MGG_2024v15n3

Maize Genomics and Genetics 2024, Vol.15, No.3, 111-122 http://cropscipublisher.com/index.php/mgg 121 Muntean L., ONA A., Berindean I., Racz I., and Muntean S., 2022, Maize breeding: from domestication to genomic tools, Agronomy, 12(10): 2365. https://doi.org/10.3390/agronomy12102365 Munyengwa N., Guen V., Bille H., Souza L., Clément-Demange A., Mournet P., Masson A., Soumahoro M., Kouassi D., and Cros D., 2021, Optimizing imputation of marker data from genotyping-by-sequencing (GBS) for genomic selection in non-model species: Rubber tree (Hevea brasiliensis) as a case study, Genomics, 113(2): 655-668. https://doi.org/10.1016/j.ygeno.2021.01.012 PMid:33508443 Nepolean T., Kaul J., Mukri G., and Mittal S., 2018, Genomics-enabled next-generation breeding approaches for developing system-specific drought tolerant hybrids in maize, Frontiers in Plant Science, 9: 361. https://doi.org/10.3389/fpls.2018.00361 PMid:29696027 PMCid:PMC5905169 Rice B., and Lipka A., 2021, Diversifying maize genomic selection models, Molecular Breeding, 41(5): 33. https://doi.org/10.1007/s11032-021-01221-4 PMid:37309328 PMCid:PMC10236107 Rice B., Fernandes S., and Lipka A., 2020, Multi-trait genome-wide association studies reveal loci associated with maize inflorescence and leaf architecture, Plant and Cell Physiology, 61(8): 1427-1437. https://doi.org/10.1093/pcp/pcaa039 PMid:32186727 Sadessa K., Beyene Y., Ifie B., Suresh L., Olsen M., Ogugo V., Wegary D., Tongoona P., Danquah E., Offei S., Prasanna B., and Gowda M., 2022, Identification of genomic regions associated with agronomic and disease resistance traits in a large set of multiple DH populations, Genes, 13(2): 351. https://doi.org/10.3390/genes13020351. Schrag T., Westhues M., Schipprack W., Seifert F., Thiemann A., Scholten S., and Melchinger A., 2018, Beyond genomic prediction: combining different types of omics data can improve prediction of hybrid performance in maize, Genetics, 208: 1373-1385. https://doi.org/10.1534/genetics.117.300374. PMid:29363551 PMCid:PMC5887136 Tiwari J., Yerasu S., Rai N., Singh D., Singh A., Karkute S., Singh P., and Behera T., 2022, Progress in marker-assisted selection to genomics-assisted breeding in tomato, Critical Reviews in Plant Sciences, 41: 321-350. https://doi.org/10.1080/07352689.2022.2130361 Torkamaneh D., Laroche J., Boyle B., Hyten D., and Belzile F., 2021, A bumper crop of SNPs in soybean through high‐density genotyping‐by‐sequencing (HD‐GBS), Plant Biotechnology Journal, 19: 860-862. https://doi.org/10.1111/pbi.13551 PMid:33476468 PMCid:PMC8131051 Varshney R., Bohra A., Yu J., Graner A., Zhang Q., and Sorrells M., 2021, Designing future crops: genomics-assisted breeding comes of age, Trends in Plant Science, 26(6): 631-649. https://doi.org/10.1016/j.tplants.2021.03.010 PMid:33893045 Wang N., Yuan Y., Wang H., Yu D., Liu Y., Zhang A., Gowda M., Nair S., Hao Z., Lu Y., Vicente F., Prasanna B., Li X., and Zhang X., 2020, Applications of genotyping-by-sequencing (GBS) in maize genetics and breeding, Scientific Reports, 10(1): 16308. PMid:33004874 PMCid:PMC7530987 Yan J., and Tan B., 2019, Maize biology: from functional genomics to breeding application, Journal of Integrative Plant Biology, 61(6): 654-657. https://doi.org/10.1111/jipb.12819. PMid:31099156 Yang N., and Yan J.B., 2021, New genomic approaches for enhancing maize genetic improvement, Current Opinion in Plant Biology, 60: 101977. https://doi.org/10.1016/j.pbi.2020.11.002. PMid:33418269 Yang Y.D., Saand M., Huang L., Abdelaal W., Zhang J., Wu Y., Li J., Sirohi M., and Wang F., 2021, Applications of multi-omics technologies for crop improvement, Frontiers in Plant Science, 12: 563953. https://doi.org/10.3389/fpls.2021.563953 PMid:34539683 PMCid:PMC8446515 Yuan Y.B., Cairns J.E., Babu R., Gowda M., Makumbi D., Magorokosho C., Zhang A., Liu Y.L., Wang N.F., Hao Z.F., Vicente F., Olsen M., Prasanna B., Lu Y.L., and Zhang X.C., 2019, Genome-wide association mapping and genomic prediction analyses reveal the genetic architecture of grain yield and flowering time under drought and heat stress conditions in maize, Frontiers in Plant Science, 9: 1919. https://doi.org/10.3389/fpls.2018.01919 PMid:30761177 PMCid:PMC6363715 Zhang X., Guan Z., Li Z., Liu P., Ma L., Zhang Y., Pan L., He S., Zhang Y., Li P., Ge F., Zou C., He Y., Gao S., Pan G., and Shen Y., 2020, A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments, Theoretical and Applied Genetics, 133: 2881-2895. https://doi.org/10.1007/s00122-020-03639-4

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