Scientia Agricultura Sinica ›› 2022, Vol. 55 ›› Issue (8): 1492-1502.doi: 10.3864/j.issn.0578-1752.2022.08.002


Unconditional and Conditional QTL Analysis of Wheat Spike Length in Common Wheat Based on 55K SNP Array

TANG HuaPing1(),CHEN HuangXin1(),LI Cong1,GOU LuLu1,TAN Cui2,MU Yang1,TANG LiWei3,LAN XiuJin1,WEI YuMing1,MA Jian1()   

  1. 1Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130
    2Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130
    3PanZhiHua Academy of Agricultural and Forestry Sciences, Panzhihua 617061, Sichuan
  • Received:2021-10-20 Accepted:2021-12-16 Online:2022-04-16 Published:2022-05-11
  • Contact: Jian MA;;


【Objective】This study is to excavate spike length (SL)-related quantitative trait loci (QTL) with potential breeding value, explore the genetic relationship between SL and other important agronomic traits in wheat, and aim at laying a foundation for fine mapping and molecular-assisted selection breeding. 【Method】A total of 126 F7 recombinant inbred lines (RIL) constructed by crossing 20828 and SY95-71 were used in this study. The RIL population including their parents were planted in seven different environments for phenotypic evaluation: Wenjiang, Chongzhou, Ya'an of Sichuan Province in China, and Khulna in Bangladesh during 2016-2017 and 2017-2018 growing seasons. Unconditional QTL mapping was performed using a genetic linkage map constructed using the wheat 55K SNP array, and QTLs’ effects were further analyzed. Conditional QTL analysis was performed to analyze the relationship between SL and other agronomic traits including plant height (PH), spike extension length (SEL), spikelet number per spike (SNS) and thousand-kernel weight (TKW). 【Result】Thirteen QTLs controlling SL were identified using unconditional QTL mapping, and they were located on chromosomes 1A, 1D, 2B, 2D, 4B, 6D, and 7A. The LOD values ranged from 2.79 to 6.19, and the phenotypic variation rate ranged from 5.35% to 12.77%. Three stable and major QTLs (QSl-sau-2SY-2B, QSl-sau-2SY-2D.5 and QSl-sau-2SY-4B) were identified, and they explained 6.54% to 11.72%, 10.16% to 12.57%, and 5.35% to 10.92% of phenotypic variation rate, respectively. Furthermore, these three major QTLs could be also detected in multi-environment analysis. Moreover, aggregation analysis suggested that the SL of lines polymerizing the positive allels at these three major QTLs was significantly longer than that of those with any two ones or those carrying only one. Meanwhile, it was found that QSl-sau-2SY-2B had no significant effect on PH, SEL, SNS and TKW. QSl-sau-2SY-2D.5 had a significant effect on improving TKW (3.98%), but no significant effect on PH, SEL and SNS. QSl-sau-2SY-4B had a significant effect on decreasing PH (-12.28%) and SEL (-22.26%), but no significant effect on SNS and TKW. The conditional QTL analysis showed that QSl-sau-2SY-2B was independent of PH and SEL, whereas, affected by SNS and TKW. QSl-sau-2SY-2D.5 was independent of SEL, SNS and TKW, but affected by PH. QSl-sau-2SY-4B was independent of SEL and TKW, but affected by PH and SNS. 【Conclusion】In this study, three stable and major QTLs were identified for SL: QSl-sau-2SY-2B, QSl-sau-2SY-2D.5, and QSl-sau-2SY-4B, among which QSl-sau-2SY-2B may be a novel QTL independent of PH and SEL.

Key words: common wheat, 55K SNP array, spike length, unconditional QTL, conditional QTL

Fig. 1

The spike length of parents and selected lines in the 2SY population"

Table 1

Phenotypic variation of spike length for parents and RIL in 2SY population"

亲本Parent (cm) 重组自交系RIL
20828 SY95-71 范围
Range (cm)
Mean (cm)
E1 15.60** 9.50 8.10—16.80 12.63 1.68 -0.03 0.06
E2 15.43** 9.83 7.83—17.20 12.28 1.95 0.34 -0.07
E3 14.70** 9.80 6.57—15.50 11.49 1.51 -0.08 0.36
E4 12.55** 8.42 7.41—14.65 10.90 1.47 -0.07 -0.47
E5 13.15** 8.46 7.10—16.12 10.73 1.56 0.20 0.15
E6 11.28** 7.54 5.84—15.62 9.91 1.80 0.29 0.12
E7 15.13** 8.55 6.08—16.33 10.71 1.96 0.64 0.56
BLUP 13.65 9.15 8.70—14.27 11.23 1.14 0.18 -0.02 0.63

Fig. 2

The frequency distribution of spike length in 2SY population E1: Wenjiang experiment base, Chengdu, Sichuan Province, China in 2017; E2: Chongzhou experiment base, Sichuan Province, China in 2017; E3: Ya'an experiment base, Sichuan Province, China in 2017; E4: Wenjiang experiment base, Chengdu, Sichuan, China in 2018; E5: Chongzhou experiment base, Sichuan Province, China in 2018; E6: Ya'an experiment base, Sichuan Province, China in 2018; E7: Experiment field in Khulna, Bangladesh in 2018"

Table 2

Correlation analysis of spike length in different environments in 2SY population"

环境Environment E1 E2 E3 E4 E5 E6 E7 BLUP
E1 1
E2 0.696** 1
E3 0.755** 0.699** 1
E4 0.581** 0.568** 0.539** 1
E5 0.642** 0.591** 0.571** 0.731** 1
E6 0.545** 0.636** 0.488** 0.570** 0.607** 1
E7 0.329** 0.424** 0.383** 0.231* 0.192* 0.279** 1
BLUP 0.838** 0.867** 0.817** 0.767** 0.788** 0.772** 0.556** 1

Table 3

Unconditional QTL for spike length in 2SY population"

Unconditional QTL
Position (cM)
Marker interval
LOD 贡献率
PVE (%)
QSl-sau-2SY-1A E7 1A-1 59 AX-110961101—AX-108871459 2.93 11.30 0.69
QSl-sau-2SY-1D.1 E5 1D 44 AX-94498629—AX-89319035 4.78 9.32 0.54
QSl-sau-2SY-1D.2 E4 1D 84 AX-111087365—AX-110640947 4.80 9.41 0.48
QSl-sau-2SY-1D.3 E2 1D 116 AX-110766802—AX-111575769 2.97 7.26 0.56
QSl-sau-2SY-2B E4 2B-2 141 AX-111019809—AX-109451490 5.91 11.72 -0.53
E5 2B-2 147 AX-94441014—AX-109521609 3.49 6.54 -0.46
BLUP 2B-2 147 AX-94441014—AX-109521609 3.97 9.86 -0.37
QSl-sau-2SY-2D.1 BLUP 2D-1 19 AX-86163393—AX-109785183 3.23 10.04 0.37
QSl-sau-2SY-2D.2 E5 2D-2 47 AX-110977542—AX-109417243 5.85 12.53 0.63
QSl-sau-2SY-2D.3 E6 2D-3 25 AX-108767381—AX-111722527 3.44 12.77 0.65
QSl-sau-2SY-2D.4 E2 2D-3 35 AX-111722527—AX-109421761 4.44 12.66 0.73
QSl-sau-2SY-2D.5 BLUP 2D-3 70 AX-109291628—AX-111093303 3.93 11.28 0.39
E1 2D-3 72 AX-111093303—AX-109338052 2.96 10.16 0.55
E4 2D-3 74 AX-109338052—AX-111656957 6.19 12.57 0.55
QSl-sau-2SY-4B E4 4B-2 0 AX-110928817—AX-111620391 2.88 5.35 0.36
E5 4B-2 0 AX-110928817—AX-111620391 5.43 10.92 0.59
E3 4B-2 4 AX-111573292—AX-111233094 3.04 10.08 0.54
QSl-sau-2SY-6D E2 6-D 31 AX-111026969—AX-109353709 2.79 9.59 0.64
QSl-sau-2SY-7A E2 7A-2 27 AX-109417084—AX-108776518 3.00 7.63 -0.58

Table 4

Multi-environment QTL for spike length in 2SY population"

Detected QTL
Marker interval
PVE (%)
QSl-sau-2SY-2B AX-94498629AX-89319035 7.11 3.60 3.51 1.23 0.76 0.47 0.21
AX-111019809AX-109451490 9.82 5.55 4.27 1.63 1.16 0.47 -0.25
AX-94441014AX-109521609 9.01 7.40 1.60 1.86 1.55 0.31 -0.29
AX-110872666AX-110373068 7.01 5.87 1.13 1.54 1.21 0.33 0.26
AX-110977542AX-109417243 11.93 8.66 3.27 1.99 1.77 0.22 0.31
AX-111722527AX-109421761 7.68 5.65 2.03 1.64 1.16 0.48 0.25
QSl-sau-2SY-2D.5 AX-109338052AX-111656957 12.32 7.68 4.65 1.97 1.60 0.37 0.30
QSl-sau-2SY-4B AX-110928817AX-111620391 10.59 4.14 6.45 1.80 0.88 0.92 0.22

Fig. 3

Pyramiding effect of major QTL for spike length in 2SY population + and -: The lines carrying and not carrying the positive allele of target QTL; #RILs: Number of corresponding lines; a, b, c and d represent significant difference. The same as below"

Fig. 4

Effects of major QTL for spike length on other agronomic traits a—d: Effects of QSl-sau-2SY-2B on plant height, spike extension length, spikelet number per spike and thousand-kernel weight, +: Contains 50 lines, -: Contains 60 lines; e—h: Effects of QSl-sau-2SY-2D.5 on plant height, spike extension length, spikelet number per spike and thousand-kernel weight, +: Contains 40 lines, -: Contains 46 lines; i—l: Effects of QSl-sau-2SY-4B on plant height, spike extension length, spikelet number per spike and thousand-kernel weight, +: Contained 43 lines, -: Contained 61 lines; * and **: The significant difference at 0.05 and 0.01 levels"

Table 5

Conditional QTL for spike length in 2SY population"

T1|T2 染色体
Position (cM)
Marker interval
LOD 贡献率
PVE (%)
Unconditional QTL
LOD 贡献率
PVE (%)
SL|PH 2B-2 147 AX-94441014AX-109521609 3.66 8.50 -0.32 QSl-sau-2SY-2B 3.97 9.86 -0.37
SL|PH 2D-2 48 AX-110977542AX-109417243 2.87 6.80 0.29 -
SL|PH 2D-3 74 AX-109338052AX-111656957 3.35 8.05 0.31 QSl-sau-2SY-2D.5 3.93 11.28 0.39
SL|PH 4B-2 3 AX-111573292AX-111233094 4.49 12.29 0.39 QSl-sau-2SY-4B
SL|PH 7D 20 AX-109130875AX-109379249 3.52 9.68 0.34 -
SL|SEL 2B-2 147 AX-94441014AX-109521609 3.62 9.15 -0.37 QSl-sau-2SY-2B 3.97 9.86 -0.37
SL| SEL 2D-1 18 AX-86163393AX-109785183 3.32 10.94 0.40 -
SL| SEL 2D-3 71 AX-109291628AX-111093303 4.02 10.92 0.40 QSl-sau-2SY-2D.5 3.93 11.28 0.39
SL|SNS 2B-2 147 AX-94441014AX-109521609 2.85 6.47 -0.29 QSl-sau-2SY-2B 3.97 9.86 -0.37
SL|SNS 2D-2 47 AX-110977542AX-109417243 3.09 7.70 0.31 -
SL|SNS 2D-3 72 AX-111093303AX-109338052 4.01 9.30 0.34 QSl-sau-2SY-2D.5 3.93 11.28 0.39
SL|SNS 4B-2 3 AX-111573292AX-111233094 2.57 6.44 0.29 QSl-sau-2SY-4B
SL|SNS 7A-2 103 AX-110518554AX-110442528 3.79 9.35 -0.35 -
SL|TGW 2B-2 146 AX-108758148AX-94441014 3.09 7.40 -0.29 QSl-sau-2SY-2B 3.97 9.86 -0.37
SL|TGW 2D-3 72 AX-111093303AX-109338052 4.02 9.47 0.33 QSl-sau-2SY-2D.5 3.93 11.28 0.39
SL|TGW 6B-1 83 AX-89344223AX-110472291 2.59 6.07 0.27 -
SL|TGW 7A-2 27 AX-109417084AX-108776518 4.05 10.10 -0.35 -
SL|TGW 7D 20 AX-109130875AX-109379249 3.98 11.30 0.36 -
[1] SHIFERAW B, SMALE M, BRAUN H J, DUVEILLER E, REYNOLDS M, MURICHO G. Crops that feed the world 10. Past successes and future challenges to the role played by wheat in global food security. Food Security, 2013, 5(3): 291-317.
doi: 10.1007/s12571-013-0263-y
[2] YANG Y, KRISHNA K, DESHPANDE P, RANGANATHAN V, JAYARAMAN V, WANG T, BEI K, KRISHNAMURTHY H. High frequency of extractable nuclear autoantibodies in wheat-related disorders. Biomarker Insights, 2018, 13: 1-6.
[3] FAROOQ J, KHALIQ I, AKBAR M, PETRESCU-MAG I V, HUSSAIN M. Genetic analysis of some grain yield and its attributes at high temperature stress in wheat (Triticum aestivum L.). Ann RSCB, 2015, 19(3): 71-81.
[4] MAUREEN T N, JACOB M, HUSSEIN S, ALFRED O. Agronomic and physiological traits, and associated quantitative trait loci (QTL) affecting yield response in wheat (Triticum aestivum L.): A review. Frontiers in Plant Science, 2019, 10: 1428.
doi: 10.3389/fpls.2019.01428
[5] JI G S, XU Z B, FAN X L, ZHOU Q, YU Q, LIU X F, LIAO S M, FENG B, WANG T.Identification of a major and stable QTL on chromosome 5A confers spike length in wheat (Triticum aestivum L.). Molecular Breeding, 2021, 41(9): 1-13.
doi: 10.1007/s11032-020-01191-z
[6] LI T, DENG G B, SU Y, YANG Z, TANG Y Y, WANG J H. QIU X B, PU X, LI J, LIU Z H, ZHANG H L, LIANG J J, YANG W Y, YU M Q, WEI Y M, LONG H. Identification and validation of two major QTLs for spike compactness and length in bread wheat (Triticum aestivum L.) showing pleiotropic effects on yield-related traits. Theoretical and Applied Genetics, 2021, 134: 3625-3641.
doi: 10.1007/s00122-021-03918-8
[7] ZHOU Y, CONWAY B, MILLER D, MARSHALL D, COOPER A, MURPHY P, CHAO S, BROWN-GUEDIRA G, COSTA J. Quantitative trait loci mapping for spike characteristics in hexaploid wheat. The Plant Genome, 2017, 10(2): plantgenome2016.10.0101.
[8] LIU J, XU Z B, FAN X L, ZHOU Q, CAO J, WANG F, JI G S, YANG L, FENG B, WANG T. A genome-wide association study of wheat spike related traits in China. Frontiers in Plant Science, 2018, 9: 1584.
doi: 10.3389/fpls.2018.01584
[9] ZHAI H J, FENG Z U, LI J, LIU X Y, XIAO S H, NI Z F, SUN Q X. QTL analysis of spike morphological traits and plant height in winter wheat (Triticum aestivum L.) using a high-density SNP and SSR-based linkage map. Frontiers in Plant Science, 2016, 7: 1617.
[10] GUO L B, XING Y Z, MEI H W, XU C G, SHI C H, WU P, LUO L J. Dissection of component QTL expression in yield formation in rice. Plant Breeding, 2005, 124(2): 127-132.
doi: 10.1111/j.1439-0523.2005.01093.x
[11] CUI F, ZHAO C H, LI J, DING A M, LI X F, BAO Y G, LI J M, JI J, WANG H G. Kernel weight per spike: What contributes to it at the individual QTL level? Molecular Breeding, 2013, 31(2): 265-278.
doi: 10.1007/s11032-012-9786-8
[12] LI C, TANG H P, LUO W, ZHANG X M, MU Y, DENG M, LIU Y X, JIANG Q T, CHEN G D, WANG J R, QI P F, PU Z E, JIANG Y F, WEI Y M, ZHENG Y L, LAN X J, MA J. A novel, validated, and plant height-independent QTL for spike extension length is associated with yield-related traits in wheat. Theoretical and Applied Genetics, 2020, 133(12): 3381-3393.
doi: 10.1007/s00122-020-03675-0
[13] ZHANG H, CHEN J S, LI R Y, DENG Z Y, ZHANG K P, LIU B, TIAN J C. Conditional QTL mapping of three yield components in common wheat (Triticum aestivum L.). The Crop Journal, 2016, 4(3): 220-228.
doi: 10.1016/j.cj.2016.01.007
[14] FAN X L, CUI F, JI J, ZHANG W, ZHAO X Q, LIU J J, MENG D Y, TONG Y P, WANG T, LI J M. Dissection of pleiotropic QTL regions controlling wheat spike characteristics under different nitrogen treatments using traditional and conditional QTL mapping. Frontiers in Plant Science, 2019, 10: 187.
doi: 10.3389/fpls.2019.00187
[15] AGATA A, ANDO K, OTA S, KOJIMA M, TAKEBAYASHI Y, TAKEHARA S, DOI K, UEGUCHI-TANAKA M, SUZUKI T, SAKAKIBARA H, MATSUOKA M, ASHIKARI M, INUKAI Y, KITANO H, HOBO T. Diverse panicle architecture results from various combinations of Prl5/GA20ox4 and Pbl6/APO1 alleles. Communications Biology, 2020, 3(1): 1-17.
doi: 10.1038/s42003-019-0734-6
[16] CUI F, LI J, DING A M, ZHAO C H, WANG L, WANG X Q, LI S S, BAO Y G, LI S F, FENG D S, KONG L G, WANG H G. Conditional QTL mapping for plant height with respect to the length of the spike and internode in two mapping populations of wheat. Theoretical and Applied Genetics, 2011, 122(8): 1517-1536.
doi: 10.1007/s00122-011-1551-6
[17] YU M, MAO S L, CHEN G Y, PU Z E, WEI Y M, ZHENG Y L. QTLs for uppermost internode and spike length in two wheat RIL populations and their affect upon plant height at an individual QTL level. Euphytica, 2014, 200(1): 95-108.
doi: 10.1007/s10681-014-1156-7
[18] SU Q N, ZHANG X L, ZHANG W, ZHANG N, SONG L, LIU L Q, LIU L, XUE X, LIUG T, LIU J J, MENG D Y, ZHI L Y, JI J, ZHAO X Q, YANG C L, TONG Y P, LIU Z Y, LI J M. QTL detection for kernel size and weight in bread wheat (Triticum aestivum L.) using a high-density SNP and SSR-based linkage map. Frontiers in Plant Science, 2018, 9: 1484.
doi: 10.3389/fpls.2018.01484
[19] MA J, QIN N N, CAI B, CHEN G Y, DING P Y, ZHANG H, YANG C C, HUANG L, MU Y, TANG H P, LIU Y X, WANG J R, QI P F, JIANG Q T, ZHENG Y L, LIU C J, LAN X J, WEI Y M. Identification and validation of a novel major QTL for all-stage stripe rust resistance on 1BL in the winter wheat line 20828. Theoretical and Applied Genetics, 2019, 132(5): 1363-1373.
doi: 10.1007/s00122-019-03283-7
[20] 舒焕麟, 杨足君, 李光蓉. 创新诱发材料SY95-71选育和利用价值研究. 四川农业大学学报, 1999, 17(3): 249-253.
SHU H L, YANG Z J, LI G R. Selection and evaluation of a wheat line SY95-71 as new yellow rust spreader. Journal of Sichuan Agricultural University, 1999, 17(3): 249-253. (in Chinese)
[21] DING P Y, MO Z Q, TANG H P, MU Y, DENG M, JIANG Q T, LIU Y X, CHEN G D, CHEN G Y, WANG J R, LI W, QI P F, JIANG Y F, KANG H Y, YAN G J, WEI Y M, ZHENG Y L, LAN X J, MA J. A major and stable QTL for wheat spikelet number per spike was validated in different genetic backgrounds. Journal of Integrative Agriculture, 2021. doi: 10.1016/S2095-3119(20)63602-4.
doi: 10.1016/S2095-3119(20)63602-4
[22] LIU J J, TANG H P, QU X R, LIU H, LI C, TU Y, LI S Q, HABIB A, MU Y, DAI S F, DENG M, JIANG Q T, LIU Y X, CHEN G Y, WANG J R, CHEN G D, LI W, JIANG Y F, WEI Y M, LAN X J, ZHENG Y L, MA J. A novel, major, and validated QTL for the effective tiller number located on chromosome arm 1BL in bread wheat. Plant Molecular Biology, 2020, 104(1): 173-185.
doi: 10.1007/s11103-020-01035-6
[23] QU X R, LIU J J, XIE X L, XU Q, TANG H P, MU Y, PU Z E, LI Y, MA J, GAO Y T, JIANG Q T, LIU Y X, CHEN G Y, WANG J R, QI P F, HABIB A, WEI Y M, ZHENG Y L, LAN X J, MA J. Genetic mapping and validation of loci for kernel-related traits in wheat (Triticum aestivum L.). Frontiers in Plant Science, 2021, 12: 667493.
[24] ZHU T, WANG L, RIMBERT H, RODRIGUEZ J C, DEAL K R, DE OLIVEIRA R, CHOULET F, KEEBLE-GAGNERE G, TIBBITS J, ROGERS J, EVERSOLE K, APPELS R, GU Y Q, MASCHER M, DVORAK J, LUO M C. Optical maps refine the bread wheat Triticum aestivum cv. Chinese Spring genome assembly. The Plant Journal, 2021, 107: 303-314.
doi: 10.1111/tpj.15289
[25] PRETINI N, VANZETTI L S, TERRILE I I, DONAIRE G, GONZÁLEZ F G. Mapping QTL for spike fertility and related traits in two doubled haploid wheat (Triticum aestivum L.) populations. BMC Plant Biology, 2021, 21(1): 1-18.
doi: 10.1186/s12870-020-02777-7
[26] XU Y F, LI S S, LI L H, MA F F, FU X Y, SHI Z L, XU H X, MA P T, AN D G. QTL mapping for yield and photosynthetic related traits under different water regimes in wheat. Molecular Breeding, 2017, 37(3): 34.
doi: 10.1007/s11032-016-0583-7
[27] 李聪, 马建, 刘航, 丁浦洋, 杨聪聪, 张涵. 兰秀锦. 基于小麦55K SNP芯片检测小麦穗长和株高性状QTL. 麦类作物学报, 2019, 39(11): 1284-1292.
LI C, MA J, LIU H, DING P Y, YANG C C, ZHANG H, LAN X J. Detection of QTLs for spike length and plant height in wheat based on 55K SNP array. Journal of Triticeae Crops, 2019, 39(11): 1284-1292. (in Chinese)
[28] MWADZINGENI L, SHIMELIS H, REES D J G, TSILO T J. Genome-wide association analysis of agronomic traits in wheat under drought-stressed and non-stressed conditions. PLoS ONE, 2017, 12(2): e0171692.
[29] ELLIS M, REBETZKE G, AZANZA F, RICHARDS R, SPIELMEYER W. Molecular mapping of gibberellin-responsive dwarfing genes in bread wheat. Theoretical and Applied Genetics, 2005, 111(3): 423-430.
doi: 10.1007/s00122-005-2008-6
[30] REBETZKE G, APPELS R, MORRISON A, RICHARDS R, MCDONALD G, ELLIS M, SPIELMEYER W, BONNETT D.Quantitative trait loci on chromosome 4B for coleoptile length and early vigour in wheat (Triticum aestivum L.). Australian Journal of Agricultural Research, 2001, 52(12): 1221-1234.
doi: 10.1071/AR01042
[31] 邹拓, 耿雷跃, 张薇, 张启星. 水稻抗病虫基因挖掘及聚合育种研究进展. 河北农业科学, 2018, 22(5): 47-67.
ZOU T, GENG L Y, ZHANG W, ZHANG Q X. Research advances on gene mining resistant to disease and insect and polymerization breeding of rice. Journal of Hebei Agricultural Sciences, 2018, 22(5): 47-67. (in Chinese)
[32] 鲁秀梅, 张宁, 陈劲枫, 钱春桃. 作物基因聚合育种的研究进展. 分子植物育种, 2017, 15(4): 1445-1454.
LU X M, ZHANG N, CHEN J F, QIAN C T. The research progress in crops pyramiding breeding. Molecular Plant Breeding, 2017, 15(4): 1445-1454. (in Chinese)
[33] LI Q F, ZHANG Y, LIU T T, WANG F F, LIU K, CHEN J S, TIAN J C. Genetic analysis of kernel weight and kernel size in wheat (Triticum aestivum L.) using unconditional and conditional QTL mapping. Molecular Breeding, 2015, 35(10): 1-15.
doi: 10.1007/s11032-015-0202-z
[34] LIU K Y, XU H, LIU G, GUAN P F, ZHOU X Y, PENG H R, NI Z F, SUN Q X, DU J K. QTL mapping of flag leaf-related traits in wheat (Triticum aestivum L.). Theoretical and Applied Genetics, 2018, 131(4): 839-849.
doi: 10.1007/s00122-017-3040-z
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