Welcome to Acta Agronomica Sinica,

Acta Agronomica Sinica ›› 2023, Vol. 49 ›› Issue (1): 86-96.doi: 10.3724/SP.J.1006.2023.12079

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

Genome-wide association analysis of indica-rice heading date based on NCII genetic mating design

XU Kai1(), ZHENG Xing-Fei2, ZHANG Hong-Yan1, HU Zhong-Li3, NING Zi-Lan1, LI Lan-Zhi1,*()   

  1. 1Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-making, College of Plant Protection, Hunan Agricultural University, Changsha 410128, Hunan, China
    2Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crop Institute, Hubei Academy of Agricultural Sciences, Wuhan 430064, Hubei, China
    3Key Laboratory of Hybrid Rice, College of Life Science, Wuhan University, Wuhan 430072, Hubei, China
  • Received:2021-12-16 Accepted:2022-05-05 Online:2023-01-12 Published:2022-05-23
  • Contact: LI Lan-Zhi E-mail:kratix_01279@163.com;lancy0829@163.com
  • Supported by:
    Open Project of the State Key Laboratory of Hybrid Rice (Hunan Hybrid Rice Research Center)(2019KF05);State Key Laboratory of Hybrid Rice (Wuhan University)(KF201912);Hunan Provincial Department of Education(19A244);Natural Science Foundation of Hunan Province(2020JJ4039);Natural Science Foundation of Hunan Province(2021JJ30351);Special Funds for Construction of Innovative Provinces in Hunan Province(2021NK1011)

Abstract:

Heading date is jointly regulated by light and temperature resources and gene network, affecting crop yield and regional adaptability of varieties. Identification of significant loci and genes associated with trait variation by genome-wide association analysis (GWAS) is of great significance to analyze the genetic basis of the heading date in rice. In this study, according to the North Carolina design II (NCII), 115 indica rice varieties as the male parents and 5 sterile lines as the female parents had been made test cross, and 575 F1 test-cross lines were obtained. GWAS was performed on the phenotypic value of the heading date of the male parental varieties (V) and testcross lines (TC), the general combining ability (GCA) of the male parent lines, the special combining ability (SCA), and better parent heterosis (BPH) of testcross lines. (1) A total of 104 significantly associated locus were located and distributed on 12 chromosomes. Of these, 16 significantly associated locus were detected on chromosome 4. There were six, five, fifteen, fifty-seven, and twenty-one significantly associated locus detected in V, GCA, TC, SCA, BPH data sets, respectively. Phenotypic variation analysis of significantly associated sites in these five data sets revealed that the total contribution rate (phenotypic variation explained, PVE) of significantly associated loci to phenotypic variation in V, GCA, TC, SCA, and BPH data sets was 79.57%, 10.51%, 33.35%, 56.42%, and 54.86%, respectively. Twenty-five significantly associated locus were simultaneously detected in two or more than two datasets, that probably was hotspot genomic region of heading date in rice. (2) By comparing all significantly associated locus with the annotation information of the Nipponbare reference genome, five cloned genes related to heading date were found. Among them, three of the five genes within 200 kb from the significantly associated locus detected in this study. Compared with the haplotype combinations in the three genes with the superior haplotype of individual clone gene, we found that the average grain yield per plant of male parental varieties with the haplotype combination SDG724 (Hap. A)_Hd17 (Hap. E)_Ghd7 (Hap. A) was higher and the heading date period was longer. The results indicated that the pyramiding superior haplotype of genes related to heading date would extend the heading date period of conventional rice varieties and improve their yield. However, the situation was different for testcross population, the haplotype combination form of SDG724 (Hap. I)_Hd17 (Hap. K)_Ghd7 (Hap. I) had the superior yield but median heading date period. None superior haplotype pyramiding resulting in high yield or long heading date was found in the testcross lines population, indicating that the genetic basis of heading date of testcross hybrids was more complicated than rice varieties. The combination of genome-wide association analysis and haplotype analysis can utilize the linkage disequilibrium information provided by multiple SNPs, which improves the efficiency of gene detection and facilitates the cultivation of high-yield rice varieties.

Key words: rice, heading date, genome-wide association analysis, haplotype, North Carolina design II

Table S1

Information of 115 varieties and 5 sterile lines used in cross experiment"

编号
Code
材料名称
Material name
编号
Code
材料名称
Material name
编号
Code
材料名称
Material name
V1 矮仔占 Aizizhan V41 88B V81 IRAT109
V2 东秋播 Dongqiubo V42 湘恢91269 Xianghui 91269 V82 华粳籼74 Huajingxian 74
V3 广秋矮 Guangqiu’ai V43 陆财号 Lucaihao V83 紫恢100 Zihui 100
V4 广场矮3784 Guangchang’ai 3784 V44 蜀丰101 Shufeng 101 V84 Varylava
V5 青丰矮 Qingfeng’ai V45 成都矮3号Chengdu’ai 3 V85 D62B
V6 江二矮 Jiang’er’ai V46 三颗寸 Sankecun V86 G46B
V7 青二矮 Qing’er’ai V47 加巴拉 Jiabala V87 IR58025B
V8 鸡对伦 Jiduilun V48 台山糯 Taishannuo V88 中9B Zhong 9B
V9 阔叶稻 Kuoyedao V49 桂朝2号 Guichao 2 V89 香5 Xiang 5
V10 叶青仑 Yeqinglun V50 沪科3号 Huke 3 V90 闷加高2 Menjiagao 2
V11 陆财号 Lucaihao V51 特青选恢 Teqingxuanhui V91 鄂香1号 Exiang 1
V12 华南15 Huanan 15 V52 黄丝桂占 Huangsiguizhan V92 Q198
V13 广场矮 Guangchang’ai 4182 V53 湘晚籼3号 Xiangwanxian 3 V93 黄秀占 Huangxiuzhan
V14 桂阳矮49 Guiyang’ai 49 V54 金优1号 Jinyou 1 V94 蜀恢527 Shuhui 527
V15 朝阳早18 Chaoyangzao 18 V55 成农水晶 Chengnongshuijing V95 蜀恢288 Shuhui 288
V16 桂朝2号 Guichao 2 V56 墨米Momi V96 蜀恢707 Shuhui 707
V17 广场13 Guangchang 13 V57 三百粒Sanbaili V97 龙恢11 Longhui 11
V18 丰青矮 Fengqing’ai V58 柳沙1号Liusha 1 V98 南恢511 Nanhui 511
V19 青农矮 Qingnong’ai V59 洞庭晚籼Dongtingwanxian V99 湘恢529 Xianghui 529
V20 丰矮占1号Feng’aizhan 1 V60 扬稻2号 Yangdao 2 V100 金恢275 Jinhui 275
V21 黄华占 Huanghuazhan V61 六十早 Liushizao V101 泸恢5240 Luhui 5240
V22 黄新占 Huangxinzhan V62 台中籼选2 Taozhongxianxuan 2 V102 明恢2088 Minghui 2088
V23 28占 28 Zhan V63 南特号 Nantehao V103 山恢287 Shanhui 287
V24 丰华占 Fenghuazhan V64 黑督4号 Heidu 4 V104 山恢8281 Shanhui 8281
V25 青六矮 Qingliu’ai V65 金南特43B Jinnante 43B V105 R238
V26 丰八占 Fengbazhan V66 湘早籼7号Xiangzaoxian 7 V106 R727
V27 长丝占 Changsizhan V67 80B V107 205R
V28 华丝占 Huasizhan V68 包协123B Baoxie123B V108 781R
V29 扬稻2号 Yangdao 2 V69 江农早1号 Jiangnongzao 1 V109 3301R
V30 扬稻六号 Yangdao 6 V70 古154 Gu 154 V110 IR24
V31 特青 Teqing V71 献改B Xiangai B V111 IR1544
V32 Sadu-cho V72 矮沱谷151 Aituogu 151 V112 圭630 Gui 630
V33 山黄占 Shanhuangzhan V73 闷加丁2 Menjiading 2 V113 辐36-2 Fu 36-2
V34 IR64 V74 解放籼 Jiefangxian V114 R1318
V35 N22 V75 白壳花螺 Baikehualuo V115 T9311
V36 矮脚南特 Aijiaonante V76 柳叶占 Liuyezhan AS 新安S Xin’an S
V37 广陆矮4号 Guanglu’ai 4 V77 珍汕97 Zhenshan 97 3A 珞红3A Luohong 3A
V38 湘矮早10号 Xiang’aizao 10 V78 明恢63 Minghui 63 Y58S Y58S
V39 青四矮16B Qingsi’ai 16B V79 9311 GZ63 广占63S Guangzhan 63S
V40 滇瑞409B Dianrui 409B V80 南京11 Nanjing 11 PA64 矮培64S Aipei 64S

Fig. 1

Distribution of phenotypic values of heading date in the population of parental varieties (V) and testcross lines (TC) (A): boxplot of phenotypic values of heading date in the population of parental varieties (V) and testcross lines (TC); (B): histogram of phenotypic values of heading date in the testcross population; (C): histogram of phenotypic values of heading date in the parental variety population."

Fig. 2

Population structure of parent and testcross populations A: the genetic structure of the parental variety population; B: K-value of the parental variety population; C: the genetic structure of the testcross population; D: K-value of the testcross population."

Fig. S1

PCA diagram of parent population and test cross population a, b,c are the 2D-PCA plots of the parental population, and d is the 3D-PCA plot; e, f, g are the 2D-PCA plots of the test cross population, and h is the 3D-PCA plot."

Fig. S2

Manhattan plot and quantile-quantile plot of GLM model"

Fig. S3

Manhattan plot and quantile-quantile plot of MLM model"

Fig. S4

Manhattan plot and quantile-quantile plot of FarmCPU model"

Table S2

Genome-wide association signals of heading date in indica rice"

数据集
DataSet
染色体
Chr.
起始位置
Start
终止位置
End
−log10 (P)最高的位点
Highest association site
P值负对数
−log10 (P)
表型方差解释率 Phenotypic variation explained (%) 克隆基因
Cloned gene
V 3 34355029 34355029 chr03_34355029 7.58 10.46 SNAC1; SPIN1; OsPHY2; OsIDS1; gh1; ZFP182; ZFP15; OsADF3;
OsRLCK118
4 4302632 4302632 chr04_4302632 5.32 24.26 OsEMF2a; ART2; OsCAS
6 4730505 4730505 chr06_4730505 10.14 8.89 OsPTF1; OsERF71; OsKASI; OsARF16
9 7869103 7869103 chr09_7869103 6.76 11.15 OsbZIP71; OsMED25; OsEMF2b; SDG724
10 16080525 16080525 chr10_16080525 6.55 22.07 OsCDC48E; OsABCG25; OsPht1; OsPht1; OsHCI1; OsMTA4
12 15155333 15155333 chr12_15155333 6.76 2.73 PIOX
GCA 1 33603983 33603983 chr01_33603983 6.86 0.40 OsGH3-1; OsPME1; OsERF3
2 4065908 4065908 chr02_4065908 5.98 5.44 OsALDH5F1; OsDPK2
4 20338147 20338147 chr04_20338147 5.19 0.53 OSINV4; GIF1; ACL1; COPT4
6 4745474 4745474 chr06_4745474 8.93 4.10 OsPTF1; OsERF71; SUS2; OsKASI; OsARF16;
11 27790672 27790672 chr11_27790672 5.62 0.04 JAmyb; Pikp_2
TC 1 35427407 35427407 chr01_35427407 7.16 5.07 OsWRKY24; OsYSL18; LAX1; OsBAG4; OsAMT2
2 28380703 28380703 chr02_28380703 7.16 9.44 OsPIE1; 709
3 2085577 2085577 chr03_2085577 5.39 2.61 RAI1; OsCYP96B4; OsDSS1; sd37; bsh1
3 14946317 14946317 chr03_14946317 7.71 0.07 OsIRO3
4 27992334 27992334 chr04_27992334 12.03 3.52 OsHMA5; OsGPX1; cZOGT1; Kala4; OsPIP1; 2; SMG2; OsMKKK10;
OsCPK12; es4
5 16703102 16703102 chr05_16703102 9.5 0.11 YGL1; ygl80; OsEm1; EMP1; OsImp
6 4745474 4831914 chr06_4831914 13.67 3.29 OsPTF1; OsERF71; RSUS2; RSs1; SUS2; OsKASI; OsARF16
7 9578963 9578963 chr07_9578963 6.92 0.30 Ghd7
7 26527050 26562456 chr07_26527050 5.18 0.85 OsLti6a; OsPDK1; Os-eIF6; 1; OsPRMT3; OsHsfB4b
7 26965963 26965963 chr07_26965963 6.21 0.11 OsbZIP60; qHMS7-ORF1; qHMS7-ORF3; CYP734A5
10 2918961 2918961 chr10_2918961 7.15 2.75 OsDIL; OsLTP6; OsPRP2; OsPRP1
11 17832018 17832018 chr11_17832018 5.62 0.91 OsHSD1; OsSOT1; STV11
12 730797 730797 chr12_730797 5.64 4.08 OsCIPK14
12 3864512 3864512 chr12_3864512 8.41 0.10 Osmyb2; OsGRX27; OsALDH3H1; OsAPx7; OsAPx6; OsAPx5
12 11533522 11533522 chr12_11533522 8.44 0.15
SCA 2 2645592 2789913 chr02_2645592 5.82 0.58 OseIF4A; OsMAPK33; OsMPK14; OsMPK3; OsPP18; OsRBCS1; LC2;
OsVIL3; YL1; LRK1
2 4255102 4310130 chr02_4255102 6.38 3.19 OsDPK2; Os4CL3; OsGL1-2
2 8481676 8481676 chr02_8481676 6.7 1.13 GluD; GluD-1; GluB1; GluB1; RPBF; OsDof3; OsDof-10; OsDof7
2 29065323 29065323 chr02_29065323 7.06 2.23 OSOTP51; OsABA8ox1
2 35116043 35133182 chr02_35116043 7.35 0.89 OsABC1-4; OsNDUFA9; flo13; OsIAA10; RTBP1; CYP97A4;
OsCBSX3; OsLpa1
3 23813743 23813743 chr03_23813743 5.75 0.04
4 18157266 18216943 chr04_18216943 5.31 0.11
4 18903071 18907437 chr04_18903071 6.46 2.19 OsExo70‐F3
4 19647607 19647607 chr04_19647607 6.36 0.30 OsAFB2; OsJAZ5; OsTIFY9; LAX2; Gnp4; OsClpC1; OsRap2.6; pi21
4 19894988 20618276 chr04_19931704 8.65 0.66 pi21; OsHAK1; OsClpD2; OSINV4; GIF1; OsCIN2; ACL1; COPT4
4 20879608 21022879 chr04_20890026 7.76 1.05 Asr4; ASR6; OsASR2
4 22158990 22189682 chr04_22164037 5.6 0.33 OsRR1; OsFRO1; OsAP37; OSZEP1
4 23386304 23437449 chr04_23386304 5.86 2.07 MOF; OsGASR2; d11; CYP724B1; CPB1; sg4; cl4; OsMYB80;
OsMYB103
4 23998714 23998714 chr04_23998714 7.28 1.17 Rf17; RMS; CRC1; OsPIMT2; OsWS1; WSL3
4 24214858 24214858 chr04_24214858 5.03 0.03 OsPIMT2; OsWS1; WSL3; OsRAD21-2
4 27009473 27236519 chr04_27058044 9.28 0.10 Glup3; OsVPE1; OsALDH3B1; OsLCBK2; Oshox22; OsYSL16; SDG703; OsERF1
4 35115325 35115325 chr04_35115325 6.27 2.23 OsBSK3; OsCAF1B
5 2264054 2450291 chr05_2284407 8.17 0.68 OsSAMS1; OsPti1a; OsLti6b; ddOs32; APG; OsMYB2P-1; OsMPK14; OsGH3-6; OsPPKL2; PTB1; OsVIL4
5 3049063 3158516 chr05_3111450 6.4 1.22 OsGRX15; OsTIR1; APIP6; SRS3; OsKinesin-13A; sar1; Chalk5
5 3511793 3814100 chr05_3607357 7.21 1.99 Chalk5; GS5; OsZIP6
5 17826917 17826917 chr05_17826917 5.04 0.87 OsBiP3; RH1; OsFTIP7; OsRLCK185
5 18633931 18854859 chr05_18633931 5.66 0.90 OsBC1L4; OsNADK3; SMOS1; shb; RLA1
5 20101785 20464861 chr05_20101785 7.02 0.91 TCD5; OsbZIP39; OsPCS1; TCM5; SERF1; OsCc1
5 21819212 23047221 chr05_22813721 6.34 1.09 OsAUX1; OsCOI1b; SH5; OsP5CS; OsP5CS1; OsALDH18B1; Osrboh4; OsAMT2; 1; OsPDC1; OsZIP5
5 23534940 23549991 chr05_23545588 6.84 1.22 OsAMTR1; OsSTN8; EUI1; i-sd-1(t)
5 23946757 23946757 chr05_23946757 5.85 3.93 OsDMI3; Osmyb5; SDG728; SDG728; OsCML9; OsCam2
6 2160801 2160801 chr06_2160801 5.12 0.02 dp1; DDF1; OsENOD93a; Hd17; Ef7; OsELF3; OsELF3-1; OsELF3.1; Hd-q; OsPRMT10; SPDT
6 21268145 21268145 chr06_21268145 5.23 0.56
6 25011887 25011887 chr06_25011887 5.46 0.86 OsARID3; OsbZIP50; OsbZIP74; TGW6; SPP
6 25716036 25716036 chr06_25716036 5.46 0.86 OsPSK
6 26086130 26086130 chr06_26086130 5.35 0.52 DCM1; OsSAL1; OVP1; OsVP1
6 26870826 26894242 chr06_26884987 6.32 1.35 OsRpoTp; OsGL1-3; Os4CL4
6 27148504 27148504 chr06_27148504 6.32 0.38 OsGRX18; OsPIN2; OsPLS1; OsbZIP52; RISBZ5
7 7918837 7918837 chr07_7918837 5.29 0.11 OsAPL4; OsAGPL4
7 8181872 8485133 chr07_8181872 5.29 0.76 OsAPL4; OsAGPL4; LLB; pls3; OsMTS1
7 9129150 9129150 chr07_9129150 5.32 0.15 OsNRAMP1; Ghd7
7 10123301 10123301 chr07_10123301 5.32 0.24
7 26337284 26337284 chr07_26337284 7.73 2.36 RNP29; OsRH36; OsLti6a; OsPDK1
7 27649737 27670134 chr07_27649737 5.09 1.25 NTRC; SPIN6; Fd-GOGAT1; lc7; ABC1; spl23
8 6184657 6293033 chr08_6184657 5.76 0.73 OsHAK12; SPL29; UAP1; OsZIP4
8 7502244 7502244 chr08_7502244 5.76 0.36 OsVIL1; OsDPK1; zl16; OsHAD1
8 9334312 9354921 chr08_9354921 7.8 1.41
8 15462160 15462160 chr08_15462160 5.66 3.11 OsBRL3; HDA705
8 20967437 20988336 chr08_20981726 5.25 0.17 GF14c; 14-3-3; OsMYB106; ONAC106
10 1520673 1520673 chr10_1520673 6.73 0.03 OsSNDP1; OsADF
10 15824748 15824748 chr10_15824748 6.07 0.09
10 16100848 16100848 chr10_16100848 7.25 0.20 OsPht1; 8; OsPT8; OsHCI1
10 16334199 16334199 chr10_16334199 5.53 0.24 Osgrp-2
10 22283651 22283651 chr10_22283651 6.51 0.92 MYBS3; OsHox1; REL2; CycP4; 1; CYCU4; 1; OsSAPK3; REK; OsCBL1; OsHUB2; FRRP1; OsCAO2
10 23018816 23183833 chr10_23018816 6.96 0.16 OsMYC2; OsITPK5; JMJ706; OsSRO1a; OsCSLD1; rth-2; OsDUR3
11 1762018 1762018 chr11_1762018 5.66 0.12 OsCML2; OsCPK25
11 10572420 10572420 chr11_10572420 5.36 0.10
11 22419901 22419901 chr11_22419901 5.66 0.52 BGL11(t)
11 27487132 27487132 chr11_27487132 5.02 2.32 OsGPAT3; OsJAMyb
11 28800508 28800508 chr11_28800508 5.02 1.27 DHD1; CycD7; 1; WDL1
12 14124949 14125467 chr12_14124949 7.3 3.19 OsNCED2
12 16519849 16519849 chr12_16519849 5.31 0.98 DEC
BPH 1 33223657 34531439 chr01_34042495 7.89 1.68 OsKTN80c; Pish; OsGH3.1; LC1; OsPME1; OsERF3; OsAP37; CycB1; 1; OsLRR1; OsCML1; OsCam3; OsCaM61; SDG709; OsGAmyb; MYBGA; OsNAC4; ONAC068
2 24241454 24241454 chr02_24241454 5.01 7.46 du3; OsCBP20; OsNST1; BC14; BBM2; LP2
2 28453213 28453213 chr02_28453213 5.07 5.16 OsPIE1; 709
2 28881879 28881879 chr02_28881879 5.33 5.16 AOX1c; OsPUT1; OsBRXL1; OsGRF4; GS2; GL2; PT2; LGS1; OSOTP51; OsABA8ox1
2 29687730 29687730 chr02_29687730 5.72 1.27 Os4CL2; AOX1c; OsPUT1; OsBRXL1; OsGRF4; GS2; OSOTP51; OsABA8ox1; ADL1; OsDEK1; OsGAP1; OsFAD2-1; Ghd2; DTH2
3 4911745 4911745 chr03_4911745 5.46 5.40 OsRab6a; OsDSR4; pRINO1; OsINO1-1
3 13598822 13598822 chr03_13598822 5.04 5.80 OsDIS1; VLN2
4 4804275 4804275 chr04_4804275 5.7 4.53 ETR2; OS-ETR2
4 5307896 5307896 chr04_5307896 5.33 0.83 OsCPS4; OsCyc1; CYP99A3; OsMAS; OsDTS2; OsKSL4; KS4;
CYP99A2
5 16703102 16703102 chr05_16703102 5.96 0.11 YGL1; ygl80; OsEm1; EMP1; OsImp
6 17983222 17983222 chr06_17983222 7.23 0.24
11 3977659 3977659 chr11_3977659 15.42 5.24
11 10747918 10763678 chr11_10747918 5.13 1.20 BBM1
12 3970723 3970723 chr12_3970723 5.44 1.91 Osmyb2; OsGRX27; OsALDH3H1; OsAPx7; OsAPx6; OsAPx5
12 10735585 10735585 chr12_10735585 5.73 0.67 Pita; Pi-4a; MIR
12 11432955 11432955 chr12_11432955 5.47 0.62 OsRBCS3; OsRBCS5; OsRBCS4
12 11767635 11767635 chr12_11767635 5.47 0.62
12 12314314 12314314 chr12_12314314 6.04 1.27
12 13772007 13772007 chr12_13772007 5.47 0.62
12 14602287 14602287 chr12_14602287 11.49 4.68
12 24447076 24447076 chr12_24447076 5.11 0.37 CycD5

Fig. 3

Manhattan plot and quantile-quantile plot of Blink model of heading date Black dashed vertical line indicates the overlapped significantly associated loci detected in two or more than two datasets; blue dashed vertical line indicates the significantly associated loci within 200 kb genomic region detected in two or more than two datasets. The genes highlighted in red, blue, and green represents the cloned gene related to heading date with 200 kb, 200-500 kb, and 500 kb-1 Mb of genomic region, respectively."

Table S3

Significant associated loci (SALs) detected in multiple data sets"

SAL 数据集
DataSet
染色体
Chromosome
起始位置
Start
终止位置
End
关联到阈值水平最高的位点
Highest Association Site
P值负对数
−log10 (P)
SAL1 V 6 4730505 4730505 chr06_4730505 10.14061526
V 10 16080525 16080525 chr10_16080525 6.545290071
GCA 1 33603983 33603983 chr01_33603983 6.85737051
GCA 2 4065908 4065908 chr02_4065908 5.976967
GCA 4 20338147 20338147 chr04_20338147 5.185557
GCA 6 4745474 4745474 chr06_4745474 8.926052
TC 2 28380703 28380703 chr02_28380703 7.163092
TC 5 16703102 16703102 chr05_16703102 6.499328302
TC 7 26527050 26562456 chr07_26527050 5.176122719
TC 12 3864512 3864512 chr12_3864512 8.410424
TC 12 11533522 11533522 chr12_11533522 8.43912
SCA 2 29065323 29065323 chr02_29065323 7.064964096
SCA 11 10572420 10572420 chr11_10572420 5.360353371
SAL2 TC 6 4745474 4831914 chr06_4831914 13.66548
SCA 10 16100848 16100848 chr10_16100848 7.247927987
BPH 1 33223657 34531439 chr01_34042495 7.888104243
SCA 2 4255102 4310130 chr02_4255102 6.381851153
SCA 4 19894988 20618276 chr04_19931704 8.646770265
TC 6 4745474 4831914 chr06_4831914 13.66548
BPH 2 28453213 28453213 chr02_28453213 5.07193869
BPH 5 16703102 16703102 chr05_16703102 5.960448446
SCA 7 26337284 26337284 chr07_26337284 7.734907569
BPH 12 3970723 3970723 chr12_3970723 5.436513114
BPH 12 11432955 11432955 chr12_11432955 5.470334349
BPH 2 28881879 28881879 chr02_28881879 5.326320712
BPH 11 10747918 10763678 chr11_10747918 5.125963338

Table 1

Corresponding phenotype of excellent haplotype in each gene"

数据集
Data set
基因
Gene name
优异单倍型
Superior haplotype
抽穗期
Heading days (d)
产量
Yield (g)
V SDG724 Hap. A 93.07±7.06 29.68±11.05
Hd17 Hap. E 93.51±6.41 30.18±10.11
Ghd7 Hap. A 93.96±6.26 30.15±9.05
TC SDG724 Hap. I 93.00±6.68 42.73±13.54
Hd17 Hap. P 93.49±6.44 43.38±13.49
Ghd7 Hap. H 90.09±7.21 43.81±12.86

Table S4

The haplotype analysis for gene SDG724 of heading date"

SNP 亲本抽穗期表型V 子代抽穗期表型TC
Hap.A Hap.B Hap.C Hap.D Hap.E Hap.F Hap.G Hap.H Hap.I Hap.J Hap.K Hap.L Hap.M Hap.N Hap.O Hap.P Hap.Q
chr09_8039256 CC CC TT TT TT TT TT TT CC CC CT CT CT CT CT CT CT
chr09_8039344 GG GG AA AA GG GG GG GG GG GG AG AG GG GG GG GG GG
chr09_8039349 CC CC AA AA AA AA AA AA CC CC AC AC AC AC AC AC CC
chr09_8039459 CC CC CC CC AA AA AA CC CC CC CC CC AC AC AC CC CC
chr09_8039498 AA AA TT TT TT TT TT TT AA AA AT AT AT AT AT AT AA
chr09_8039637 CC CC GG GG GG GG GG GG CC CC CG CG CG CG CG CG CG
chr09_8040762 AA AA GG GG GG GG GG GG AA AA AG AG AG AG AG AG AG
chr09_8040844 CC CC GG GG GG GG GG GG CC CC CG CG CG CG CG CG CC
chr09_8041219 CC CC GG GG GG GG GG GG CC CC CG CG CG CG CG CG CC
chr09_8041764 TT TT AA AA AA AA AA AA TT TT AT AT AT AT AT AT TT
chr09_8042022 CC CC TT TT CC CC CC CC CC CC CT CT CC CC CC CC CC
chr09_8042255 AA AA AA GG GG GG GG GG AA AA AA AG AG AG AG AG AA
chr09_8042778 AA AA GG GG GG GG GG GG AA AA AG AG AG AG AG AG AA
chr09_8042789 TT TT CC CC TT TT TT TT TT TT CT CT TT TT TT TT TT
chr09_8043742 TT TT GG GG GG GG GG GG TT TT GT GT GT GT GT GT TT
chr09_8043997 GG GG GG GG AA AA GG GG GG GG GG GG AG AG GG GG GG
chr09_8044399 GG GG CC CC CC CC CC CC GG GG CG CG CG CG CG CG GG
chr09_8044407 TT TT CC CC CC CC CC CC TT TT CT CT CT CT CT CT TT
chr09_8044747 AA AA GG GG GG GG GG GG AA AA AG AG AG AG AG AG AA
chr09_8044939 CC CC TT TT CC CC CC TT CC CC CT CT CC CC CC CT CC
chr09_8044997 TT TT CC CC TT TT TT TT TT TT CT CT TT TT TT TT TT
chr09_8045096 CC CC TT TT CC TT TT TT CC CC CT CT CC CT CT CT CC
chr09_8045337 AA AA CC CC CC CC CC CC AA AA AC AC AC AC AC AC AA
chr09_8045404 TT TT CC CC CC CC CC CC TT TT CT CT CT CT CT CT TT
chr09_8045607 TT TT CC CC CC CC CC CC TT TT CT CT CT CT CT CT CT
chr09_8045608 GG GG AA AA AA AA AA AA GG GG AG AG AG AG AG AG GG
chr09_8045752 TT TT TT TT GG GG GG TT TT TT TT TT GT GT GT TT TT
chr09_8045837 GG GG AA AA AA AA AA AA GG GG AG AG AG AG AG AG GG
chr09_8045891 CC CC CC CC TT TT TT CC CC CC CC CC CT CT CT CC CC
chr09_8046082 AA AA GG GG GG GG GG GG AA AA AG AG AG AG AG AG AG
chr09_8046222 GG GG AA AA AA AA AA AA GG GG AG AG AG AG AG AG GG
chr09_8046390 TT TT AA AA TT TT TT TT TT TT AT AT TT TT TT TT TT
chr09_8046463 AA AA AA AA GG GG GG AA AA AA AA AA AG AG AG AA AA
chr09_8046722 AA GG GG GG GG GG GG GG AA AG AG AG AG AG AG AG AA

Table S5

The corresponding heading date and yield performance to the haplotype of gene SDG724"

数据集
Dataset
单倍型
Haplotype
抽穗期
hd (mean±sd, d)
产量
yield (mean±sd, g)
数量
Count
V Hap.A 93.07±7.06 29.67±11.01 48
Hap.B 80.5±NA 47.21±NA 1
Hap.C 98±9.19 29.51±11.45 2
Hap.D 89.26±8.49 27.93±8.99 37
Hap.E 92.5±NA 18.36±NA 1
Hap.F 93.62±5.12 28.59±10.24 17
Hap.G 85.25±15.91 37.25±20 2
Hap.H 89.12±4.46 37.07±20.21 4
TC Hap.I 92.81±6.98 42.72±14.07 224
Hap.J 87.7±10.37 33.4±4.38 5
Hap.K 88.15±16.29 36.11±10.99 10
Hap.L 91.76±9.51 41.83±12.97 158
Hap.M 95.9±4.16 56.53±17.87 5
Hap.N 90.38±10.54 39.53±13.1 74
Hap.O 94.31±5.5 58.29±21.91 8
Hap.P 86.94±9.7 33.4±14.23 17
Hap.Q 98.5±3.67 43.86±17.47 5

Table S6

The haplotype analysis for gene Ghd7 of heading date"

数据集
DataSet
单倍型
Haplotype
chr07_9152479 chr07_9152659 chr07_9154485 chr07_9154489 抽穗期
hd (mean±sd, d)
产量
yield (mean±sd, g)
数量
Count
V Hap.A CC CC GG GG 93.96±6.16 29.09±9.91 57
Hap.B GG CC GG GG 87.3±9 29.88 ± 12.85 5
Hap.C GG TT TT CC 89.31±8.24 29.67±11.75 50
TC Hap.D CC CC GG GG 95.7±6.75 42.4±11.44 48
Hap.E CG CC GG GG 93.38±6.7 39.94±12.84 118
Hap.F CG CT GT CG 93.46±8.4 41.16±15.06 143
Hap.G GG CC GG GG 85.64±15.42 43.47±23.5 11
Hap.H GG CT GT CG 89.37±8.82 43.59±12.83 102
Hap.I GG TT TT CC 88.85±10.05 42.96±14.85 84

Table S7

The haplotype analysis for gene Hd17 of heading date"

数据集
DataSet
单倍型
Haplotype
chr06_2234168 chr06_2234700 chr06_2234735 chr06_2235191 chr06_2235522 chr06_2236645 chr06_2237266 chr06_2237521 chr06_2238002 chr06_2238193 chr06_2238719 chr06_2239035 抽穗期
hd
(mean±sd, d)
产量
yield
(mean±sd, g)
数量
Count
V Hap.A GG CC GG GG CC AA AA GG AA CC AA GG 91.11±8 29.52±11.32 63
Hap.B GG CC GG GG CC AA TT GG AA CC AA GG 89.29±7.72 24.97±7.54 7
Hap.C GG CC GG GG CC GG AA AA GG GG AA GG 87.25±8.96 20.01±2.59 4
Hap.D TT TT AA AA TT AA AA AA GG CC GG GG 80.5±NA 47.21±NA 1
Hap.E TT TT AA AA TT GG AA AA GG GG GG TT 93.52±6.41 30.18±10.11 33
Hap.F TT TT AA GG TT GG AA AA GG GG GG TT 94.25±7.46 33.28±12.46 4
TC Hap.G GG CC GG GG CC AA AA GG AA CC AA GG 90.2±8.93 40.86±12.86 121
Hap.H GG CC GG GG CC AA AT GG AA CC AA GG 85.73±14.37 46.25±12.64 13
Hap.I GG CC GG GG CC AG AA AG AG CG AA GG 89.75±10.38 34.52±14.33 8
Hap.J GT CT AG AG CT AA AA AG AG CC AG GG 98.75±2.47 29.9±3.04 2
Hap.K GT CT AG AG CT AG AA AG AG CG AG GT 92.22±8.69 42.1±14.82 223
Hap.L GT CT AG AG CT AG AT AG AG CG AG GT 89.38±8.37 41.91±14.6 21
Hap.M GT CT AG AG CT GG AA AA GG GG AG GT 100.89±12.14 33.86±11.89 9
Hap.N GT CT AG GG CT AG AA AG AG CG AG GT 95.29±6.96 50.74±17.13 7
Hap.O TT TT AA AA TT AG AA AA GG CG GG GT 80.33±2.89 35.73±3.66 3
Hap.P TT TT AA AA TT GG AA AA GG GG GG TT 93.49±6.44 43.34±13.59 88
Hap.Q TT TT AA AG TT GG AA AA GG GG GG TT 97.41±4.81 39.72±11.23 11

Table 2

Corresponding phenotypic values of haplotype combinations in different genes of parent breed population and test cross population"

数据集
Data set
单倍型Haplotype 个数
No.
亲本抽穗期
HD.V (d)
子代抽穗期
HD.TC (d)
一般
配合力
GCA
特殊
配合力
SCA
超亲
优势值
BPH
亲本
产量
YD.V (g)
子代
产量
YD.TC (g)
SDG724 Hd17 Ghd7
V Hap.A Hap.E Hap.A 23 94.30 93.59 2.09 -0.06 1.12 31.97 41.88
Hap.A HapA Hap.A 9 92.22 92.92 1.41 0.06 0.08 28.68 37.21
Hap.D HapA Hap.A 12 94.21 94.94 3.43 -0.13 1.91 29.88 40.68
Hap.D Hap.B Hap.C 5 86.80 88.78 -2.73 -0.25 0.08 22.52 44.59
Hap.A HapA Hap.C 13 90.31 90.27 -1.24 -0.04 0.68 25.92 47.03
Hap.D HapA Hap.C 12 86.71 88.54 -3.10 0.12 1.08 29.76 41.98
Hap.F HapA Hap.C 11 93.32 90.83 -2.32 1.34 -1.26 32.15 39.79
TC Hap.I Hap.P Hap.D 20 93.43 95.73 2.24 -0.33 3.26 31.12 40.48
Hap.L Hap.G Hap.E 24 94.21 94.09 3.43 -0.33 1.23 29.88 39.46
Hap.I Hap.K Hap.E 45 94.14 93.59 2.25 0.37 0.76 32.09 42.10
Hap.I Hap.K Hap.F 27 91.24 93.93 1.15 0.50 0.84 28.93 43.61
Hap.L Hap.K Hap.F 28 90.55 94.19 1.98 0.05 2.79 31.55 40.46
Hap.I Hap.P Hap.F 43 94.01 92.58 1.94 -0.80 1.44 31.54 43.33
Hap.I Hap.G Hap.H 26 90.31 90.37 -1.24 0.62 -0.54 25.92 45.75
Hap.L Hap.G Hap.H 22 84.41 90.09 -3.35 2.45 2.13 29.88 44.01
Hap.I Hap.K Hap.I 23 89.85 90.83 0.20 -0.77 1.02 25.68 48.86
[1] Cai M H, Zhu S S, Wu M M, Zheng X M, Wang J C, Zhou L, Zheng T H, Cui S, Zhou S R, Li C N, Zhang H, Chai J T, Zhang X Y, Jin X, Cheng Z J, Zhang X, Lei C L, Ren Y L, Lin Q B, Guo X P, Zhao L, Wang J, Zhao Z C, Jiang L, Wang H Y, Wan J M. DHD4, a CONSTANS-like family transcription factor, delays heading date by affecting the formation of the FAC complex in rice. Mol Plant, 2021, 14: 330-343.
doi: 10.1016/j.molp.2020.11.013 pmid: 33246053
[2] Nemoto Y, Nonoue Y, Yano M, Izawa T. Hd1, a CONSTANS ortholog in rice, functions as an Ehd1 repressor through interaction with monocot-specific CCT-domain protein Ghd7. Plant J, 2016, 86: 221-233.
doi: 10.1111/tpj.13168
[3] Sakamoto T, Kimura S. Plant temperature sensors. Sensors, 2018, 18: 4365.
doi: 10.3390/s18124365
[4] Zhao Q, Feng Q, Lu H Y, Li Y, Wang A H, Tian Q L, Zhan Q L, Lu Y Q, Zhang L, Huang T, Wang Y C, Fan D L, Zhao Y, Wang Z Q, Zhou C C, Chen J Y, Zhu C R, Li W J, Weng Q J, Xu Q, Wang Z X, Wei X H, Han B, Huang X H. Pan-genome analysis highlights the extent of genomic variation in cultivated and wild rice. Nat Genet, 2018, 50: 278-284.
doi: 10.1038/s41588-018-0041-z pmid: 29335547
[5] Wei X, Qiu J, Yong K C, Fan J J, Zhang Q, Hua H, Liu J, Wang Q, Olsen K M, Han B, Huang X H. A quantitative genomics map of rice provides genetic insights and guides breeding. Nat Genet, 2021, 53: 243-253.
doi: 10.1038/s41588-020-00769-9 pmid: 33526925
[6] Wang W, Hu B, Yuan D Y, Liu Y Q, Che R H, Hu Y C, Ou S J, Liu Y X, Zhang Z H, Wang H R, Li H, Jiang Z M, Zhang Z L, Gao X K, Qiu Y H, Meng X B, Liu Y X, Bai Y, Liang Y, Wang Y Q, Zhang L H, Li L G, Sodmergen, Jing H C, Li J Y, Chu C C. Expression of the nitrate transporter gene OsNRT1.1A/OsNPF6.3 confers high yield and early maturation in rice. Plant Cell, 2018, 30: 638-651.
doi: 10.1105/tpc.17.00809
[7] Purugganan M D. Evolutionary insights into the nature of plant domestication. Curr Biol, 2019, 29: R705-R714.
doi: 10.1016/j.cub.2019.05.053
[8] Lai X J, Bendix C, Yan L, Zhang Y, Schnable J C, Harmon F G. Interspecific analysis of diurnal gene regulation in panicoid grasses identifies known and novel regulatory motifs. BMC Genomics, 2020, 21: 428.
doi: 10.1186/s12864-020-06824-3 pmid: 32586356
[9] Lu S J, Zhao X H, Hu Y L, Liu S L, Nan H Y, Li X M, Fang C, Cao D, Shi X Y, Kong L P, Su T, Zhang F G, Li S C, Wang Z, Yuan X H, Cober E R, Weller J L, Liu B H, Hou X L, Tian Z X, Kong F J. Natural variation at the soybean J locus improves adaptation to the tropics and enhances yield. Nat Genet, 2017, 49: 773-779.
doi: 10.1038/ng.3819 pmid: 28319089
[10] Zhang B, Liu H Y, Qi F X, Zhang Z Y, Li Q P, Han Z M, Xing Y Z. Genetic interactions among Ghd7, Ghd8, OsPRR37 and Hd1 contribute to large variation in heading date in rice. Rice, 2019, 12: 48.
doi: 10.1186/s12284-019-0314-x pmid: 31309345
[11] Lu Q, Zhang M C, Niu X J, Wang S, Xu Q, Feng Y, Wang C H, Deng H Z, Yuan X P, Yu H Y, Wang Y P, Wei X H. Genetic variation and association mapping for 12 agronomic traits in indica rice. BMC Genomics, 2015, 16: 1067.
doi: 10.1186/s12864-015-2245-2
[12] Wang Q X, Xie W B, Xing H K, Yan J, Meng X Z, Li X L, Fu X K, Xu J Y, Lian X M, Yu S B, Xing Y Z, Wang G W. Genetic architecture of natural variation in rice chlorophyll content revealed by a genome-wide association study. Mol Plant, 2015, 8: 946-957.
doi: 10.1016/j.molp.2015.02.014 pmid: 25747843
[13] Yano K, Yamamoto E, Aya K, Takeuchi H, Lo P C, Hu L, Matsuoka M. Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nat Genet, 2016, 48: 927-934.
doi: 10.1038/ng.3596 pmid: 27322545
[14] Han Z M, Zhang B, Zhao H, Ayaad M, Xing Y Z. Genome-wide association studies reveal that diverse heading date genes respond to short- and long-day lengths between indica and japonica rice. Front Plant Sci, 2016, 7: 1270.
[15] Jing L, Rui X, Wang C C, Lan Q, Zheng X M, Wang W S, Ding Y B, Zhang L Z, Wang Y Y, Cheng Y L, Zhang L F, Qiao W H, Yang Q W. A heading date QTL, qHD7.2, from wild rice (Oryza rufipogon) delays flowering and shortens panicle length under long-day conditions. Sci Rep, 2018, 8: 2928.
doi: 10.1038/s41598-018-21330-z pmid: 29440759
[16] Wang X, Xu Y, Hu Z L, Xu C W. Genomic selection methods for crop improvement: current status and prospects. Crop J, 2018, 6: 330-340.
doi: 10.1016/j.cj.2018.03.001
[17] Wang Y S, Cai Q H, Xie H G, Wu F X, Lian L, He W, Chen L P, xie H A, Zhang J F. Determination of heterotic groups and heterosis analysis of yield performance in indica rice. Rice Sci, 2018, 25: 261-269.
doi: 10.1016/j.rsci.2018.08.002
[18] Belser C, Istace B, Denis E, Dubarry M, Baurens F C, Falentin C, Aury J M. Chromosome-scale assemblies of plant genomes using nanopore long reads and optical maps. Nat Plants, 2018, 4: 879-887.
doi: 10.1038/s41477-018-0289-4 pmid: 30390080
[19] Pushalkar S, Hundeyin M, Daley D, Zambirinis C P, Kurz E, Mishra A, Miller G. The pancreatic cancer microbiome promotes oncogenesis by induction of innate and adaptive immune suppression. Cancer Discover, 2018, 8: 403-416.
doi: 10.1158/2159-8290.CD-17-1134
[20] Li H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics, 2018, 34: 3094-3100.
doi: 10.1093/bioinformatics/bty191 pmid: 29750242
[21] Tam V, Patel N, Turcotte M, Bossé Y, Paré G, Meyre D. Benefits and limitations of genome-wide association studies. Nat Rev Genet, 2019, 20: 467-484.
doi: 10.1038/s41576-019-0127-1 pmid: 31068683
[22] Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M A, Bender D, Maller J, Sklar P, Bakker P I, Daly M J, Sham P C. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Human Genet, 2007, 81: 559-575.
doi: 10.1086/519795
[23] Li B, Dewey C N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinfor, 2011, 12: 323.
doi: 10.1186/1471-2105-12-323
[24] Lipka A E, Tian F, Wang Q S, Peiffer J, Li M, Bradbury P J, Gore M A, Buckler E S, Zhang Z W. GAPIT: genome association and prediction integrated tool. Bioinformatics, 2012, 28: 2397-2399.
pmid: 22796960
[25] Kang H M, Sul J H, Service S K, Zaitlen N A, Kong S Y, Freimer N B, Sabatti C, Eskin E. Variance component model to account for sample structure in genome-wide association studies. Nat Genet, 2010, 42: 348-354.
doi: 10.1038/ng.548 pmid: 20208533
[26] 侯青青, 司丽珍, 黄学辉, 韩斌. 水稻复杂性状研究的新途径:水稻重要农艺性状全基因组关联分析. 生命科学, 2016, 28: 1250-1257.
Hou Q Q, Si L Z, Huang X H, Han B. Progress on genome-wide association study of important agronomic traits in rice. Chin Bull Life Sci, 2016, 28: 1250-1257. (in Chinese with English abstract)
[27] Fang C, Ma Y M, Wu S W, Liu Z, Wang Z, Yang R, Hu G H, Zhou Z K, Yu H, Zhang M, Pan Y, Zhou G A, Ren H X, Du W G, Yan H R, Wang Y P, Han D Z, Shen Y T, Liu S L, Liu T F, Zhang J X, Qin H, Yuan J, Yuan X H, Kong F J, Li J Y, Zhang Z W, Wang G D, Zhu B G, Tian Z. Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean. Genome Biol, 2017, 18: 161.
doi: 10.1186/s13059-017-1289-9 pmid: 28838319
[28] Sakai H, Lee S S, Tanaka T, Numa H, Kim J, Kawahara Y, Itoh T. Rice Annotation Project Database (RAP-DB): an integrative and interactive database for rice genomics. Plant Cell Phys, 2013, 54: e6.
[29] 董骥驰, 杨靖, 郭涛, 陈立凯, 陈志强, 王慧. 基于高密度Bin图谱的水稻抽穗期QTL定位. 作物学报, 2018, 44: 938-946.
Dong J C, Yang J, Guo T, Chen L K, Chen Z Q, Wang H. QTL mapping for heading date in rice using high-density Bin map. Acta Agron Sin, 2018, 44: 938-946. (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2018.00938
[30] Sun C H, Fang J, Zhao T L, Xu B, Zhang F T, Liu L C, Tang J Y, Zhang G F, Deng X J, Chen F, Qian Q, Cao X F, Chu C C. The histone methyltransferase SDG724 mediates H3K36me2/3 deposition at MADS50 and RFT1 and promotes flowering in rice. Plant Cell, 2012, 24: 3235-3247.
doi: 10.1105/tpc.112.101436
[31] Zhao S Q, Xiang J J, Xue H W. Studies on the rice LEAF INCLINATION1 (LC1), an IAA-amido synthetase, reveal the effects of auxin in leaf inclination control. Mol Plant, 2013, 6: 174-187.
doi: 10.1093/mp/sss064
[32] Kanneganti V, Gupta A K. Isolation and Expression analysis of OsPME1, encoding for a putative Pectin Methyl Esterase from Oryza sativa (subsp. indica). Phys Mol Biol Plants, 2009, 15: 123-131.
[33] Zhao Y, Cheng S F, Song Y L, Huang Y L, Zhou S L, Liu X Y, Zhou D X. The interaction between rice ERF3 and WOX11 promotes crown root development by regulating gene expression involved in cytokinin signaling. Plant Cell, 2015, 27: 2469-2483.
doi: 10.1105/tpc.15.00227
[34] Marigorta U M, Rodríguez J A, Gibson G, Navarro A. Replicability and prediction: lessons and challenges from GWAS. Trends Genet, 2018, 34: 504-517.
doi: S0168-9525(18)30060-X pmid: 29716745
[35] De R, Bush W S, Moore J H. Bioinformatics challenges in genome-wide association studies (GWAS). Clinic Bioinfor, 2014, 1168: 63-81.
[36] Qian L W, Hickey L T, Stahl A, Werner C R, Hayes B, Snowdon R J, Voss-Fels K P. Exploring and harnessing haplotype diversity to improve yield stability in crops. Front Plant Sci, 2017, 8: 1534.
doi: 10.3389/fpls.2017.01534 pmid: 28928764
[1] CHEN Sai-Hua, PENG Sheng, YOU Yi-Wen, ZHANG Lu-Yao, WANG Kai, XUE Ming, YANG Yuan-Zhu, WAN Jian-Min. Genetic analysis of photosensitivity divergence among hybrids derived from rice sterile line Xiangling 628S  [J]. Acta Agronomica Sinica, 2023, 49(2): 332-342.
[2] YANG Xiao-Yi, WANG Hui-Hui, ZHANG Yan-Wen, HOU Dian-Yun, ZHANG Hong-Xiao, KANG Guo-Zhang, XU Hua-Wei. Function Analysis of OsPIN5c Gene by CRISPR/Cas9 [J]. Acta Agronomica Sinica, 2023, 49(2): 354-364.
[3] LI Zhao-Wei, MO Zu-Yi, SUN Cong-Ying, SHI Yu, SHANG Ping, LIN Wei-Wei, FAN Kai, LIN Wen-Xiong. Construction of rice mutants by gene editing of OsNAC2d and their response to drought stress [J]. Acta Agronomica Sinica, 2023, 49(2): 365-376.
[4] CAI Xiao-Xi, HU Bing-Shuang, SHEN Yang, WANG Yan, CHEN Yue, SUN Ming-Zhe, JIA Bo-Wei, SUN Xiao-Li. Effects of GsERF6 overexpression on salt-alkaline tolerance in rice [J]. Acta Agronomica Sinica, 2023, 49(2): 561-569.
[5] TAO Shi-Bao, KE Jian, SUN Jie, YIN Chuan-Jun, ZHU Tie-Zhong, CHEN Ting-Ting, HE Hai-Bing, YOU Cui-Cui, GUO Shuang-Shuang, WU Li-Quan. High-yielding population agronomic characteristics of middle-season indica hybrid rice with different panicle sizes in the middle and lower reaches of the Yangtze River [J]. Acta Agronomica Sinica, 2023, 49(2): 511-525.
[6] ZHAO Ling, LIANG Wen-Hua, ZHAO Chun-Fang, WEI Xiao-Dong, ZHOU Li-Hui, YAO Shu, WANG Cai-Lin, ZHANG Ya-Dong. Mapping of QTLs for heading date of rice with high-density bin genetic map [J]. Acta Agronomica Sinica, 2023, 49(1): 119-128.
[7] JIANG Yan, ZHAO Can, CHEN Yue, LIU Guang-Ming, ZHAO Ling-Tian, LIAO Ping-Qiang, WANG Wei-Ling, XU Ke, LI Guo-Hui, WU Wen-Ge, HUO Zhong-Yang. Effects of nitrogen panicle fertilizer application on physicochemical properties and fine structure of japonica rice starch and its relationship with eating quality [J]. Acta Agronomica Sinica, 2023, 49(1): 200-210.
[8] DING Pu-Yang, ZHOU Jie-Guang, ZHAO Cong-Hao, TANG Hua-Ping, MU Yang, TANG Li-Wei, DENG Mei, WEI Yu-Ming, LAN Xiu-Jin, MA Jian. Dissection of haplotypes, geographical distribution and breeding utilization of WAPO1 associated with spike development in wheat [J]. Acta Agronomica Sinica, 2022, 48(9): 2196-2209.
[9] XUE Jiao, LU Dong-Bai, LIU Wei, LU Zhan-Hua, WANG Shi-Guang, WANG Xiao-Fei, FANG Zhi-Qiang, HE Xiu-Ying. Genetic analysis and fine mapping of a bacterial blight resistance major QTL qBB-11-1 in high-quality rice ‘Yuenong Simiao’ [J]. Acta Agronomica Sinica, 2022, 48(9): 2210-2220.
[10] HUANG Yi-Wen, SUN Bin, CHENG Can, NIU Fu-An, ZHOU Ji-Hua, ZHANG An-Peng, TU Rong-Jian, LI Yao, YAO Yao, DAI Yu-Ting, XIE Kai-Zhen, CHEN Xiao-Rong, CAO Li-Ming, CHU Huang-Wei. QTL mapping of seed storage tolerance in rice (Oryza sativa L.) [J]. Acta Agronomica Sinica, 2022, 48(9): 2255-2264.
[11] ZHOU Qun, YUAN Rui, ZHU Kuan-Yu, WANG Zhi-Qin, YANG Jian-Chang. Characteristics of grain yield and nitrogen absorption and utilization of indica/japonica hybrid rice Yongyou 2640 under different nitrogen application rates [J]. Acta Agronomica Sinica, 2022, 48(9): 2285-2299.
[12] WU La-Mei, YANG Hao-Na, WANG Li-Feng, LI Zu-Ren, DENG Xi-Le, BAI Lian-Yang. Application of weeding bast fiber film in rice seedling field and its effect on rice [J]. Acta Agronomica Sinica, 2022, 48(9): 2315-2324.
[13] CHEN Zhi-Qing, FENG Yuan, WANG Rui, CUI Pei-Yuan, LU Hao, WEI Hai-Yan, ZHANG Hai-Peng, ZHANG Hong-Cheng. Effects of exogenous molybdenum on yield formation and nitrogen utilization in rice [J]. Acta Agronomica Sinica, 2022, 48(9): 2325-2338.
[14] WANG Quan, WANG Le-Le, ZHU Tie-Zhong, REN Hao-Jie, WANG Hui, CHEN Ting-Ting, JIN Ping, WU LI-Quan, YANG Ru, YOU Cui-Cui, KE Jian, HE Hai-Bing. Effects of HgCl2 on photosynthetic characteristics and its physiological mechanism of rice leaves in vitro feeding [J]. Acta Agronomica Sinica, 2022, 48(9): 2377-2389.
[15] SANG Guo-Qing, TANG Zhi-Guang, MAO Ke-Biao, DENG Gang, WANG Jing-Wen, LI Jia. High-resolution paddy rice mapping using Sentinel data based on GEE platform: a case study of Hunan province, China [J]. Acta Agronomica Sinica, 2022, 48(9): 2409-2420.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 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 .
[2] WANG Li-Yan;ZHAO Ke-Fu. Some Physiological Response of Zea mays under Salt-stress[J]. Acta Agron Sin, 2005, 31(02): 264 -268 .
[3] 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 .
[4] XING Guang-Nan, ZHOU Bin, ZHAO Tuan-Jie, YU De-Yue, XING Han, HEN Shou-Yi, GAI Jun-Yi. Mapping QTLs of Resistance to Megacota cribraria (Fabricius) in Soybean[J]. Acta Agronomica Sinica, 2008, 34(03): 361 -368 .
[5] KE Li-Ping;ZHENG Tao;WU Xue-Long;HE Hai-Yan;CHEN Jin-Qing. Analysis of Self-Incompatibility Locus Gene in Brassica napus[J]. Acta Agron Sin, 2008, 34(05): 764 -769 .
[6] LÜ Li-Hua;TAO Hong-Bin;XIA Lai-Kun; HANG Ya-Jie;ZHAO Ming;ZHAO Jiu-Ran;WANG Pu;. Canopy Structure and Photosynthesis Traits of Summer Maize under Different Planting Densities[J]. Acta Agron Sin, 2008, 34(03): 447 -455 .
[7] WANG Cheng-Zhang;HAN Jin-Feng;SHI Ying-Hua;LI Zhen-Tian;LI De-Feng. Production Performance in Alfalfa with Different Classes of Fall Dormancy[J]. Acta Agron Sin, 2008, 34(01): 133 -141 .
[8] TIAN Zhi-Jian;Yi Rong;CHEN Jian-Rong;GUO Qing-Quan;ZHANG Xue-Wen;. Cloning and Expression of Cellulose Synthase Gene in Ramie [Boehme- ria nivea (Linn.) Gaud.][J]. Acta Agron Sin, 2008, 34(01): 76 -83 .
[9] WANG Chun-Mei;FENG Yi-Gao;ZHUANG Li-Fang;CAO Ya-Ping;QI Zeng-Jun;BIE Tong-De;CAO Ai-Zhong;CHEN Pei-Du. Screening of Chromosome-Specific Markers for Chromosome 1R of Secale cereale, 1V of Haynaldia villosa and 1Rk#1 of Roegneria kamoji[J]. Acta Agron Sin, 2007, 33(11): 1741 -1747 .
[10] SHAO Rui-Xin;SHANG-GUAN Zhou-Ping. Effects of Exogenous Nitric Oxide Donor Sodium Nitroprusside on Photosynthetic Pigment Content and Light Use Capability of PS II in Wheat under Water Stress[J]. Acta Agron Sin, 2008, 34(05): 818 -822 .