Gene based markers improve precision of genome-wide association studies and accuracy of genomic predictions in rice breeding-Reference-Cited by-同舟云学术

Gene based markers improve precision of genome-wide association studies and accuracy of genomic predictions in rice breeding

Published:2023-02-15 Issue:5 Volume:130 Page:335-345
ISSN:0018-067X
Container-title:Heredity
language:en
Short-container-title:Heredity

Author:

Anilkumar Chandrappa^ORCID,Muhammed Azharudheen T. P.,Sah Rameswar Prasad,Sunitha Nagenahalli Chandrappa^ORCID,Devanna Basavantraya N.,Marndi Bishnu Charan,Patra Bhaskar Chandra

Publisher

Springer Science and Business Media LLC

Subject

Genetics (clinical),Genetics

Link

https://www.nature.com/articles/s41437-023-00599-5.pdf

Reference83 articles.

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2. Ahmar S, Gill RA, Jung K-H, Faheem A, Qasim MU, Mubeen M et al. (2020) Conventional and molecular techniques from simple breeding to speed breeding in crop plants: recent advances and future outlook. Int J Mol Sci 21:2590. https://doi.org/10.3390/ijms21072590

3. Alvarado G, Rodríguez FM, Pacheco A, Burgueño J, Crossa J, Vargas M et al. (2020) META-R: A software to analyze data from multi-environment plant breeding trials. Crop J 8:745–756. https://doi.org/10.1016/j.cj.2020.03.010

4. Anilkumar C, Sah RP, Muhammed ATP, Sunitha NC, Behera S, Marndi BC et al. (2022a) Genomic selection in rice: current status and future prospects. in: genomic selection in plants a guide for breeders, CRC Press, Taylor and Francis group, United States, pp 68–82

5. Anilkumar C, Sah RP, Muhammed Azharudheen TP, Behera S, Singh N, Prakash NR et al. (2022b) Understanding complex genetic architecture of rice grain weight through QTL-meta analysis and candidate gene identification. Sci Rep. 12:13832. https://doi.org/10.1038/s41598-022-17402-w

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