Scientia Agricultura Sinica ›› 2020, Vol. 53 ›› Issue (16): 3205-3213.doi: 10.3864/j.issn.0578-1752.2020.16.001

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

Genome-Wide Association Study and Candidate Gene Mining of Tillering Number in Japonica Rice

ZHANG JiFeng(),LIU HuaDong,WANG JingGuo,LIU HuaLong,SUN Jian,YANG LuoMiao,JIA Yan,WU WenShen,ZHENG HongLiang(),ZOU DeTang()   

  1. Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Ministry of Education, Northeast Agricultural University, Harbin 150030
  • Received:2019-10-18 Accepted:2020-01-13 Online:2020-08-16 Published:2020-08-27
  • Contact: HongLiang ZHENG,DeTang ZOU E-mail:13804689362@163.com;zhenghongliang008@126.com;zoudtneau@126.com

Abstract:

【Objective】Genome-wide association study (GWAS) was used to detect SNP loci that were significantly related to tillering number in japonica rice, and to screen candidate genes affecting tillering number 【Method】This study used 295 japonica rice varieties from around the world, in 2018 and 2019 survey from the tillering stage of rice tillering number, the combination of high throughput sequencing weight gain high quality 788396 polymorphism, SNP, using TASSEL 5.0 software genome-wide association analysis of MLM model, using the GEC software to calculate the number of effective independent SNPS for the determination of threshold value, determine the significance of SNP markers associated with target traits. Based on the peak SNP detected in two years and the LD attenuation distance of each chromosome in rice, the major QTLs for co-localization of biennial number were determined, and the non-synonymous SNPs and promoter regions of all gene exon regions in the QTL interval were further extracted. SNPs were subjected to haplotype analysis, and then combined with gene annotation to screen candidate genes affecting japonica rice tillering number. 【Result】 The tillering number of 295 japonica rice varieties were basically the same in 2018 and 2019, and they all had a large phenotypic distribution. Under the threshold of P < 5.46 × 10-6, three QTLs (qTiller8, qTiller9 and qTiller10) related to tillering number of Japonica rice were identified on chromosomes 8, 9 and 10 by genome-wide association analysis. qTiller9 jointly detected that the contribution rate of phenotype in 2018 and 2019 was 11.86% and 10.61%, respectively. qtiller8 and qtiller10 were only detected in 2018, and the contribution rate of phenotype was 10.61% The rates were 9.36% and 9.10%, respectively. Haplotype analysis of all 15 genes in qTiller9 interval showed that there were 6 genes in qTiller9 interval (LOC_Os09g25090, LOC_Os09g25100, LOC_Os09g25150, LOC_Os09g25190, LOC_Os09g25200 and LOC_Os09g25220). LOC_Os09g25090 was divided into two haplotypes by promoter SNP, and the tillering number of hap2 (TAA) was significantly higher than that of hap1 (AGG). LOC_Os09g25100 was divided into two haplotypes by non-synonymy mutation SNP, and hap2 (GAGA) had a significantly higher tillering number than hap1 (AGCC). LOC_Os09g25150 was divided into two haplotypes by non-synonymy mutation SNP, and the tillering number of hap2 (ATG) was significantly higher than that of hap1 (GCC). LOC_Os09g25190 was divided into two haplotypes by promoter SNP and the tillering number of hap2 (GCATCGCATCGACGCCGA) was significantly higher than that of hap1 (ATGCTGATGAAGTCATCC). LOC_Os09g25200 was divided into two haplotypes by non-synonymic mutant SNP and the tillering number of hap2 (TAG) was significantly higher than that of hap1 (AGA). LOC_Os09g25220 was divided into two haplotypes by non-synonymic mutant SNP, and the tillering number of hap1 (GG) was significantly higher than that of hap2 (AA).Combined with gene annotation, it was found that LOC_Os09g25090 and LOC_Os09g25100 both predicted the encoding of calcineurin dependent protein kinases and were Ca2+ sensors necessary for abscisic acid (ABA) expression. Previous studies have shown that ABA can affect both tillering number and branch number of Arabidopsis. Therefore, LOC_Os09g25090 and LOC_Os09g25100 are candidate genes affecting the tillering number in japonica rice. 【Conclusion】LOC_Os09g25090 and LOC_Os09g25100 were screened as candidate genes affecting the tiller number of japonica rice.

Key words: japonica rice, tillering number, genome-wide association study, haplotype analysis, candidate gene

Table 1

The phenotypic values of tillering number among 295 japonica rice varieties in two years"

年份 Year 均值±标准差 Mean±standard 变幅 Range 变异系数 CV (%) 偏度 Skewness 峰度 Kurtosis
2018 18.35±5.98 7.00—49.00 32.58 1.31 0.49
2019 15.75±4.65 6.00—33.80 29.55 3.09 0.05

Fig. 1

Histogram of tillering number frequency distribution under 2-year environmental conditions"

Table 2

Significant loci associated with tillering number in japonica rice"

QTL 年份
Year
峰值SNP
Peak SNP
染色体
Chr.
P
P value
表型贡献率
R2(%)
已定位QTL
QTL located
qTiller8 2018 7527329 8 2.02E-06 9.36
qTiller9 2018 15065450 9 6.99E-08 11.86 qNOT9-1[29]
qTiller10 2018 15406671 10 2.64E-06 9.10
qTiller9 2019 15060619 9 2.55E-07 10.61 qNOT9-1[29]

Fig. 2

Manhattan plots and quantile-quantile (Q-Q) plots of genome-wide association studies for the tillering number A and B indicate the result of 2018 and 2019, respective"

Table 3

Candidate gene haplotype group and the composition of each haplotype SNP"

基因
Gene
单倍型1/品种数
hap1/Number
单倍型2/品种数
hap2/Number
单倍型3/品种数
hap3/Number
LOC_Os09g25090 AGG/182 TAA/81
LOC_Os09g25100 AGCC/188 GAGA/89
LOC_Os09g25150 ATG/190 GCC/69 GTC/17
LOC_Os09g25190 ATGCTGATGAAGTCATCC/126 GCATCGCATCGACGCCGA/76
LOC_Os09g25200 AGA/181 TAG/89
LOC_Os09g25220 GG/97 AA/187

Fig. 3

Boxplots for the tillering number based on the haplotypes(hap) for candidate gene Green, yellow and blue indicate phenotypic result for hap1, hap2 and hap3, respectively"

Table 4

Candidate gene of gene annotation"

基因 Gene 基因功能注释 Gene annotation
LOC_Os09g25090 钙调蛋白依赖性蛋白激酶
Calmodulin depedent protein kinases
LOC_Os09g25100 钙调蛋白依赖性蛋白激酶
Calmodulin depedent protein kinases
LOC_Os09g25150 肉桂酰辅酶A还原酶
Cinnamoyl-CoA reductase
LOC_Os09g25190 蛋白结合蛋白Protein binding protein
LOC_Os09g25200 蛋白结合蛋白Protein binding protein
LOC_Os09g25220 蛋白结合蛋白Protein binding protein
[1] LI X Y, QIAN Q, FU Z M, WANG Y H, XIONG G S, ZENG D L, WANG X Q, LIU X F, TENG S, FUJIMOTO H, YUAN M, LOU D, HAN B, LI J Y. Control of tillering in rice. Nature, 2003,422(6932):618.
doi: 10.1038/nature01518 pmid: 12687001
[2] SHAO G, LU Z, XIONG J, WANG B, JING Y, MENG X, LIU G, MA H, LIANG Y, CHEN F, WANG Y, LI J, YU H. Tiller bud formation regulators MOC1 and MOC3 cooperatively promote tiller bud outgrowth by activating FON1 expression in rice. Molecular Plant, 2019,12(8):1090-1102.
doi: 10.1016/j.molp.2019.04.008 pmid: 31048024
[3] KOUMOTO T, SHIMADA H, KUSANO H, SHE , SHE K C, IWAMOTO M, TAKANO M. Rice monoculm mutation moc2, which inhibits outgrowth of the second tillers, is ascribed to lack of a fructose-1, 6-bisphosphatase. Plant Biotechnology, 2013,30(1):47-56.
doi: 10.5511/plantbiotechnology.12.1210a
[4] LU Z F, SHAO G N, XIONG J S, JIAO Y Q, WANG J, LIU G F, MENG X B, LIANG Y, XIONG G S, WANG Y H. MONOCULM 3, an ortholog of WUSCHEL in rice, is required for tiller bud formation. Journal of Genetics and Genomics, 2015,42(2):71-78.
doi: 10.1016/j.jgg.2014.12.005 pmid: 25697101
[5] TANAKA W, OHMORI Y, USHIJIMA T, MATSUSAKA H, MATSUSHITA T, KUMAMARU T, KAWANO S, HIRANO H. Y. Axillary meristem formation in rice requires the WUSCHEL ortholog TILLERS ABSENT1. The Plant Cell, 2015,27(4):1173-1184.
pmid: 25841039
[6] TETSUO O, JUNKO K. Two-Step Regulation of LAX PANICLE1 protein accumulation in axillary meristem formation in rice. The Plant Cell, 2009,21(4):1095-1108.
pmid: 19346465
[7] KOMATSU K, MASAHIKO M, SHIN U, YUZUKI S, IKUYO F, HIRONOBU O, KO S, JUNKO K. LAX and SPA: Major regulators of shoot branching in rice. Proceedings of the National Academy of Sciences of the United States of America, 2003,100(20):11765-11770.
doi: 10.1073/pnas.1932414100 pmid: 13130077
[8] HIROAKI T, YU Z, SUSUMU H, MINAMI O, SAE S S, TETSUO O, QIAN Q, MINORU N, HIDEMI K, HE X. LAX PANICLE2 of rice encodes a novel nuclear protein and regulates the formation of axillary meristems. The Plant Cell, 2011,23(9):3276-3287.
pmid: 21963665
[9] LIU K, LIU L L, REN Y L, WANG Z Q, ZHOU K N, LIU X, WANG D, ZHENG M, CHENG Z J, LIN Q B. Dwarf and tiller-enhancing 1 regulates growth and development by influencing boron uptake in boron limited conditions in rice. Plant Science, 2015,236:18-28.
pmid: 26025517
[10] MACKAY I, POWELL W. Methods for linkage disequilibrium mapping in crops. Trends in Plant Science, 2007,12(2):57-63.
doi: 10.1016/j.tplants.2006.12.001 pmid: 17224302
[11] MACKAY T, STONE E A, AYROLES J F. The genetics of quantitative traits: challenges and prospects. Nature Reviews Genetics, 2009,10(8):565-577.
pmid: 19584810
[12] KLEIN R J, ZEISS C, CHEW E Y, TSAI J Y, SACKLER R S, HAYNES C, HENNING A K, SANGIOVANNI J P, MANE S M, MAYNE S T, BRACKEN M B, FERRIS F L, OTT J, BARNSTABLE C, HOH J. Complement factor H polymorphism in age-related macular degeneration. Science, 2005,308(5720):385-389.
doi: 10.1126/science.1109557 pmid: 15761122
[13] BAI X F, ZHAO H, HUANG Y, XIE W B, HAN Z M, ZHANG B, GUO Z L, YANG L, DONG H J, XUE W Y. Genome-wide association analysis reveals different genetic control in panicle architecture between and rice. The Plant Genome, 2016,9(2).
pmid: 27898819
[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. Frontiers in Plant Science, 2016,7:1270.
[15] MAGWA R A, ZHAO H, XING Y Z. Genome-wide association mapping revealed a diverse genetic basis of seed dormancy across subpopulations in rice (Oryza sativa L.). BMC Genetics, 2016,17(1):28.
doi: 10.1186/s12863-016-0340-2
[16] MAGWA R A, ZHAO H U, YAO W, XIE W B, YANG L, XING Y Z, BAI X F. Genome wide association analysis for awn length linked to the seed shattering gene qSH1 in rice. Journal of Genetics, 2016,95(3):639.
doi: 10.1007/s12041-016-0679-1 pmid: 27659335
[17] ZHOU H, LI P B, XIE W B, HUSSAIN S, LI Y B, XIA D, ZHAO H, SUN S Y, CHEN J X, YE H, HOU J, ZHAO D, GAO G J, ZHANG Q L, WANG G W, LIAN X M, XIAO J H, YU S B, HE Y Q. Genome-wide association analyses reveal the genetic basis of stigma exsertion in Rice. Molecular Plant, 2017,10(4):634-644.
pmid: 28110091
[18] HUANG X H, HAN B. Natural variations and genome-wide association studies in crop plants. Annual Review of Plant Biology, 2014,65(1):531-551.
doi: 10.1146/annurev-arplant-050213-035715
[19] HUANG X H, ZHAO Y, WEI X H, LI C Y, WANG A, ZHAO Q, LI W J, GUO Y L, DENG L W, ZHU C R. Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm. Nature Genetics, 2012,44(1):32.
doi: 10.1038/ng.1018 pmid: 22138690
[20] HUANG X H, WEI X H, SANG T, ZHAO Q, FENG Q, ZHAO Y, LI C Y, ZHU C R, LU T T, ZHANG Z W. Genome-wide association studies of 14 agronomic traits in rice landraces. Nature Genetics, 2010,42(11):961.
doi: 10.1038/ng.695 pmid: 20972439
[21] FANG C, MA Y, WU S W, LIU Z, WANG Z, YANG R, HU G G, ZHOU Z K, YU H, ZHANG M. Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean. Genome Biology, 2017,18(1):161.
doi: 10.1186/s13059-017-1289-9 pmid: 28838319
[22] TIAN C G, WAN P, SUN S H, LI J Y, CHEN M S. Genome-wide analysis of the GRAS gene family in rice and Arabidopsis. Plant Molecular Biology, 2004,54(4):519-532.
doi: 10.1023/B:PLAN.0000038256.89809.57 pmid: 15316287
[23] LI N, ZHENG H L, CUI J N, WANG J G, LIU H L, SUN J, LIU T T, ZHAO H W, LAI Y C, ZOU D T. Genome-wide association study and candidate gene analysis of alkalinity tolerance in japonica rice germplasm at the seedling stage, Rice, 2019,12(1):24-35.
doi: 10.1186/s12284-019-0285-y pmid: 30976929
[24] YANG J, LEE S, GODDARD M E, VISSCHER P M. GCTA: A tool for genome-wide complex trait analysis. The American Journal of Human Genetics, 2011,88(1):76-82.
doi: 10.1016/j.ajhg.2010.11.011 pmid: 21167468
[25] SAITOU N, NEI M. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Molecular Biology and Evolution, 1987,4(4):406-425.
doi: 10.1093/oxfordjournals.molbev.a040454 pmid: 3447015
[26] KUMAR S, STECHER G, TAMURA K. MEGA7: Molecular evolutionary genetics analysis version 7.0 for bigger datasets. Molecular Biology and Evolution, 2016,33(7):1870-1874.
pmid: 27004904
[27] BRADBURY P J, ZHANG Z W, 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(19):2633-2635.
doi: 10.1093/bioinformatics/btm308 pmid: 17586829
[28] 郑天清, 余泓, 张洪亮, 吴志超, 王文生, 太帅帅, 迟璐, 阮珏, 韦朝春, 石建新. 水稻功能基因组育种数据库(RFGB): 3K水稻SNP与InDel子数据库. 科学通报, 2015(4):367-371.
ZHENG T Q, YU H, ZHANG H L, WU Z C, WANG W S, TAI S S, CHI L, RUAN Y, WEI C C, SHI J X. Rice functional genome breeding database (RFGB): 3K rice SNP and InDel subdatabase, Science Bulletin, 2015(4):367-371. (in Chinese)
[29] HEMAMALINI G S, SHASHIDHAR H E, HITTALMANI S, Molecular marker assisted tagging of morphological and physiological traits under two contrasting moisture regimes at peak vegetative stage in rice (Oryza sativa L.), Euphytica, 2000,112(1):69-78.
[30] PATIL S, TAKEZAWA D, POOVAIAH B W. Chimeric plant calcium/ calmodulin-dependent protein kinase gene with a Neural Visinin-like calcium-binding domain. Proceedings of the National Academy of Sciences of the United States of America, 1995,92(11):4897-4901.
pmid: 7761420
[31] TAKEZAWA D, RAMACHANDIRAN S, PARANJAPE V, POOVAIAH B W. Dual regulation of a chimeric plant serine/threonine kinase by calcium and calcium/calmodulin. The Journal of Biological Chemistry, 1996,271(14):8126.
doi: 10.1074/jbc.271.14.8126 pmid: 8626500
[32] ZHU G, YE N, ZHANG J. Glucose-induced delay of seed germination in rice is mediated by the suppression of ABA catabolism rather than an enhancement of ABA biosynthesis. Plant and Cell Physiology, 2009,50(3):644-651.
pmid: 19208695
[33] LUO L, TAKAHASHI M, KAMEOKA H, QIN R, SHIGA T, KANNO Y, SEO M, ITOH M, XU G H, KYOZUKA J. Developmental analysis of the early steps in strigolactone-mediated axillary bud dormancy in rice. The Plant Journal, 2019,97(6):1006-1021.
pmid: 30740793
[34] SCHWARTZ S H, TAN B C, MCCARTY D R, WELCH W, ZEEVAART J A D. Substrate specificity and kinetics for VP14, a carotenoid cleavage dioxygenase in the ABA biosynthetic pathway, Biochimica et Biophysica Acta-General Subjects, 2003,1619(1):9-14.
[35] SOREFAN K, BOOKER J, HAUROGNÉ K, GOUSSOT M, LEYSER O. MAX4 and RMS1 are orthologous dioxygenase-like genes that regulate shoot branching in Arabidopsis and Pea. Genes & Development, 2003,17(12):1469-1474.
doi: 10.1101/gad.256603 pmid: 12815068
[36] SCHWARTZ S H, QIN X, LOEWEN M C. The biochemical characterization of two carotenoid cleavage enzymes from Arabidopsis indicates that a carotenoid-derived compound inhibits lateral branching. Journal of Biological Chemistry, 2004,279(45):46940-46945.
pmid: 15342640
[37] ZHANG A Y, JIANG M Y, ZHANG J H, DING H D, XU S C, HU X L, TAN M P. Nitric oxide induced by hydrogen peroxide mediates abscisic acid-induced activation of the mitogen-activated protein kinase cascade involved in antioxidant defense in maize leaves. New Phytologist, 2007,175(1):36-50.
pmid: 17547665
[38] ZHANG A Y, JIANG M Y, ZHANG J H, TAN M P, HU X L. Mitogen-activated protein kinase is involved in abscisic acid-induced antioxidant defense and acts downstream of reactive oxygen species production in leaves of maize plants. Plant Physiology, 2006,141(2):475.
pmid: 16531486
[39] 杨洪强, 接玉玲, 李林光. 脱落酸信号转导研究进展. 植物学通报, 2001(4):427-435.
YANG H Q, JIE Y L, LI L G. Research progress on abscisic acid signal transduction, Botany bulletin, 2001(4):427-435. (in Chinese)
[1] HU Sheng,LI YangYang,TANG ZhangLin,LI JiaNa,QU CunMin,LIU LieZhao. Genome-Wide Association Analysis of the Changes in Oil Content and Protein Content Under Drought Stress in Brassica napus L. [J]. Scientia Agricultura Sinica, 2023, 56(1): 17-30.
[2] ZHU DaWei,ZHANG LinPing,CHEN MingXue,FANG ChangYun,YU YongHong,ZHENG XiaoLong,SHAO YaFang. Characteristics of High-Quality Rice Varieties and Taste Sensory Evaluation Values in China [J]. Scientia Agricultura Sinica, 2022, 55(7): 1271-1283.
[3] ZHI Lei,ZHE Li,SUN NanNan,YANG Yang,Dauren Serikbay,JIA HanZhong,HU YinGang,CHEN Liang. Genome-Wide Association Analysis of Lead Tolerance in Wheat at Seedling Stage [J]. Scientia Agricultura Sinica, 2022, 55(6): 1064-1081.
[4] LI Heng,ZI XiangDong,WANG Hui,XIONG Yan,LÜ MingJie,LIU Yu,JIANG XuDong. Screening of Key Regulatory Genes for Litter Size Trait Based on Whole Genome Re-Sequencing in Goats (Capra hircus) [J]. Scientia Agricultura Sinica, 2022, 55(23): 4753-4768.
[5] 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.
[6] 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.
[7] LinHan ZOU,XinYing ZHOU,ZeYuan ZHANG,Rui YU,Meng YUAN,XiaoPeng SONG,JunTao JIAN,ChuanLiang ZHANG,DeJun HAN,QuanHao SONG. QTL Mapping of Thousand-Grain-Weight and Its Related Traits in Zhou 8425B × Xiaoyan 81 Population and Haplotype Analysis [J]. Scientia Agricultura Sinica, 2022, 55(18): 3473-3483.
[8] BaoHua CHU,FuGuo CAO,NingNing BIAN,Qian QIAN,ZhongXing LI,XueWei LI,ZeYuan LIU,FengWang MA,QingMei GUAN. Resistant Evaluation of 84 Apple Cultivars to Alternaria alternata f. sp. mali and Genome-Wide Association Analysis [J]. Scientia Agricultura Sinica, 2022, 55(18): 3613-3628.
[9] CHANG LiGuo,HE KunHui,LIU JianChao. Mining of Genetic Locus of Maize Stay-Green Related Traits Under Multi-Environments [J]. Scientia Agricultura Sinica, 2022, 55(16): 3071-3081.
[10] LI Ting,DONG Yuan,ZHANG Jun,FENG ZhiQian,WANG YaPeng,HAO YinChuan,ZHANG XingHua,XUE JiQuan,XU ShuTu. Genome-Wide Association Study of Ear Related Traits in Maize Hybrids [J]. Scientia Agricultura Sinica, 2022, 55(13): 2485-2499.
[11] WANG Juan, MA XiaoMei, ZHOU XiaoFeng, WANG Xin, TIAN Qin, LI ChengQi, DONG ChengGuang. Genome-Wide Association Study of Yield Component Traits in Upland Cotton (Gossypium hirsutum L.) [J]. Scientia Agricultura Sinica, 2022, 55(12): 2265-2277.
[12] CUI ChengQi, LIU YanYang, JIANG XiaoLin, SUN ZhiYu, DU ZhenWei, WU Ke, MEI HongXian, ZHENG YongZhan. Multi-Locus Genome-Wide Association Analysis of Yield-Related Traits and Candidate Gene Prediction in Sesame (Sesamum indicum L.) [J]. Scientia Agricultura Sinica, 2022, 55(1): 219-232.
[13] ZHANG PengFei,SHI LiangYu,LIU JiaXin,LI Yang,WU ChengBin,WANG LiXian,ZHAO FuPing. Advance in Genome-Wide Scan of Runs of Homozygosity in Domestic Animals [J]. Scientia Agricultura Sinica, 2021, 54(24): 5316-5326.
[14] YAN YongLiang,SHI XiaoLei,ZHANG JinBo,GENG HongWei,XIAO Jing,LU ZiFeng,NI ZhongFu,CONG Hua. Genome-Wide Association Study of Grain Quality Related Characteristics of Spring Wheat [J]. Scientia Agricultura Sinica, 2021, 54(19): 4033-4047.
[15] SONG ChunHui,CHEN XiaoFei,WANG MeiGe,ZHENG XianBo,SONG ShangWei,JIAO Jian,WANG MiaoMiao,MA FengWang,BAI TuanHui. Identification of Candidate Genes for Waterlogging Tolerance in Apple Rootstock by Using SLAF-seq Technique [J]. Scientia Agricultura Sinica, 2021, 54(18): 3932-3944.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!