210 related articles for article (PubMed ID: 38448703)
1. Multi-locus genome-wide association studies reveal the dynamic genetic architecture of flowering time in chrysanthemum.
Su J; Zeng J; Wang S; Zhang X; Zhao L; Wen S; Zhang F; Jiang J; Chen F
Plant Cell Rep; 2024 Mar; 43(4):84. PubMed ID: 38448703
[TBL] [Abstract][Full Text] [Related]
2. Multi-locus genome-wide association study and genomic prediction for flowering time in chrysanthemum.
Su J; Lu Z; Zeng J; Zhang X; Yang X; Wang S; Zhang F; Jiang J; Chen F
Planta; 2023 Dec; 259(1):13. PubMed ID: 38063918
[TBL] [Abstract][Full Text] [Related]
3. Identification of QTNs, QTN-by-environment interactions and genes for yield-related traits in rice using 3VmrMLM.
Zhang J; Wang S; Wu X; Han L; Wang Y; Wen Y
Front Plant Sci; 2022; 13():995609. PubMed ID: 36325550
[TBL] [Abstract][Full Text] [Related]
4. Identification of QTNs, QTN-by-environment interactions, and their candidate genes for salt tolerance related traits in soybean.
Chen Y; Yue XL; Feng JY; Gong X; Zhang WJ; Zuo JF; Zhang YM
BMC Plant Biol; 2024 Apr; 24(1):316. PubMed ID: 38654195
[TBL] [Abstract][Full Text] [Related]
5. Identification of favorable SNP alleles and candidate genes responsible for inflorescence-related traits via GWAS in chrysanthemum.
Chong X; Su J; Wang F; Wang H; Song A; Guan Z; Fang W; Jiang J; Chen S; Chen F; Zhang F
Plant Mol Biol; 2019 Mar; 99(4-5):407-420. PubMed ID: 30701353
[TBL] [Abstract][Full Text] [Related]
6. Identification of QTNs, QTN-by-environment interactions, and their candidate genes for grain size traits in main crop and ratoon rice.
Zhao Q; Shi XS; Wang T; Chen Y; Yang R; Mi J; Zhang YW; Zhang YM
Front Plant Sci; 2023; 14():1119218. PubMed ID: 36818826
[TBL] [Abstract][Full Text] [Related]
7. Genome-wide detection of genotype environment interactions for flowering time in
Han X; Tang Q; Xu L; Guan Z; Tu J; Yi B; Liu K; Yao X; Lu S; Guo L
Front Plant Sci; 2022; 13():1065766. PubMed ID: 36479520
[TBL] [Abstract][Full Text] [Related]
8. Genome-wide association studies of five free amino acid levels in rice.
He L; Wang H; Sui Y; Miao Y; Jin C; Luo J
Front Plant Sci; 2022; 13():1048860. PubMed ID: 36420042
[TBL] [Abstract][Full Text] [Related]
9. Identification of QTNs and Their Candidate Genes for 100-Seed Weight in Soybean (Glycine max L.) Using Multi-Locus Genome-Wide Association Studies.
Ikram M; Han X; Zuo JF; Song J; Han CY; Zhang YW; Zhang YM
Genes (Basel); 2020 Jun; 11(7):. PubMed ID: 32604988
[TBL] [Abstract][Full Text] [Related]
10. Genetic dissection of flowering time in flax (Linum usitatissimum L.) through single- and multi-locus genome-wide association studies.
Soto-Cerda BJ; Aravena G; Cloutier S
Mol Genet Genomics; 2021 Jul; 296(4):877-891. PubMed ID: 33903955
[TBL] [Abstract][Full Text] [Related]
11. Genetic dissection of maize (Zea mays L.) chlorophyll content using multi-locus genome-wide association studies.
Xiong X; Li J; Su P; Duan H; Sun L; Xu S; Sun Y; Zhao H; Chen X; Ding D; Zhang X; Tang J
BMC Genomics; 2023 Jul; 24(1):384. PubMed ID: 37430212
[TBL] [Abstract][Full Text] [Related]
12. Identification of QTNs and their candidate genes for flowering time and plant height in soybean using multi-locus genome-wide association studies.
Han X; Xu ZR; Zhou L; Han CY; Zhang YM
Mol Breed; 2021 Jun; 41(6):39. PubMed ID: 37309439
[TBL] [Abstract][Full Text] [Related]
13. A compressed variance component mixed model for detecting QTNs and QTN-by-environment and QTN-by-QTN interactions in genome-wide association studies.
Li M; Zhang YW; Zhang ZC; Xiang Y; Liu MH; Zhou YH; Zuo JF; Zhang HQ; Chen Y; Zhang YM
Mol Plant; 2022 Apr; 15(4):630-650. PubMed ID: 35202864
[TBL] [Abstract][Full Text] [Related]
14. Genome-wide association studies using multi-models and multi-SNP datasets provide new insights into pasmo resistance in flax.
He L; Sui Y; Che Y; Wang H; Rashid KY; Cloutier S; You FM
Front Plant Sci; 2023; 14():1229457. PubMed ID: 37954993
[TBL] [Abstract][Full Text] [Related]
15. New insights into QTNs and potential candidate genes governing rice yield via a multi-model genome-wide association study.
Sachdeva S; Singh R; Maurya A; Singh VK; Singh UM; Kumar A; Singh GP
BMC Plant Biol; 2024 Feb; 24(1):124. PubMed ID: 38373874
[TBL] [Abstract][Full Text] [Related]
16. Multi-omics analysis reveals novel loci and a candidate regulatory gene of unsaturated fatty acids in soybean (Glycine max (L.) Merr).
Zhao X; Zhan Y; Li K; Zhang Y; Zhou C; Yuan M; Liu M; Li Y; Zuo P; Han Y; Zhao X
Biotechnol Biofuels Bioprod; 2024 Mar; 17(1):43. PubMed ID: 38493136
[TBL] [Abstract][Full Text] [Related]
17. Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses.
Wen YJ; Wu X; Wang S; Han L; Shen B; Wang Y; Zhang J
Front Plant Sci; 2023; 14():1050313. PubMed ID: 36875585
[TBL] [Abstract][Full Text] [Related]
18. Compressed variance component mixed model reveals epistasis associated with flowering in
Han L; Shen B; Wu X; Zhang J; Wen YJ
Front Plant Sci; 2023; 14():1283642. PubMed ID: 38259933
[TBL] [Abstract][Full Text] [Related]
19. Genome-wide association studies reveal novel QTLs, QTL-by-environment interactions and their candidate genes for tocopherol content in soybean seed.
Yu K; Miao H; Liu H; Zhou J; Sui M; Zhan Y; Xia N; Zhao X; Han Y
Front Plant Sci; 2022; 13():1026581. PubMed ID: 36388509
[TBL] [Abstract][Full Text] [Related]
20. Genetic Dissection of Epistatic Interactions Contributing Yield-Related Agronomic Traits in Rice Using the Compressed Mixed Model.
Li L; Wu X; Chen J; Wang S; Wan Y; Ji H; Wen Y; Zhang J
Plants (Basel); 2022 Sep; 11(19):. PubMed ID: 36235370
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]