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380 related items for PubMed ID: 31862941

  • 1. Exploring genetic architecture of grain yield and quality traits in a 16-way indica by japonica rice MAGIC global population.
    Zaw H, Raghavan C, Pocsedio A, Swamy BPM, Jubay ML, Singh RK, Bonifacio J, Mauleon R, Hernandez JE, Mendioro MS, Gregorio GB, Leung H.
    Sci Rep; 2019 Dec 20; 9(1):19605. PubMed ID: 31862941
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  • 2. QTL analysis of novel genomic regions associated with yield and yield related traits in new plant type based recombinant inbred lines of rice (Oryza sativa L.).
    Marathi B, Guleria S, Mohapatra T, Parsad R, Mariappan N, Kurungara VK, Atwal SS, Prabhu KV, Singh NK, Singh AK.
    BMC Plant Biol; 2012 Aug 09; 12():137. PubMed ID: 22876968
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  • 4. Validation of Yield Component Traits Identified by Genome-Wide Association Mapping in a tropical japonica × tropical japonica Rice Biparental Mapping Population.
    Eizenga GC, Jia MH, Jackson AK, Boykin DL, Ali ML, Shakiba E, Tran NT, McCouch SR, Edwards JD.
    Plant Genome; 2019 Mar 09; 12(1):. PubMed ID: 30951093
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  • 5. Genetic connection between cell-wall composition and grain yield via parallel QTL analysis in indica and japonica subspecies.
    Xu Z, Li S, Zhang C, Zhang B, Zhu K, Zhou Y, Liu Q.
    Sci Rep; 2017 Oct 02; 7(1):12561. PubMed ID: 28970550
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  • 6. Mapping QTLs for improving grain yield using the USDA rice mini-core collection.
    Li X, Yan W, Agrama H, Jia L, Shen X, Jackson A, Moldenhauer K, Yeater K, McClung A, Wu D.
    Planta; 2011 Aug 02; 234(2):347-61. PubMed ID: 21479810
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  • 7. Enhanced Expression of QTL qLL9/DEP1 Facilitates the Improvement of Leaf Morphology and Grain Yield in Rice.
    Fu X, Xu J, Zhou M, Chen M, Shen L, Li T, Zhu Y, Wang J, Hu J, Zhu L, Gao Z, Dong G, Guo L, Ren D, Chen G, Lin J, Qian Q, Zhang G.
    Int J Mol Sci; 2019 Feb 17; 20(4):. PubMed ID: 30781568
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  • 13. Identifying natural genotypes of grain number per panicle in rice (Oryza sativa L.) by association mapping.
    Xie J, Li F, Khan NU, Zhu X, Wang X, Zhang Z, Ma X, Zhao Y, Zhang Q, Zhang S, Zhang Z, Li J, Li Z, Zhang H.
    Genes Genomics; 2019 Mar 17; 41(3):283-295. PubMed ID: 30456522
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  • 17. Identify QTLs and candidate genes underlying source-, sink-, and grain yield-related traits in rice by integrated analysis of bi-parental and natural populations.
    Wang Y, Wang J, Zhai L, Liang C, Chen K, Xu J.
    PLoS One; 2020 Mar 17; 15(8):e0237774. PubMed ID: 32797075
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  • 18. Genetic analysis of grain shape and weight after cutting rice husk.
    Fu JR, Zhu LX, Sun XT, Zhou DH, Ouyang LJ, Bian JM, He HH, Xu J.
    Genet Mol Res; 2015 Dec 22; 14(4):17739-48. PubMed ID: 26782419
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  • 20. QTL analysis and dissection of panicle components in rice using advanced backcross populations derived from Oryza Sativa cultivars HR1128 and 'Nipponbare'.
    Sun Z, Yin X, Ding J, Yu D, Hu M, Sun X, Tan Y, Sheng X, Liu L, Mo Y, Ouyang N, Jiang B, Yuan G, Duan M, Yuan D, Fang J.
    PLoS One; 2017 Dec 22; 12(4):e0175692. PubMed ID: 28422981
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