Scientia Agricultura Sinica ›› 2024, Vol. 57 ›› Issue (7): 1255-1266.doi: 10.3864/j.issn.0578-1752.2024.07.004

• SPECIAL FOCUS: SEED GERMINATION AND PRE-HARVEST SPROUTING • Previous Articles     Next Articles

Utilization Efficiency of Improving the Resistance for Pre-Harvest Sprouting by Synthetic Hexaploid Wheat and Chinese Wheat Landrace

LIU ZeHou1(), WANG Qin1, YE MeiJin2, WAN HongShen1, YANG Ning1, YANG ManYu1, YANG WuYun1(), LI Jun1()   

  1. 1 Crop Research Institute, Sichuan Academy of Agricultural Sciences/Key Laboratory of Wheat Biology and Genetic Improvement in Southwestern China, Ministry of Agriculture and Rural Affairs/Environmentally Friendly Crop Germplasm Innovation and Genetic Improvement Key Laboratory of Sichuan Province, Chengdu 610066
    2 College of Chemistry and Life Sciences, Chengdu Normal University, Wenjiang 611130, Sichuan
  • Received:2022-11-09 Accepted:2022-12-23 Online:2024-04-01 Published:2024-04-09
  • Contact: YANG WuYun, LI Jun

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Abstract:

【Objective】Pre-harvest sprouting (PHS) is a serious limiting factor for wheat (Triticum aestivum L.) grain yield and end-use quality. Synthetic hexaploid wheats (SHW) and wheat landraces (WL) are important germplasm resources for improving PHS resistance in wheat. The objective of this study is to utilize PHS-resistant loci from SHW and WL for breeding PHS-resistant elite materials, which will provide a theoretical basis for improving PHS resistance of wheat cultivars.【Method】In this study, SYN792 (a synthetic hexaploid wheat from CIMMYT) and Fulingxuxumai (a Chinese wheat landrace) were used as female parents to cross and backcross with Chuanmai 45 (a sensitive variety to PHS), respectively. Two BC1F7 populations including 1 796 lines were established. Seed germination index (GI) and seed germination rate of each spike (SGR) in different environments were used to evaluate PHS resistance. Two germination temperature of 25 ℃ (18GI) and 32 ℃ (19GI) were set to examine seed germinability in 2018 and 2019. 1 796 BC1F7 lines were evaluated preliminarily by SGR phenotype and molecular markers detection in 2017, and the introgression lines with PHS-3D and PHS-A1 resistant loci and SGR less than 35% were screened. Introgression lines with PHS-3D and PHS-A1 resistant loci were used to analyze utilization efficiency of SHW and WL in PHS-resistance breeding by identifying PHS-resistance and yield related traits in 2018 and 2019.【Result】PHS resistance of 1 796 lines was evaluated preliminarily, and 537 lines with SGR value less than 35% were screened for further molecular marker detection. A total of 332 lines with PHS-3D and PHS-A1 were selected by SSR marker, and the frequency of WL introgression lines was significantly higher than that of SHW introgression lines. 332 introgression lines were used to analyze PHS-resistance and yield related traits in 2018 and 2019. There was a significant positive correlation between different PHS indexes in different years, but there was no significant difference in the values of 18GI, 18SGR and 19SGR between SHW and WL introgression lines. The average values of 18SGR, 19SGR and 18GI in SHW and WL introgression lines were lower than 23%. As far as GI value was concerned, there was obvious difference between different germination temperatures. At the germination temperature of 32 ℃, the mean 19GI value of SHW PHS-3D introgression lines was significantly lower than that of WL PHS-A1 introgression lines. Grain color was associated with PHS resistance in SHW introgression lines, and the red-grained SHW introgression lines had lower the mean GI and SGR values than the white-grained lines. Among 73 SHW introgression lines, 11 white-grained lines showed medium or higher resistance to PHS，and the GI values of 14 red-grained lines at different germination temperatures were lower than 35%. According to the data of agronomic traits in 2018 and 2019, thousand grain weight of SHW introgression lines was significantly higher than that of WL introgression lines, but the number of grains per spike was significantly lower than that of WL introgression lines. 23 elite introgression lines including seven SHW introgression lines and 16 WL introgression lines were selected. Two SHW white-grained introgression lines had better resistance to PHS, and the GI values of two red-grained introgression lines at different germination temperatures were lower than 25%.【Conclusion】It is feasible to transfer PHS-3D and PHS-A1 resistance loci to PHS from SHW and WL for improving PHS-resistance of modern wheat cultivars. In this study, the breeding efficiency of WL for PHS-resistance was better than that of SHW. However, the stability of PHS-resistance of SHW introgression lines was better than that of WL introgression lines. 23 SHW and WL elite introgression lines could be used as parents to improve the PHS-resistance and yield traits in wheat. In particular, the white-grained SHW introgression line No.5201 and the red-grained SHW introgression lines No.5497 and No.5505 were very valuable parents for wheat breeding of PHS resistance.

Key words: wheat, synthetic hexaploid wheat (SHW), wheat landraces, pre-harvest sprouting (PHS), yield related yield

Table 1

Selection frequency of resistance to PHS in two populations derived from SHW and WL"

反应型
Infection type		 人工合成小麦群体Synthetic hexaploid wheat population 地方品种群体Wheat landrace population
株系数No. of lines 占比Proportion (%) 株系数No. of lines 占比Proportion (%)
高抗HR 110 10.29 267 36.73
抗R 26 2.43 53 7.29
中抗MR 29 2.72 52 7.15
中感MS 38 3.55 64 8.80
感S 96 8.98 78 10.73
高感HS 770 72.03 213 29.30
合计Total 1069 100.00 727 100.00

Fig. 1

Detection of PHS resistant loci of PHS-3D (Xgwm341) and PHS-A1 (Xbarc170) in two populations P1: Synthetic hexaploid wheat SYN792; P2: Chuanmai 45; P3: Wheat landrace Fulingxuxumai"

Table 2

Correlation coefficient of PHS indexs of introgression lines in 2018 and 2019"

性状Traits 18SGR 19SGR 18GI
19SGR 0.476**
18GI 0.327** 0.244**
19GI 0.342** 0.257** 0.467**

Table 3

Statistical analysis of PHS indexs of introgression lines"

性状
Traits		 PHS-3D导入系PHS-3D introgression lines PHS-A1导入系PHS-A1 introgression lines
均值±标准差
Mean (%)±SD		 最小值
Min (%)		 最大值
Max (%)		 均值±标准差
Mean (%)±SD		 最小值
Min (%)		 最大值
Max (%)
18SGR 20.41±0.29 0.00 98.78 22.82±0.21 0.00 98.97
19SGR 20.65±0.28 0.00 96.04 18.28±0.22 0.00 99.60
18GI 18.88±0.15 1.70 76.32 15.51±0.12 0.33 56.10
19GI 44.67**±0.26 3.84 93.44 60.83**±0.24 1.74 96.32

Table 4

Differences of PHS resistance between red and white grain SHW introgression lines"

性状
Traits		 粒色
Grain colors		 PHS-3D导入系PHS-3D introgression lines
均值Mean (%) 标准差SD 标准误SE
18SGR W 27.50* 0.3526 0.0633
R 14.80* 0.2356 0.0373
19SGR W 39.46** 0.3231 0.0580
R 5.56** 0.1002 0.0158
18GI W 12.20 0.1860 0.0334
R 8.67 0.1082 0.0171
19GI W 52.38* 0.2803 0.0503
R 37.72* 0.2288 0.0362

Table 5

Frequency of red and white grain SHW introgression lines at different levels to PHS resistance"

反应型
Infection type		 红粒系Red-grains lines 白粒系White-grains lines
株系数No. of lines 占比Proportion (%) 株系数No. of lines 占比Proportion (%)
高抗HR 11 26.83 0 0.00
抗R 8 19.51 5 15.63
中抗MR 10 24.39 6 18.75
中感MS 5 12.20 8 25.00
感S 7 17.07 6 18.75
高感HS 0 0.00 7 21.87
合计Total 41 100.00 32 100.00

Table 6

Correlation coefficient between yield-related traits and PHS indexs"

性状 Traits 18SGR 19SGR 18GI 18GN 19GN 18TKW 19TKW 18PH 19PH 18TN
19SGR 0.476**
18GI 0.327** 0.244**
19GI 0.342** 0.257** 0.467**
18GN 0.253** 0.194** -0.118*
19GN 0.122* 0.191** -0.038 0.434**
18TKW 0.061 0.077 0.126* -0.265** -0.312**
19TKW -0.142 -0.075 0.111 -0.302** -0.202** 0.570**
18PH -0.187** -0.276** -0.151 -0.135* -0.210** 0.173** 0.093
19PH -0.171** -0.183** -0.167** -0.152** -0.149** 0.132* 0.101 0.722**
18TN -0.095 -0.065 -0.038 -0.189** -0.185** 0.004 -0.041 0.220** 0.23**
19TN -0.09 -0.031 -0.084 -0.213** -0.049 0.088 0.039 0.024 0.161** 0.081

Table 7

Statistical analysis of yield-related traits"

性状
Traits		 PHS-3D导入系PHS-3D introgression lines PHS-A1导入系PHS-A1 introgression lines
均值±标准差
Mean±SD		 最小值
Min		 最大值
Max		 均值±标准差
Mean±SD		 最小值
Min		 最大值
Max
18PH 113.7±15.47 88.00 151.50 111.02±14.06 54.00 145.50
19PH 110.22±14.43 85.67 149.00 110.44±12.11 59.67 143.67
18TN 4.42±0.96 3.00 7.00 4.28±0.97 2.00 8.00
19TN 2.74±0.69 1.00 4.00 2.82±0.75 1.30 6.80
18GN 31.04±9.85** 13.00 62.33 37.17±9.34** 14.88 66.86
19GN 32.60±8.24** 14.90 57.10 39.67±8.05** 19.80 61.40
18TKW 45.97±10.49** 16.50 66.30 38.92±7.06** 16.50 56.70
19TKW 59.16±7.66** 38.32 76.80 47.66±8.48** 22.30 68.20

Table 8

Statistical analysis of PHS resistance and yield-related traits in the elite introgression lines."

株系<BOLD>L</BOLD>ines 编号No. of lines GN TKW PH TN GI (%) SGR (%)
PHS-3D导入系
PHS-3D introgression lines		 5201 44.5 47.28 103.33 4.3 22.08 8.21
5203 47.1 47.43 100.33 4.0 30.59 19.46
5207 40.0 52.48 107.67 2.5 23.34 13.27
5212 48.9 53.31 101.67 2.0 28.21 10.33
5213 38.3 54.31 95.67 2.3 26.01 9.67
5497 38.7 52.84 105.33 2.9 10.73 2.80
5505 34.0 62.38 96.67 3.7 15.84 11.08
PHS-A1导入系PHS-A1 introgression lines 5224 37.3 44.93 97.33 3.0 27.99 17.35
5231 43.8 48.45 100.67 3.7 30.95 4.76
5234 44.2 44.41 95.33 3.0 21.69 8.90
5236 51.9 47.69 92.33 3.2 32.99 6.68
5237 41.7 52.57 75.67 3.5 34.16 1.86
5249 44.0 47.39 104.00 3.5 26.85 16.83
5259 49.0 43.04 88.00 2.9 33.66 5.51
5263 41.2 44.83 84.00 2.8 20.05 4.61
5269 51.5 41.40 105.33 3.3 19.69 1.77
5327 42.6 50.96 103.83 3.0 34.02 20.45
5354 47.5 47.41 101.00 3.8 33.95 18.97
5392 45.5 40.42 59.67 3.2 35.01 18.73
5395 40.4 46.29 93.00 3.1 32.32 12.04
5411 38.9 54.06 78.00 3.3 23.75 19.32
5425 48.0 52.10 103.67 2.7 34.74 14.23
5435 49.5 53.09 98.00 2.6 33.53 13.32
[1]
GROOS C, GAY G, PERRETANT M R, GERVAIS L, BERNARD M, DEDRYVER F, CHARMET G. Study of the relationship between preharvest sprouting and grain color by quantitative trait loci analysis in a white × red grain bread-wheat cross. Theoretical and Applied Genetics, 2002, 104(1): 39-47.

doi: 10.1007/s001220200004
[2]
VETCH J M, STOUGAARD R N, MARTIN J M, GIROUX M J. Review: Revealing the genetic mechanisms of pre-harvest sprouting in hexaploid wheat (Triticum aestivum L.). Plant Science, 2019, 281:180-185.

doi: 10.1016/j.plantsci.2019.01.004
[3]
SIMSEK S, OHM J B, LU H Y, RUGG M, BERZONSKY W, ALAMRI M S, MERGOUM M. Effect of pre-harvest sprouting on physicochemical changes of proteins in wheat. Journal of the Science of Food and Agriculture, 2014, 94(2): 205-212.

doi: 10.1002/jsfa.6229 pmid: 23674491
[4]
ALI A, CAO J J, JIANG H, CHANG C, ZHANG H P, SHEIKH S W, SHAH L, MA C X. Unraveling molecular and genetic studies of wheat (Triticum aestivum L.)resistance against factors causing pre-harvest sprouting. Agronomy, 2019, 9(3): 117.
[5]
XIAO S, ZHANG X Y, YAN C, LIN H. Germplasm improvement for preharvest sprouting resistance in Chinese white-grained wheat: An overview of the current strategy. Euphytica, 2002, 126: 35-38.

doi: 10.1023/A:1019679924173
[6]
HUANG Y W, DAI X R, LIU H W, YU S, MAI C Y, YU L Q, YU G J, YANG L, ZHOU Y, LI H J, ZHANG H J. Identification of effective alleles and haplotypes conferring pre-harvest sprouting resistance in winter wheat cultivars. BMC Plant Biology, 2022, 22(1): 326.
[7]
IMTIAZ M, OGBONNAYA F C, OMAN J, VAN GINKEL M V. Characterization of quantitative trait loci controlling genetic variation for preharvest sprouting in synthetic backcross-derived wheat lines. Genetics, 2008, 178(3): 1725-1736.

doi: 10.1534/genetics.107.084939 pmid: 18245824
[8]
刘莉, 王庆海, 陈国志. 小麦穗发芽研究进展. 作物杂志, 2013(4): 6-11.
LIU L, WANG Q H, CHEN G Z. Advances on resistance to pre-harvest sprouting in wheat. Crops, 2013(4): 6-11. (in Chinese)
[9]
ROY J K, PRASAD M, VARSHNEY R K, BALYAN H S, BLAKE T K, DHALIWAL H S, EDWARDS K J, GUPTA P K. Identification of a microsatellite on chromosomes 6B and a STS on 7D of bread wheat showing an association with preharvest sprouting tolerance. Theoretical and Applied Genetics, 1999, 99(1/2): 336-340.

doi: 10.1007/s001220051241
[10]
REHMAN ARIF M A, NEUMANN K, NAGEL M, KOBILJSKI B, LOHWASSER U, BÖRNER A. An association mapping analysis of dormancy and pre-harvest sprouting in wheat. Euphytica, 2012, 188(3): 409-417.

doi: 10.1007/s10681-012-0705-1
[11]
FLINTHAM J, ADLAM R E, BASSOI M, HOLDSWORTH M, GALE M. Mapping genes for resistance to sprouting damage in wheat. Euphytica, 2002, 126: 39-45.

doi: 10.1023/A:1019632008244
[12]
JAISWAL V, MIR R R, MOHAN A, BALYAN H S, GUPTA P K. Association mapping for pre-harvest sprouting tolerance in common wheat (Triticum aestivum L.). Euphytica, 2012, 188(1): 89-102.

doi: 10.1007/s10681-012-0713-1
[13]
KULWAL P L, SINGH R, BALYAN H S, GUPTA P K. Genetic basis of pre-harvest sprouting tolerance using single-locus and two-locus QTL analyses in bread wheat. Functional & Integrative Genomics, 2004, 4(2): 94-101.
[14]
MARES D, RATHJEN J, MRVA K, CHEONG J. Genetic and environmental control of dormancy in white-grained wheat (Triticum aestivum L.). Euphytica, 2009, 168(3): 311-318.

doi: 10.1007/s10681-009-9927-2
[15]
SINGH A K, KNOX R E, CLARKE J M, CLARKE F R, SINGH A, DEPAUW R M, CUTHBERT R D. Genetics of pre-harvest sprouting resistance in a cross of Canadian adapted durum wheat genotypes. Molecular Breeding, 2014, 33(4): 919-929.

doi: 10.1007/s11032-013-0006-y
[16]
ZHANG X Q, LI C D, TAY A, LANCE R, MARES D, CHEONG J, CAKIR M, MA J H, APPELS R. A new PCR-based marker on chromosome 4AL for resistance to pre-harvest sprouting in wheat (Triticum aestivum L.). Molecular Breeding, 2008, 22(2): 227-236.

doi: 10.1007/s11032-008-9169-3
[17]
CHEN C X, CAI S B, BAI G H. A major QTL controlling seed dormancy and pre-harvest sprouting resistance on chromosome 4A in a Chinese wheat landrace. Molecular Breeding, 2008, 21(3): 351-358.

doi: 10.1007/s11032-007-9135-5
[18]
WANG X Y, LIU H, MIA M S, SIDDIQUE K H M, YAN G J. Development of near-isogenic lines targeting a major QTL on 3AL for pre-harvest sprouting resistance in bread wheat. Crop and Pasture Science, 2018, 69(9): 864-872.

doi: 10.1071/CP17423
[19]
MOULLET O, DÍAZ BERMÚDEZ G, FOSSATI D, BRABANT C, MASCHER F, SCHORI A. Pyramiding wheat pre-harvest sprouting resistance genes in triticale breeding. Molecular Breeding, 2022, 42(10): 1-19.

doi: 10.1007/s11032-021-01272-7
[20]
FOFANA B, HUMPHREYS D G, RASUL G, CLOUTIER S, BRÛLÉ-BABEL A, WOODS S, LUKOW O M, SOMERS D J. Mapping quantitative trait loci controlling pre-harvest sprouting resistance in a red × white seeded spring wheat cross. Euphytica, 2009, 165(3): 509-521.

doi: 10.1007/s10681-008-9766-6
[21]
MARES D J, MRVA K. Mapping quantitative trait loci associated with variation in grain dormancy in Australian wheat. Australian Journal of Agricultural Research, 2001, 52(12): 1257-1266.

doi: 10.1071/AR01049
[22]
TORADA A, IKEGUCHI S, KOIKE M. Mapping and validation of PCR-based markers associated with a major QTL for seed dormancy in wheat. Euphytica, 2005, 143(3): 251-255.

doi: 10.1007/s10681-005-7872-2
[23]
ZHANG D L HE, J, HUANG L Y, ZHANG C C, ZHOU Y, SU Y R, LI S P. An advanced backcross population through synthetic octaploid wheat as a “bridge”: Development and QTL detection for seed dormancy. Frontiers in Plant Science, 2017, 8: 2123.

doi: 10.3389/fpls.2017.02123
[24]
ZHOU Y, TANG H, CHENG M P, DANKWA K O, CHEN Z X, LI Z Y, GAO S, LIU Y X, JIANG Q T, LAN X J, PU Z E, WEI Y M, ZHENG Y L, HICKEY L T, WANG J R. Genome-wide association study for pre-harvest sprouting resistance in a large germplasm collection of Chinese wheat landraces. Frontiers in Plant Science, 2017, 8: 401.

doi: 10.3389/fpls.2017.00401 pmid: 28428791
[25]
YANG J, LIU Y X, PU Z E, ZHANG L Q, YUAN Z W, CHEN G Y, WEI Y M, ZHENG Y L, LIU D C, WANG J R. Molecular characterization of high pI α-amylase and its expression QTL analysis in synthetic wheat RILs. Molecular Breeding, 2014, 34(3): 1075-1085.

doi: 10.1007/s11032-014-0098-z
[26]
YANG J, TAN C, LANG J, TANG H, HAO M, TAN Z, YU H, ZHOU Y, LIU Z H, LI M L, ZHOU Y, CHENG M P, ZHANG L Q, LIU D C, WANG J R. Identification of qPHS.sicau-1B and qPHS.sicau-3D from synthetic wheat for pre-harvest sprouting resistance wheat improvement. Molecular Breeding, 2019, 39(9): 1-12.

doi: 10.1007/s11032-018-0907-x
[27]
MARES D, MRVA K, CHEONG J, WILLIAMS K, WATSON B, STORLIE E, SUTHERLAND M, ZOU Y. A QTL located on chromosome 4A associated with dormancy in white- and red-grained wheats of diverse origin. Theoretical and Applied Genetics, 2005, 111(7): 1357-1364.

doi: 10.1007/s00122-005-0065-5 pmid: 16133305
[28]
HE J, ZHANG D L, CHEN X, LI Y G, HU M J, SUN S G, SU Q, SU Y R, LI S P. Identification of QTLs and a candidate gene for reducing pre-harvest sprouting in Aegilops tauschii-Triticum aestivum chromosome segment substitution lines. International Journal of Molecular Sciences, 2021, 22(7): 3729.
[29]
LANG J, FU Y X, ZHOU Y, CHENG M P, DENG M, LI M L, ZHU T T, YANG J, GUO X J, GUI L X, LI L C, CHEN Z X, YI Y J, ZHANG L Q, HAO M, HUANG L, TAN C, CHEN G Y, JIANG Q T, QI P F, PU Z E, MA J, LIU Z H, LIU Y J, LUO M C, WEI Y M, ZHENG Y L, WU Y R, LIU D C, WANG J R. Myb10-D confers PHS-3D resistance to pre-harvest sprouting by regulating NCED in ABA biosynthesis pathway of wheat. New Phytologist, 2021, 230(5): 1940-1952.

doi: 10.1111/nph.v230.5
[30]
KUMAR J, MIR R R, KUMAR N, KUMAR A, MOHAN A, PRABHU K V, BALYAN H S, GUPTA P K. Marker-assisted selection for pre-harvest sprouting tolerance and leaf rust resistance in bread wheat. Plant Breeding, 2010, 129(6): 617-621.

doi: 10.1111/pbr.2010.129.issue-6
[31]
TYAGI S, MIR R R, KAUR H, CHHUNEJA P, RAMESH B, BALYAN H S, GUPTA P K. Marker-assisted pyramiding of eight QTLs/genes for seven different traits in common wheat (Triticum aestivum L.). Molecular Breeding, 2014, 34(1): 167-175.

doi: 10.1007/s11032-014-0027-1
[32]
郝明, 张连全, 黄林, 甯顺腙, 袁中伟, 姜博, 颜泽洪, 伍碧华, 郑有良, 刘登才. 合成六倍体小麦的遗传育种. 植物遗传资源学报, 2022, 23(1): 40-48.

doi: 10.13430/j.cnki.jpgr.20210518002
HAO M, ZHANG L Q, HUANG L, NING S Z, YUAN Z W, JIANG B, YAN Z H, WU B H, ZHENG Y L, LIU D C. Genetic improvement of synthesized hexaploid wheat in breeding. Journal of Plant Genetic Resources, 2022, 23(1): 40-48. (in Chinese)

doi: 10.13430/j.cnki.jpgr.20210518002
[33]
ROBERTS E H. Dormancy in rice seed: III. The influence of temperature, moisture, and gaseous environment. Journal of Experimental Botany, 1962, 13(1): 75-94.

doi: 10.1093/jxb/13.1.75
[34]
FENNIMORE S A, NYQUIST W E, SHANER G E, MYERS S P, FOLEY M E. Temperature response in wild oat (Avena fatua L.) generations segregating for seed dormancy. Heredity, 1998, 81(6): 674-682.

doi: 10.1046/j.1365-2540.1998.00431.x
[35]
FOLEY M E. Temperature and water status of seed affect afterripening in wild oat (Avena fatua). Weed Science, 1994, 42(2): 200-204.

doi: 10.1017/S0043174500080279
[36]
MARES D J. Temperature dependence of germinability of wheat (Triticum aestivum L.) grain in relation to pre-harvest sprouting. Australian Journal of Agricultural Research, 1984, 35(2): 115-128.

doi: 10.1071/AR9840115
[37]
李俊, 魏会廷, 胡晓蓉, 李朝苏, 汤永禄, 刘登才, 杨武云. 川麦42中源于人工合成小麦的一个高产位点鉴定. 作物学报, 2011, 37(2): 255-262.
LI J, WEI H T, HU X R, LI C S, TANG Y L, LIU D C, YANG W Y. Identification of a high-yield introgression locus from synthetic hexaploid wheat in Chuanmai 42. Acta Agronomica Sinica, 2011, 37(2): 255-262. (in Chinese)
[38]
BUCK H T, NISI J E, SALOMON N. Wheat Production in Stressed Environments. Dordrecht: Springer Netherlands Press, 2007.
[39]
LIU Y J, LIU Y X, ZHOU Y, WIGHT C, PU Z E, QI P F, JIANG Q T, DENG M, WANG Z X, WEI Y M, CAO W G, LIU D C, ZHENG Y L, LIU C J, FRÉGEAU-REID J, WANG J R. Conferring resistance to pre-harvest sprouting in durum wheat by a QTL identified in Triticum spelta. Euphytica, 2016, 213(1): 1-10.

doi: 10.1007/s10681-016-1788-x
[40]
XU F, TANG J Y, WANG S X, CHENG X, WANG H R, OU S J, GAO S P, LI B S, QIAN Y W, GAO C X, CHU C C. Antagonistic control of seed dormancy in rice by two bHLH transcription factors. Nature Genetics, 2022, 54(12): 1972-1982.

doi: 10.1038/s41588-022-01240-7 pmid: 36471073
[41]
GUPTA P K, BALYAN H S, SHARMA S, KUMAR R. Genetics of yield, abiotic stress tolerance and biofortification in wheat (Triticum aestivum L.). Theoretical and Applied Genetics, 2020, 133(5): 1569-1602.

doi: 10.1007/s00122-020-03583-3
[42]
HUANG X Q, KEMPF H, GANAL M W, RÖDER M S. Advanced backcross QTL analysis in progenies derived from a cross between a German elite winter wheat variety and a synthetic wheat (Tritium aestivum L.). Theoretical and Applied Genetics, 2004, 109(5): 933-943.

doi: 10.1007/s00122-004-1708-7
[43]
MCCARTNEY C A, SOMERS D J, HUMPHREYS D G, LUKOW O, AMES N, NOLL J, CLOUTIER S, MCCALLUM B D. Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452 בAC Domain’. Genome, 2005, 48(5): 870-883.

doi: 10.1139/g05-055
[44]
QUARRIE S A, STEED A, CALESTANI C, SEMIKHODSKII A, LEBRETON C, CHINOY C, STEELE N, PLJEVLJAKUSIĆ D, WATERMAN E, WEYEN J, SCHONDELMAIER J, HABASH D Z, FARMER P, SAKER L, CLARKSON D T, ABUGALIEVA A, YESSIMBEKOVA M, TURUSPEKOV Y, ABUGALIEVA S, TUBEROSA R, SANGUINETI M C, HOLLINGTON P A, ARAGUÉS R, ROYO A, DODIG D. A high-density genetic map of hexaploid wheat (Triticum aestivum L.) from the cross Chinese Spring × SQ1 and its use to compare QTLs for grain yield across a range of environments. Theoretical and Applied Genetics, 2005, 110(5): 865-880.

doi: 10.1007/s00122-004-1902-7
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