Plant Gene and Traits 2024, Vol.15, No.4, 207-219 http://genbreedpublisher.com/index.php/pgt 217 Grattapaglia D., Silva-Junior O., Resende R., Cappa E., Müller B., Tan B., Isik F., Ratcliffe B., and El-Kassaby Y., 2018, Quantitative genetics and genomics converge to accelerate forest tree breeding, Frontiers in Plant Science, 9: 1693. https://doi.org/10.3389/fpls.2018.01693 PMid:30524463 PMCid:PMC6262028 Hasan N., Choudhary S., Naaz N., Sharma N., and Laskar R., 2021, Recent advancements in molecular marker-assisted selection and applications in plant breeding programmes, Journal of Genetic Engineering & Biotechnology, 19(1): 128. https://doi.org/10.1186/s43141-021-00231-1 PMid:34448979 PMCid:PMC8397809 Jaganathan D., Ramasamy K., Sellamuthu G., Jayabalan S., and Venkataraman G., 2018, CRISPR for crop improvement: an update review, Frontiers in Plant Science, 9: 985. https://doi.org/10.3389/fpls.2018.00985 PMid:30065734 PMCid:PMC6056666 Jighly A., Lin Z., Pembleton L., Cogan N., Spangenberg G., Hayes B., and Daetwyler H., 2019, Boosting genetic gain in allogamous crops via speed breeding and genomic selection, Frontiers in Plant Science, 10: 1364. https://doi.org/10.3389/fpls.2019.01364 PMid:31803197 PMCid:PMC6873660 Karunarathna K., Mewan K., Weerasena O., Perera S., and Edirisinghe E., 2020, A functional molecular marker for detecting blister blight disease resistance in tea (Camellia sinensis L.), Plant Cell Reports, 40: 351-359. https://doi.org/10.1007/s00299-020-02637-6 PMid:33247387 Kawall K., 2021, Genome-edited Camelina sativa with a unique fatty acid content and its potential impact on ecosystems, Environmental Sciences Europe, 33: 38. https://doi.org/10.1186/s12302-021-00482-2 Kim M., Nguyen T., Ahn J., Kim G., and Sim S., 2021, Genome-wide association study identifies QTL for eight fruit traits in cultivated tomato (Solanum lycopersicumL.), Horticulture Research, 8: 203. https://doi.org/10.1038/s41438-021-00638-4 PMid:34465758 PMCid:PMC8408251 Lima L., Azevedo C., Resende M., Nascimento M., and Silva F., 2022, Evaluation of Bayesian methods of genomic association via chromosomic regions using simulated data, Scientia Agricola, 79: e20200202. https://doi.org/10.1590/1678-992x-2020-0202 Liu C.C., 2024, Interaction between tea tree root probiotics and tea yellowing disease, Journal of Tea Science Research, 14(1): 10-18. Lubanga N., Massawe F., and Mayes S., 2021, Genomic and pedigree‐based predictive ability for quality traits in tea (Camellia sinensis (L.) O. Kuntze), Euphytica, 217: 32. https://doi.org/10.1007/s10681-021-02774-3 Mahmood U., Li X., Fan Y., Chang W., Niu Y., Li J., Qu C., and Lu K., 2022, Multi-omics revolution to promote plant breeding efficiency, Frontiers in Plant Science, 13: 1062952. https://doi.org/10.3389/fpls.2022.1062952 PMid:36570904 PMCid:PMC9773847 Marone D., Mastrangelo A., and Borrelli G., 2023, From transgenesis to genome editing in crop improvement: applications, marketing, and legal issues, International Journal of Molecular Sciences, 24(8): 7122. https://doi.org/10.3390/ijms24087122 PMid:37108285 PMCid:PMC10138802 Merrick L., Herr A., Sandhu K., Lozada D., and Carter A., 2022, Optimizing plant breeding programs for genomic selection, Agronomy, 12(3): 714. https://doi.org/10.3390/agronomy12030714 Mohammadi M., Xavier A., Beckett T., Beyer S., Chen L., Chikssa H., Cross V., Moreira F., French E., Gaire R., Griebel S., López M., Prather S., Russell B., and Wang W., 2020, Identification, deployment, and transferability of quantitative trait loci from genome-wide association studies in plants, Current Plant Biology, 24: 100145. https://doi.org/10.1016/j.cpb.2020.100145 Nascimento F., Rocha A., Soares J., Mascarenhas M., Ferreira M., Lino L., Ramos A., Diniz L., Mendes T., Ferreira C., Santos-Serejo J., and Amorim E., 2023, Gene editing for plant resistance to abiotic factors: a systematic review, Plants, 12(2): 305. https://doi.org/10.3390/plants12020305 PMid:36679018 PMCid:PMC9860801 Pascual L., Albert E., Sauvage C., Duangjit J., Bouchet J., Bitton F., Desplat N., Brunel D., Paslier M., Ranc N., Bruguier L., Chauchard B., Verschave P., and Causse M., 2016, Dissecting quantitative trait variation in the resequencing era: complementarity of bi-parental, multi-parental and association panels, Plant Science, 242: 120-130. https://doi.org/10.1016/j.plantsci.2015.06.017 PMid:26566830
RkJQdWJsaXNoZXIy MjQ4ODYzMg==