583 related articles for article (PubMed ID: 25689273)
1. Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.
Spindel J; Begum H; Akdemir D; Virk P; Collard B; Redoña E; Atlin G; Jannink JL; McCouch SR
PLoS Genet; 2015 Feb; 11(2):e1004982. PubMed ID: 25689273
[TBL] [Abstract][Full Text] [Related]
2. 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; 10(3):e0119873. PubMed ID: 25785447
[TBL] [Abstract][Full Text] [Related]
3. Genome-Wide Association Mapping for Yield and Yield-Related Traits in Rice (
Ashfaq M; Rasheed A; Zhu R; Ali M; Javed MA; Anwar A; Tabassum J; Shaheen S; Wu X
Genes (Basel); 2023 May; 14(5):. PubMed ID: 37239449
[TBL] [Abstract][Full Text] [Related]
4. A comparison of five methods to predict genomic breeding values of dairy bulls from genome-wide SNP markers.
Moser G; Tier B; Crump RE; Khatkar MS; Raadsma HW
Genet Sel Evol; 2009 Dec; 41(1):56. PubMed ID: 20043835
[TBL] [Abstract][Full Text] [Related]
5. Genomic Prediction Accuracy of Seven Breeding Selection Traits Improved by QTL Identification in Flax.
Lan S; Zheng C; Hauck K; McCausland M; Duguid SD; Booker HM; Cloutier S; You FM
Int J Mol Sci; 2020 Feb; 21(5):. PubMed ID: 32106624
[TBL] [Abstract][Full Text] [Related]
6. Accuracy of genomic selection for a sib-evaluated trait using identity-by-state and identity-by-descent relationships.
Vela-Avitúa S; Meuwissen TH; Luan T; Ødegård J
Genet Sel Evol; 2015 Feb; 47(1):9. PubMed ID: 25888184
[TBL] [Abstract][Full Text] [Related]
7. Genome-wide prediction of traits with different genetic architecture through efficient variable selection.
Wimmer V; Lehermeier C; Albrecht T; Auinger HJ; Wang Y; Schön CC
Genetics; 2013 Oct; 195(2):573-87. PubMed ID: 23934883
[TBL] [Abstract][Full Text] [Related]
8. Genomic Prediction for Grain Yield and Yield-Related Traits in Chinese Winter Wheat.
Ali M; Zhang Y; Rasheed A; Wang J; Zhang L
Int J Mol Sci; 2020 Feb; 21(4):. PubMed ID: 32079240
[TBL] [Abstract][Full Text] [Related]
9. Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement.
Spindel JE; Begum H; Akdemir D; Collard B; Redoña E; Jannink JL; McCouch S
Heredity (Edinb); 2016 Apr; 116(4):395-408. PubMed ID: 26860200
[TBL] [Abstract][Full Text] [Related]
10. Optimizing Training Population Data and Validation of Genomic Selection for Economic Traits in Soft Winter Wheat.
Hoffstetter A; Cabrera A; Huang M; Sneller C
G3 (Bethesda); 2016 Sep; 6(9):2919-28. PubMed ID: 27440921
[TBL] [Abstract][Full Text] [Related]
11. Developing high throughput genotyped chromosome segment substitution lines based on population whole-genome re-sequencing in rice (Oryza sativa L.).
Xu J; Zhao Q; Du P; Xu C; Wang B; Feng Q; Liu Q; Tang S; Gu M; Han B; Liang G
BMC Genomics; 2010 Nov; 11():656. PubMed ID: 21106060
[TBL] [Abstract][Full Text] [Related]
12. Breeding value estimation for fat percentage using dense markers on Bos taurus autosome 14.
de Roos AP; Schrooten C; Mullaart E; Calus MP; Veerkamp RF
J Dairy Sci; 2007 Oct; 90(10):4821-9. PubMed ID: 17881705
[TBL] [Abstract][Full Text] [Related]
13. Genome-Wide Association Study Using Historical Breeding Populations Discovers Genomic Regions Involved in High-Quality Rice.
Quero G; Gutiérrez L; Monteverde E; Blanco P; Pérez de Vida F; Rosas J; Fernández S; Garaycochea S; McCouch S; Berberian N; Simondi S; Bonnecarrère V
Plant Genome; 2018 Nov; 11(3):. PubMed ID: 30512035
[TBL] [Abstract][Full Text] [Related]
14. Gene based markers improve precision of genome-wide association studies and accuracy of genomic predictions in rice breeding.
Anilkumar C; Muhammed Azharudheen TP; Sah RP; Sunitha NC; Devanna BN; Marndi BC; Patra BC
Heredity (Edinb); 2023 May; 130(5):335-345. PubMed ID: 36792661
[TBL] [Abstract][Full Text] [Related]
15. Genome-Wide Association Study of Grain Appearance and Milling Quality in a Worldwide Collection of Indica Rice Germplasm.
Qiu X; Pang Y; Yuan Z; Xing D; Xu J; Dingkuhn M; Li Z; Ye G
PLoS One; 2015; 10(12):e0145577. PubMed ID: 26714258
[TBL] [Abstract][Full Text] [Related]
16. Accuracy of Genomic Selection in a Rice Synthetic Population Developed for Recurrent Selection Breeding.
Grenier C; Cao TV; Ospina Y; Quintero C; Châtel MH; Tohme J; Courtois B; Ahmadi N
PLoS One; 2015; 10(8):e0136594. PubMed ID: 26313446
[TBL] [Abstract][Full Text] [Related]
17. Evaluation of genomic selection methods for predicting fiber quality traits in Upland cotton.
Islam MS; Fang DD; Jenkins JN; Guo J; McCarty JC; Jones DC
Mol Genet Genomics; 2020 Jan; 295(1):67-79. PubMed ID: 31473809
[TBL] [Abstract][Full Text] [Related]
18. Genetic and phenotypic characterization of rice grain quality traits to define research strategies for improving rice milling, appearance, and cooking qualities in Latin America and the Caribbean.
Cruz M; Arbelaez JD; Loaiza K; Cuasquer J; Rosas J; Graterol E
Plant Genome; 2021 Nov; 14(3):e20134. PubMed ID: 34510797
[TBL] [Abstract][Full Text] [Related]
19. An efficient unified model for genome-wide association studies and genomic selection.
Li H; Su G; Jiang L; Bao Z
Genet Sel Evol; 2017 Aug; 49(1):64. PubMed ID: 28836943
[TBL] [Abstract][Full Text] [Related]
20. From gene banks to farmer's fields: using genomic selection to identify donors for a breeding program in rice to close the yield gap on smallholder farms.
Tanaka R; Lui-King J; Mandaharisoa ST; Rakotondramanana M; Ranaivo HN; Pariasca-Tanaka J; Kanegae HK; Iwata H; Wissuwa M
Theor Appl Genet; 2021 Oct; 134(10):3397-3410. PubMed ID: 34264372
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
