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491 related items for PubMed ID: 27698483
1. Comparative and parallel genome-wide association studies for metabolic and agronomic traits in cereals. Chen W, Wang W, Peng M, Gong L, Gao Y, Wan J, Wang S, Shi L, Zhou B, Li Z, Peng X, Yang C, Qu L, Liu X, Luo J. Nat Commun; 2016 Oct 04; 7():12767. PubMed ID: 27698483 [Abstract] [Full Text] [Related]
2. Genome wide association mapping for grain shape traits in indica rice. Feng Y, Lu Q, Zhai R, Zhang M, Xu Q, Yang Y, Wang S, Yuan X, Yu H, Wang Y, Wei X. Planta; 2016 Oct 04; 244(4):819-30. PubMed ID: 27198135 [Abstract] [Full Text] [Related]
3. Genetic variation and association mapping for 12 agronomic traits in indica rice. Lu Q, Zhang M, Niu X, Wang S, Xu Q, Feng Y, Wang C, Deng H, Yuan X, Yu H, Wang Y, Wei X. BMC Genomics; 2015 Dec 16; 16():1067. PubMed ID: 26673149 [Abstract] [Full Text] [Related]
4. Comparative Genetics of Seed Size Traits in Divergent Cereal Lineages Represented by Sorghum (Panicoidae) and Rice (Oryzoidae). Zhang D, Li J, Compton RO, Robertson J, Goff VH, Epps E, Kong W, Kim C, Paterson AH. G3 (Bethesda); 2015 Mar 31; 5(6):1117-28. PubMed ID: 25834216 [Abstract] [Full Text] [Related]
5. Genome wide screening and comparative genome analysis for Meta-QTLs, ortho-MQTLs and candidate genes controlling yield and yield-related traits in rice. Khahani B, Tavakol E, Shariati V, Fornara F. BMC Genomics; 2020 Apr 10; 21(1):294. PubMed ID: 32272882 [Abstract] [Full Text] [Related]
6. Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism. Chen W, Gao Y, Xie W, Gong L, Lu K, Wang W, Li Y, Liu X, Zhang H, Dong H, Zhang W, Zhang L, Yu S, Wang G, Lian X, Luo J. Nat Genet; 2014 Jul 10; 46(7):714-21. PubMed ID: 24908251 [Abstract] [Full Text] [Related]
7. Fine-mapping of qGW4.05, a major QTL for kernel weight and size in maize. Chen L, Li YX, Li C, Wu X, Qin W, Li X, Jiao F, Zhang X, Zhang D, Shi Y, Song Y, Li Y, Wang T. BMC Plant Biol; 2016 Apr 12; 16():81. PubMed ID: 27068015 [Abstract] [Full Text] [Related]
8. Genome-wide association mapping for yield and other agronomic traits in an elite breeding population of tropical rice (Oryza sativa). Begum H, Spindel JE, Lalusin A, Borromeo T, Gregorio G, Hernandez J, Virk P, Collard B, McCouch SR. PLoS One; 2015 Apr 12; 10(3):e0119873. PubMed ID: 25785447 [Abstract] [Full Text] [Related]
9. Genome-wide association study of rice grain width variation. Zheng XM, Gong T, Ou HL, Xue D, Qiao W, Wang J, Liu S, Yang Q, Olsen KM. Genome; 2018 Apr 12; 61(4):233-240. PubMed ID: 29193996 [Abstract] [Full Text] [Related]
10. 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 12; 12(1):. PubMed ID: 30951093 [Abstract] [Full Text] [Related]
11. Genome-wide association study (GWAS) reveals the genetic architecture of four husk traits in maize. Cui Z, Luo J, Qi C, Ruan Y, Li J, Zhang A, Yang X, He Y. BMC Genomics; 2016 Nov 21; 17(1):946. PubMed ID: 27871222 [Abstract] [Full Text] [Related]
12. Genetic analysis for rice grain quality traits in the YVB stable variant line using RAD-seq. Peng Y, Hu Y, Mao B, Xiang H, Shao Y, Pan Y, Sheng X, Li Y, Ni X, Xia Y, Zhang G, Yuan L, Quan Z, Zhao B. Mol Genet Genomics; 2016 Feb 21; 291(1):297-307. PubMed ID: 26334612 [Abstract] [Full Text] [Related]
13. Genome-wide association mapping of leaf mass traits in a Vietnamese rice landrace panel. Hoang GT, Gantet P, Nguyen KH, Phung NTP, Ha LT, Nguyen TT, Lebrun M, Courtois B, Pham XH. PLoS One; 2019 Feb 21; 14(7):e0219274. PubMed ID: 31283792 [Abstract] [Full Text] [Related]
14. GWAS identifies an ortholog of the rice D11 gene as a candidate gene for grain size in an international collection of hexaploid wheat. Tekeu H, Ngonkeu ELM, Bélanger S, Djocgoué PF, Abed A, Torkamaneh D, Boyle B, Tsimi PM, Tadesse W, Jean M, Belzile F. Sci Rep; 2021 Sep 30; 11(1):19483. PubMed ID: 34593838 [Abstract] [Full Text] [Related]
15. Genome-wide association study of important agronomic traits within a core collection of rice (Oryza sativa L.). Zhang P, Zhong K, Zhong Z, Tong H. BMC Plant Biol; 2019 Jun 17; 19(1):259. PubMed ID: 31208337 [Abstract] [Full Text] [Related]
16. OsSPL13 controls grain size in cultivated rice. Si L, Chen J, Huang X, Gong H, Luo J, Hou Q, Zhou T, Lu T, Zhu J, Shangguan Y, Chen E, Gong C, Zhao Q, Jing Y, Zhao Y, Li Y, Cui L, Fan D, Lu Y, Weng Q, Wang Y, Zhan Q, Liu K, Wei X, An K, An G, Han B. Nat Genet; 2016 Apr 17; 48(4):447-56. PubMed ID: 26950093 [Abstract] [Full Text] [Related]
17. Combined GWAS and QTL analysis for dissecting the genetic architecture of kernel test weight in maize. Zhang X, Guan Z, Wang L, Fu J, Zhang Y, Li Z, Ma L, Liu P, Zhang Y, Liu M, Li P, Zou C, He Y, Lin H, Yuan G, Gao S, Pan G, Shen Y. Mol Genet Genomics; 2020 Mar 17; 295(2):409-420. PubMed ID: 31807910 [Abstract] [Full Text] [Related]
18. Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Yano K, Yamamoto E, Aya K, Takeuchi H, Lo PC, Hu L, Yamasaki M, Yoshida S, Kitano H, Hirano K, Matsuoka M. Nat Genet; 2016 Aug 17; 48(8):927-34. PubMed ID: 27322545 [Abstract] [Full Text] [Related]
19. OsBRKq1, Related Grain Size Mapping, and Identification of Grain Shape Based on QTL Mapping in Rice. Park JR, Resolus D, Kim KM. Int J Mol Sci; 2021 Feb 25; 22(5):. PubMed ID: 33669006 [Abstract] [Full Text] [Related]
20. Unraveling candidate genomic regions responsible for delayed leaf senescence in rice. Singh UM, Sinha P, Dixit S, Abbai R, Venkateshwarlu C, Chitikineni A, Singh VK, Varshney RK, Kumar A. PLoS One; 2020 Feb 25; 15(10):e0240591. PubMed ID: 33057376 [Abstract] [Full Text] [Related] Page: [Next] [New Search]