CGG_2025v16n5

Cotton Genomics and Genetics 2025, Vol.16, No.5, 249-258 257 Kuang Z., Xiao C., Ilyas M., Ibrar D., Khan S., Guo L., Wang W., Wang B., Huang H., Li Y., Zheng J., Saleem S., Tahir A., Ghafoor A., and Chen H., 2022, Use of SSR markers for the exploration of genetic diversity and DNA fingerprinting in early-maturing upland cotton (Gossypium hirsutum L.) for future breeding programs, Agronomy, 12(7): 1513. https://doi.org/10.3390/agronomy12071513 Kumar R., Das J., Puttaswamy R., Kumar M., Balasubramani G., and Prasad Y., 2024, Targeted genome editing for cotton improvement: prospects and challenges, The Nucleus, 67(1): 181-203. https://doi.org/10.1007/s13237-024-00479-1 Kushanov F., Turaev O., Ernazarova D., Gapparov B., Oripova B., Kudratova M., Rafieva F., Khalikov K., Erjigitov D., Khidirov M., Khusenov N., Amanboyeva R., Saha S., Yu J., and Abdurakhmonov I., 2021, Genetic diversity, QTL mapping, and marker-assisted selection technology in cotton (Gossypiumspp.), Frontiers in Plant Science, 12: 779386. https://doi.org/10.3389/fpls.2021.779386 Li C., Dong Y., Zhao T., Li L., Li C., Yu E., Mei L., Daud M., He Q., Chen J., and Zhu S., 2016, Genome-wide SNP linkage mapping and QTL analysis for fiber quality and yield traits in the upland cotton recombinant inbred lines population, Frontiers in Plant Science, 7: 1356. https://doi.org/10.3389/fpls.2016.01356 Li C., Guan Y., Dong Z., and Mei Y., 2024, Genetic contribution and decision-making coefficients analysis of agronomic components of upland cotton in Southern Xinjiang to yield traits, Euphytica, 220(6): 86. https://doi.org/10.1007/s10681-024-03346-x Li H., Pan Z., He S., Jia Y., Geng X., Chen B., Wang L., Pang B., and Du X., 2021, QTL mapping of agronomic and economic traits for four F2 populations of upland cotton, Journal of Cotton Research, 4(1): 3. https://doi.org/10.1186/s42397-020-00076-y Li T., Jiang S., Fu R., Wang X., Cheng Q., and Jiang S., 2023, IP4GS: bringing genomic selection analysis to breeders, Frontiers in Plant Science, 14: 1131493. https://doi.org/10.3389/fpls.2023.1131493 Li Z., Liu S., Conaty W., Zhu Q., Moncuquet P., Stiller W., and Wilson I., 2022, Genomic prediction of cotton fibre quality and yield traits using Bayesian regression methods, Heredity, 129(2): 103-112. https://doi.org/10.1038/s41437-022-00537-x Liu X., Yang L., Wang J., Wang Y., Guo Z., Li Q., Yang J., Wu Y., Chen L., Teng Z., Liu D., Guo K., and Zhang Z., 2022, Analyzing quantitative trait loci for fiber quality and yield-related traits from a recombinant inbred line population with Gossypium hirsutumrace palmeri as one parent, Frontiers in Plant Science, 12: 817748. https://doi.org/10.3389/fpls.2021.817748 Ma X., Guo W., He L., and Cao X., 2024, Polygenic genetic analysis of principal genes for yield traits in land cotton, Agronomy, 14(11): 2749. https://doi.org/10.3390/agronomy14112749 Ma Z., Zhang Y., Wu L., Zhang G., Sun Z., Li Z., Jiang Y., Ke H., Chen B., Liu Z., Gu Q., Wang Z., Wang G., Yang J., Wu J., Yan Y., Meng C., Li L., Li X., Mo S., Wu N., Chen L., Zhang M., Si A., Yang Z., Wang N., Wu L., Zhang D., Cui Y., Cui J., Lv X., Li Y., Shi R., Duan Y., Tian S., and Wang X., 2021, High-quality genome assembly and resequencing of modern cotton cultivars provide resources for crop improvement, Nature Genetics, 53(9): 1385-1391. https://doi.org/10.1038/s41588-021-00910-2 Morales N., Bauchet G., Tantikanjana T., Powell A., Ellerbrock B., Tecle I., and Mueller L., 2020, High density genotype storage for plant breeding in the Chado schema of Breedbase, PLoS ONE, 15(11): e0240059. https://doi.org/10.1371/journal.pone.0240059 Rasheed A., Hao Y., Xia X., Khan A., Xu Y., Varshney R., and He Z., 2017, Crop breeding chips and genotyping platforms: progress, challenges, and perspectives, Molecular Plant, 10(8): 1047-1064. https://doi.org/10.1016/j.molp.2017.06.008 Shakoor N., Lee S., and Mockler T., 2017, High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field, Current Opinion in Plant Biology, 38: 184-192. https://doi.org/10.1016/j.pbi.2017.05.006 Shehzad M., Ditta A., Iqbal M.S., and Jarwar, A.H., 2017, Role of molecular markers and importance of SNP for the development of cotton programs, Journal of Biology, Agriculture and Healthcare, 7(21): 61-73. Si Z., Jin S., Li J., Han Z., Li Y., Wu X., Ge Y., Fang L., Zhang T., and Hu Y., 2022, The design, validation, and utility of the “ZJU CottonSNP40K” liquid chip through genotyping by target sequencing, Industrial Crops and Products, 188: 115629. https://doi.org/10.1016/j.indcrop.2022.115629 Tan Z., Zhang Z., Sun X., Li Q., Sun Y., Yang P., Wang W., Liu X., Chen C., Liu D., Teng Z., Guo K., Zhang J., Liu D., and Zhang Z., 2018, Genetic map construction and fiber quality QTL mapping using the CottonSNP80K array in upland cotton, Frontiers in Plant Science, 9: 225. https://doi.org/10.3389/fpls.2018.00225 Varshney R., Singh V., Hickey J., Xun X., Marshall D., Wang J., Edwards D., and Ribaut J., 2016, Analytical and decision support tools for genomics-assisted breeding, Trends in Plant Science, 21(4): 354-363. https://doi.org/10.1016/j.tplants.2015.10.018 Wang F., Zhang J., Chen Y., Zhang C., Gong J., Song Z., Zhou J., Wang J., Zhao C., Jiao M., Liu A., Du Z., Yuan Y., Fan S., and Zhang J., 2020, Identification of candidate genes for key fibre-related QTLs and derivation of favourable alleles in Gossypium hirsutumrecombinant inbred lines with G. barbadense introgressions, Plant Biotechnology Journal, 18(3): 707-720. https://doi.org/10.1111/pbi.13237

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