Scientia Agricultura Sinica ›› 2022, Vol. 55 ›› Issue (21): 4091-4103.doi: 10.3864/j.issn.0578-1752.2022.21.001

Previous Articles     Next Articles

Genome-Wide Association Study of Cold Tolerance at the Germination Stage of Rice

PANG HongBo1(),CHENG Lu1,YU MingLan1,CHEN Qiang2,LI YueYing1,WU LongKun3,WANG Ze1,PAN XiaoWu4,ZHENG XiaoMing5,6()   

  1. 1College of Life Science, Shenyang Normal University, Shenyang 110034
    2Experiment Teaching Center, Shenyang Normal University, Shenyang 110034
    3College of Grain Science and Technology, Shenyang Normal University, Shenyang 110034
    4Rice Research Institute, Hunan Academy of Agricultural Sciences, Changsha 410125
    5Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081
    6Sanya National Research Institute of Breeding in Hainan, Chinese Academy of Agricultural Sciences, Sanya 571700, Hainan
  • Received:2022-07-15 Accepted:2022-08-17 Online:2022-11-01 Published:2022-11-09
  • Contact: HongBo PANG,XiaoMing ZHENG E-mail:panghb@synu.edu.cn;zhengxiaoming@caas.cn

Abstract:

【Objective】Rice is an important food crop, and its growth and development are most vulnerable at the germination stage. Under cold stress, direct-seeded rice exhibited significantly reduced germination rates (GRs) and yield compared with normally grown plants. Thus, a better understanding of genetic mechanisms regulating cold tolerance will enable to develop rice varieties with improved tolerance during germination. 【Method】238 representative rice germplasm resources from 14 countries worldwide were tested in phenotypic identification in Shenyang in 2021 and 2022; the low-temperature germination rate and relative low-temperature germination rate (LTGR and relative LTGR; 1-10 days under 15℃) were evaluated in an artificial climate incubator, and a 5-10 day LTGR histogram was constructed using R. The day suitable for GWAS was determined by phenotypic variation (Hill) and a mixed linear model combining LTGR and relative LTGR phenotype data with resequencing data. 【Result】LTGR histogram and phenotypic variation showed optimal GR on day 8 (Hill=0.84), i.e., it was higher than on other days (Hill=0.48-0.83), which could be used for GWAS. The principal component analysis results divided all germplasms into five groups—indica, aus, temperate japonica, tropical japonica, and aromatic. GWAS analysis of two indicators detected three identical significant single nucleotide polymorphisms (SNPs) related to cold tolerance in rice at the germination stage. These were located on chromosome 4, which could explain 11.9%-25.4% of the phenotype. In addition, 24 candidate genes were screened in the 50-kb region upstream and downstream of these three SNPs. Further linkage disequilibrium analysis and haplotype analysis were carried out and highly significant differences were found between different haplotypes of the LOC_Os04g24840 and LOC_Os04g25140 genes for cold tolerance. LOC_Os04g24840 was divided into five haplotypes by the coding region SNP, and Hap_3 was significantly more cold tolerant than Hap_1; LOC_Os04g25140 was divided into 18 haplotypes by the coding region SNP and the amino acid variation (S>L) at 77 bp was different in japonica and indica rice. These results showed that the genes encoding glycosyltransferases (LOC_Os04g24840) and F-box protein (LOC_Os04g25140) might be closely related to cold tolerance in rice.【Conclusion】 A total of three SNP loci were detected in 238 rice germplasm resources, and two candidate genes were screened for their association with cold tolerance during germination in rice.

Key words: Oryza sativa L., seed germinability, cold tolerance, germination rate, GWAS

Fig. 1

Frequency histogram of GR of 5-10 days"

Fig. 2

PCA analysis of rice whole-genome SNP data"

Fig. 3

Histogram of kinship between samples and heat map of kinship A: Histogram of kinship between samples; B: Heat map of relationship between samples"

Fig. 4

Genome-wide association study analysis of LTGR and relative LTGR in 238 rice accessions"

Table 1

Gene annotation of 24 candidate genes"

染色体 Chr. 基因号 Gene ID 基因注释 Annotation
Chr.4 LOC_Os04g24830 含锌指、CCHC型结构域的蛋白质 Zinc finger, CCHC-type domain containing protein
Chr.4 LOC_Os04g24840 糖基转移酶,推测,表达Glycosyltransferase, putative, expressed
Chr.4 LOC_Os04g24850 细胞分裂素-O-葡糖基转移酶2,假定的,表达Cytokinin-O-glucosyltransferase 2, putative, expressed
Chr.4 LOC_Os04g24860 逆转录酶子蛋白,推定,未分类,表达Retrotransposon protein, putative, unclassified, expressed
Chr.4 LOC_Os04g24870 逆转录酶子蛋白,推定,未分类Retrotransposon protein, putative, unclassified
Chr.4 LOC_Os04g24880 逆转录酶子蛋白,推定,未分类,表达Retrotransposon protein, putative, unclassified, expressed
Chr.4 LOC_Os04g24900 表达蛋白Expressed protein
Chr.4 LOC_Os04g24910 表达蛋白Expressed protein
Chr.4 LOC_Os04g24920 转座子蛋白,推定,CACTA,En/Spm亚类,表达
Transposon protein, putative, CACTA, En/Spm sub-class, expressed
Chr.4 LOC_Os04g24930 表达蛋白Expressed protein
Chr.4 LOC_Os04g24940 表达蛋白Expressed protein
Chr.4 LOC_Os04g24950 假定的蛋白质Hypothetical protein
Chr.4 LOC_Os04g24960 转座子蛋白,推定,CACTA,En/Spm亚类,表达
Transposon protein, putative, CACTA, En/Spm sub-class, expressed
Chr.4 LOC_Os04g25100 转座子蛋白,推定,未分类,表达Transposon protein, putative, unclassified, expressed
Chr.4 LOC_Os04g25110 Ulp1蛋白酶家族,含有C端催化域的蛋白,表达式ulp1;
Ulp1 protease family, C-terminal catalytic domain containing protein, expressedulp1
Chr.4 LOC_Os04g25120 表达蛋白Expressed protein
Chr.4 LOC_Os04g25130 逆转录子蛋白,推定,LINE亚类,表达Retrotransposon protein, putative, LINE subclass, expressed
Chr.4 LOC_Os04g25140 OsFBDUF20-含有F-box和DUF结构域的蛋白,已表达;
OsFBDUF20- F-box and DUF domain containing protein, expressed
Chr.4 LOC_Os04g25150 花粉过敏原,推定,表达Pollen allergen, putative, expressed
Chr.4 LOC_Os04g25160 花粉过敏原,推定,表达Pollen allergen, putative, expressed
Chr.4 LOC_Os04g25170 逆转录酶原蛋白,推定,未分类,表达Retrotransposon protein, putative, unclassified, expressed
Chr.4 LOC_Os04g25180 假定的蛋白质Hypothetical protein
Chr.4 LOC_Os04g25190 花粉过敏原,推定,表达Pollen allergen, putative, expressed
Chr.4 LOC_Os04g25210 转座子蛋白,推定,未分类,表达Transposon protein, putative, unclassified, expressed

Fig. 5

Gene prediction in linkage disequilibrium region of association locus The 24 black boxes in the middle part of the figure are the 24 candidate genes in order, the red vertical lines represent the locations of the 3 significant SNPs and the 4 grey arrows indicate LOC_Os04g24830, LOC_Os04g24840, LOC_Os04g24850 and LOC_Os04g25140, respectively"

Fig. 6

Nucleotide diversity in the coding region of LOC_Os04g24840 and LOC_Os04g25140 in 165 cultivated rice Red represents haplotypes common to both japonica and indica, blue represents sense mutations in SNPs in the coding region of the gene; green identifies a nucleotide variation at 235 bp (C>T) leading to an early terminator in the gene; yellow indicates a base difference between japonica and indica rice at 77 bp (C>T)"

[1] ZHENG S, LIU S, FENG J, WANG W, WANG Y, YU Q, LIAO Y, MO Y, XU Z, LI L, GAO X, JIA X, ZHU J, CHEN R. Overexpression of a stress response membrane protein gene OsSMP1 enhances rice tolerance to salt, cold and heavy metal stress. Environmental and Experimental Botany, 2021, 182: 104327.
[2] WANG H, LEE A R, PARK S Y, JIN S H, LEE J, HAM T H, PARK Y, ZHAO W G, KWON S W. Genome-wide association study reveals candidate genes related to low temperature tolerance in rice (Oryza sativa) during germination. 3 Biotech, 2018, 8(5): 1-13.
[3] CHENG S H, CAO L Y, ZHUANG J Y, CHEN S G, ZHAN X D, FAN Y Y, ZHU D F, MIN S K. Super hybrid rice breeding in China: Achievements and prospects. Journal of Integrative Plant Biology, 2007, 49(6): 805-810.
[4] VILAS J M, CORIGLIANO M G, CLEMENTE M, MAIALE S J, RODRIGUEZ A A. Close relationship between the state of the oxygen evolving complex and rice cold stress tolerance. Plant Science, 2020, 296: 110488.
[5] SIPASEUTH, BASNAYAKE J, FUKAI S, FARRELL T C, SENTHONGHAE M, SENGKEO, PHAMIXAY S, LINQUIST B, CHANPHENGSAY M. Opportunities to increasing dry season rice productivity in low temperature affected areas. Field Crops Research, 2007, 102(2): 87-97.
[6] ZHANG M, YE J, XU Q, FENG Y, YUAN X, YU H, WANG Y, WEI X, YANG Y. Genome-wide association study of cold tolerance of Chinese indica rice varieties at the bud burst stage. Plant Cell Reports, 2018, 37(3): 529-539.
[7] SUH J P, JEUNG J U, LEE J I, CHOI Y H, YEA J D, VIRK P S, MACKILL D J, JENA K K. Identification and analysis of QTLs controlling cold tolerance at the reproductive stage and validation of effective QTLs in cold-tolerant genotypes of rice (Oryza sativa L.). Theoretical and Applied Genetics, 2010, 120(5): 985-995.
[8] FUJINO K, MATSUDA Y. Genome-wide analysis of genes targeted by qLTG3-1 controlling low-temperature germinability in rice. Plant Molecular Biology, 2010, 72(1): 137-152.
[9] FUJINO K, SEKIGUCHI H, MATSUDA Y, SUGIMOTO K, ONO K, YANO M. Molecular identification of a major quantitative trait locus, qLTG3-1, controlling low-temperature germinability in rice. Proceedings of the National Academy of Sciences of the United States of America, 2008, 105(34): 12623-12628.
[10] SAITO K, HAYANO-SAITO Y, MARUYAMA-FUNATSUKI W, SATO Y, KATO A. Physical mapping and putative candidate gene identification of a quantitative trait locus Ctb1 for cold tolerance at the booting stage of rice. Theoretical and Applied Genetics, 2004, 109(3): 515-522.
[11] FUJINO K, SEKIGUCHI H, SATO T, KIUCHI H, NONOUE Y, TAKEUCHI Y, ANDO T, LIN S Y, YANO M. Mapping of quantitative trait loci controlling low-temperature germinability in rice (Oryza sativa L.). Theoretical and Applied Genetics, 2004, 108(5): 794-799.
[12] ANDAYA V C, TAI T H. Fine mapping of the qCTS12 locus, a major QTL for seedling cold tolerance in rice. Theoretical and Applied Genetics, 2006, 113(3): 467-475.
[13] LOU Q, CHEN L, SUN Z, XING Y, LI J, XU X, MEI H, LUO L. A major QTL associated with cold tolerance at seedling stage in rice (Oryza sativa L.). Euphytica, 2007, 158(1): 87-94.
[14] KUMAR V, LADHA J K. Direct seeding of rice. recent developments and future research needs. Advances in Agronomy, 2011, 111: 297-413.
[15] IWATA N, SHINADA H, KIUCHI H, SATO T, FUJINO K. Mapping of QTLs controlling seedling establishment using a direct seeding method in rice. Breeding Science, 2010, 60(4): 353-360.
[16] ZHANG Z H, QU X S, WAN S, CHEN L H, ZHU Y G. Comparison of QTL controlling seedling vigour under different temperature conditions using recombinant inbred lines in rice (Oryza sativa). Annals of Botany, 2005, 95(3): 423-429.
[17] CHEN L, LOU Q J, SUN Z X, XING Y Z, XIN-QIAO Y U, LUO L J. QTL mapping of low temperature on germination rate of rice. Rice Science, 2006, 13(2): 93-98.
[18] JI S L, JIANG L, WANG Y H, ZHANG W W, LIU X, LIU S J, CHEN L M, ZHAI H Q, WAN J M. Quantitative trait loci mapping and stability for low temperature germination ability of rice. Plant Breeding, 2009, 128(4): 387-392.
[19] WAN J M, JIANG L, TANG J Y, WANG C M, HOU M Y, JING W, ZHANG L X. Genetic dissection of the seed dormancy trait in cultivated rice (Oryza sativa L.). Plant Science, 2006, 170(4): 786-792.
[20] SUGIMOTO K, TAKEUCHI Y, EBANA K, MIYAO A, HIROCHIKA H, HARA N, ISHIYAMA K, KOBAYASHI M, BAN Y, HATTORI T, YANO M. Molecular cloning of Sdr4, a regulator involved in seed dormancy and domestication of rice. Proceedings of the National Academy of Sciences of the United States of America, 2010, 107(13): 5792-5797.
[21] SHARIFI P. Evaluation on sixty-eight rice germplasms in cold tolerance at germination stage. Rice Science, 2010, 17(1): 77-81.
[22] LI L, LIU X, XIE K, WANG Y, LIU F, LIN Q, WANG W, YANG C, LU B, LIU S, CHEN L, JIANG L, WAN J. qLTG-9, a stable quantitative trait locus for low-temperature germination in rice (Oryza sativa L.). Theoretical and Applied Genetics, 2013, 126(9): 2313-2322.
[23] ALBINANA C, GROVE J, MCGRATH J J, AGERBO E, WRAY N R, BULIK C M, NORDENTOFT M, HOUGAARD D M, WERGE T, BORGLUM A D, MORTENSEN P B, PRIVE F, VILHJALMSSON B J. Leveraging both individual-level genetic data and GWAS summary statistics increases polygenic prediction. American Journal of Human Genetics, 2021, 108(6): 1001-1011.
[24] HUANG X, WEI X, SANG T, ZHAO Q, FENG Q, ZHAO Y, LI C, ZHU C, LU T, ZHANG Z, LI M, FAN D, GUO Y, WANG A, WANG L, DENG L, LI W, LU Y, WENG Q, LIU K, HUANG T, ZHOU T, JING Y, LI W, LIN Z, BUCKLER E S, QIAN Q, ZHANG Q F, LI J, HAN B. Genome-wide association studies of 14 agronomic traits in rice landraces. Nature Genetics, 2010, 42(11): 961-967.
[25] HUANG X, ZHAO Y, WEI X, LI C, WANG A, ZHAO Q, LI W, GUO Y, DENG L, ZHU C, FAN D, LU Y, WENG Q, LIU K, ZHOU T, JING Y, SI L, DONG G, HUANG T, LU T, FENG Q, QIAN Q, LI J, HAN B. Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm. Nature Genetics, 2011, 44(1): 32-39.
[26] ZHAO K, TUNG C W, EIZENGA G C, WRIGHT M H, ALI M L, PRICE A H, NORTON G J, ISLAM M R, REYNOLDS A, MEZEY J, MCCLUNG A M, BUSTAMANTE C D, MCCOUCH S R. Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nature Communications, 2011, 2(1): 1-10.
[27] HSIAO C F, CHIU Y F, CHIANG F T, HO L T, LEE W J, HUNG Y J, CHEN Y D, DONLON T A, JORGENSON E, CURB D, RISCH N, HSIUNG C A, GROUP S A S. Genome-wide linkage analysis of lipids in nondiabetic Chinese and Japanese from the SAPPHIRe family study. American Journal of Hypertension, 2006, 19(12): 1270-1277.
[28] NICOLAE D L, GAMAZON E, ZHANG W, DUAN S, DOLAN M E, COX N J. Trait-associated SNPs are more likely to be eQTLs: Annotation to enhance discovery from GWAS. PLoS Genetics, 2010, 6(4): e1000888.
[29] YANG J, FERREIRA T, MORRIS A P, MEDLAND S E, GENETIC INVESTIGATION OF A T C, REPLICATION D I G, META ANALYSIS C, MADDEN P A, HEATH A C, MARTIN N G, MONTGOMERY G W, WEEDON M N, LOOS R J, FRAYLING T M, MCCARTHY M I, HIRSCHHORN J N, GODDARD M E, VISSCHER P M. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nature Genetics, 2012, 44(4): 369-375.
[30] LI Y H, LI D, JIAO Y Q, SCHNABLE J C, LI Y F, LI H H, CHEN H Z, HONG H L, ZHANG T, LIU B, LIU Z X, YOU Q B, TIAN Y, GUO Y, GUAN R X, ZHANG L J, CHANG R Z, ZHANG Z, REIF J, ZHOU X A, SCHNABLE P S, QIU L J. Identification of loci controlling adaptation in Chinese soya bean landraces via a combination of conventional and bioclimatic GWAS. Plant Biotechnology Journal, 2020, 18(2): 389-401.
[31] HWANG E Y, SONG Q, JIA G, SPECHT J E, HYTEN D L, COSTA J, CREGAN P B. A genome-wide association study of seed protein and oil content in soybean. BMC Genomics, 2014, 15(1): 1-12.
[32] WU S, ALSEEKH S, CUADROS-INOSTROZA A, FUSARI C M, MUTWIL M, KOOKE R, KEURENTJES J B, FERNIE A R, WILLMITZER L, BROTMAN Y. Combined use of genome-wide association data and correlation networks unravels key regulators of primary metabolism in Arabidopsis thaliana. PLoS Genetics, 2016, 12(10): e1006363.
[33] WENG J, XIE C, HAO Z, WANG J, LIU C, LI M, ZHANG D, BAI L, ZHANG S, LI X. Genome-wide association study identifies candidate genes that affect plant height in Chinese elite maize (Zea mays L.) inbred lines. PLoS ONE, 2011, 6(12): e29229.
[34] WU J, FENG F, LIAN X, TENG X, WEI H, YU H, XIE W, YAN M, FAN P, LI Y, MA X, LIU H, YU S, WANG G, ZHOU F, LUO L, MEI H. Genome-wide association study (GWAS) of mesocotyl elongation based on re-sequencing approach in rice. BMC Plant Biology, 2015, 15: 218.
[35] LI Z, WANG X, CUI Y, QIAO K, ZHU L, FAN S, MA Q. Comprehensive genome-wide analysis of thaumatin-like gene family in four cotton species and functional identification of GhTLP19 involved in regulating tolerance to Verticillium dahlia and drought. Frontiers in Plant Science, 2020, 11: 575015.
[36] FUJINO K, OBARA M, SHIMIZU T, KOYANAGI K O, IKEGAYA T. Genome-wide association mapping focusing on a rice population derived from rice breeding programs in a region. Breeding Science, 2015, 65(5): 403-410.
[37] PAN Y, ZHANG H, ZHANG D, LI J, XIONG H, YU J, LI J, RASHID M A, LI G, MA X, CAO G, HAN L, LI Z. Genetic analysis of cold tolerance at the germination and booting stages in rice by association mapping. PLoS ONE, 2015, 10(3): e0120590.
[38] HAN L Z, ZHANG Y Y, QIAO Y L, CAO G L, ZHANG S Y, KIM J H, KOH H J. Genetic and QTL analysis for low-temperature vigor of germination in rice. Acta Genetica Sinica, 2006, 33(11): 998-1006.
[39] ZHOU X, STEPHENS M. Genome-wide efficient mixed-model analysis for association studies. Nature Genetics, 2012, 44(7): 821-824.
[40] PEET R K. The measurement of species diversity. Annual Review of Ecology and Systematics, 1974, 5(1): 285-307.
[41] YANG J, YANG M, SU L, ZHOU D, HUANG C, WANG H, GUO T, CHEN Z. Genome-wide association study reveals novel genetic loci contributing to cold tolerance at the germination stage in indica rice. Plant Science, 2020, 301: 110669.
[42] LIN J, ZHU W Y, ZHANG Y D, ZHU Z, ZHAO L, CHEN T, ZHAO Q Y, ZHOU L H, FANG X W, WANG Y P, WANG C L. Detection of QTL for cold tolerance at bud bursting stage using chromosome segment substitution lines in rice (Oryza sativa). Rice Science, 2011, 18(1): 71-74.
[43] XIAO H, CHEN J F, ZHANG Z X. Influence of deposition temperature on the structure of Si3N4 thin film prepared by MWECR-PECVD. Plasma Science & Technology, 2004, 6(5): 2485-2488.
[44] 纪素兰, 江玲, 王益华, 刘世家, 刘喜, 翟虎渠, 吉村醇, 万建民. 水稻种子耐低温发芽力的QTL定位及上位性分析. 作物学报, 2008, 34(4): 551-556.
JI S L, JIANG L, WANG Y H, LIU S J, LIU X, ZHAI H Q, YOSHIMURA A, WAN J M. QTL and epistasis for low temperature germinability in rice. Acta Agronomica Sinica, 2008, 34(4): 551-556. (in Chinese)
[45] MIURA K, LIN S Y, YANO M, NAGAMINE T. Mapping quantitative trait loci controlling low temperature germinability in rice (Oryza sativa L.). Breeding Science, 2001, 51(4): 293-299.
[46] HYUN D Y, OH M, CHOI Y M, LEE S, LEE M C, OH S. Morphological and molecular evaluation for germinability in rice varieties under low-temperature and anaerobic conditions. Journal of Crop Science and Biotechnology, 2017, 20(1): 21-27.
[47] ANGAJI S A, SEPTININGSIH E M, MACKILL D J, ISMAIL A M. QTLs associated with tolerance of flooding during germination in rice (Oryza sativa L.). Euphytica, 2009, 172(2): 159-168.
[48] CRUZ R P, MILACH S C K. Cold tolerance at the germination stage of rice: Methods of evaluation and characterization of genotypes. Scientia Agricola, 2004, 61(1): 1-8.
[49] YE C, FUKAI S, GODWIN I, REINKE R, SNELL P, SCHILLER J, BASNAYAKE J. Cold tolerance in rice varieties at different growth stages. Crop and Pasture Science, 2009, 60(4): 328-338.
[50] WANG X, WANG H, LIU S, FERJANI A, LI J, YAN J, YANG X, QIN F. Genetic variation in ZmVPP1 contributes to drought tolerance in maize seedlings. Nature Genetics, 2016, 48(10): 1233-1241.
[51] WAN H, CHEN L, GUO J, LI Q, WEN J, YI B, MA C, TU J, FU T, SHEN J. Genome-wide association study reveals the genetic architecture underlying salt tolerance-related traits in rapeseed (Brassica napus L.). Frontiers in Plant Science, 2017, 8: 593.
[52] JIA L, YAN W, ZHU C, AGRAMA H A, JACKSON A, YEATER K, LI X, HUANG B, HU B, MCCLUNG A, WU D. Allelic analysis of sheath blight resistance with association mapping in rice. PLoS ONE, 2012, 7(3): e32703.
[53] KANG H, WANG Y, PENG S, ZHANG Y, XIAO Y, WANG D, QU S, LI Z, YAN S, WANG Z, LIU W, NING Y, KORNILIEV P, LEUNG H, MEZEY J, MCCOUCH S R, WANG G L. Dissection of the genetic architecture of rice resistance to the blast fungus Magnaporthe oryzae. Molecular Plant Pathology, 2016, 17(6): 959-972.
[54] YANG W, GUO Z, HUANG C, DUAN L, CHEN G, JIANG N, FANG W, FENG H, XIE W, LIAN X, WANG G, LUO Q, ZHANG Q, LIU Q, XIONG L. Combining high-throughput phenotyping and genome- wide association studies to reveal natural genetic variation in rice. Nature Communications, 2014, 5(1): 1-9.
[55] WANG D, LIU J, LI C, KANG H, WANG Y, TAN X, LIU M, DENG Y, WANG Z, LIU Y, ZHANG D, XIAO Y, WANG G L. Genome-wide association mapping of cold tolerance genes at the seedling stage in rice. Rice, 2016, 9(1): 61.
[56] JIANG L, LIU S, HOU M, TANG J, CHEN L, ZHAI H, WAN J. Analysis of QTLs for seed low temperature germinability and anoxia germinability in rice (Oryza sativa L.). Field Crops Research, 2006, 98(1): 68-75.
[57] LI J, ZENG Y, PAN Y, ZHOU L, ZHANG Z, GUO H, LOU Q, SHUI G, HUANG H, TIAN H, GUO Y, YUAN P, YANG H, PAN G, WANG R, ZHANG H, YANG S, GUO Y, GE S, LI J, LI Z. Stepwise selection of natural variations at CTB2 and CTB4a improves cold adaptation during domestication of japonica rice. New Phytologist, 2021, 231(3): 1056-1072.
[58] LI P, LI Y J, ZHANG F J, ZHANG G Z, JIANG X Y, YU H M, HOU B K. Arabidopsis UDP‐glycosyltransferases UGT79B2 and UGT79B3, contribute to cold, salt and drought stress tolerance via modulating anthocyanin accumulation. The Plant Journal, 2017, 89(1): 85-103.
[59] SHI Y, HUY P, LIU Y, CAO S, ZHANG Z, CHU C, SCHLPPI M R. Glycosyltransferase OsUGT90A1 helps protect the plasma membrane during chilling stress in rice. Journal of Experimental Botany, 2020, 71(9): 2723-2739.
[60] SAITO K, HAYANO-SAITO Y, KUROKI M, SATO Y. Map-based cloning of the rice cold tolerance gene Ctb1. Plant Science, 2010, 179(1/2): 97-102.
[61] CALLIS D J. Ubiquitin,hormones and biotic stress in plants. Annals of Botany, 2007, 99(5): 787-822.
[62] YAN Y S, CHEN X Y, YANG K., SUN Z X, FU Y P, ZHANG Y M, FANG R X. Overexpression of an F-box protein gene reduces abiotic stress tolerance and promotes root growth in rice. Molecular Plant, 2011, 4(1): 190-197.
[63] KOCH K. Sucrose metabolism: Regulatory mechanisms and pivotal roles in sugar sensing and plant development. Current Opinion in Plant Biology, 2004, 7(3): 235-246.
[1] WANG JunJuan,LU XuKe,WANG YanQin,WANG Shuai,YIN ZuJun,FU XiaoQiong,WANG DeLong,CHEN XiuGui,GUO LiXue,CHEN Chao,ZHAO LanJie,HAN YingChun,SUN LiangQing,HAN MingGe,ZHANG YueXin,FAN YaPeng,YE WuWei. Characteristics and Cold Tolerance of Upland Cotton Genetic Standard Line TM-1 [J]. Scientia Agricultura Sinica, 2022, 55(8): 1503-1517.
[2] ZHAO ChunFang,ZHAO QingYong,LÜ YuanDa,CHEN Tao,YAO Shu,ZHAO Ling,ZHOU LiHui,LIANG WenHua,ZHU Zhen,WANG CaiLin,ZHANG YaDong. Screening of Core Markers and Construction of DNA Fingerprints of Semi-Waxy Japonica Rice Varieties [J]. Scientia Agricultura Sinica, 2022, 55(23): 4567-4582.
[3] SHEN Qian,ZHANG SiPing,LIU RuiHua,LIU ShaoDong,CHEN Jing,GE ChangWei,MA HuiJuan,ZHAO XinHua,YANG GuoZheng,SONG MeiZhen,PANG ChaoYou. Construction of A Comprehensive Evaluation System and Screening of Cold Tolerance Indicators for Cold Tolerance of Cotton at Seedling Emergence Stage [J]. Scientia Agricultura Sinica, 2022, 55(22): 4342-4355.
[4] XIE XiaoYu, WANG KaiHong, QIN XiaoXiao, WANG CaiXiang, SHI ChunHui, NING XinZhu, YANG YongLin, QIN JiangHong, LI ChaoZhou, MA Qi, SU JunJi. Restricted Two-Stage Multi-Locus Genome-Wide Association Analysis and Candidate Gene Prediction of Boll Opening Rate in Upland Cotton [J]. Scientia Agricultura Sinica, 2022, 55(2): 248-264.
[5] DENG AiXing,LIU YouHong,MENG Ying,CHEN ChangQing,DONG WenJun,LI GeXing,ZHANG Jun,ZHANG WeiJian. Effects of 1.5℃ Field Warming on Rice Yield and Quality in High Latitude Planting Area [J]. Scientia Agricultura Sinica, 2022, 55(1): 51-60.
[6] ZHANG YaDong,LIANG WenHua,HE Lei,ZHAO ChunFang,ZHU Zhen,CHEN Tao,ZHAO QingYong,ZHAO Ling,YAO Shu,ZHOU LiHui,LU Kai,WANG CaiLin. Construction of High-Density Genetic Map and QTL Analysis of Grain Shape in Rice RIL Population [J]. Scientia Agricultura Sinica, 2021, 54(24): 5163-5176.
[7] ZHANG PengXia,ZHOU XiuWen,LIANG Xue,GUO Ying,ZHAO Yan,LI SiShen,KONG FanMei. Genome-Wide Association Analysis for Yield and Nitrogen Efficiency Related Traits of Wheat at Seedling Stage [J]. Scientia Agricultura Sinica, 2021, 54(21): 4487-4499.
[8] XU ZiYi,CHENG Xing,SHEN Qi,ZHAO YaNan,TANG JiaYu,LIU Xi. Identification and Gene Functional Analysis of Yellow Green Leaf Mutant ygl3 in Rice [J]. Scientia Agricultura Sinica, 2021, 54(15): 3149-3157.
[9] ZHANG QiKai,XING ZhenLong,WU ShengYong,XU RuiRui,LEI ZhongRen. Response of Liriomyza trifolii to Cold Acclimation and Differences of Cold Tolerance Among Different Populations [J]. Scientia Agricultura Sinica, 2021, 54(13): 2781-2788.
[10] REN ZhiJie,LI Qian,SUN YuJia,KONG DongDong,LIU LiangYu,HOU CongCong,LI LeGong. OsCSC11 Mediates Dry-Hot Wind/Drought-Induced Ca2+ Signal to Regulate Stamen Development in Rice [J]. Scientia Agricultura Sinica, 2021, 54(10): 2039-2052.
[11] ZHANG Fang,REN Yi,CAO JunMei,LI FaJi,XIA XianChun,GENG HongWei. Genome-wide Association Analysis of Wheat Grain Size Related Traits Based on SNP Markers [J]. Scientia Agricultura Sinica, 2021, 54(10): 2053-2063.
[12] JunYi GAI,JianBo HE. Major Characteristics, Often-Raised Queries and Potential Usefulness of the Restricted Two-Stage Multi-Locus Genome-Wide Association Analysis [J]. Scientia Agricultura Sinica, 2020, 53(9): 1699-1703.
[13] XiaoShuai HAO,MengMeng FU,ZaiDong LIU,JianBo HE,YanPing WANG,HaiXiang REN,DeLiang WANG,XingYong YANG,YanXi CHENG,WeiGuang DU,JunYi GAI. Genome-Wide QTL-Allele Dissection of 100-Seed Weight in the Northeast China Soybean Germplasm Population [J]. Scientia Agricultura Sinica, 2020, 53(9): 1717-1729.
[14] KunNeng ZHOU,JiaFa XIA,Peng YUN,YuanLei WANG,TingChen MA,CaiJuan ZHANG,ZeFu LI. Transcriptome Research of Erect and Short Panicle Mutant esp in Rice [J]. Scientia Agricultura Sinica, 2020, 53(6): 1081-1094.
[15] ShuJun MENG,XueHai ZHANG,QiYue WANG,Wen ZHANG,Li HUANG,Dong DING,JiHua TANG. Identification of miRNAs and tRFs in Response to Salt Stress in Rice Roots [J]. Scientia Agricultura Sinica, 2020, 53(4): 669-682.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!