IJMEC_2026v16n1

International Journal of Molecular Ecology and Conservation, 2026, Vol.16, No.1, 13-21 http://ecoevopublisher.com/index.php/ijmec 21 Sofer T., 2017, Confidence intervals for heritability via Haseman-Elston regression, Stat. Appl. Genet. Mol. Biol., 16(4): 259-273. https://doi.org/10.1515/sagmb-2016-0076 Stanton-Geddes J., Paape T., Epstein B., Briskine R., Yoder J., Mudge J., Bharti A., Farmer A., Zhou P., Denny R., May G., Erlandson S., Yakub M., Sugawara M., Sadowsky M., Young N., and Tiffin P., 2013, Candidate genes and genetic architecture of symbiotic and agronomic traits revealed by whole-genome, sequence-based association genetics in Medicago truncatula, PLoS ONE, 8 (6): e65688. https://doi.org/10.1371/journal.pone.0065688 Susmitha P., Kumar P., Yadav P., Sahoo S., Kaur G., Pandey M., Singh V., Tseng T., and Gangurde S., 2023, Genome-wide association study as a powerful tool for dissecting competitive traits in legumes, Front. Plant Sci., 14: 1123631. https://doi.org/10.3389/fpls.2023.1123631 Tam V., Patel N., Turcotte M., BosséY., ParéG., and Meyre D., 2019, Benefits and limitations of genome-wide association studies, Nat. Rev. Genet., 20(8): 467-484. https://doi.org/10.1038/s41576-019-0127-1 Taniguti C., Taniguti L., Amadeu R., Lau J., De Siqueira Gesteira G., De Paula Oliveira T., et al., 2022, Developing best practices for genotyping-by-sequencing analysis in the construction of linkage maps, GigaScience, 12(1): giad092. https://doi.org/10.1093/gigascience/giad092 Tibbs Cortes L., Zhang Z., and Yu J., 2021, Status and prospects of genome-wide association studies in plants, The plant genome, 14(1): e20077. https://doi.org/10.1002/tpg2.20077 Uffelmann E., Huang Q.Q., Munung N.S., De Vries J., Okada Y., Martin A.R., Martin H.C., Lappalainen T., and Posthuma D., 2021, Genome-wide association studies, Nat. Rev. Methods Primers, 1(1): 1-21. https://doi.org/10.1038/s43586-021-00056-9 Wang T., and Elston R.C., 2005, Two-level Haseman-Elston regression for general pedigree data analysis, Genet. Epidemiol., 29(1): 12-22. https://doi.org/10.1002/gepi.20075 Wang X., Wang J., Xia X., Xu X., Li L., Cao S., Hao Y., and Zhang L., 2024, Effect of genotyping errors on linkage map construction based on repeated chip analysis of two recombinant inbred line populations in wheat (Triticum aestivum L.), BMC Plant Biol., 24(1): 306. https://doi.org/10.1186/s12870-024-05005-8 Watanabe K., Stringer S., Frei O., Mirkov U.G., de Leeuw C.A., Polderman T.J., et al., 2019, A global overview of pleiotropy and genetic architecture in complex traits, Nat. Genet., 51(9): 1339-1348. https://doi.org/10.1038/s41588-019-0481-0 Xu T., Qi G., Zhu J., Xu H., and Chen G., 2021, Subsampling technique to estimate variance component for UK-Biobank traits, Front. Genet., 12: 612045. https://doi.org/10.3389/fgene.2021.612045 Xu Y., Li P., Yang Z., and Xu C., 2017, Genetic mapping of quantitative trait loci in crops, Crop J., 5(2): 175-184. https://doi.org/10.1016/j.cj.2016.06.003 Zhang L., Li H., and Wang J., 2015, Linkage analysis and map construction in genetic populations of clonal F1 and double cross, G3 (Bethesda), 5(3): 427-439. https://doi.org/10.1534/g3.114.016022 Zhang Y., Jia Z., and Dunwell J.M., 2019, The applications of new multi-locus GWAS methodologies in the genetic dissection of complex traits, Front. Plant Sci., 10: 100. https://doi.org/10.3389/fpls.2019.00100 Zhang Y., Wang M., Li Z., Yang X., Li K., Xie A., Dong F., Wang S.H., Yan J.B., and Liu J., 2024, An overview of detecting gene-trait associations by integrating GWAS summary statistics and eQTLs, Sci. China Life Sci., 67 (6): 1133-1154. https://doi.org/10.1007/s11427-023-2522-8 Zheng C., Boer M., and van Eeuwijk F., 2019, Construction of genetic linkage maps in multiparental populations, Genetics, 212(4): 1031-1044. https://doi.org/10.1534/genetics.119.302229 Zhou X., 2017, A unified framework for variance component estimation with summary statistics in genome-wide association studies, Ann. Appl. Stat., 11(4): 2027-2051. https://doi.org/10.1214/17-AOAS1052 Zhu M., and Zhao S., 2007, Candidate gene identification approach: Progress and challenges, Int. J. Biol. Sci., 3(7): 420-427. https://doi.org/10.7150/ijbs.3.420

RkJQdWJsaXNoZXIy MjQ4ODYzNA==