–14 g kg−1 in the soil surface to a depth of 15 cm, and DTPA-Fe concentration between 10 and 20 mg/kg. In the calcareous soil, the availability of Fe3+ is decreased substantially as the results of precipitation of inorganic Fe-III. The soil causes iron deficiency chlorosis (IDC) where interveinal leaf tissue is yellowish or necrotic while the veins remain green, resulting in limited growth, development and production. Breeding for IDC resistance is an important objective in breeding program of several crops. Mungbean [Vigna radiata (L.) Wilczek] is a socio-economically important legume in South and Southeast Asia with the annual
∗ Corresponding author. Tel.: +66 34 281267; fax: +66 34 281267. E-mail address: [email protected] (P. Srinives). 1 These authors contributed equally to this research. 0378-4290/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.fcr.2012.08.002
planting area of about 6 million ha. It is mainly cultivated in China, Bangladesh, India, Myanmar, Pakistan, Sri Lanka, Thailand, the Philippines, and Viet Nam. In Thailand and the Philippines, planting area of mungbean is greater than any other legume crops. Seed of mungbean is an inexpensive source of dietary proteins and amino acids for common people and vegetarians in the region. Sprout produced from mungbean seed is popularly consumed in Eastern and Western cuisines as a vegetable for minerals and vitamins. Thailand is a major producer and exporter of mungbean seeds and products with the main production in the lower North and upper Central regions. In these regions high pH soil appears in patches across several hundred thousand hectares, yield losses due to IDC have been observed in most high yielding mungbean varieties (Nopparat et al., 1997). As a result, average yield of mungbean in Thailand is only about 750 kg/ha, although yield potential of the cultivars released in Thailand is between 1.8 and 2.5 ton/ha. Although foliar application of iron chelate on mungbean can alleviate IDC, it is not practical or economic for small-farm holders. There are only a few reports on genetic control of IDC in mungbean. Nopparat et al. (1997) reported that resistance to IDC is controlled by the inhibitory action of two genes, but a single
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dominant gene action is also possible. By using bulk segregant analysis technique in a recombinant inbred line population, Sommanus (2000) identified two amplified fragment length polymorphism (AFLP) makers, E-CAG/M-TAC and E-CGT/M-CTG, associated with the IDC resistance. Later, by studying in a hydroponic condition Srinives et al. (2010) reported that resistance to IDC is controlled by a single dominant gene, designated as IR, with modifying genes. The authors confirmed an association between the AFLP markers reported by Sommanus (2000) and the IR gene, and also identified two new AFLP markers, E-ACT/M-CTA and E-ACC/M-CTG, associated with the IR gene. The QTL controlling the resistance, designated as qIR, was located between the two markers and explained as high as 76% of the variation in IDC. However, these markers are not highly effective for marker-assisted selection (MAS) because they are relatively far from the qIR (3.1 and 10 cM, respectively) and are a dominant (Srinives et al., 2010). In legume crops, genetics of the resistance to IDC has been well studied in soybean (Glycine max (L.) Merr.) (Charlson et al., 2005; Cianzio and Fehr, 1980, 1982; Lin et al., 1997, 2000; O’Rourke et al., 2007, 2009; Wang et al., 2008). Cianzio and Fehr (1980) showed that resistance to IDC is controlled by a single major gene with modifiers. Later, Lin et al. (1997) associated located a major QTL on chromosome 3 of soybean for the IDC resistance. Although several candidate genes were found associated with IDC (Mamidi et al., 2012; O’Rourke et al., 2007, 2009), Peiffer et al. (2012) identified two genes, Glyma03g28610 and Glyma03g28630, with the positions coincide with the QTL region for IDC resistance on chromosome 3 identified by Lin et al. (1997), and found that Glyma03g28610 has a 12-bp deletion within a predicted dimerization domain. The authors hypothesized that the deletion may hinder the FIT/bHLH heterodimer which induce other iron acquisition genes. The objectives of this study were to locate the QTL(s) controlling resistance to IDC under field condition and to determine if results confirm the QTL identified earlier by Srinives et al. (2010). DNA markers developed from sequences within and/or nearby the bHLH gene from common bean [Phaseolus vulgaris (L.)] and soybean were also analyzed to test for their association with the IDC resistance in mungbean.
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7.92, 2.1% organic matter, 17.83 mg/kg of available P, 97.01 mg/kg of exchangeable K, 15,883 mg/kg of exchangeable Ca, 499.63 mg/kg of exchangeable Mg, 0.99 mg/kg of extractable Fe, 13.62 mg/kg of extractable Mn, 1.63 mg/kg of extractable Cu, and 0.47 mg/kg of extractable Zn. In the dry season (March) of 2010 and 2011, the 122 RILs and their parents were sown in a randomized complete block design (RCBD) with two and three replications, respectively. Dry season plantings helped avoid interference from rains that often causes reduction in soil pH and increasing iron availability during RIL evaluation. In each block, each entry was sown in a single row 2.5 m long with 12.5 cm intra-row spacing (ca. 20 plants/row) and 50 cm inter-row spacing. In both experiments, IDC was evaluated by two methods, viz., visual scoring and soil-plant analysis development (SPAD) measurement at 3 weeks after planting. For visual score, plants were evaluated in rows based on leaf chlorosis symptoms. Scoring system was the same as reported by Srinives et al. (2010), viz., 1 (no yellowing), 2 (slight yellowing), 3 (moderate yellowing), 4 (intense yellowing coverage), and 5 (severe yellowing with some necrosis). Scoring was conducted by a panel of two trained staff. For SPAD measurement, 5 plants from each RIL were determined using a MINOLTA SPAD-502 meter (MINOLTA, Tokyo). Each plant was measured on 4 spots (2 each on the left and right of the midrib) on the terminal leaflet of the youngest fully expanded trifoliate leaf of the plant. The measurement was done immediately after visual scoring. The average SPAD reading from 5 plants was used to characterize IDC symptom of a RIL. 2.3. Estimation of heritability of IDC Narrow-sense heritability (h2 ) was estimated based on the property that RILs are theoretically a population of pure lines. Thus only additive genetic variation (a2 ) and interaction between the additive genes contribute to total genetic variation (g2 ), while dominant genetic variation (d2 ) can be negligible. Analysis of variance for SPAD value and visual score were performed on the RIL data using R-program version 2.10.0 (R Development Core Team, 2008). The heritability for both traits were estimated from the formula h2 = g2 /[g2 + (e2 /r)]; where e2 is the experimental error variance and r is the number of replications in each season.
2. Materials and methods 2.1. Plant materials A recombinant inbred line (RIL) population was used in this study. The population was developed from a cross between resistant line “NM10-12-1” and susceptible cultivar “Kamphaeng Saen 2” (KPS2), using KPS2 as the female parent. The parental mungbeans used in this study are the same as those used by Nopparat et al. (1997), Sommanus (2000) and Srinives et al. (2010), although the population or generation used is different. An F1 seed from the cross was grown, self-fertilized and generations advanced as F2 derived lines by single seed descent method. Finally, a population of 122 F8 RILs was obtained. Genomic DNA of the parents and RILs were extracted from young leaves following the method described by Lodhi et al. (1994). DNA was quantified against lambda DNA on 1.5% agarose gel stained with ethidium bromide. 2.2. Evaluation for resistance to iron deficiency chlorosis Field evaluation for resistance to IDC was carried out in an experimental field of Nakhon Sawan Field Crops Research Center, Nakhon Sawan province, Thailand where alkaline soil is uniformly prevailing (Srinives et al., 2010). The soil in this field had pH of
2.4. SSR marker analysis A total of 1191 SSR primer pairs from various legume crops were screened for polymorphism between the parents. Among them, 530 were from mungbean (Seehalak et al., 2009; Somta et al., 2008, 2009; Tangphatsornruang et al., 2009), 332 from azuki bean [Vigna angularis (Ohwi) Ohwi & Ohashi] (Wang et al., 2004), 152 from common bean (Phaseolus vulgaris L.) (Blair et al., 2003; Buso et al., 2006; Gaitán-Solís et al., 2002; Guerra-Sanz, 2004), and 177 from cowpea [Vigna unguiculata (L.) Walp.] (Kongjaimun et al., 2012; Li et al., 2001; Xu et al., 2010). Polymerase chain reaction (PCR) amplification was performed in a 10 l reaction volumes containing 2 ng genomic DNA, 1× Taq buffer with (NH4 )2 SO4 , 1.5 mM MgCl2 , 2 mM dNTPs, 5 pmol of each forward and reverse primers and 1 U Taq DNA polymerase (Fermentas). The DNA was amplified in a GeneAmp® PCR System 9700 thermocycler (Applied Biosystems). Thermal cycling was programmed as follow: 94 ◦ C for 2 min followed by 35 cycles of 94 ◦ C for 30 s, 47–60 ◦ C (depending on primers) for 30 s, 72 ◦ C for 1 min, and 72 ◦ C for 10 min. The PCR products were mixed with 10 l of formamide containing 10 mM EDTA, 0.02% bromophenol blue and xylene-cyanol, denatured at 94 ◦ C for 2 min. Then 1.5–2 l of the final product was loaded onto 5% polyacrylamide gel and visualized by silver staining.
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To confirm the AFLP markers associated with the resistance reported earlier by Sommanus (2000) and Srinives et al. (2010), four AFLP primer combinations reported by them were screened for polymorphism between the parents, and then analyzed in the RIL population using the same procedure. 2.6. Marker development from soybean and common bean bHLH gene Apart from the DNA markers mentioned above, more markers were developed and used for DNA analysis. Since it has been shown in soybean that the null function of the Glyma03g28610 (a basic helix–loop–helix (bHLH) gene) is responsible for susceptibility to iron deficiency (Peiffer et al., 2012), we hypothesized that bHLH might also be involved in iron deficiency resistance in mungbean. Due to unavailability of mungbean genome sequence, we used a comparative mapping approach to test this hypothesis. Glyma03g28610 was searched for SSRs, and primer pairs were designed to detect them. Glyma03g28610 was also compared to common bean genome sequence assembly (Phaseolus vulgaris v0.9; http://www.phytozome.net) to identify bHLH using BLAST. Once identified, a primer pair was designed targeting to an intron in the bHLH gene. SSRs were also searched from the bHLH gene and the DNA sequences surrounding the gene using the SSRIT program (http://www.gramene.org/microsat/ssr.html). All the SSRs were identified by SSRIT, while all primers were designed by Primer3 (http://www.frodo.wi.mit.edu). Marker analysis was performed as described in the SSR analysis. 2.7. Linkage map and QTL analyses A genetic linkage map was constructed using JoinMap version 3.0 software. A minimum LOD threshold of 3.0 and maximum recombination frequency of 0.50 were applied for grouping the markers into a linkage group. Map distance in centimorgan (cM) was calculated using Kosambi mapping function (Kosambi, 1944). Linkage groups were named following Chankaew et al. (2011) based on common markers. For QTL analysis, single regression analysis was performed to determine significant association between a DNA marker and visual score or SPAD value at P = 0.01 using R-program 10.2.0 (R Development Core Team, 2008). Software WinQTL Cartographer version 2.5 (Wang et al., 2010) was used to locate QTLs associated with the resistance by composite interval mapping (CIM). Walking speed was set at 1 cM. Significant threshold for the QTL was computed by 3000 run of a permutation test at P = 0.001. 3. Results 3.1. IDC response in RILs In the dry season of 2010, KPS2 showed high susceptibility to iron deficiency with the visual score of 5.0 and SPAD value of 4.10, while NM10-12 showed resistance to iron deficiency with the visual score of 2.20 and SPAD value of 38.50. The RILs showed different responses with the visual scores ranged from 1 to 5 and the average of 3.53, while the SPAD values varied from 1.49 to 41.66 with the average of 18.86. In the 2011 season, the results from the parents and RIL were similar to those of the 2010 season. KPS2 had the visual score of 4.80 and SPAD value of 13.8, while NM10-12 had the visual score of 1.30 and SPAD value of 35.70. The visual scores in the RIL population ranged from 1 to 5 with the average of 2.29, while the SPAD values varied from 11.39 to 42.82 with the average of 29.59 (Fig. 1). When the data from 2 years were combined, KPS2
(a)
NM10-12
50
2010
45
2011
KPS2
Combined
40
Number of lines
2.5. AFLP marker analysis
35 30 25
KPS2
NM10-12
20
NM10-12
KPS2
15 10 5 0 1.0-1.5 1.6-2.0 2.1-2.5 2.6-3.0 3.1-3.5 3.6-4.0 4.1-4.5 4.6-5.0
Visual score
(b) 50 Number of lines
232
2010
45
2011
40
Combined
35
NM10-12
KPS2
30 25
NM10-12
KPS2 KPS2
20
NM10-12
15 10 5 0 0-5.0
5.1-10 10.1-15 15.1-20 20.1-25 25.1-30 30.1-35 35.1-40 40.1-45
SPAD value
Fig. 1. Frequency distribution of visual score and SPAD value for response to iron deficiency in RIL population of the mungbean cross between KPS2 and NM1012, evaluated in a calcareous field at Nakhon Sawan Field Crops Research Center, Thailand in 2010 (a) and 2011 (b).
showed a visual score of 4.90 and SPAD value of 8.95, while NM1012 had a visual score of 1.75 and SPAD value of 37.10. In the RILs, a visual score varied between 1.0 and 5.0 with an average of 2.99 and SPAD value ranged from 7.0 to 39.45 with an average of 23.48. There was a high negative correlation between visual score and SPAD value for IDC in 2010 (r = −0.91, P < 0.0001), 2011 (r = −0.83, P < 0.0001) and combined data (r = −0.95, P < 0.0001). Frequency distribution of visual score and SPAD value in each year and combined data showed continuous distribution, suggesting that resistance to IDC in NM10-12 is quantitatively inherited. However, in 2010 visual score of the population skewed toward KPS2, while in 2011 visual score and SPAD value skewed toward NM10-12. 3.2. Heritability of resistance to IDC Analysis of variance (ANOVA) was performed on for visual score and SPAD value in the RIL population to estimate narrow-sense heritability. Results of the ANOVA are shown (Table 1). The h2 estimated for visual score and SPAD value in the 2010 season were 86.04% and 91.96%, respectively, while those in the 2011 season were 54.44% and 88.04%, respectively. The results indicated the importance of genetic factor(s) controlling resistance to IDC in mungbean. 3.3. Marker development and linkage map construction We have developed an SSR marker from the soybean sequence of Glyma03g28610. In silico search using Glyma03g28610 identified Phvulv091030676m.g (scaffold00144: 118332–120552) as a bHLH
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Table 1 Analysis of variance of visual score and SPAD value in RIL population of the mungbean cross KPS2 × NM10-12 evaluated for iron deficiency chlorosis at Nakhon Sawan Field Crops Research Center, Thailand in 2010 and 2011. Year 2010
Year 2011
df
Visual score MS
SOV Rep Line Error Total
2.67*** 3.66*** 0.27
1 121 121 243
CV (%) ***
14.82
SPAD value MS
df
981.61*** 308.29*** 12.92
2 121 242 365
Visual score MS
SPAD value MS
9.78*** 3.53*** 1.04
19.05
838.10*** 150.60*** 17.00
41.95
14.67
Significant at the 0.001 probability level.
Table 2 SSR markers associated with resistance to iron deficiency chlorosis based on the data from RIL population of the mungbean cross KPS2 × NM10-12 as detected by single regression analysis at P < 0.01. Marker (LG)
cp03715 (2) CEDG100 (2) cp02662 (2) VR169 (3) E-ACT/M-CTA175 (3) CEDG159 (3) CEDC031(3) CEDG084 (3) E-CAG/M-TAC100 (3) VR-SSR011 (11) CEDG044 (11) VR303 (11) CEDG013 (11) a b c
Year 2010
Year 2011
Combined data
Visual score
SPAD value
Visual score
SPAD value
Visual score
SPAD value
R2 (%)a
Pb
R2 (%)
P
R2 (%)
P
R2 (%)
R2 (%)
P
R2 (%)
7.31 6.58 5.64 9.29 39.58 31.04 59.59 55.30 25.59 Ns Ns Ns Ns
0.0063 0.0043 0.0023 0.0006 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
Nsc Ns Ns <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
Ns Ns Ns 11.35 39.55 37.77 61.60 58.62 28.78 7.05 7.39 8.83 9.16
0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0023 0.0008 0.0009 0.0006
Ns Ns 5.43 9.98 31.57 36.68 51.79 50.65 35.17 Ns Ns Ns 5.91
7.16 5.94 3.90 12.45 40.63 38.42 66.17 62.57 33.93 Ns 4.54 Ns 6.35
0.0082 0.0068 0.0054 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
6.94 Ns 3.44 11.75 41.94 42.88 69.09 66.51 35.61 Ns Ns Ns 5.47
13.41 31.91 37.08 54.05 50.55 35.00 Ns Ns Ns Ns
P
0.0098 0.0003 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
0.0060
0.0079 0.0041
P 0.0094 0.0089 0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
0.0082
Coefficient of the determination. Probability. Non-significant difference.
gene for common bean. Phvulv091030676m.g has a full genomic sequence length of 2221 bp and contains two introns. One intron length polymorphism (ILP) primer pair was designed to target the intron of Phvulv091030676m.g, and 12 pairs were designed to amplify SSRs in and around this gene (Suppl. Table S1). Of the 1203 SSR markers screened for polymorphism between KPS2 and NM10-12-1, 860 (71.49%) were able to amplify the parents and only 62 (7.21%) of these showed polymorphism. In the case of AFLP markers, 4 primer combinations produced 8 polymorphic loci. Linkage map analysis assigned 54 polymorphic markers into 12 linkage groups (LG) with a total genetic distance of 991.98 cM (Suppl. Fig. S1), while 16 markers were unlinked. The shortest linkage group was 23.66 cM, the longest linkage group was 139.45 cM, and the average total distance per linkage was 82.66 cM. Number of markers per LG was between 2 and 8 (LG 3) with an average of 4.5. 3.4. QTL controlling IDC resistance Single marker analysis in the RIL population using both visual score and SPAD value data from each year, and combined data showed that 12 markers from LGs 2, 3 and 11 associated with IDC resistance (P < 0.001) (Table 2). All the significant markers on LG3 were associated with both visual score and SPAD value, while all except one of the markers on LG3 were associated with visual score only. In the 2010 evaluation, the coefficient of determination (R2 ) of these markers for visual score data ranged from 5.64% (cp02662) to 58.89% (CEDC031), while for the SPAD value data varied between 13.41% (VR116) and 62.67% (CEDC031). In 2011 evaluation, R2 of these markers for visual score data ranged from 7.05% (VR-SSR011) to 61.60% (CEDC031), while for the SPAD value data varied from
5.43% (cp02662) to 51.79% (CEDC031). When combined data were used, R2 of these markers for visual score were between 3.90% (cp02662) and 66.17% (CEDC031), while for the SPAD value were 3.44% (cp02662) to 69.09% (CEDC031). Six markers on LG 3, namely VR169, E-ACT/M-CTA175, CEDG159, CEDC031, CEDG084, and ECAG/M-TAC100 showed highly significant association with visual score and SPAD value data, in all cases. Markers CEDC031 and VR169 showed highest and lowest R2 , respectively (Table 2). Composite interval mapping was conducted in the RIL population to locate QTLs for IDC onto the linkage map. For the visual score, permutation tests (3000 runs at P = 0.001) for the data in 2010 and 2011 of the RIL population revealed that LOD score thresholds for the QTL were 5.3 and 6.9, respectively. In both years, CIM identified one major QTL for the visual score locating at 126.9 cM on LG3 between markers CEDC031 and CEDG084 (Table 3; Fig. 2). The QTL was designated as qIDC-SCORE3.1. The qIDC-SCORE3.1 explained 41.467% and 36.72% of the visual score variation in the 2010 and 2011, respectively. Additive effects of the qIDC-SCORE3.1 were 1.25 and 0.98, respectively. However, in 2010, CIM detected another QTL, qIDC-SCORE2.1, locating at 35.7 cM on LG2 between markers CEDG100 and cp02662. The QTL accounted for 45.66% of the total score variation, and had additive effects of 0.45 (Table 3). In case of SPAD value, a 3000-run permutation test at P = 0.001 for the year 2010 and 2011 data gave LOD score thresholds for QTL of 9.6 and 4.7 in that order. CIM consistently identified a major QTL, designated as qIDC-SPAD3.1, for both SPAD data sets (Table 3; Fig. 2). qIDC-SPAD3.1 was located on LG3 between markers CEDC031 and CEDG084 at 126.9 and 127.9 cM using the 2010 and 2011 data in that order. The qIDC-SPAD explained 35.56 and 13.31% of the variation in SPAD values 2010 and 2011, respectively. Additive effects of the qIDC-SPAD were −10.13 and −5.45, respectively.
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P. Prathet et al. / Field Crops Research 137 (2012) 230–236
Table 3 Quantitative trait loci conditioning resistance to iron deficiency based on the data from RIL population of the mungbean cross KPS2 × NM10-12 as detected by composite interval mapping. Trait
Year
QTL name
LGa
Marker interval
Positionb
LOD score
PVEc (%)
Visual score
2010 2011 Combined
qIDC-SCORE2.1 qIDC-SCORE3.1 qIDC-SCORE3.1 qIDC-SCORE3.1
2 3 3 3
CEDG100–cp02662 CEDC031–CEDG084 CEDC031–CEDG084 CEDC031–CEDG084
35.7 126.9 126.9 126.9
8.41 18.0 32.5 44.3
45.66 41.67 36.72 23.14
0.45 1.25 0.98 1.04
2010 2011 Combined
qIDC-SPAD3.1 qIDC-SPAD3.1 qIDC-SPAD3.1
3 3 3
CEDC031–CEDG084 CEDC031–CEDG084 CEDC031–CEDG084
126.9 127.9 126.9
34.8 29.9 46.9
35.56 13.31 12.14
−10.13 −5.45 −7.93
SPAD value
a b c
Additive effect
Linkage group. Position on the linkage group (centimorgan; cM). Percentage of phenotypic variance explained by the QTL.
(a)
Visual score 2010
Visual score 2011
Combined visual score
SPAD value 2010
SPAD value 2011
Combined SPAD value
48 44 40
LOD score
36 32 28 24 20 16 12 8 4
cM
Visual score 2010
Visual score 2011
Combined visual score
SPAD value 2010
SPAD value 2011
Combined SPAD value
139.5 E-CAG/M-TAC100
10
CEDG184 126.0 CEDC031
(b)
CEDG159 112.0
Linkage group 3
E-ACT/M-CTA175 98.0
84.0
70.0
56.0
42.0
VR169
28.0
cp00361
14.0
0
0
LOD score
8
6
4
2
cM 75.8 CEDG244
60.0 CEDG225
66.0 CEDG108
54.0
48.0
42.0 cp02662
36.0
30.0 CEDG100
cp03715 24.0
18.0
12.0
BM220
6.0
0
0
Linkage group 2 Fig. 2. Position of the QTL controlling iron deficiency resistance and LOD score plotted for composite interval mapping (CIM) on linkage groups 3 (a) and 2 (b) in the RIL population of the cross between KPS2 and NM10-12 as evaluated by visual score and SPAD measurement. The lines parallel to the linkage maps represent LOD threshold.
P. Prathet et al. / Field Crops Research 137 (2012) 230–236
Combined data from 2 years were also used for locating the QTL. LOD score threshold determined by permutation test for combined visual score and combined SPAD value were 7.68 and 5.87 in that order. In both traits, CIM detected a single QTL at 126.9 cM on LG3 (Table 3; Fig. 2). qIDC-SCORE3.1 accounted for 23.14% of the total trait variation, while qIDC-SPAD3.1 explained 12.14% of the total trait variation. These QTLs had additive effects of 1.04 and −7.93 in that order. Since the qIDC-SCORE3.1 and qIDC-SPAD3.1 were identified using data from different years, they are very likely the same QTL. We named this QTL as qIDC3.1, and named qIDC-SCORE2.1 as qIDC2.1. 4. Discussion Iron deficiency chlorosis is a world-wide problem in crop production. Plant breeders have long been interested in improving cultivars with resistance to IDC. In Thailand, popular high-yielding mungbean cultivars such as Kamphaeng Saen 1 and KPS2 are susceptible to IDC. Mutation breeding of KPS2 using gamma ray resulted in a high-yielding and IDC resistance cultivar Chai Nat 72 (Anonymous, 2001). Breeding progress to improve resistance to IDC in these varieties by backcrossing or other methods is limited by difficulty in IDC evaluation, although several resistance sources are available and the genetics of the resistance is simple (Srinives et al., 2010). In this study, although QTL mapping reveals QTLs qIDC2.1 and qIDC3.1 controlling the IDC resistance, only qIDC3.1 was consistently detected and confirmed as the major QTL for IDC. qIDC3.1 was found in the dry season in both years with similar or same location and effect. Thus this QTL is robust and considered as the major QTL for IDC resistance in mungbean. qIDC2.1 appears to be a modifier for IDC resistance, and is sensitive to the environment. Although it was found only visual score in 2010, the LOD peak of this QTL almost reached the threshold in 2011 (Table 3; Fig. 2b). Similarly, LOD peaks of this genomic region detected using SPAD values from 2010 and combined data were not far from the threshold (Fig. 2b). The low penetrance or expressivity of this QTL may in part accounts for the low heritability (54.44%) of visual score in 2011. Nonetheless, it is worth noting that results from single marker analysis suggested the presence of other minor QTL(s) for visual score and SPAD value on LG11 in year 2010 (Table 2). These results are in agreement with the report of Srinives et al. (2010) that IDC resistance in mungbean NM10-12 is controlled by a single gene or one major QTL with modifiers. Similarly, it is also reported in soybean that a single gene or single major QTL with modifiers confer resistance to IDC (Cianzio and Fehr, 1980; Lin et al., 1997). In addition, two AFLP markers flanking to QTL for IDC resistance in mungbean under hydroponic condition reported by Srinives et al. (2010) also flank to the QTL found in the present study. This indicates that those QTLs are the same and the mechanisms of the resistance to IDC under hydroponic and field conditions are common. In soybean, a major QTL identified for resistance to IDC under field condition (Lin et al., 1997) is the same QTL as for the resistance under hydroponic condition (Peiffer et al., 2012). Although the heritability of SPAD values in both 2010 and 2011 were as high as 86.04% and 91.96%, respectively, the percentage of variance explained by the QTLs for this trait was lower than 40%. This indicated that additional QTL(s) conditioning IDC in mungbean, if any exists, were undetectable in the present study. It is mainly due to low saturation of the markers and genome coverage resulting from low polymorphism between the parents used. It is worth noting that the linkage map constructed in this study lacks LG7 and LG8 (Suppl. Fig. S1). Low polymorphism in both cultivated × cultivated and cultivated × wild mapping populations of mungbean has been reported (Chankaew et al., 2011; Sompong et al., 2012).
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In contrast to the grass family (Poaceae or Gramineae) which uses “strategy II”, all other plants use “strategy I” to cope with iron-deficiency soil to reduce and acquire Fe2+ (Marschner et al., 1986) for which they acidify the surrounding soil to promote solubilizing unavailable ferric iron by pumping protons into the plasma membrane using an H+ -ATPase. A ferric-chelate reductase (FRO2) reduces chelated Fe3+ into available Fe2+ which is then transported into roots by an iron-regulated transporter (IRT1) (Walker and Connolly, 2008). Gene expression studies of response to iron deficiency in Arabidopsis (Arabidopsis thaliana) revealed that when iron concentration is low in cell an unknown factor triggers the response which activates three transcription factors; Fe-deficiency-induced transcription factor (FIT), basic helix–loop–helix 038 (bHLH038) and bHLH039 (Bauer et al., 2007; Lingam et al., 2011; Wang et al., 2007). Results reported by Yuan et al. (2008) suggest that under the iron deficiency conditions FIT regulates the expression of FRO2 and IRT1 by binding to bHLH. Through fine mapping using nearisogenic lines and gene expression analysis in soybean, Peiffer et al. (2012) identified Glyma03g28610 coding for bHLH as the candidate gene controlling IDC resistance. The authors demonstrated that resistance varieties possess functional bHLH encoded by the Glyma03g28610, while susceptible varieties have defective bHLH encoded by the same locus containing a 12-bp deletion. Since the inheritance of IDC resistance in soybean and mungbean are similar, it is possible that a gene coding bHLH is also responsible for IDC resistance in mungbean. High genome conservation among soybean, mungbean and common bean has been demonstrated (Choi et al., 2004). We tested whether the gene coding for bHLH also controls IDC in mungbean using comparative gene mapping. A genic SSR from Glyma03g28610 failed to amplify DNA of the mungbean parents. Bioinformatics analysis identified Phvulv091030676m.g as the gene for bHLH in common bean. Twelve SSR and one ILP markers in and/or around Phvulv091030676m.g were developed and screened for polymorphism in the parents, but all of them failed to amplify and the ILP showed monomorphism. However, involvement of the gene for bHLH in the IDC resistance in mungbean still cannot be ruled out. It is worth investigating the association between sequence variation of bHLH encoded gene and IDC in the resistance and susceptible mungbeans when the whole genome sequence of mungbean becomes available. This can aid identification of the causal mutation leading to IDC susceptibility in mungbean, and hence enable the functional marker(s) to be developed for marker-assisted selection. Initially, SSR markers CEDC031 and CEDG084 which are closely linked to the resistance gene may be used for MAS of the IDC resistance mungbean. 5. Conclusion This study identified and confirmed QTL for iron deficiency chlorosis in mungbean grown in the calcareous soil using genetic linkage map of RIL population derived from a cross between “Kamphaengsaen 2” and “NM10-12”. A major QTL with similar or same location was identified across 2 years in both visual score and soil-plant analysis development measured for iron deficiency chlorosis, supporting previous findings that iron deficiency chlorosis in mungbean is controlled by a single gene and modifier(s). The QTL identified in this study is the same locus identified for iron deficiency chlorosis in mungbean grown under hydroponic condition. Thus the mechanism of the resistance in the field and hydroponic conditions are the same. Acknowledgements This research was supported by Thailand’s National Science and Technology Development Agency (NSTDA). A part of this research was also funded by Center of Advanced Studies for Agriculture and
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