267 related articles for article (PubMed ID: 37047112)
21. Multiple interval QTL mapping and searching for PSTOL1 homologs associated with root morphology, biomass accumulation and phosphorus content in maize seedlings under low-P.
Azevedo GC; Cheavegatti-Gianotto A; Negri BF; Hufnagel B; E Silva Lda C; Magalhaes JV; Garcia AA; Lana UG; de Sousa SM; Guimaraes CT
BMC Plant Biol; 2015 Jul; 15():172. PubMed ID: 26148492
[TBL] [Abstract][Full Text] [Related]
22. Meta-Analysis of Quantitative Traits Loci (QTL) Identified in Drought Response in Rice (
Selamat N; Nadarajah KK
Plants (Basel); 2021 Apr; 10(4):. PubMed ID: 33917162
[TBL] [Abstract][Full Text] [Related]
23. Consensus map integration and QTL meta-analysis narrowed a locus for yield traits to 0.7 cM and refined a region for late leaf spot resistance traits to 0.38 cM on linkage group A05 in peanut (Arachis hypogaea L.).
Lu Q; Liu H; Hong Y; Li H; Liu H; Li X; Wen S; Zhou G; Li S; Chen X; Liang X
BMC Genomics; 2018 Dec; 19(1):887. PubMed ID: 30526476
[TBL] [Abstract][Full Text] [Related]
24. Comparative mapping combined with homology-based cloning of the rice genome reveals candidate genes for grain zinc and iron concentration in maize.
Jin T; Chen J; Zhu L; Zhao Y; Guo J; Huang Y
BMC Genet; 2015 Feb; 16():17. PubMed ID: 25888360
[TBL] [Abstract][Full Text] [Related]
25. Meta-analysis of grain iron and zinc associated QTLs identified hotspot chromosomal regions and positional candidate genes for breeding biofortified rice.
Raza Q; Riaz A; Sabar M; Atif RM; Bashir K
Plant Sci; 2019 Nov; 288():110214. PubMed ID: 31521222
[TBL] [Abstract][Full Text] [Related]
26. Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping.
Chen L; An Y; Li YX; Li C; Shi Y; Song Y; Zhang D; Wang T; Li Y
Front Plant Sci; 2017; 8():2190. PubMed ID: 29312420
[TBL] [Abstract][Full Text] [Related]
27. Genome-wide association screening and verification of potential genes associated with root architectural traits in maize (Zea mays L.) at multiple seedling stages.
Moussa AA; Mandozai A; Jin Y; Qu J; Zhang Q; Zhao H; Anwari G; Khalifa MAS; Lamboro A; Noman M; Bakasso Y; Zhang M; Guan S; Wang P
BMC Genomics; 2021 Jul; 22(1):558. PubMed ID: 34284723
[TBL] [Abstract][Full Text] [Related]
28. Meta-QTLs, ortho-meta QTLs and related candidate genes for yield and its component traits under water stress in wheat (
Kumar A; Saini DK; Saripalli G; Sharma PK; Balyan HS; Gupta PK
Physiol Mol Biol Plants; 2023 Apr; 29(4):525-542. PubMed ID: 37187772
[TBL] [Abstract][Full Text] [Related]
29. Genome-wide association study to identify genomic loci associated with early vigor in bread wheat under simulated water deficit complemented with quantitative trait loci meta-analysis.
Rahimi Y; Khahani B; Jamali A; Alipour H; Bihamta MR; Ingvarsson PK
G3 (Bethesda); 2023 Feb; 13(2):. PubMed ID: 36458966
[TBL] [Abstract][Full Text] [Related]
30. A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice.
Aloryi KD; Okpala NE; Amo A; Bello SF; Akaba S; Tian X
Front Plant Sci; 2022; 13():1035851. PubMed ID: 36466247
[TBL] [Abstract][Full Text] [Related]
31. Genomic analysis of ionome-related QTLs in Arabidopsis thaliana.
Shariatipour N; Heidari B; Ravi S; Stevanato P
Sci Rep; 2021 Sep; 11(1):19194. PubMed ID: 34584138
[TBL] [Abstract][Full Text] [Related]
32. Comparative Genomic Analysis of Quantitative Trait Loci Associated With Micronutrient Contents, Grain Quality, and Agronomic Traits in Wheat (
Shariatipour N; Heidari B; Tahmasebi A; Richards C
Front Plant Sci; 2021; 12():709817. PubMed ID: 34712248
[TBL] [Abstract][Full Text] [Related]
33. Comprehensive meta-analysis of QTL and gene expression studies identify candidate genes associated with
Baisakh N; Da Silva EA; Pradhan AK; Rajasekaran K
Front Plant Sci; 2023; 14():1214907. PubMed ID: 37534296
[TBL] [Abstract][Full Text] [Related]
34. Integrating GWAS and Gene Expression Analysis Identifies Candidate Genes for Root Morphology Traits in Maize at the Seedling Stage.
Wang H; Wei J; Li P; Wang Y; Ge Z; Qian J; Fan Y; Ni J; Xu Y; Yang Z; Xu C
Genes (Basel); 2019 Oct; 10(10):. PubMed ID: 31581635
[TBL] [Abstract][Full Text] [Related]
35. Improved resolution in the position of drought-related QTLs in a single mapping population of rice by meta-analysis.
Khowaja FS; Norton GJ; Courtois B; Price AH
BMC Genomics; 2009 Jun; 10():276. PubMed ID: 19545420
[TBL] [Abstract][Full Text] [Related]
36. Meta-QTLs for multiple disease resistance involving three rusts in common wheat (Triticum aestivum L.).
Pal N; Jan I; Saini DK; Kumar K; Kumar A; Sharma PK; Kumar S; Balyan HS; Gupta PK
Theor Appl Genet; 2022 Jul; 135(7):2385-2405. PubMed ID: 35699741
[TBL] [Abstract][Full Text] [Related]
37. Genome-wide meta-analysis of QTL for morphological related traits of flag leaf in bread wheat.
Du B; Wu J; Islam MS; Sun C; Lu B; Wei P; Liu D; Chen C
PLoS One; 2022; 17(10):e0276602. PubMed ID: 36279291
[TBL] [Abstract][Full Text] [Related]
38. Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding.
Tanin MJ; Saini DK; Sandhu KS; Pal N; Gudi S; Chaudhary J; Sharma A
Sci Rep; 2022 Aug; 12(1):13680. PubMed ID: 35953529
[TBL] [Abstract][Full Text] [Related]
39. Reproductive tissues-specific meta-QTLs and candidate genes for development of heat-tolerant rice cultivars.
Raza Q; Riaz A; Bashir K; Sabar M
Plant Mol Biol; 2020 Sep; 104(1-2):97-112. PubMed ID: 32643113
[TBL] [Abstract][Full Text] [Related]
40. Meta-QTL analysis explores the key genes, especially hormone related genes, involved in the regulation of grain water content and grain dehydration rate in maize.
Wang W; Ren Z; Li L; Du Y; Zhou Y; Zhang M; Li Z; Yi F; Duan L
BMC Plant Biol; 2022 Jul; 22(1):346. PubMed ID: 35842577
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]