Mapping resistant QTLs for rice sheath blight disease with a doubled haploid population

Journal of Integrative Agriculture 2015, 14(5): 801–810 Available online at www.sciencedirect.com

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RESEARCH ARTICLE

Mapping resistant QTLs for rice sheath blight disease with a doubled haploid population ZENG Yu-xiang*, XIA Ling-zhi*, WEN Zhi-hua*, JI Zhi-juan, ZENG Da-li, QIAN Qian, YANG Chang-deng State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou 310006, P.R.China

Abstract Sheath blight (SB) disease, caused by Rhizoctonia solani Kühn, is one of the most serious diseases causing rice (Oryza sativa L.) yield loss worldwide. A doubled haploid (DH) population was constructed from a cross between a japonica variety CJ06 and an indica variety TN1, and to analyze the quantitative trait loci (QTLs) for SB resistance under three different environments (environments 1–3). Two traits were recorded to evaluate the SB resistance, namely lesion height (LH) and disease rating (DR). Based on field evaluation of SB resistance and a genetic map constructed with 214 markers, a total of eight QTLs were identified for LH and eight QTLs for DR under three environments, respectively. The QTLs for LH were anchored on chromosomes 1, 3, 4, 5, 6, and 8, and explained 4.35–17.53% of the phenotypic variation. The SB resistance allele of qHNLH4 from TN1 decreased LH by 3.08 cm, and contributed to 17.53% of the variation at environment 1. The QTL for LH (qHZaLH8) detected on chromosome 8 in environment 2 explained 16.71% of the variation, and the resistance allele from CJ06 reduced LH by 4.4 cm. Eight QTLs for DR were identified on chromosomes 1, 5, 6, 8, 9, 11, and 12 under three conditions with the explained variation from 2.0 to 11.27%. The QTL for DR (qHZaDR8), which explained variation of 11.27%, was located in the same interval as that of qHZaLH8, both QTLs were detected in environment 2. A total of six pairs of digenic epistatic loci for DR were detected in three conditions, but no epistatic locus was observed for LH. In addition, we detected 12 QTLs for plant height (PH) in three environments. None of the PH-QTLs were co-located with the SB-QTLs. The results facilitate our understanding of the genetic basis for SB resistance in rice. Keywords: rice, sheath blight, quantitative trait locus, resistance

Kühn, causes significant yield losses in rice-growing regions

1. Introduction Sheath blight (SB) disease, caused by Rhizoctonia solani

worldwide (Zheng et al. 2013). SB is considered to be an important disease next to rice blast. In China, the rice yield losses caused by SB have exceeded those caused by blast, making SB the most serious disease (Zuo et al. 2008; Zeng et al. 2011). In the southern United States, SB is also the most important rice disease where the major goal

Received 16 May, 2014 Accepted 22 September, 2014 Correspondence YANG Chang-deng, Tel/Fax: +86-57163370367, E-mail: [email protected]; QIAN Qian, Tel/Fax: +86-571-63371418, E-mail: [email protected] * These authors contributed equally to this study.

of rice-breeding programmes is to improve SB resistance

© 2015, CAAS. All rights reserved. Published by Elsevier Ltd. doi: 10.1016/S2095-3119(14)60909-6

the most desirable control measure (Lee and Rush 1983).

(Groth and Bond 2007). Although the fungicide has been commonly used to manage SB disease, host resistance has been regarded However, progress in breeding SB-resistant rice cultivars

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has been slow due to the lacking of complete genetic resistance, and the complexity of resistance to SB has hindered the genetic studies. Rice resistance to SB is generally considered a typical quantitative trait controlled by quantitative trait loci (QTLs). Since the first publication of QTL mapping studies for rice SB resistance in 1995 (Li et al. 1995), SB resistance QTLs have been identified on all 12 rice chromosomes (Pan et al. 1999; Zou et al. 2000; Kunihiro et al. 2002; Sato et al. 2004; Pinson et al. 2005; Liu et al. 2009; Sharma et al. 2009; Channamallikarjuna et al. 2010; Fu et al. 2011; Xu et al. 2011; Nelson et al. 2012; Eizenga et al. 2013; Liu et al. 2013, 2014; Taguchi-Shiobara et al. 2013; Wen et al. 2015). Some SB-QTLs have been validated and evaluated by using introgression lines, including qSB-7TQ on chromosome 7, qSB9-2 and qSB-9TQ on chromosom 9, and qSB12-1 on chromosome 12 (Wang et al. 2012; Chen et al. 2014). But only a few SB-QTLs have been fine mapped, including qSBR-11-1 and qSB-11LE (Channamallikarjuna et al. 2010; Zuo et al. 2013). Candidate genes responsible for rice sheath blight resistance have been identified by transcriptome analysis (Venu et al. 2007; Zhao et al. 2008) and genome sequencing (Silva et al. 2012). No SB-QTLs have been cloned yet. This study was to identify QTLs responsible for rice SB resistance using a doubled haploid (DH) population derived from the cross of CJ06, a SB susceptible japonica variety, and TN1, a SB-resistant indica variety. QTL analysis was performed in three environments to provide information for utilizing potentially in rice breeding programmes.

2. Results 2.1. SB resistance of parental varieties The SB resistances of the two parental varieties in three environments were listed in Table 1. Analysis of variance

(ANOVA) indicated that the disease rating (DR) of the two parents were significantly different in environment 1 (P<0.01), but no significant differences were detected in the other two environments. The lesion height (LH) of the two parents were significantly different in environments 1 and 2 (P<0.01), but not significant in environment 3 (Table 1).

2.2. Distribution of lesion height (LH), disease rating (DR) and plant height (PH) in three environments The distribution of phenotypic values for LH and DR in DH population were apparently not normal in environment 3. For LH, the distributions were continuous in environments 1 and 2; it suggested that LH was controlled by polygene under these conditions. DR was also continuous in environments 1 and 2, but most of the DH lines had high DR values. The distributions of PH were normal in all three environments (Fig. 1).

2.3. Main-effect QTLs for sheath blight resistance A total of 16 QTLs, including eight QTLs for LH and eight QTLs for DR, were detected under three different environments (Table 2; Fig. 2). The eight QTLs for LH can explain 4.35 to 17.53% of the phenotypic variation. The allele of qHNLH4 from CJ06 increased LH by 3.08 cm (Table 2). But qHNLH4 was identified only in one environment, which explained variation of 17.53%. Eight QTLs for DR were anchored on chromosomes 1, 5, 6, 8, 9, 11, and 12 under three conditions with the explained variation from 2.0 to 11.27%. A QTL for LH, qHZaLH8, was located on the same marker interval on chromosome 8 as that of qHZaDR8, a QTL for DR. Resistance was attributed to CJ06 at this locus. But this locus was detected only in environment 2. A QTL locus, located on chromosome 5 between RM3321 and RM3616, was found responsible for both LH and DR, but it was detected only in environment 3, with the SB-resistant

Table 1 The disease rating (DR), lesion height (LH) and plant height (PH) of the two parents grown in three environments Environment1) 1

2

3

1)

Trait DR LH (cm) PH (cm) DR LH (cm) PH (cm) DR LH (cm) PH (cm)

Mean±SD CJ06 8.67±0.29** 38.83±5.06** 53.50±1.85** 4.83±0.58 46.07±2.42** 94.17±2.41* 0.83±0.29 2.53±0.68 96.80±4.42*

TN1 2.33±0.58** 12.73±2.96** 84.80±2.21** 3.67±0.29 34.70±2.80** 106.40±3.95* 0.67±0.29 2.37±1.36 108.87±3.23*

DH population (range)2) 8.13±0.81 (4.00–8.50) 41.26±6.49 (19.60–53.30) 66.59±9.41 (43.20–96.80) 6.72±1.60 (3.00–9.00) 33.98±10.14 (17.20–58.60) 95.40±11.68 (74.80–123.70) 1.98±2.15 (0.50–8.50) 12.84±12.80 (0.60–57.20) 95.70±10.05 (77.20–123.40)

Environment 1, winter 2012 in Hainan; environment 2, spring 2013 in Hangzhou; environment 3, summer 2013 in Hangzhou. The same as below. DH, doubled haploid. * P<0.05, **P<0.01. The same as below. 2)

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TN1

35

CJ06 TN1

TN1 CJ06

CJ06

Number of lines

30 Environment 1

25

Environment 2

20

Environment 3

15 10 5 0

0–5

5–10

10–15

15–20

20–25

25–30

30–35

35–40

40–45

45–50

50–55

55–60

Lesion height (cm) 80 70

CJ06 TN1

TN1

TN1

CJ06

3–4

4–5

Number of lines

60 50 40 30 20 10 0

0–1

1–2

2–3

5–6

6–7

7–8

8–9

Disease rating CJ06

50 45

TN1 CJ06 CJ06

TN1 TN1

40

Number of lines

35 30 25 20 15 10 5 0

0–10

10–20 20–30 30–40 40–50 50–60 60–70 70–80 80–90 90–100 100–110 110–120 120–130 Plant height (cm)

Fig. 1 Distributions of lesion height (LH), disease rating (DR) and plant height (PH) in doubled haploid (DH) population observed in three environments. Environment 1, winter 2012 in Hainan; environment 2, spring 2013 in Hangzhou; environment 3, summer 2013 in Hangzhou. The same as below.

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Table 2 Main-effect QTLs for LH and DR detected in three environments Trait/Environment LH/1

LH/2

LH/3 DR/1

DR/2 DR/3 1)

2)

QTL qHNLH3 qHNLH4 qHNLH6 qHZaLH1 qHZaLH3 qHZaLH6 qHZaLH8 qHZbLH5 qHNDR1 qHNDR6 qHNDR11 qHNDR12 qHZaDR8 qHZaDR9 qHZbDR5 qHZbDR9

Marker interval RM6759–STS146.1 RM255–SSIII-1 AP3510–AP4991 RM428B–RM5302 RM143–RM514 WX–RM587 RM1376–RM4085 RM3321–RM3616 RM259–RM600 AP3510–AP4991 STS30–RM202 RM3226–RM12 RM1376–RM4085 RM444–AGPSMA RM3321–RM3616 RM278–RM3919B

A1) 2.14 3.08 1.54 –2.66 2.54 –2.81 –4.40 –3.70 –0.61 –0.66 1.34 1.30 –0.62 –0.38 –0.71 –0.62

F 11.60 10.40 6.92 7.13 5.12 9.73 16.21 6.05 2.22 2.33 1.99 1.34 18.73 4.98 5.60 3.23

P-value <0.0001 <0.0001 0.0034 0.0049 0.0029 0.0012 <0.0001 0.0011 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0021 0.0002 0.0012

H2(A)2) (%) 8.46 17.53 4.35 6.12 5.57 6.79 16.71 7.15 2.00 2.38 9.77 9.15 11.27 4.26 8.97 6.76

A, additive effect. Since lower values of LH and DR indicate enhanced resistance, a positive value and a negative value denote TN1 and CJ06 are the source of the resistance alleles, respectively. The same as below. H2(A), the heritability of additive effect. The same as below.

allele from CJ06. In addition, a locus for both LH and DR was anchored on chromosome 6 between markers AP3510 and AP4991, but it was also detected only in one environment. We did not detect stable SB resistance QTLs across all three environments. It indicated that the SB resistance QTL was specific to the environment.

2.4. Main-effect QTLs for PH Twelve QTLs for PH were identified, with 7, 2 and 3 QTLs detected in the three environments, respectively. They were located on chromosomes 1, 2, 3, 4, 5, 6, 8, 9, and 10, and explained 3.74 to 22.19% of the phenotypic variation (Table 3 and Fig. 2). A QTL locus located in the RM228 to RM4771 interval on chromosome 10 was detected in two environments, explaining 6.46 and 22.19% of the phenotypic variation, respectively. The allele of this locus from CJ06 decreased PH by 2.84 and 6.23 cm in environments 1 and 3, respectively. A QTL anchored on chromosome 9 between RM7048 and RM257 was detected in two environments, which explained 14.06 and 13.87% of the phenotypic variation, respectively. The allele of this QTL from CJ06 increased PH by 5.04 and 4.93 cm in environments 2 and 3, respectively.

2.5. Digenic epistasis for SB resistance and PH The digenic epistatic effects of LH, DR and PH were calculated to further examine the genetic components of these traits. No significant epistasis was detected for LH, which indicated that the main-effect QTL was the primary genetic basis for LH. A total of six pairs of digenic epistatic loci for

DR were detected in three different conditions, which explained 4.22 to 8.11% of the epistatic variation. Ten pairs of epistatic loci for PH were estimated in three environments, and they accounted for 4.01 to 6.81% of the epistatic variation (Table 4).

2.6. Correlation between SB resistance and PH To understand the correlations between SB resistance and PH, we calculated the correlation coefficients among LH, DR and PH in the DH population in each environment (Table 5). No significant correlations were detected between LH and PH in three environments. It indicated that LH and PH may be controlled by different genetic systems. Significant negative correlation between PH and DR was observed in only one environment (r=–0.36, P<0.01). It suggested that PH had little effect on DR. Highly significant positive correlations (P<0.0001) between LH and DR were detected in environments 2 and 3. It indicated that LH and DR were highly associated in the two environments.

3. Discussion 3.1. Distinct environments result in detection of environment-specific SB-QTLs This study identified eight QTLs for LH and eight QTLs for DR in three environments using a DH population. By comparing the locations of the SB-QTLs, we found that these SB-QTLs were detected only in one environment, although some LH-QTLs were co-located with DR-QTLs within the same environment. To examine explanations of why the

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Fig. 2 Main-effect QTLs for lesion height (LH), disease rating (DR) and plant height (PH) detected in three different environments.

SB-QTLs detected were so poorly replicated among three environments, we calculated the correlation coefficients of LH, DR and PH among different mapping conditions (Tables 6–8). The results showed that the correlation coefficients of LH between different environments were very low, and no significant correlations were detected (Table 6). The cor-

relation coefficients of DR between different environments were also very low, significant correlations were detected only between environments 1 and 2, with the r=0.21 (Table 7). These results can explain the reason why stable SB-QTLs were not detected across three environments, because the LH and DR of the DH population recorded in

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Table 3 QTLs for plant height (PH) detected in three environments Environment 1

QTL qHNPH1 qHNPH2 qHNPH3 qHNPH5 qHNPH6 qHNPH8 qHNPH10 qHZaPH9 qHZaPH10 qHZbPH4 qHZbPH9 qHZbPH10

2 3

Marker interval RM1282–RM428B RM240–RM5607 RM6676–RM6266 AGPLAR–RM31 RM3183–RM3827 RM5493–RM3120 RM228–RM4771 RM7048–RM257 STS64.1–RM228 RM6997–RM252 RM7048–RM257 RM228–RM4771

A 2.35 –2.80 –2.16 2.65 –2.23 2.66 –2.84 5.04 –5.34 3.37 4.93 –6.23

F 7.65 11.89 8.71 2.08 9.85 1.87 7.69 6.93 7.97 3.81 10.52 5.62

P-value 0.0002 <0.0001 0.0013 <0.0001 0.0003 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001

H2(A) (%) 4.46 6.31 3.74 5.63 3.99 5.70 6.46 14.06 15.81 6.51 13.87 22.19

AA1) 1.09 –0.88 1.05 –0.48 0.42 0.68 –2.71 –2.51 –2.23 –2.25 –3.08 –3.32 3.10 –3.45 2.71 –3.04

P-value <0.0001 <0.0001 <0.0001 0.0005 0.0013 0.0015 <0.0001 0.0005 0.0009 0.0004 0.0018 0.0005 0.0002 <0.0001 0.0002 <0.0001

H2(AA) (%) 6.44 4.22 6.03 6.87 5.13 8.11 5.89 5.05 4.01 4.07 5.26 6.11 5.49 6.81 4.21 5.28

Table 4 Epistatic loci detected for LH, DR and PH in three environments Trait DR

Environment 1

2

PH

3 1

2 3

1)

Chr. 1 1 1 1 4 1 1 2 3 4 1 1 1 1 7 9

Marker interval RM259–RM600 RM259–RM600 RM13–RM1353 RM1198–RM104 RM3735–RM241 RM5389–RM1198 RM1282–RM428B RM240–RM5607 RM6676–RM6266 RM3735–RM241 RM8094–RM6716 RM8094–RM6716 RM1282–RM428B RM1282–RM428B GBSSII–RM3755 RM7048–RM257

Chr. 2 7 11 9 9 8 4 10 5 8 6 9 4 7 9 10

Marker interval RM5622–RM1358 RM13–RM1353 STS30–RM202 RM444–AGPSMA RM444–AGPSMA AGPS2A–RM3153 RM3735–RM241 RM228–RM4771 AGPLAR–RM31 RM5493–RM3120 RM587–RM8200 RM7048–RM257 RM6997–RM252 GBSSII–RM3755 RM7048–RM257 RM228–RM4771

AA, the additive by additive effect.

Table 5 Correlations among LH, DR and PH from DH population observed in different environments1)

Table 6 Correlations of LH assessed in the DH population among different environments

Environment 1

Trait/ LH/ LH/ LH/ Environment Environment 1 Environment 2 Environment 3 LH/Environment 1 1 LH/Environment 2 0.17 1 LH/Environment 3 0.01 0.03 1

2

3

1)

Trait LH DR PH LH DR PH LH DR PH

LH 1 0.18 0.22 1 0.78** –0.21 1 0.97** –0.08

DR

PH

1 –0.02

1

1 –0.36*

1

1 –0.17

1

The correlation coefficients were calculated within a specific environment, based on the environment given in the first column.

three environments were apparently different as shown in Tables 6 and 7. The three environments that we performed QTL analysis were totally different: The DH mapping populations were sown in winter in Hainan (environment 1), spring in Hangzhou (environment 2) and early summer in Hangzhou (environment 3), respectively. Therefore, the

Table 7 Correlations of DR assessed in the DH population among different environments Trait/ DR/ DR/ DR/ Environment Environment 1 Environment 2 Environment 3 DR/Environment 1 1 DR/Environment 2 0.21* 1 DR/Environment 3 0.02 0.18 1

SB-QTLs identified were environment-specific. As for PH, highly significant correlations were detected between different environments, and the correlation coefficients were high compared with that of the LH and DR (Tables 6–8).

ZENG Yu-xiang et al. Journal of Integrative Agriculture 2015, 14(5): 801–810

Table 8 Correlations of PH assessed in the DH population among different environments Trait/ PH/ PH/ PH/ Environment Environment 1 Environment 2 Environment 3 PH/Environment 1 1 PH/Environment 2 0.57** 1 PH/Environment 3 0.66** 0.91** 1

It suggested that the PH assessed in the DH population was highly correlated among different mapping conditions. Therefore, it was not surprised that we detected stable PHQTLs on chromosomes 9 and 10 (Fig. 2 ).

3.2. Close SB-QTLs detected in two environments We also detected SB-QTLs on similar chromosome segments in two different mapping conditions: qHNLH3 detected in environment 1 and qHZaLH3 detected in environment 2 were very close (Fig. 2, Table 2), the SB resistance alleles of both QTLs came from TN1, but it was not clear whether they were same gene locating on similar location due to poor mapping resolution, or they were two different individual genes. Similar situation was found at qHZaLH6 and qHNDR6, the resistance alleles of both QTLs came from CJ06, and they were also close to each other. These SB-QTLs are worth further investigation if they were across at least two environments.

3.3. Comparion of the SB-QTLs between present and previous studies A comparison was made between the SB-QTLs detected in this study and the SB-QTLs reported in previous studies (Appendixes A–I). Before comparison, the marker intervals of the SB-QTLs were converted into physical distances by aligment of the markers in relation to the Nipponbare reference sequence using BLAST on NCBI website. We found that 10 of the SB-QTLs detected in this study were co-localized in same chromosome segments with the SB-QTLs reported in previous studies: qHZaLH1 was co-localized with two QTLs (qLL-1b and qLH-1b) reported by Liu et al. (2014); qHNDR1 was collocated with qSB-1 (Pinson et al. 2005) and qLH-1c (Liu et al. 2014); qHNLH3 was co-localized with qSBR-3 (Kunihiro et al. 2002) and qSBD-3-2 (Wen et al. 2015); qHNLH4 was co-localized with QSh4 (Xie et al. 2008) and qSB-4-2 (Pinson et al. 2005); qHZbLH5 (or qHZbDR5) was co-localized with qSB-5 (Han et al. 2002); qHNLH6 (or qHNDR6) was co-localized with qSB-6-1 (Pinson et al. 2005); qHZaLH8 (or qHZaDR8) was co-localized with qSB-8-1 (Pinson et al. 2005), QSbr8a (Li et al. 1995) and QDs8 (Li et al. 2009); qHZbDR9 was co-localized with qSBR-9 (Taguchi-Shiobara et al. 2013) and qSB-9-2 (Zou

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et al. 2000); qHNDR11 was co-localized with qSB-11 (Zou et al. 2000), qSBR11-2 (Channamallikarjuna et al. 2010), qSBR11-3 (Channamallikarjuna et al. 2010), and qShB11 (Eizenga et al. 2013); and qHNDR12 was co-located with qSB-12 (Pinson et al. 2005) and QRh12 (Li et al. 2009). Besides, we also found that some SB-QTLs identified were co-localized or located in similar or overlapped chromosome segments with the QTLs for plant height (PH) and heading date (HD): qHNDR1 was co-localized with HD-QTL qHD-1 (Sato et al. 2004) and overlapped with PH-QTL qPH-1b (Liu et al. 2014); qHNLH3 was co-localized with PH-QTLs qCL3 (Kunihiro et al.2002), qPH3 (Fu et al. 2011) and qPH-3 (Liu et al. 2014); qHZaLH3 was overlapped with PH-QTLs qCL-3 (Kunihiro et al.2002), qpht_3.1 (Nelson et al. 2012), qPH3 (Fu et al. 2011), and qPH-3 (Wen et al. 2015), and co-localized with qPH-3 (Liu et al. 2014), PH3 (Pan et al. 1999), qPH-3 (Zou et al. 2000), HD3 (Pan et al. 1999), and qHD-3 (Zou et al. 2000); qHNLH4 was co-localized with PH-QTL qPH-4 (Wen et al. 2015); qHZbLH5 (or qHZbDR5) was co-localized with PH-QTL qpht_5.1 (Nelson et al. 2012); qHZaLH6, qHNLH6 and qHNDR6 were co-localized with HD-QTL qHD-6 (Liu et al. 2014); qHZaLH8 (or qHZaDR8) was co-localized with PH-QTL QPh8a and HD-QTL QHd8a (Li et al. 1995), and overlapped with HD-QTLs qHD-8 (Kunihiro et al. 2002) and qDH8 (Eizenga et al. 2013); and qHNDR12 was co-localized with PH-QTL QPh12 (Li et al. 2009), and overlapped with PH-QTL qPH12 (Eizenga et al. 2013). The detailed information of the comparison between the SB-QTLs detected in this study and the QTLs related to sheath blight resistance reported in previous studies were listed in Appendixes A–I.

3.4. Plant height and SB resistance PH has been reported to be correlated with SB resistance (Li et al. 1995, 2009; Zou et al. 2000; Channamallikarjuna et al. 2010; Fu et al. 2011; Eizenga et al. 2013), and co-localization of PH-QTL and SB-QTL has been observed (Li et al.1995; Kunihiro et al. 2002; Fu et al. 2011). In this study, significant correlation between PH and SB resistance was not detected except that a significant negative correlation between PH and DR was observed in environment 2 (r=–0.36, P<0.01). We did not found co-localization of PH- and SB-QTL in this study, which indicated that the SBQTLs were irrelevant to PH, and may be used in breeding SB-resistant varieties.

3.5. Comparison between statistical analysis and the SB-QTL results It seemed that a bimodal-like distribution of phenotypic values for LH and DR were observed in environment 3, indicat-

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ing that there may be a gene with large effect controlling LH and DR under this condition. We indeed detected a locus on chromosome 5 at the RM3321 to RM3616 interval responsible for both LH and DR: The qHZbLH5 and qHZbDR5 were identified in environment 3, which decreased LH by 3.7 cm and reduced DR by 0.71, respectively. But they explained a small portion of the variation, only 7.15% of the variation for LH and 8.97% of the variation for DR, respectively. We also noticed that LH and DR were highly correlated in environments 2 and 3, with r=0.78 and r=0.97, respectively (Table 5). The LH-QTL qHZaLH8 was co-localized with the DR-QTL qHZaDR8, both of them were detected in environment 2; the LH-QTL qHZbLH5 was co-localized with the DR-QTL qHZbDR5, both of them were identified in environment 3. Therefore, the correlation analysis results and the QTL analysis results were identical.

4. Conclusion A total of 16 environment-specific SB-QTLs were detected, including eight QTLs for LH and eight QTLs for DR. Ten of the SB-QTLs detected in this study were co-localized with the SB-QTLs reported in previous studies. Six pairs of digenic epistatic loci for DR were detected in three different conditions, while no significant epistasis was detected for LH. Twelve QTLs for PH were identified in three environments, but none of which were co-localized with the SB-QTLs.

5. Materials and methods 5.1. Plant materials and field evaluation of SB resistance A japonica variety CJ06 was crossed with an indica variety TN1 to develop DH population by anther culture (Leng et al. 2014). The DH population consisting of 116 lines was grown in three different environments to evaluate the SB resistance. Environment 1, the DH population was planted on November 25, 2012 in Lingshui, Hainan, China (110°02´E, 18°48´N); environment 2, the population was sown on March 20, 2013 in the farm of China National Rice Research Institute (CNRRI) in Fuyang, Hangzhou, China (119°95´E, 30°07´N); environment 3, the mapping population was sown on June 10, 2013 in the same farm in CNRRI as mentioned above. The management of field planting followed common practice in Hainan or Hangzhou. For each environment, the 116 DH lines and the two parental varieties were grown in paddy field following a randomized complete block design with three replications, and 18 plants for each DH line (or parental variety) were arranged in three rows (6 plants in each row) with spacing

of 17 and 20 cm between hills and between rows, respectively. At late tillering stage, three plants in the middle row of each DH line were randomly selected for inoculation and evaluation of SB resistance. We inoculated three tillers in each individual plant, that was nine tillers within a DH line in each environment. The Rhizoctonia solani isolate ZJ03 stored in this lab was used for inoculation. We used truncated bamboo-toothpicks (2–2.5 cm long) as inoculums for pathogen infection based on the method described by Zou et al. (2000) with some modification: the toothpicks were incubated with the ZJ03 strain on potato dextrose agar medium for 7 d in the dark at 28°C, then inserted to the third leaf sheath, counting from the top during the late tillering stage. The rice reactions to SB disease were recorded 30 d after inoculation. The lesion height (LH) and disease rating (DR) were recorded to evaluate SB resistance of each inoculated plant. Since SB lesions were observed along the stem, the LH was measured from the lowest site of lesion to the highest site of lesion. For DR, we used the 0–9 rating system, DR =(LH/Plant height (PH))×10 (Li et al. 1995). The plant height was measured from the soil surface to the tip of the tallest panicle at maturity (Sharma et al. 2009). The maximum LH and DR of the three examined plants within a DH line were used in QTL analysis. The average plant height of three plants within a DH line was used in QTL-mapping.

5.2. Construction of a linkage map More than 600 markers were tested to search polymorphic markers between CJ06 and TN1. A total of 214 polymorphic markers were selected to construct a marker linkage map using Mapmaker/EXP ver. 3.0 software (Lander et al. 1987). This linkage map was 1444.5 cM, with an average of 7.4 cM between adjacent markers.

5.3. QTL-mapping and statistical analyses The QTLMAPPER 1.6 software was used to map single-locus main-effect QTLs and epistatic loci for LH, DR and PH. The QTL mapping is based on the mixed linear model (Wang et al. 1999). The putative QTL were determined using a threshold of P<0.0005 as described by Leng et al. (2014). The calculation of correlation coefficients and ANOVA was run in SAS software (ver. 8.01).

5.4. Comparison of the SB-QTLs detected in this study and the QTLs related to SB resistance in previous studies To enable comparisons among different studies, the physical positions of the markers flanking the SB-QTLs (or plant

ZENG Yu-xiang et al. Journal of Integrative Agriculture 2015, 14(5): 801–810

height-QTLs and heading date-QTLs identified in SB-QTL mapping studies) detected in previous studies were obtained. First, the sequence information of the molecular markers was attained from Gramene (http://www.gramene. org) and used as a query to BLAST against the Nipponbare sequence on the NCBI website (http://www.ncbi.nlm.nih. gov/). Based on the BLAST results, the physical positions (Mb) of the corresponding markers were obtained.

Acknowledgements This work was supported by the National Natural Science Foundation of China (31101004, 31221004), the National High-Tech R&D Program of China (863 Program, 2012AA101201), a fund from Zhejiang Province for public welfare (2014C32013), a special fund for technical innovation team in Zhejiang Province, China (2010R50024), and a fund from the Chinese Academy of Agricultural Sciences to the Scientific and Technical Innovation Team. Appendix associated with this paper can be available on http://www.ChinaAgriSci.com/V2/En/appendix.htm

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