Welcome to Acta Agronomica Sinica,

Acta Agronomica Sinica ›› 2024, Vol. 50 ›› Issue (3): 590-602.doi: 10.3724/SP.J.1006.2024.31034

• CROP GENETICS & BREEDINGZ·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

QTL mapping and GWAS analysis of coleoptile length in bread wheat

HAO Qian-Lin1(), YANG Ting-Zhi1, LYU Xin-Ru1, QIN Hui-Min1, WANG Ya-Lin1, JIA Chen-Fei1, XIA Xian-Chun2, MA Wu-Jun1, XU Deng-An1,*()   

  1. 1College of Agronomy, Qingdao Agricultural University, Qingdao 266109, Shandong, China
    2Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2023-05-18 Accepted:2023-09-13 Online:2024-03-12 Published:2023-09-27
  • Contact: *E-mail: xudengan200@126.com
  • Supported by:
    High-level Talents Project of Qingdao Agricultural University(663/1122023);Shandong Provincial Natural Science Foundation(ZR202103020229);National Natural Science Foundation of China(32101733)

Abstract:

Under drought conditions, the emergence rate of wheat (Triticum aestivum L.) can be improved by proper deep sowing. The maximum sowing depth of wheat is determined by the length of the coleoptile, so it is very important to cultivate wheat varieties with long coleoptile. In this study, a recombinant inbred line (RIL) population consisting of 275 lines derived from the cross of Doumai and Shi 4185, and 186 natural population materials were used as the experimental materials. Genotyping results of 90K SNP chip were used to identify QTL for wheat coleoptile length in three different environments. The results showed that two stable QTL sites were identified by inclusive composite interval mapping in the RIL population. The two QTL located on Chromosome 4BS (30.17-40.59 Mb) and 6BL (700.08-703.53 Mb), respectively, and explained 26.29%-28.46% and 4.16%- 4.36% of the phenotypic variance, respectively. A total of 36 stable QTL were identified in the genome-wide association study (GWAS) using the mixed linear model. They were located on Chromosome 1A (3), 1B (3), 1D (2), 2A (1), 3A (2), 3B (2), 4B (11), 5A (1), 5B (3), 6B (4), 7A (2), and 7B (2), respectively. Seven significant association loci were repeatedly detected in the three environments, three of which overlapped or were adjacent to reported loci, and the other four loci were presumed to be new loci. They were located on Chromosomes 1A (499.03 Mb), 3A (73.06 Mb), 4B (648.74-648.87 Mb), and 7A (36.31 Mb), respectively. Five candidate genes (TraesCS1A03G0748300, Rht1, TraesCS4B03G0110000, TraesCS4B03G0112200, and TraesCS7A03G0146600) were predicted. A major QTL locus on Chromosome 4BS (30.17-40.59 Mb) was identified in both RIL and natural populations, and the candidate gene Rht1 at this locus had been shown to reduce the length of wheat coleoptile. The results of this study lay a foundation for the identification of genes controlling the length of coleoptile in wheat and the maker-assisted selection breeding.

Key words: wheat, coleoptile length, QTL mapping, GWAS

Table 1

Basic statistics of coleoptile length of two parents and 275 lines of the Doumai/Shi 4185 RIL population"

环境
Environment
亲本 Parents RIL家系 RIL lines
豆麦
Doumai
石4185
Shi 4185
最小值
Min.
最大值
Max.
均值
Mean
标准差
SD
变异系数
CV (%)
E1 5.41 4.49 2.88 6.33 4.32 0.57 13.31
E2 5.65 4.57 3.23 6.16 4.29 0.56 13.06
E3 5.16 4.54 3.10 6.21 4.27 0.58 13.50
BLUE 5.40 4.54 3.14 6.20 4.29 0.55 12.76

Fig. 1

Seedlings of two parents (Shi 4185 and Doumai)"

Fig. 2

Distributions of coleoptile length for the parents and 275 lines of the Doumai/Shi 4185 RIL population E1, E2, and E3 represent the length of coleoptile measured by seeds were collected from Qingdao in 2020 and 2021, Qingdao in 2021 and 2022, and Xinxiang in 2020 and 2021, respectively."

Table 2

Correlations across environments and broad-sense heritability for coleoptile length of the parents and 275 lines of the Doumai/Shi 4185 RIL population"

环境
Environment
相关系数 Correlation coefficient 广义遗传力
H2
E1 E2 E3
E1 1 0.92
E2 0.89** 1
E3 0.80** 0.88** 1

Fig. 3

QTL for coleoptile length identified in the Doumai/Shi 4185 RIL population Only partial of the markers in the presented linkage interval are showed in the maps. The “Green Revolution” gene Rht1 showed on linkage groups 4BS, was not used for linkage map construction, and it was arranged on the map based on its and the neighboring markers’ physical positions in Chinese Spring reference genome IWGSC RefSeq v2.1 (http://www.wheatgenome.org/[40])."

Table 3

QTL for coleoptile length identified in the Doumai/Shi4185 RIL population"

数量性状位点a
QTL a
环境
Environment
侧翼标记
Flanking marker
物理区间b
Physiol interval (Mb) b
LOD值c
LOD value c
贡献率
PVE (%)
加性效应
Add
QCL.qau-4BS E1 IWA102-IWB54814 30.17-40.59 18.43 27.84 0.32
E2 IWA102-IWB54814 30.17-40.59 15.51 26.29 0.30
E3 IWA102-IWB54814 30.17-40.59 16.99 26.66 0.31
BLUE IWA102-IWB54814 30.17-40.59 19.32 28.46 0.31
QCL.qau-6BL E1 IWB19986-IWB35852 702.16-703.53 3.15 4.16 -0.12
E3 IWB63870-IWB19986 700.08-702.16 3.02 4.36 -0.12
BLUE IWB19986-IWB35852 702.16-703.53 15.03 20.97 -0.25

Table 4

Statistical analysis on coleoptile length evaluated on 186 natural population materials"

环境
Environment
均值
Mean
标准差
SD
变异系数
CV (%)
相关系数 Correlation coefficient 遗传力
H2
E1 E2 E3
E1 3.98 0.55 13.74 1 0.91
E2 4.01 0.56 14.07 0.94** 1
E3 4.03 0.57 14.25 0.93** 0.93** 1
BLUE 4.01 0.55 13.70

Fig. 4

Distributions of coleoptile length of the 186 natural population materials E1, E2, and E3 represent the length of coleoptile measured by seeds collected from Qingdao in 2020 and 2021, Qingdao in 2021 and 2022, and Xinxiang in 2020 and 2021, respectively."

Fig. 5

Kinships and population structure of the 186 natural population materials used in this study A: phylogenetic relationship; B: principal component analysis; C: Neighbor-Jointing tree analysis."

Table 5

CL-associated loci detected in at least two environments by MLM"

环境a
Environment a
标记名称
Marker name
基因型b
Allele b
物理位置c
Physical position (Mb) c
P最小值d
P-value min. d
P最大值d
P-value max. d
E1/BLUE IWB30674 G/A 1A:48.36 1.59E-04 3.16E-05
E1/E2/E3/BLUE IWB50788 G/A 1A:499.03 6.07E-04 1.40E-04
E3/BLUE IWA7871 G/A 1A:505.76 5.98E-04 1.23E-04
E1/E3/BLUE IWB21039 G/A 1B:30.67 9.25E-04 1.99E-04
E3/BLUE IWB53874 G/A 1B:588.25 2.83E-04 2.28E-04
E3/BLUE IWB74028 G/A 1B:690.58 8.03E-04 7.03E-04
E1/BLUE IWB18554 G/A 1D:42.77 1.00E-03 4.68E-04
E1/BLUE IWA830 G/A 1D:43.07 1.00E-03 4.68E-04
E1/E2/BLUE IWB64018 G/A 2A:757.65 3.83E-04 1.30E-05
E2/E3/BLUE IWB2733 G/A 3A:72.88 8.60E-04 6.15E-04
E1/E2/E3/BLUE IWB53051 G/A 3A:73.06 5.40E-04 1.52E-04
E1/E2/E3/BLUE IWB24605 G/A 3B:19.95 2.26E-04 1.17E-04
E1/BLUE IWB39644 G/A 3B:75.98 7.11E-04 5.20E-04
E1/E2/E3/BLUE IWB49875 G/A 4B:24.28 8.57E-04 5.50E-05
E1/E2/E3/BLUE IWB70449 G/A 4B:40.43 7.36E-04 9.01E-05
E1/E2/E3/BLUE IWB54814 G/A 4B:40.59 3.42E-05 7.35E-06
E1/BLUE IWA6850 G/A 4B:40.76 9.74E-04 8.55E-04
E1/E3/BLUE IWB4719 G/A 4B:40.77 5.04E-04 1.79E-04
E1/E3/BLUE IWB25737 G/A 4B:41.02 5.55E-04 2.55E-04
E1/BLUE IWB40899 G/A 4B:574.98 7.29E-04 5.86E-04
E1/BLUE IWB59718 G/A 4B:577.08 8.58E-04 8.18E-04
E1/BLUE IWB71859 G/A 4B:578.54 9.42E-04 7.17E-04
E1/E2/E3/BLUE IWB53155 G/A 4B:648.74 3.86E-04 5.06E-05
E1/E2/E3/BLUE IWB42023 G/A 4B:648.87 5.14E-04 6.61E-05
E1/E3 IWB35845 G/A 5A:710.07 5.69E-04 5.66E-04
E1/BLUE IWA6527 G/A 5B:211.64 7.49E-04 2.81E-04
E1/BLUE IWB71849 G/A 5B:607.90 9.62E-04 2.43E-04
E/E2 IWB63425 G/A 5B:75.60 9.64E-04 9.60E-04
E2/E3 IWB62054 G/A 6B:123.26 7.01E-04 6.74E-04
E2/BLUE IWB56800 G/A 6B:128.10 6.75E-04 4.32E-04
E2/E3 IWB68130 G/A 6B:146.70 9.96E-04 5.02E-04
E2/E3 IWB65561 G/A 6B:683.94 8.99E-04 7.31E-04
E2/E3 IWB22879 G/A 7A:31.41 7.50E-04 5.52E-04
E1/E2/E3/BLUE IWB11001 G/A 7A:36.31 8.74E-04 4.53E-05
E3/BLUE IWB72566 G/A 7B:203.84 9.80E-04 4.88E-04
E1/E3/BLUE IWB11945 G/A 7B:204.38 7.06E-04 1.98E-04

Fig. 6

Genome wide association study of coleoptile length in 186 natural population materials A: the manhattan plot for the BLUE of coleoptile length based on the mixed linear models, X-axis shows SNP markers along each wheat chromosome, Y-axis is the -log10 (P-value); B: the quantile-quantile plot for the BLUE of coleoptile length based on the mixed linear models, the X-axis shows -log10 transformed expected P-values and Y-axis shows -log10 transformed observed P-values."

Table 6

Candidate genes for the loci associated with CL"

标记名称
Marker name
标记物理位置a
Position (Mb) a
基因名称b
Gene name b
基因物理位置c
Position (Mb) c
同源基因d
Homologs d
基因功能
Gene function
IWB50788 1A:499.03 1A03G0748300 1A:496.71 OsEXP4[48] Alpha-expansin OsEXPA4
IWB70449 4B:40.43 Rht1 4B:33.61 DELLA protein
IWB54814 4B:40.59 4B03G0110000 4B:42.02 AT5G39760[50] Zinc finger homeodomain protein
IWB54814 4B:40.59 4B03G0112200 4B:43.56 AT1G09570[51] Phytochrome A
IWB11001 7A:36.31 7A03G0146600 7A:32.23 AT5G13320[52] Auxin-responsive GH3 protein
[1] 何中虎, 庄巧生, 程顺和, 于振文, 赵振东, 刘旭. 中国小麦产业发展与科技进步. 农学学报, 2018, 8(1): 107-114.
doi: 10.11923/j.issn.2095-4050.cjas2018-1-107
He Z H, Zhuang Q S, Cheng S H, Yu Z W, Zhao Z D, Liu X. Wheat production and technology improvement in China. J Agric Sci, 2018, 8(1): 107-114 (in Chinese with English abstract).
[2] 霍治军. 胚芽鞘在小麦抗旱性鉴定中的作用研究. 广西农学报, 2016, 31(3): 8-12.
Huo Z J. Study on the role between the change of coleoptiles and drought-resistance in wheat. J Guangxi Agric, 2016, 31(3): 8-12 (in Chinese with English abstract).
[3] Rebetzke G J, Ellis M H, Bonnett D G, Richards R A. Molecular mapping of genes for coleoptile growth in bread wheat (Triticum aestivum L.). Theor Appl Genet, 2007, 114: 1173-1183.
doi: 10.1007/s00122-007-0509-1 pmid: 17294164
[4] Singh K, Khanna-Chopra R. Physiology and QTL analysis of coleoptile length, a trait for drought tolerance in wheat. J Plant Biol, 2010, 37: 1-9.
[5] Yu J, Bai G. Mapping quantitative trait loci for long coleoptile in Chinese wheat landrace Wangshuibai. Crop Sci, 2010, 50: 43-50.
doi: 10.2135/cropsci2009.02.0065
[6] Schillinger W F U A, Donaldson E, Allan R E, Jones S S. Winter wheat seedling emergence from deep sowing depths. Agron J, 1998, 90: 582-586.
doi: 10.2134/agronj1998.00021962009000050002x
[7] Rebetzke G J, Richards R A, Fettell N A, Long M, Condon A G, Forrester R I, Botwright T L. Genotypic increases in coleoptile length improves stand establishment, vigour and grain yield of deep-sown wheat. Field Crops Res, 2007, 100: 10-23.
doi: 10.1016/j.fcr.2006.05.001
[8] 潘前颖, 文学飞, 潘田园, 史引红, 潘田雨, 潘幸来. 小麦胚芽鞘与耐深播抗旱研究进展. 干旱地区农业研究, 2012, 30(3): 51-57.
Pan Q Y, Wen X F, Pan T Y, Shi Y H, Pan T Y, Pan X L. Wheat coleoptile and emergence vigor and drought-resistance. Agric Res Arid Areas, 2012, 30(3): 51-57 (in Chinese).
[9] Blackburn A, Sidhu G, Schillinger W F, Skinner D, Gill K. QTL mapping using GBS and SSR genotyping reveals genomic regions controlling wheat coleoptile length and seedling emergence. Euphytica, 2021, 217: 45.
doi: 10.1007/s10681-021-02778-z
[10] Rebetzke G J, Verbyla A P, Verbyla K L, Morell M K, Cavanagh C R. Use of a large multiparent wheat mapping population in genomic dissection of coleoptile and seedling growth. Plant Biotechnol J, 2014, 12: 219-230.
doi: 10.1111/pbi.12130 pmid: 24151921
[11] Whan B R W. The emergence of semidwarf and standard wheats, and its association with coleoptile length. Aust J Exp Biol Med Sci, 1976, 16: 411-416.
[12] Rebetzke G J, Richards R A, Sirault X R R, Morrison A D. Genetic analysis of coleoptile length and diameter in wheat. Aust J Agric Res, 2004, 55: 733.
doi: 10.1071/AR04037
[13] Spielmeyer W, Hyles J, Joaquim P, Azanza F, Bonnett D, Ellis M E, Moore C, Richards R A. A QTL on chromosome 6A in bread wheat (Triticum aestivum) is associated with longer coleoptiles, greater seedling vigor and final plant height. Theor Appl Genet, 2007, 115: 59-66.
doi: 10.1007/s00122-007-0540-2 pmid: 17429602
[14] Singh K, Shukla S, Kadam S, Semwal V K, Singh N K, Khanna-Chopra R. Genomic regions and underlying candidate genes associated with coleoptile length under deep sowing conditions in a wheat RIL population. J Plant Biochem Biotechnol, 2015, 24: 324-330.
doi: 10.1007/s13562-014-0277-3
[15] Li G, Xu X, Bai G, Carver B F, Hunger R, Bonman J M, Kolmer J, Dong H. Genome-wide association mapping reveals novel QTL for seedling leaf rust resistance in a worldwide collection of winter wheat. Plant Genome, 2016, 9: 1-12.
[16] Ellis M H, Rebetzke G J, Chandler P, Bonnett D, Spielmeyer W, Richards R A. The effect of different height reducing genes on the early growth of wheat. Functional Plant Biol, 2004, 31: 583-589.
doi: 10.1071/FP03207
[17] Li P J, Chen P, Wu J, Zhang C, Chu D, See G, Brown-Guedira G, Zemetra R, Souza E. Quantitative trait loci analysis for the effect of Rht-Bl dwarfing gene on coleoptile length and seedling root length and number of bread wheat. Crop Sci, 2011, 51: 2561-2568.
doi: 10.2135/cropsci2011.03.0116
[18] Alam M, Kashif M, Easterly A C, Wang F, Boehm J D, Baenziger P S. Coleoptile length comparison of three winter small grain cereals adapted to the great plains. Cereal Res Commun, 2022, 50: 127-136.
doi: 10.1007/s42976-021-00151-3
[19] Botwright T L, Rebetzke G J, Condon A G, Richards R A. Influence of the gibberellin-sensitive Rht8 dwarfing gene on leaf epidermal cell dimensions and early vigour in wheat (Triticum aestivum L.). Ann Bot, 2005, 95: 631-639.
doi: 10.1093/aob/mci069
[20] Bai G, Das M K, Carver B F, Xu X, Krenzer E G. Covariation for microsatellite marker alleles associated with Rht8 and coleoptile length in winter wheat. Crop Sci, 2004, 44: 1187-1194.
doi: 10.2135/cropsci2004.1187
[21] Xiong H, Zhou C, Fu M, Guo H, Xie Y, Zhao L, Gu J, Zhao S, Ding Y, Li Y, Zhang J, Wang K, Li X, Liu L. Cloning and functional characterization of Rht8, a “Green Revolution” replacement gene in wheat. Mol Plant, 2022, 15: 373-376.
doi: 10.1016/j.molp.2022.01.014
[22] Tian X, Xia X, Xu D, Liu Y, Xie L, Hassan M A, Song J, Li F, Wang D, Zhang Y, Hao Y, Li G, Chu C, He Z, Cao S. Rht24b, an ancient variation of TaGA2ox-A9, reduces plant height without yield penalty in wheat. New Phytol, 2022, 233: 738-750.
doi: 10.1111/nph.v233.2
[23] Borrill P, Mago R, Xu T, Ford B, Williams S J, Derkx A, Bovill W D, Hyles J, Bhatt D, Xia X, MacMillan C, White R, Buss W, Molnár I, Walkowiak S, Olsen O, Doležel J, Pozniak C J, Spielmeyer W. An autoactive NB-LRR gene causes Rht13 dwarfism in wheat. Proc Natl Acad Sci USA, 2022, 119: e2085092177.
[24] Abdolshahi R, Foroodi-Safat S, Mokhtarifar K, Ataollahi R, Moud A M, Kazemipour A, Pourseyedi S, Rahmani A. Challenges of breeding for longer coleoptile in bread wheat (Triticum aestivum L.). Genet Resour Crop Evol, 2021, 68: 1517-1527.
doi: 10.1007/s10722-020-01081-5
[25] 袁倩倩, 李卓坤, 田纪春, 韩淑晓. 不同水分胁迫下小麦胚芽鞘和胚根长度的QTL分析. 作物学报, 2011, 37: 294-301.
doi: 10.3724/SP.J.1006.2011.00294
Yuan Q Q, Li Z K, Tian J C, Han S X. QTL mapping for coleoptile length and radicle length in wheat under different simulated moisture stresses. Acta Agron Sin, 2011, 37: 294-301 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2011.00294
[26] Zhang H, Cui F, Wang H. Detection of quantitative trait loci (QTLs) for seedling traits and drought tolerance in wheat using three related recombinant inbred line (RIL) populations. Euphytica, 2014, 196: 313-330.
doi: 10.1007/s10681-013-1035-7
[27] Ma J, Lin Y, Tang S, Duan S, Wang Q, Wu F, Li C, Jiang X, Zhou K, Liu Y. A genome-wide association study of coleoptile length in different Chinese wheat landraces. Front Plant Sci, 2020, 11: 677.
doi: 10.3389/fpls.2020.00677 pmid: 32582239
[28] Sidhu J S, Singh D, Gill H S, Brar N K, Qiu Y, Halder J, Al Tameemi R, Turnipseed B, Sehgal S K. Genome-wide association study uncovers novel genomic regions associated with coleoptile length in hard winter wheat. Front Genet, 2020, 10: 1345.
doi: 10.3389/fgene.2019.01345
[29] Wei N, Zhang S, Liu Y, Wang J, Wu B, Zhao J, Qiao L, Zheng X, Wang J, Zheng J. Genome-wide association study of coleoptile length with Shanxi wheat. Front Plant Sci, 2022, 13: 1016551.
doi: 10.3389/fpls.2022.1016551
[30] Xu D, Hao Q, Yang T, Lyu X, Qin H, Wang Y, Jia C, Liu W, Dai X, Zeng J, Zhang H, He Z, Xia X, Cao S, Ma W. Impact of “Green Revolution” gene Rht-B1b on coleoptile length of wheat. Front Plant Sci, 2023, 14: 1147019.
doi: 10.3389/fpls.2023.1147019
[31] 唐斯. 中国小麦地方品种胚芽鞘生长动态的关联分析. 四川农业大学硕士学位论文, 四川成都, 2019. pp 10-13.
Tang S. Correlation Analysis of Coleoptile Growth Dynamics of Local Wheat Varieties in China. MS Thesis of Sichuan Agricultural University, Chengdu, Sichuan, China, 2019. pp 10-13 (in Chinese with English abstract).
[32] Yin C, Li H, Li S, Xu L, Zhao Z, Wang J. Genetic dissection on rice grain shape by the two-dimensional image analysis in one japonica × indica population consisting of recombinant inbred lines. Theor Appl Genet, 2015, 128: 1969-1986.
doi: 10.1007/s00122-015-2560-7
[33] Holland J B, Nyquist W E, Cervantes Martínez C T. Estimating and interpreting heritability for plant breeding: an update. Plant Breed Rev, 2002, 22: 9-12.
[34] Wen W, He Z, Gao F, Liu J, Jin H, Zhai S, Qu Y, Xia X. A high-density consensus map of common wheat integrating four mapping populations scanned by the 90K SNP array. Front Plant Sci, 2017, 8: 1389.
doi: 10.3389/fpls.2017.01389 pmid: 28848588
[35] Meng L, Li H, Zhang L, Wang J. QTL IciMapping: integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations. Crop J, 2015, 3: 269-283.
doi: 10.1016/j.cj.2015.01.001
[36] Li H, Ye G, Wang J. A modified algorithm for the improvement of composite interval mapping. Genetics, 2007, 175: 361-374.
doi: 10.1534/genetics.106.066811 pmid: 17110476
[37] Wang S, Wong D, Forrest K, Allen A, Chao S, Huang B E, Maccaferri M, Salvi S, Milner S G, Cattivelli L, Mastrangelo A M, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, Lillemo M, Mather D, Appels R, Dolferus R, Brown Guedira G, Korol A, Akhunova A R, Feuillet C, Salse J, Morgante M, Pozniak C, Luo M C, Dvorak J, Morell M, Dubcovsky J, Ganal M, Tuberosa R, Lawley C, Mikoulitch I, Cavanagh C, Edwards K J, Hayden M, Akhunov E. Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array. Plant Biotechnol J, 2014, 12: 787-796.
doi: 10.1111/pbi.2014.12.issue-6
[38] Bradbury P J, Zhang Z, Kroon D E, Casstevens T M, Ramdoss Y, Buckler E S. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 2007, 23: 2633-2635.
doi: 10.1093/bioinformatics/btm308 pmid: 17586829
[39] Yu J, Pressoir G, Briggs W H, Vroh Bi I, Yamasaki M, Doebley J F, Mcmullen M D, Gaut B S, Nielsen D M, Holland J B, Kresovich S, Buckler E S. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet, 2006, 38: 203-208.
doi: 10.1038/ng1702 pmid: 16380716
[40] Zhu T, Wang L, Rimbert H, Rodriguez J C, Deal K R, De Oliveira R, Choulet F, Keeble Gagnère 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. Plant J, 2021, 107: 303-314.
doi: 10.1111/tpj.v107.1
[41] Yang C, Ma B, He S, Xiong Q, Duan K, Yin C, Chen H, Lu X, Chen S, Zhang J. MAOHUZI6/ETHYLENE INSENSITIVE3- LIKE1 and ETHYLENE INSENSITIVE3-LIKE2 regulate ethylene response of roots and coleoptiles and negatively affect salt tolerance in rice. Plant Physiol, 2015, 169: 148-165.
doi: 10.1104/pp.15.00353
[42] Ma B, He S, Duan K, Yin C, Chen H, Yang C, Xiong Q, Song Q, Lu X, Chen H, Zhang W, Lu T, Chen S, Zhang J. Identification of rice ethylene-response mutants and characterization of MHZ7/ OsEIN2 in distinct ethylene response and yield trait regulation. Mol Plant, 2013, 6: 1830-1848.
doi: 10.1093/mp/sst087
[43] Ma B, Yin C, He S, Lu X, Zhang W, Lu T, Chen S, Zhang J S. Ethylene-induced inhibition of root growth requires abscisic acid function in rice (Oryza sativa L.) seedlings. PLoS Genet, 2014, 10: e1004701.
doi: 10.1371/journal.pgen.1004701
[44] Christians M J, Robles L M, Zeller S M, Larsen P B. The eer5 mutation, which affects a novel proteasome-related subunit, indicates a prominent role for the COP9 signalosome in resetting the ethylene-signaling pathway in Arabidopsis. Plant J, 2008, 55: 467-477.
doi: 10.1111/tpj.2008.55.issue-3
[45] Zhang Y, Gong S, Li Q, Sang Y, Yang H. Functional and signaling mechanism analysis of rice CRYPTOCHROME 1. Plant J, 2006, 46: 971-983.
doi: 10.1111/j.1365-313X.2006.02753.x pmid: 16805731
[46] Zeng Y, Schotte S, Trinh H K, Verstraeten I, Li J, Van de Velde E, Vanneste S, Geelen D. Genetic dissection of light-regulated adventitious root induction in Arabidopsis thaliana hypocotyls. IJMS, 2022, 23: 5301.
[47] Stawska M, Oracz K. PhyB and HY5 are involved in the blue light-mediated alleviation of dormancy of Arabidopsis seeds possibly via the modulation of expression of genes related to light, GA, and ABA. IJMS, 2019, 20: 5882.
[48] Choi D, Lee Y, Cho H, Kende H. Regulation of expansion gene expression affects growth and development in transgenic rice plants. Plant Cell, 2003, 15: 1386-1398.
doi: 10.1105/tpc.011965
[49] Zdanio M, Boron A K, Balcerowicz D, Schoenaers S, Markakis M N, Mouille G, Pintelon I, Suslov D, Gonneau M, Höfte H, Vissenberg K. The proline-rich family protein EXTENSIN33 is required for etiolated Arabidopsis thaliana hypocotyl growth. Plant Cell Physiol, 2020, 61: 1191-1203.
doi: 10.1093/pcp/pcaa049
[50] Jiang H, Peng K, Hsu T, Chiou Y, Hsieh H. Arabidopsis FIN219/JAR1 interacts with phytochrome A under far-red light and jasmonates in regulating hypocotyl elongation via a functional demand manner. PLoS Genet, 2023, 19: e1010779.
doi: 10.1371/journal.pgen.1010779
[51] Perrella G, Davidson M L H, O Donnell L, Nastase A, Herzyk P, Breton G, Pruneda-Paz J L, Kay S A, Chory J, Kaiserli E. ZINC-FINGER interactions mediate transcriptional regulation of hypocotyl growth in Arabidopsis. Proc Natl Acad Sci USA, 2018, 115: 4503-4511.
doi: 10.1073/pnas.1718099115 pmid: 29686058
[52] Murphy K, Balow K, Lyon S R, Jones S S. Response to selection, combining ability and heritability of coleoptile length in winter wheat. Euphytica, 2008, 164: 709-718.
doi: 10.1007/s10681-008-9692-7
[53] Zhang N, Pan R Q, Liu J J, Zhang X L, Su Q N, Cui F, Zhao C H, Song L Q, Ji J, Li J M. QTL for sensitivity of seedling height to exogenous GA3 and their effects on adult plant height in common wheat. Cereal Res Commun, 2018, 46: 412-423.
doi: 10.1556/0806.46.2018.021
[54] Francki M G, Stainer G S, Walker E, Rebetzke G J, Stefanova K T, French R J. Phenotypic evaluation and genetic analysis of seedling emergence in a global collection of wheat genotypes (Triticum aestivum L.) under limited water availability. Front Plant Sci, 2021, 12: 796176.
doi: 10.3389/fpls.2021.796176
[55] Nagel M, Navakode S, Scheibal V, Baum M, Nachit M, Röder M S, Börner A. The genetic basis of durum wheat germination and seedling growth under osmotic stress. Biol Plant, 2014, 58: 681-688.
doi: 10.1007/s10535-014-0436-3
[56] Rebetzke G J, Appels R, Morrison A D, Richards R A, McDonald G, Ellis M H, Spielmeyer W, Bonnett D G. Quantitative trait loci on chromosome 4B for coleoptile length and early vigour in wheat (Triticum aestivum L.). Aust J Agric Res, 2001, 52: 1221.
doi: 10.1071/AR01042
[57] Lin Q, Gong J, Zhang Z, Meng Z, Wang J, Wang S, Sun J, Gu X, Jin Y, Wu T, Yan N, Wang Y, Kai L, Jiang J, Qi S. The Arabidopsis thaliana trehalose-6-phosphate phosphatase gene AtTPPI regulates primary root growth and lateral root elongation. Front Plant Sci, 2023, 13: 1088278.
doi: 10.3389/fpls.2022.1088278
[1] ZHANG Zhen, ZHAO Jun-Ye, SHI Yu, ZHANG Yong-Li, YU Zhen-Wen. Effects of different sowing space on photosynthetic characteristics after anthesis and grain yield of wheat [J]. Acta Agronomica Sinica, 2024, 50(4): 981-990.
[2] XU Nai-Yin, JIN Shi-Qiao, JIN Fang, LIU Li-Hua, XU Jian-Wen, LIU Feng-Ze, REN Xue-Zhen, SUN Quan, XU Xu, PANG Bin-Shuang. Genetic similarity and its detection accuracy analysis of wheat varieties based on SNP markers [J]. Acta Agronomica Sinica, 2024, 50(4): 887-896.
[3] HUANG Hong-Sheng, ZHANG Xin-Yue, JU Hui, and HAN Xue. Spectral characteristics of winter wheat canopy and estimation of aboveground biomass under elevated atmospheric CO2 concentration [J]. Acta Agronomica Sinica, 2024, 50(4): 991-1003.
[4] WANG Tian-Ning, FENG Ya-Lan, JU Ji-Hao, WU Yi, ZHANG Jun, MA Chao. Whole genome identification and analysis of GRFs transcription factor family in wheat and its ancestral species [J]. Acta Agronomica Sinica, 2024, 50(4): 897-913.
[5] QI Xue-Li, LI Ying, LI Chun-Ying, HAN Liu-Peng, ZHAO Ming-Zhong, ZHANG Jian-Zhou. Alleviative effect of salicylic acid on wheat seedlings with stripe rust based on transcriptome and differentially expressed genes [J]. Acta Agronomica Sinica, 2024, 50(4): 1080-1090.
[6] JU Ji-Hao, MA Chao, WANG Tian-Ning, WU Yi, DONG Zhong, FANG Mei-E, CHEN Yu-Shu, ZHANG Jun, FU Guo-Zhan. Genome wide identification and expression analysis of TaPOD family in wheat [J]. Acta Agronomica Sinica, 2024, 50(3): 779-792.
[7] ZHANG Bao-Hua, LIU Jia-Jing, TIAN Xiao, TIAN Xu-Zhao, DONG Kuo, WU Yu-Jie, XIAO Kai, LI Xiao-Juan. Cloning, expression, and functional analysis of wheat (Triticum aestivum L.) TaSPX1 gene in low nitrogen stress tolerance [J]. Acta Agronomica Sinica, 2024, 50(3): 576-589.
[8] ZHANG Yue, WANG Zhi-Hui, HUAI Dong-Xin, LIU Nian, JIANG Hui-Fang, LIAO Bo-Shou, LEI Yong. Research progress on genetic basis and QTL mapping of oil content in peanut seed [J]. Acta Agronomica Sinica, 2024, 50(3): 529-542.
[9] WANG Qiong, ZHU Yu-Xiang, ZHOU Mi-Mi, ZHANG Wei, ZHANG Hong-Mei, CEHN Xin, CEHN Hua-Tao, CUI Xiao-Yan. Genome-wide association analysis and candidate genes predication of leaf characteristics traits in soybean (Glycine max L.) [J]. Acta Agronomica Sinica, 2024, 50(3): 623-632.
[10] ZHAO Rong-Rong, CONG Nan, ZHAO Chuang. Optimal phase selection for extracting distribution of winter wheat and summer maize over central subregion of Henan Province based on Landsat 8 imagery [J]. Acta Agronomica Sinica, 2024, 50(3): 721-733.
[11] FAN Zi-Pei, LI Long, SHI Yu-Gang, SUN Dai-Zhen, LI Chao-Nan, JING Rui-Lian. Cloning of TabHLH112-2B gene and development of its functional marker associated with the number of spikelet per spike in wheat [J]. Acta Agronomica Sinica, 2024, 50(2): 403-413.
[12] ZHANG Kang, NIE Zhi-Gang, WANG Jun, LI Guang. Sensitivity analysis and optimization of spring wheat grain growth parameters under APSIM model with the increase of temperature [J]. Acta Agronomica Sinica, 2024, 50(2): 464-477.
[13] TAN Dan, CHEN Jia-Ting, GAO Yu, ZHANG Xiao-Jun, LI Xin, YAN Gui-Yun, LI Rui, CHEN Fang, CHANG Li-Fang, ZHANG Shu-Wei, GUO Hui-Juan, CHANG Zhi-Jian, QIAO Lin-Yi. Discovery of auxin pathway genes involving spike type and association analysis between TaARF23-A and spikelet number in wheat [J]. Acta Agronomica Sinica, 2024, 50(2): 506-513.
[14] LI Yan, FANG Yu-Hui, WANG Yong-Xia, PENG Chao-Jun, HUA Xia, QI Xue-Li, HU Lin, XU Wei-Gang. Transcriptomics profile of transgenic OsPHR2 wheat under different phosphorus stress [J]. Acta Agronomica Sinica, 2024, 50(2): 340-353.
[15] XIE Wei, HE Peng, MA Hong-Liang, LEI Fang, HUANG Xiu-Lan, FAN Gao-Qiong, YANG Hong-Kun. Effects of straw mulching from autumn fallow and phosphorus application on nitrogen uptake and utilization of winter wheat [J]. Acta Agronomica Sinica, 2024, 50(2): 440-450.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] Li Shaoqing, Li Yangsheng, Wu Fushun, Liao Jianglin, Li Damo. Optimum Fertilization and Its Corresponding Mechanism under Complete Submergence at Booting Stage in Rice[J]. Acta Agronomica Sinica, 2002, 28(01): 115 -120 .
[2] Wang Lanzhen;Mi Guohua;Chen Fanjun;Zhang Fusuo. Response to Phosphorus Deficiency of Two Winter Wheat Cultivars with Different Yield Components[J]. Acta Agron Sin, 2003, 29(06): 867 -870 .
[3] YANG Jian-Chang;ZHANG Jian-Hua;WANG Zhi-Qin;ZH0U Qing-Sen. Changes in Contents of Polyamines in the Flag Leaf and Their Relationship with Drought-resistance of Rice Cultivars under Water Deficiency Stress[J]. Acta Agron Sin, 2004, 30(11): 1069 -1075 .
[4] Yan Mei;Yang Guangsheng;Fu Tingdong;Yan Hongyan. Studies on the Ecotypical Male Sterile-fertile Line of Brassica napus L.Ⅲ. Sensitivity to Temperature of 8-8112AB and Its Inheritance[J]. Acta Agron Sin, 2003, 29(03): 330 -335 .
[5] Wang Yongsheng;Wang Jing;Duan Jingya;Wang Jinfa;Liu Liangshi. Isolation and Genetic Research of a Dwarf Tiilering Mutant Rice[J]. Acta Agron Sin, 2002, 28(02): 235 -239 .
[6] WANG Li-Yan;ZHAO Ke-Fu. Some Physiological Response of Zea mays under Salt-stress[J]. Acta Agron Sin, 2005, 31(02): 264 -268 .
[7] TIAN Meng-Liang;HUNAG Yu-Bi;TAN Gong-Xie;LIU Yong-Jian;RONG Ting-Zhao. Sequence Polymorphism of waxy Genes in Landraces of Waxy Maize from Southwest China[J]. Acta Agron Sin, 2008, 34(05): 729 -736 .
[8] HU Xi-Yuan;LI Jian-Ping;SONG Xi-Fang. Efficiency of Spatial Statistical Analysis in Superior Genotype Selection of Plant Breeding[J]. Acta Agron Sin, 2008, 34(03): 412 -417 .
[9] WANG Yan;QIU Li-Ming;XIE Wen-Juan;HUANG Wei;YE Feng;ZHANG Fu-Chun;MA Ji. Cold Tolerance of Transgenic Tobacco Carrying Gene Encoding Insect Antifreeze Protein[J]. Acta Agron Sin, 2008, 34(03): 397 -402 .
[10] ZHENG Xi;WU Jian-Guo;LOU Xiang-Yang;XU Hai-Ming;SHI Chun-Hai. Mapping and Analysis of QTLs on Maternal and Endosperm Genomes for Histidine and Arginine in Rice (Oryza sativa L.) across Environments[J]. Acta Agron Sin, 2008, 34(03): 369 -375 .