Identification of Stable Quantitative Trait Loci for Sheath Blight Resistance Using Recombinant Inbred Line

doi:10.1016/j.rsci.2019.08.007

Abstract

Abstract:

To identify stable quantitative trait loci (QTLs) responsible for sheath blight resistance, a recombinant inbred line mapping population consisting of 219 lines was developed by crossing Lemont and Yangdao 4. Average disease rating, average lesion length, maximum disease rating and maximum lesion length were assayed in six different environments. A total of 128 minor effect QTLs were detected by multiple interval mapping. These QTLs explained less than 11.2% of the phenotypic variations individually, and 106 QTLs were clustered in 20 QTL-rich regions/putative loci. Significant QTL × environment interactions were detected at three putative loci (qSBR11.1, qSBR11.2 and qSBR11.3), indicating that these three loci were not stable. The other 17 stable loci (qSBR1.1, qSBR1.2, qSBR2.1, qSBR2.3, qSBR3.1, qSBR3.2, qSBR3.5, qSBR3.6, qSBR5.1, qSBR7.1, qSBR8.1, qSBR9.1, qSBR9.2, qSBR9.3, qSBR12.1, qSBR12.2 and qSBR12.4) provided a foundation for marker-assisted selection in breeding. Analysis of allelic effect on the 20 putative loci identified 7 highly stable loci, including qSBR3.2, qSBR7.1, qSBR8.1, qSBR9.2, qSBR9.3, qSBR12.1 and qSBR12.2.

Key words: rice, sheath blight resistance, quantitative trait locus, recombinant inbred line

Yuan Chen, Yuxiang Zeng, Zhijuan Ji, Yan Liang, Zhihua Wen, Changdeng Yang. Identification of Stable Quantitative Trait Loci for Sheath Blight Resistance Using Recombinant Inbred Line[J]. Rice Science, 2019, 26(5): 331-338.

Figures/Tables 3

References 47

[1]	Channamallikarjuna V, Sonah H, Prasad M, Rao G J N, Chand S, Upreti H C, Singh N K, Sharma T R.2010. Identification of major quantitative trait loci qSBR11-1 for sheath blight resistance in rice. Mol Breeding, 25(1): 155-166.
[2]	Chen X J, Chen Y, Zhang L N, Xu B, Zhang J H, Chen Z X, Tong Y H, Zuo S M, Xu J Y.2016. Overexpression of OsPGIP1 enhances rice resistance to sheath blight. Plant Dis, 100(2): 388-395.
[3]	Chen Z X, Zhang Y F, Feng F, Feng M H, Jiang W, Ma Y Y, Pan C H, Hua H L, Li G S, Pan X B, Zuo S M.2014. Improvement of japonica rice resistance to sheath blight by pyramiding qSB-9TQ and qSB-7TQ. Field Crops Res, 161: 118-127.
[4]	Datta K, Velazhahan R, Oliva N, Ona I, Mew T, Khush G S, Muthukrishnan S, Datta S K.1999. Over-expression of the cloned rice thaumatin-like protein (PR-5) gene in transgenic rice plants enhances environmental friendly resistance to Rhizoctoniasolani causing sheath blight disease. Theor Appl Genet, 98: 1138-1145.
[5]	Eizenga G C, Prasad B, Jackson A K, Jia M H.2013. Identification of rice sheath blight and blast quantitative trait loci in two different O. sativa/O. nivara advanced backcross populations. Mol Breeding, 31(4): 889-907.
[6]	Fu D, Chen L, Yu G H, Liu Y, Lou Q J, Mei H W, Xiong L, Li M S, Xu X Y, Luo L J.2011. QTL mapping of sheath blight resistance in a deep-water rice cultivar.Euphytica, 180(2): 209-218.
[7]	Gao Y, Zhang C, Han X, Wang Z Y, Ma L, Yuan D P, Wu J N, Zhu X F, Liu J M, Li D P, Hu Y B, Xuan Y H.2018. Inhibition of OsSWEET11 function in mesophyll cells improves resistance of rice to sheath blight disease. Mol Plant Pathol, 19(9): 2149-2161.
[8]	Ghosh P, Sen S, Chakraborty J, Das S.2016. Monitoring the efficacy of mutated Allium sativum leaf lectin in transgenic rice against Rhizoctonia solani. BMC Biotechnol, 16: 24.
[9]	Groth D E, Bond J A.2007. Effects of cultivars and fungicides on rice sheath blight, yield, and quality.Plant Dis, 91(12): 1647-1650.
[10]	Helliwell E E, Wang Q, Yang Y N.2013. Transgenic rice with inducible ethylene production exhibits broad-spectrum disease resistance to the fungal pathogens Magnaporthe oryzae and Rhizoctonia solani. Plant Biotechnol J, 11(1): 33-42.
[11]	Jiang S F, Wang C J Z, Shu C W, Zhou E X.2018. Cloning and expression analysis of RsPhm gene in Rhizoctonia solani AG-1 IA of rice sheath blight pathogen. Chin J Rice Sci, 32(2): 111-118. (in Chinese with English abstract)
[12]	Kao C H, Zeng Z B, Teasdale R D.1999. Multiple interval mapping for quantitative trait loci. Genetics, 152(3): 1203-1216.
[13]	Kunihiro Y, Qian Q, Sato H, Teng S, Zeng D L, Fujimoto K, Zhu L H.2002. QTL analysis of sheath blight resistance in rice (Oryza sativa L.). Acta Genet Sin, 29(1): 50-55. (in Chinese with English abstract)
[14]	Li Z K, Pinson S R M, Marchetti M A, Stansel J W, Park W D.1995. Characterization of quantitative trait loci (QTLs) in cultivated rice contributing to ﬁeld resistance to sheath blight (Rhizoctonia solani). Theor Appl Genet, 91(2): 382-388.
[15]	Li F, Cheng L R, Xu M R, Zhou Z, Zhang F, Sun Y, Zhou Y L, Zhu L H, Xu J L, Li Z K.2009. QTL mining for sheath blight resistance using the backcross selected introgression lines for grain quality in rice.Acta Agron Sin, 35(9): 1729-1737. (in Chinese with English abstract)
[16]	Lin W, Anuratha C S, Datta K, Potrykus I, Muthukrishnan S, Datta S K.1995. Genetic engineering of rice for resistance to sheath blight.Nat Biotechnol, 13: 686-691.
[17]	Liu G, Jia Y, Correa-Victoria F J, Prado G A, Yeater K M, McClung A, Correll J C.2009. Mapping quantitative trait loci responsible for resistance to sheath blight in rice.Phytopathology, 99: 1078-1084.
[18]	Liu G, Jia Y, McClung A, Oard J H, Lee F N, Correll J C.2013. Confirming QTLs and finding additional loci responsible for resistance to rice sheath blight disease.Plant Dis, 97(1): 113-117.
[19]	Molla K A, Karmakar S, Chanda P K, Ghosh S, Sarkar S N, Datta S K, Datta K.2013. Rice oxalate oxidase gene driven by green tissue-specific promoter increases tolerance to sheath blight pathogen (Rhizoctonia solani) in transgenic rice. Mol Plant Pathol, 14(9): 910-922.
[20]	Nelson J C, Oard J H, Groth D, Utomo H S, Jia Y, Liu G, Moldenhauer K A K, Correa-Victoria F J, Fjellstrom R G, Scheffler B, Prado G A.2012. Sheath-blight resistance QTLs in japonica rice germplasm. Euphytica, 184(1): 23-34.
[21]	Pan X B, Zou J H, Chen Z X, Lu J F, Yu H X, Li H T, Wang Z B, Pan X Y, Rush M C, Zhu L H.1999. Tagging major quantitative trait loci for sheath blight resistance in a rice variety, Jasmine 85.Chin Sci Bull, 44(19): 1783-1789.
[22]	Park D S, Sayler R J, Hong Y G, Nam M H, Yang Y N.2008. A method for inoculation and evaluation of rice sheath blight disease.Plant Dis, 92: 25-29.
[23]	Pinson S R M, Capdevielle F M, Oard J H.2005. Confirmation QTLs and finding additional loci conditioning sheath blight resistance in rice using recombinant inbred lines.Crop Sci, 45(2): 503-510.
[24]	Srinivasachary S, Willocquet L, Savary S.2011. Resistance to rice sheath blight (Rhizoctonia solani) [(teleomorph: Thanatephorus cucumeris (A.B. Frank) Donk.] disease: Current status and perspectives. Euphytica, 178(1): 1-22.
[25]	Tan C X, Ji X M, Yang Y, Pan X Y, Zuo S M, Zhang Y F, Zou J H, Chen Z X, Zhu L H, Pan X B.2005. Identification and marker- assisted selection of two major quantitative genes controlling rice sheath blight resistance in backcross generations.Acta Genet Sin, 32(4): 399-405. (in Chinese with English abstract)
[26]	Tonnessen B W, Manosalva P, Lang J M, Baraoidan M, Bordeos A, Mauleon R, Oard J, Hulbert S, Leung H, Leach J E.2015. Rice phenylalanine ammonialyase gene OsPAL4 is associated with broad spectrum disease resistance. Plant Mol Biol, 87(3): 273-286.
[27]	Wang H H, Meng J, Peng X X, Tang X K, Zhou P L, Xiang J H, Deng X B.2015. Rice WRKY4 acts as a transcriptional activator mediating defense responses toward Rhizoctonia solani, the causing agent of rice sheath blight. Plant Mol Biol, 89: 157-171.
[28]	Wang R, Lu L X, Pan X B, Hu Z L, Ling F, Yan Y, Liu Y M, Lin Y J.2015. Functional analysis of OsPGIP1 in rice sheath blight resistance. Plant Mol Biol, 87: 181-191.
[29]	Wang Y, Pinson S R M, Fjellstrom R G, Tabien R E.2012. Phenotypic gain from introgression of two QTL, qsheath blight9-2 and qsheath blight12-1, for rice sheath blight resistance. Mol Breeding, 30(1): 293-303.
[30]	Wen Z H, Zeng Y X, Ji Z J, Yang C D.2015. Mapping quantitative trait loci for sheath blight disease resistance in Yangdao 4 rice.Genet Mol Res, 14(1): 1636-1649.
[31]	Xu Q, Yuan X P, Yu H Y, Wang Y P, Tang S X, Wei X H.2011. Mapping quantitative trait loci for sheath blight resistance in rice using double haploid population.Plant Breeding, 130(3): 404-406.
[32]	Xue X, Cao Z X, Zhang X T, Wang Y, Zhang Y F, Chen Z X, Pan X B, Zuo S M.2016. Overexpression of OsOSM1 enhances resistance to rice sheath blight. Plant Dis, 100(8): 1634-1642.
[33]	Yadav S, Anuradha G, Kumar R R, Vemireddy L R, Sudhakar R, Donempudi K, Venkata D, Jabeen F, Narasimhan Y K, Marathi B, Siddiq E A.2015. Identification of QTLs and possible candidate genes conferring sheath blight resistance in rice (Oryza sativa L.). Springer Plus, 4: 175.
[34]	Yuan D P, Zhang C, Wang Z Y, Zhu X F, Xuan Y H.2018. RAVL1 activates brassinosteroids and ethylene signaling to modulate response to sheath blight disease in rice. Phytopathology, 108(9): 1104-1113.
[35]	Zeng Y X, Ji Z J, Ma L Y, Li X M, Yang C D.2011. Advances in mapping loci conferring resistance to rice sheath blight and mining Rhizoctonia solani resistant resources. Rice Sci, 18(1): 56-66.
[36]	Zeng Y X, Wen Z H, Ma L Y, Ji Z J, Li X M, Yang C D.2013. Development of 1047 insertion-deletion markers for rice genetic studies and breeding.Genet Mol Res, 12(4): 5226-5235.
[37]	Zeng Y X, Ji Z J, Yang C D.2015a. The way to a more precise sheath blight resistance QTL in rice.Euphytica, 203(1): 33-45.
[38]	Zeng Y X, Xia L Z, Wen Z H, Ji Z J, Zeng D L, Qian Q, Yang C D.2015b. Mapping resistant QTLs for rice sheath blight disease with a doubled haploid population.J Integr Agric, 14(5): 801-810.
[39]	Zeng Y X, Ji Z J, Wen Z H, Liang Y, Yang C D.2016. Combination of eight alleles at four quantitative trait loci determines grain length in rice.PLoS One, 11(3): e0150832.
[40]	Zeng Y X, Shi J S, Ji Z J, Wen Z H, Liang Y, Yang C D.2017. Genotype by environment interaction: The greatest obstacle in precise determination of rice sheath blight resistance in the field.Plant Dis, 101: 1795-1801.
[41]	Zeng Y X, Chen Y, Ji Z J, Liang Y, Yang C D.2019. Twenty-four alleles at twelve quantitative trait loci act additively to control tiller angle in cultivated rice.Plant Growth Regul, 88(2): 195-203.
[42]	Zhang Q X, Zhang Y, He L L, Chen X J, Tong Y H, Ji Z L.2018. Identification of strain 7-5, antagonistic to rice sheath blight, and preliminary study of its biocontrol mechanism.Chin J Rice Sci, 32(3): 277-284. (in Chinese with English abstract)
[43]	Zou J H, Pan X B, Chen Z X, Xu J Y, Lu J F, Zhai W X, Zhu L H.2000. Mapping quantitative trait loci controlling sheath blight resistance in two rice cultivars (Oryza sativa L.). Theor Appl Genet, 101(4): 569-573.
[44]	Zuo S M, Zhang L, Wang H, Yin Y J, Zhang Y F, Chen Z X, Ma Y Y, Pan X B.2008. Prospect of the QTL qSB-9Tq utilized in molecular breeding program of japonica rice against sheath blight. J Genet Genom, 35(8): 499-505.
[45]	Zuo S M, Yin Y J, Pan C H, Chen Z X, Zhang Y F, Gu S L, Zhu L H, Pan X B.2013. Fine mapping of qSB-11LE, the QTL that confers partial resistance to rice sheath blight. Theor Appl Genet, 126(5): 1257-1272.
[46]	Zuo S M, Zhu Y J, Yin Y J, Wang H, Zhang Y F, Chen Z X, Gu S L, Pan X B.2014a. Comparison and confirmation of quantitative trait loci conferring partial resistance to rice sheath blight on chromosome 9.Plant Dis, 98(7): 957-964.
[47]	Zuo S M, Zhang Y F, Yin Y J, Li G Z, Zhang G W, Wang H, Chen Z X, Pan X B.2014b. Fine-mapping of qSB-9TQ, a gene conferring major quantitative resistance to rice sheath blight. Mol Breeding, 34(4): 2191-2203.

Environment	Trait	Trait
Environment	Trait	ADR	MDR	ALL
Jun-18	MDR	0.98**
	ALL	0.91**	0.89**
	MLL	0.86**	0.86**	0.95**
May-18	MDR	0.93**
	ALL	0.91**	0.86**
	MLL	0.79**	0.84**	0.90**
May-17	MDR	0.97**
	ALL	0.92**	0.87**
	MLL	0.86**	0.87**	0.95**
May-16	MDR	0.94**
	ALL	0.90**	0.85**
	MLL	0.80**	0.83**	0.90**
May-15	MDR	0.92**
	ALL	0.93**	0.86**
	MLL	0.84**	0.90**	0.93**
May-13	MDR	0.91**
	ALL	0.91**	0.83**
	MLL	0.79**	0.89**	0.89**

Environment	Trait	Trait
Environment	Trait	ADR	MDR	ALL
Jun-18	MDR	0.98**
	ALL	0.91**	0.89**
	MLL	0.86**	0.86**	0.95**
May-18	MDR	0.93**
	ALL	0.91**	0.86**
	MLL	0.79**	0.84**	0.90**
May-17	MDR	0.97**
	ALL	0.92**	0.87**
	MLL	0.86**	0.87**	0.95**
May-16	MDR	0.94**
	ALL	0.90**	0.85**
	MLL	0.80**	0.83**	0.90**
May-15	MDR	0.92**
	ALL	0.93**	0.86**
	MLL	0.84**	0.90**	0.93**
May-13	MDR	0.91**
	ALL	0.91**	0.83**
	MLL	0.79**	0.89**	0.89**

Trait for sheath blight resistance	Year/mapping population	QTL	Chromosome	LOD	Marker interval		Nearest marker	R²(%)	Additive effect ^a
Average disease rating	June 2018/F₁₅	qDR2.1	2	2.9	D223	-D225	D223	7.9	0.47
		qDR3.3	3	2.1	D328B	-RM5813	D331B	3.2	0.33
		qDR7.1	7	2.9	D709	-D715	D709	7.2	0.48
		qDR9.2	9	3	D943	-D948	D947	5.1	0.4
		qDR11.2	11	7.5	D1113	-RM3701	D1113	11.2	-0.75
		qDR12.3	12	2.5	D1246	-D1250	D1246	4.5	0.39
	May 2018/F₁₅	qDR1.3	1	2	D142C	-D144A	D144A	2.9	-0.3
		qDR2.1	2	2.7	D223	-D225	D225	6.2	0.38
		qDR7.1	7	3.8	D709	-D715	D709	8.9	0.49
		qDR11.2	11	2	D1113	-RM3701	RM3701	4	-0.37
		qDR12.1	12	2	D1211	-D1220	D1211	3.7	0.31
	May 2017/F₁₃	qDR1.1	1	2.9	D101D	-D105C	D105C	7.5	-0.49
		qDR2.1	2	5	D223	-D225	D223	6.8	0.53
		qDR8.2	8	2.8	RM8264	-D849	RM8264	4.6	-0.41
		qDR9.2	9	7.1	D948	-D949	D949	8.2	0.58
		qDR11.2	11	4.7	D1113	-RM3701	D1113	8.9	-0.54
		qDR12.2	12	5.1	D1239	-D1246	D1246	8.6	0.54
	May 2016/F₁₁	qDR1.2	1	2.6	D130B	-D134B	D130B	5.8	0.36
		qDR3.2	3	2.2	D325A	-D328B	D327B	4.1	0.31
		qDR4.1	4	1.9	D456	-D457B	D456	4.1	0.29
		qDR5.1	5	2.1	D546	-D553	D550	3	-0.28
		qDR9.2	9	6.5	D948	-D949	D949	10.8	0.51
		qDR12.2	12	3.6	D1220	-D1239	D1239	7.4	0.4
	May 2015/F₉	qDR1.1	1	2.6	D101D	-D105C	D101D	5.2	-0.4
		qDR2.2	2	2.6	RM425	-RM5607	RM5607	4.1	0.38
		qDR3.1	3	1.6	GL31C	-RM232	D309	2.1	-0.29
		qDR9.2	9	4.1	D948	-D949	D949	6.3	0.45
		qDR11.1	11	2.3	D1106	-D1113	RM26155	3.8	-0.35
		qDR12.4	12	2.6	D1252	-D1260	D1260	6.4	0.41
	May 2013/F₆	qDR3.4	3	2.4	D336B	-GL32G	GL32G	5.1	0.36
		qDR9.1	9	2.2	RM409	-D932	RM409	5.8	0.38
		qDR12.4	12	3	D1252	-D1260	D1252	8.4	0.47
Maximum disease rating	June 2018/F₁₅	qDR2.1	2	3.5	D223	-D225	D223	7.9	0.53
		qDR3.3	3	2.1	D328B	-RM5813	D331B	3.3	0.36
		qDR7.1	7	3.1	D709	-D715	D709	7.7	0.53
		qDR9.2	9	3.1	D943	-D947	D947	6.4	0.47
		qDR11.2	11	5.8	D1113	-RM3701	RM3701	9.7	-0.71
		qDR12.3	12	2.5	D1246	-D1250	D1250	5	0.43
	May 2018/F₁₅	qDR1.1	1	1.9	D101D	-RM1	D105C	3.3	-0.29
		qDR2.1	2	2.4	D223	-D225	D225	5.7	0.38
		qDR7.1	7	2.1	RM427	-D709	D709	5.1	0.36
		qDR11.1	11	1.5	RM26155	-D1113	D1113	4.9	-0.37
	May 2017/F₁₃	qDR1.1	1	2.1	D101D	-D105C	D105C	7.5	-0.46
		qDR2.1	2	2.6	D223	-D225	D225	3.4	0.4
		qDR9.2	9	5.8	D948	-D949	D949	7.6	0.52
		qDR10.1	10	2.8	RM271	-D1047	D1042	3.7	-0.36
		qDR11.2	11	4.2	D1113	-RM3701	D1113	8.6	-0.53
		qDR12.2	12	5.9	D1239	-D1246	D1246	9.3	0.59
	May 2016/F₁₁	qDR1.2	1	2.5	D130B	-D134B	D130B	6.6	0.46
		qDR4.1	4	1.8	D456	-D457B	D456	4.4	0.34
		qDR5.1	5	3.5	D546	-D550	D550	5.2	-0.46
		qDR8.1	8	1.7	D802	-RM8018	D804	3.6	0.3
		qDR9.2	9	5.1	D948	-D949	D949	9.2	0.54
		qDR12.2	12	1.6	D1220	-D1239	D1239	4.2	0.33
	May 2015/F₉	qDR1.1	1	2.5	D101D	-D105C	D101D	6.7	-0.59
		qDR2.2	2	2.9	RM5607	-D238A	RM5607	5	0.54
		qDR3.1	3	1.8	GL31C	-RM232	D309	2.5	-0.42
		qDR9.2	9	4.7	D948	-D949	D949	6.8	0.65
		qDR11.1	11	2.5	D1106	-D1113	RM26155	3.6	-0.49
		qDR12.4	12	3	D1252	-1260	D1260	6.5	0.57
	May 2013/F₆	qDR3.4	3	2.5	D336B	-GL32G	GL32G	5.4	0.47
		qDR9.1	9	2.2	D927	-RM409	RM409	6	0.49
		qDR12.2	12	2.9	D1220	-D1246	D1239	5.7	0.49
Trait for sheath blight resistance	Year/Mapping population	QTL	Chromosome	LOD	Marker interval		Nearest marker	R²(%) ^a	Additive effect ^b
Average lesion length	June 2018/F₁₅	qLL2.1	2	3.2	D223	-D225	D223	6.4	2.4
		qLL3.2	3	3.3	D311	-RM282	D311	6.5	-2.81
		qLL3.5	3	2.3	D331B	-RM5813	D331B	4.3	1.92
		qLL7.1	7	3.7	D709	-D715	D709	8.4	2.77
		qLL9.4	9	6	D948	-D949	D949	8.2	3.11
		qLL11.1	11	5.5	RM26155	-D1113	D1113	9.6	-3.51
	May 2018/F₁₅	qLL2.1	2	2.6	D223	-D225	D225	4.3	2.71
		qLL3.2	3	2.4	RM282	-D313B	RM282	2.5	-2.74
		qLL7.1	7	4	D709	-D715	D709	8.4	3.89
		qLL9.4	9	2	D948	-D949	D949	4.7	2.46
		qLL11.1	11	2.7	RM26155	-D1113	D1113	5.2	-3.44
		qLL12.1	12	2.3	D1211	-D1220	D1211	4	2.59
	May 2017/F₁₃	qLL3.3	3	2.7	D315	-D325A	D315	7.1	-3.78
		qLL7.1	7	1.9	D709	-D730	D715	2.7	2.46
		qLL9.4	9	4.3	D948	-D949	D949	6.6	3.72
		qLL11.2	11	4.8	D1113	-RM3701	RM3701	11.1	-4.7
	May 2016/F₁₁	qLL1.3	1	3.9	D130B	-D134B	D130B	8.2	4.33
		qLL2.2	2	1.6	RM3688	-RM3355	D229A	2.3	2.48
		qLL5.2	5	4.4	D546	-D553	D550	5.3	-3.99
		qLL9.4	9	6.2	D948	-D949	D949	10.1	4.73
		qLL11.3	11	2.5	D1133	-D1142	D1133	3.6	-3.58
	May 2015/F₉	qLL1.1	1	4.3	D101D	-D105C	D101D	8.1	-4.15
		qLL2.1	2	2.2	D223	-D225	D225	2.7	2.69
		qLL3.1	3	2.7	D307	-D309	GL31C	3	-2.84
		qLL4.1	4	3	RM1113	-D468	D467	4.6	2.72
		qLL5.1	5	2.3	D531	-RM430	D535	1.8	-2.38
		qLL7.1	7	1.9	RM427	-D715	D709	3.6	2.52
		qLL8.1	8	1.8	D802	-RM8018	D804	4.1	2.12
		qLL9.4	9	2.8	D948	-D949	D949	5.8	2.74
		qLL11.1	11	4.2	D1106	-D1113	RM26155	6.2	-3.68
	May 2013/F₆	qLL9.3	9	2.4	D943	-D947	D947	7.7	3.26
	May 2013/F₆	qLL10.1	10	1.6	D1003	-D1009	D1003	3.6	2.28
Maximum lesion length	June 2018/F₁₅	qLL1.2	1	3.4	D122E	-D128A	D124	5.7	2.36
		qLL3.2	3	2.5	D311	-RM282	D311	5.4	-2.61
		qLL7.1	7	4.2	D709	-D715	D709	8.6	3.08
		qLL9.1	9	1.8	D902	-D915	D902	3.3	2.06
		qLL9.4	9	4.7	D948	-D949	D949	7.2	2.9
		qLL11.1	11	6.3	RM26155	-D1113	D1113	9.9	-4.27
	May 2018/F₁₅	qLL2.1	2	2	D223	-D225	D223	4.5	3.03
		qLL3.2	3	1.9	D311	-D313B	RM282	2.9	-2.81
		qLL7.1	7	2	RM427	-D715	D709	3.9	3.06
		qLL9.4	9	3.4	D947	-D948	D948	6.4	3.79
		qLL11.3	11	1.8	D1133	-D1142	D1133	3.4	-3.07
	May 2017/F₁₃	qLL3.3	3	1.8	D315	-D325A	D315	5.8	-3.34
		qLL9.4	9	4.2	D948	-D949	D949	6.7	3.84
		qLL11.2	11	3.7	D1113	-RM3701	RM3701	8.9	-4.24
	May 2016/F₁₁	qLL2.2	2	3.2	RM3688	-RM3355	D229A	3.7	4.11
		qLL3.4	3	2.2	D325A	-D328B	D327B	2.7	3.42
		qLL5.2	5	3.9	D546	-D553	D550	5.5	-4.79
		qLL9.4	9	4.5	D948	-D949	D949	6	4.73
		qLL10.2	10	4	D1022	-D1029	D1029	8.1	5.7
		qLL10.3	10	2.7	D1042	-D1047	D1047	11.2	-5.55
		qLL11.3	11	3.2	D1133	-D1142	D1142	5.3	-4.62
	May 2015/F₉	qLL1.1	1	3	D101D	-D105C	D101D	6.4	-5.04
		qLL1.4	1	2.6	D142C	-D144A	D144A	2.1	-3.89
		qLL2.3	2	1.9	D236	-RM5607	RM425	2.8	3.75
		qLL3.1	3	3.7	GL31C	-RM232	D309	4.2	-4.84
		qLL8.1	8	2.8	D802	-RM8018	D804	5.4	4.05
		qLL9.3	9	1.6	D934	-D937	RM7424	0.9	-3.11
		qLL9.4	9	5.3	D948	-D949	D949	7.6	5.68
		qLL11.1	11	1.9	D1106	-D1113	RM26155	3.7	-3.75
		qLL12.1	12	2.1	D1211	-D1220	D1211	4.1	3.98
	May 2013/F₆	qLL3.6	3	1.8	GW32F	-GL32G	D336B	4.2	3.14
		qLL9.2	9	1.8	D927	-D932	RM409	5.6	3.44
		qLL12.2	12	1.8	D1220	-D1246	D1239	4.2	3.15

Trait for sheath blight resistance	Year/mapping population	QTL	Chromosome	LOD	Marker interval		Nearest marker	R²(%)	Additive effect ^a
Average disease rating	June 2018/F₁₅	qDR2.1	2	2.9	D223	-D225	D223	7.9	0.47
		qDR3.3	3	2.1	D328B	-RM5813	D331B	3.2	0.33
		qDR7.1	7	2.9	D709	-D715	D709	7.2	0.48
		qDR9.2	9	3	D943	-D948	D947	5.1	0.4
		qDR11.2	11	7.5	D1113	-RM3701	D1113	11.2	-0.75
		qDR12.3	12	2.5	D1246	-D1250	D1246	4.5	0.39
	May 2018/F₁₅	qDR1.3	1	2	D142C	-D144A	D144A	2.9	-0.3
		qDR2.1	2	2.7	D223	-D225	D225	6.2	0.38
		qDR7.1	7	3.8	D709	-D715	D709	8.9	0.49
		qDR11.2	11	2	D1113	-RM3701	RM3701	4	-0.37
		qDR12.1	12	2	D1211	-D1220	D1211	3.7	0.31
	May 2017/F₁₃	qDR1.1	1	2.9	D101D	-D105C	D105C	7.5	-0.49
		qDR2.1	2	5	D223	-D225	D223	6.8	0.53
		qDR8.2	8	2.8	RM8264	-D849	RM8264	4.6	-0.41
		qDR9.2	9	7.1	D948	-D949	D949	8.2	0.58
		qDR11.2	11	4.7	D1113	-RM3701	D1113	8.9	-0.54
		qDR12.2	12	5.1	D1239	-D1246	D1246	8.6	0.54
	May 2016/F₁₁	qDR1.2	1	2.6	D130B	-D134B	D130B	5.8	0.36
		qDR3.2	3	2.2	D325A	-D328B	D327B	4.1	0.31
		qDR4.1	4	1.9	D456	-D457B	D456	4.1	0.29
		qDR5.1	5	2.1	D546	-D553	D550	3	-0.28
		qDR9.2	9	6.5	D948	-D949	D949	10.8	0.51
		qDR12.2	12	3.6	D1220	-D1239	D1239	7.4	0.4
	May 2015/F₉	qDR1.1	1	2.6	D101D	-D105C	D101D	5.2	-0.4
		qDR2.2	2	2.6	RM425	-RM5607	RM5607	4.1	0.38
		qDR3.1	3	1.6	GL31C	-RM232	D309	2.1	-0.29
		qDR9.2	9	4.1	D948	-D949	D949	6.3	0.45
		qDR11.1	11	2.3	D1106	-D1113	RM26155	3.8	-0.35
		qDR12.4	12	2.6	D1252	-D1260	D1260	6.4	0.41
	May 2013/F₆	qDR3.4	3	2.4	D336B	-GL32G	GL32G	5.1	0.36
		qDR9.1	9	2.2	RM409	-D932	RM409	5.8	0.38
		qDR12.4	12	3	D1252	-D1260	D1252	8.4	0.47
Maximum disease rating	June 2018/F₁₅	qDR2.1	2	3.5	D223	-D225	D223	7.9	0.53
		qDR3.3	3	2.1	D328B	-RM5813	D331B	3.3	0.36
		qDR7.1	7	3.1	D709	-D715	D709	7.7	0.53
		qDR9.2	9	3.1	D943	-D947	D947	6.4	0.47
		qDR11.2	11	5.8	D1113	-RM3701	RM3701	9.7	-0.71
		qDR12.3	12	2.5	D1246	-D1250	D1250	5	0.43
	May 2018/F₁₅	qDR1.1	1	1.9	D101D	-RM1	D105C	3.3	-0.29
		qDR2.1	2	2.4	D223	-D225	D225	5.7	0.38
		qDR7.1	7	2.1	RM427	-D709	D709	5.1	0.36
		qDR11.1	11	1.5	RM26155	-D1113	D1113	4.9	-0.37
	May 2017/F₁₃	qDR1.1	1	2.1	D101D	-D105C	D105C	7.5	-0.46
		qDR2.1	2	2.6	D223	-D225	D225	3.4	0.4
		qDR9.2	9	5.8	D948	-D949	D949	7.6	0.52
		qDR10.1	10	2.8	RM271	-D1047	D1042	3.7	-0.36
		qDR11.2	11	4.2	D1113	-RM3701	D1113	8.6	-0.53
		qDR12.2	12	5.9	D1239	-D1246	D1246	9.3	0.59
	May 2016/F₁₁	qDR1.2	1	2.5	D130B	-D134B	D130B	6.6	0.46
		qDR4.1	4	1.8	D456	-D457B	D456	4.4	0.34
		qDR5.1	5	3.5	D546	-D550	D550	5.2	-0.46
		qDR8.1	8	1.7	D802	-RM8018	D804	3.6	0.3
		qDR9.2	9	5.1	D948	-D949	D949	9.2	0.54
		qDR12.2	12	1.6	D1220	-D1239	D1239	4.2	0.33
	May 2015/F₉	qDR1.1	1	2.5	D101D	-D105C	D101D	6.7	-0.59
		qDR2.2	2	2.9	RM5607	-D238A	RM5607	5	0.54
		qDR3.1	3	1.8	GL31C	-RM232	D309	2.5	-0.42
		qDR9.2	9	4.7	D948	-D949	D949	6.8	0.65
		qDR11.1	11	2.5	D1106	-D1113	RM26155	3.6	-0.49
		qDR12.4	12	3	D1252	-1260	D1260	6.5	0.57
	May 2013/F₆	qDR3.4	3	2.5	D336B	-GL32G	GL32G	5.4	0.47
		qDR9.1	9	2.2	D927	-RM409	RM409	6	0.49
		qDR12.2	12	2.9	D1220	-D1246	D1239	5.7	0.49
Trait for sheath blight resistance	Year/Mapping population	QTL	Chromosome	LOD	Marker interval		Nearest marker	R²(%) ^a	Additive effect ^b
Average lesion length	June 2018/F₁₅	qLL2.1	2	3.2	D223	-D225	D223	6.4	2.4
		qLL3.2	3	3.3	D311	-RM282	D311	6.5	-2.81
		qLL3.5	3	2.3	D331B	-RM5813	D331B	4.3	1.92
		qLL7.1	7	3.7	D709	-D715	D709	8.4	2.77
		qLL9.4	9	6	D948	-D949	D949	8.2	3.11
		qLL11.1	11	5.5	RM26155	-D1113	D1113	9.6	-3.51
	May 2018/F₁₅	qLL2.1	2	2.6	D223	-D225	D225	4.3	2.71
		qLL3.2	3	2.4	RM282	-D313B	RM282	2.5	-2.74
		qLL7.1	7	4	D709	-D715	D709	8.4	3.89
		qLL9.4	9	2	D948	-D949	D949	4.7	2.46
		qLL11.1	11	2.7	RM26155	-D1113	D1113	5.2	-3.44
		qLL12.1	12	2.3	D1211	-D1220	D1211	4	2.59
	May 2017/F₁₃	qLL3.3	3	2.7	D315	-D325A	D315	7.1	-3.78
		qLL7.1	7	1.9	D709	-D730	D715	2.7	2.46
		qLL9.4	9	4.3	D948	-D949	D949	6.6	3.72
		qLL11.2	11	4.8	D1113	-RM3701	RM3701	11.1	-4.7
	May 2016/F₁₁	qLL1.3	1	3.9	D130B	-D134B	D130B	8.2	4.33
		qLL2.2	2	1.6	RM3688	-RM3355	D229A	2.3	2.48
		qLL5.2	5	4.4	D546	-D553	D550	5.3	-3.99
		qLL9.4	9	6.2	D948	-D949	D949	10.1	4.73
		qLL11.3	11	2.5	D1133	-D1142	D1133	3.6	-3.58
	May 2015/F₉	qLL1.1	1	4.3	D101D	-D105C	D101D	8.1	-4.15
		qLL2.1	2	2.2	D223	-D225	D225	2.7	2.69
		qLL3.1	3	2.7	D307	-D309	GL31C	3	-2.84
		qLL4.1	4	3	RM1113	-D468	D467	4.6	2.72
		qLL5.1	5	2.3	D531	-RM430	D535	1.8	-2.38
		qLL7.1	7	1.9	RM427	-D715	D709	3.6	2.52
		qLL8.1	8	1.8	D802	-RM8018	D804	4.1	2.12
		qLL9.4	9	2.8	D948	-D949	D949	5.8	2.74
		qLL11.1	11	4.2	D1106	-D1113	RM26155	6.2	-3.68
	May 2013/F₆	qLL9.3	9	2.4	D943	-D947	D947	7.7	3.26
	May 2013/F₆	qLL10.1	10	1.6	D1003	-D1009	D1003	3.6	2.28
Maximum lesion length	June 2018/F₁₅	qLL1.2	1	3.4	D122E	-D128A	D124	5.7	2.36
		qLL3.2	3	2.5	D311	-RM282	D311	5.4	-2.61
		qLL7.1	7	4.2	D709	-D715	D709	8.6	3.08
		qLL9.1	9	1.8	D902	-D915	D902	3.3	2.06
		qLL9.4	9	4.7	D948	-D949	D949	7.2	2.9
		qLL11.1	11	6.3	RM26155	-D1113	D1113	9.9	-4.27
	May 2018/F₁₅	qLL2.1	2	2	D223	-D225	D223	4.5	3.03
		qLL3.2	3	1.9	D311	-D313B	RM282	2.9	-2.81
		qLL7.1	7	2	RM427	-D715	D709	3.9	3.06
		qLL9.4	9	3.4	D947	-D948	D948	6.4	3.79
		qLL11.3	11	1.8	D1133	-D1142	D1133	3.4	-3.07
	May 2017/F₁₃	qLL3.3	3	1.8	D315	-D325A	D315	5.8	-3.34
		qLL9.4	9	4.2	D948	-D949	D949	6.7	3.84
		qLL11.2	11	3.7	D1113	-RM3701	RM3701	8.9	-4.24
	May 2016/F₁₁	qLL2.2	2	3.2	RM3688	-RM3355	D229A	3.7	4.11
		qLL3.4	3	2.2	D325A	-D328B	D327B	2.7	3.42
		qLL5.2	5	3.9	D546	-D553	D550	5.5	-4.79
		qLL9.4	9	4.5	D948	-D949	D949	6	4.73
		qLL10.2	10	4	D1022	-D1029	D1029	8.1	5.7
		qLL10.3	10	2.7	D1042	-D1047	D1047	11.2	-5.55
		qLL11.3	11	3.2	D1133	-D1142	D1142	5.3	-4.62
	May 2015/F₉	qLL1.1	1	3	D101D	-D105C	D101D	6.4	-5.04
		qLL1.4	1	2.6	D142C	-D144A	D144A	2.1	-3.89
		qLL2.3	2	1.9	D236	-RM5607	RM425	2.8	3.75
		qLL3.1	3	3.7	GL31C	-RM232	D309	4.2	-4.84
		qLL8.1	8	2.8	D802	-RM8018	D804	5.4	4.05
		qLL9.3	9	1.6	D934	-D937	RM7424	0.9	-3.11
		qLL9.4	9	5.3	D948	-D949	D949	7.6	5.68
		qLL11.1	11	1.9	D1106	-D1113	RM26155	3.7	-3.75
		qLL12.1	12	2.1	D1211	-D1220	D1211	4.1	3.98
	May 2013/F₆	qLL3.6	3	1.8	GW32F	-GL32G	D336B	4.2	3.14
		qLL9.2	9	1.8	D927	-D932	RM409	5.6	3.44
		qLL12.2	12	1.8	D1220	-D1246	D1239	4.2	3.15

QTL	Marker interval	Physical position (Mb) ^a	Resistance allele	Reference
qSBR1.1	D101D-RM1	1.1-4.6	Lemont	Present study
qSB-1	RG140-RZ382	5.0-9.7	Teqing	Pinson et al, 2005
qSBR2.1	D216-D225	11.4-19.6	Yangdao 4	Present study
Rh-2	G243-RG171	11.77-18.26	Jasmine 85	Pan et al, 1999
qSB-2	G243-RG171	11.70-18.27	Jasmine 85	Zou et al, 2000
qSBR-2	G243A-RG171	11.77-18.26	ZYQ8	Kunihiro et al, 2002
qShB2-1	RM424-RM5427	11.40-22.38	Jasmine 85	Liu et al, 2009
qSB2.1-TX	RM424-RM341	11.4-20.2	Jasmine 85	Liu et al, 2013
qSBR7.1	RM427-D730	2.7-14.5	Yangdao 4	Present study
Rh-7	RG30-RG477	6.8-12.8	Jasmine 85	Pan et al, 1999
qSB-7	RG30-RG477	6.8-12.8	Jasmine 85	Zou et al, 2000
QRh7	RM180	5.7	TaromMolaii	Li et al, 2009
qSB7-AR, qSB7-LA	RM5711-RM2	3.1-16.0	Jasmine 85	Liu et al, 2013
qSBR9.3	D948-D949	22.5-22.9	Yangdao 4	Present study
qSB-9	RM201-RM205	20.2-22.7	Teqing	Tan et al, 2005
qSB-9	RZ404	22.2	Teqing	Pinson et al, 2005
qShB9-2	RM215-RM245	21.2-22.3	Jasmine 85	Liu et al, 2009
qsbr_9.1	RM24708-RM3823	21.1-22.1	MCR10277	Nelson et al, 2012
qSB9-AR, qSB9-TX, qSB9-LA	RM215-RM245	21.2-22.3	Jasmine 85	Liu et al, 2013
qSB-9^TQ	CY85-Y86	21.37-21.52	Teqing	Zuo et al, 2014b
qHZbDR9	RM278-RM3919	19.3-19.6	CJ06	Zeng et al, 2015b
qshb9.3	RM24260-RM3744	14.2-22.7	-	Yadav et al, 2015
qSBR11.1	D1106-D1113	2.3-5.6	Lemont	Present study
qSB-11	RG118-G44	4.4-10.0	Lemont	Zou et al, 2000
qSB-11	RM167-Y529	4.06	Lemont	Tan et al, 2005
qSBR11-2	RM3428-RM209	4.0-20.0	-	Channamallikarjuna et al, 2010
qSB11.1-TX	RM7203-RM536	1.0-9.0	Lemont	Liu et al, 2013
qShB11	RM332-RM21	2.8-21.4	Bengal	Eizenga et al, 2013
qSB-11^LE	Z22-27C-Z23-33C	4.77-4.85	Lemont	Zuo et al, 2013
qSBD-11-1, qSBDL-11-1, qSBDPL-11-1	D1103-RM26155	0.8-3.7	Lemont	Wen et al, 2015
qSBD-11-2, qSBDL-11-2, qSBDPL-11-2	RM26155-D1113	3.7-5.6	Lemont	Wen et al, 2015
qSBR11.2	D1113-RM3701	5.6-8.1	Lemont	Present study
qShB11	RM332-RM21	2.8-21.4	Bengal	Eizenga et al, 2013
qSBR12.2	D1220-D1246	6.7-18.0	Yangdao 4	Present study
qSB12-1	RM6998-RM277	4.7-22.4	Teqing	Wang et al, 2012
qShB12-mc	RM5746-RM277	5.1-18.4	Bengal	Eizenga et al, 2013
qSBD-12-1	D1239-D1246	15.4-18.1	Yangdao 4	Wen et al, 2015