Computational Molecular Biology 2026, Vol.16, No.3, 159-180 http://bioscipublisher.com/index.php/cmb 175 Da Y., Wang C., Wang S., and Hu G., 2014, Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers, PLoS One, 9(1): e87666. https://doi.org/10.1371/journal.pone.0087666 Dao C., Jiang J., Paul D., and Zhao H., 2021, Variance estimation and confidence intervals from genome-wide association studies through high-dimensional misspecified mixed model analysis, Journal of Statistical Planning and Inference, 220: 15-23. https://doi.org/10.1016/j.jspi.2022.01.003 Derbyshire M.C., Newman T.E., Thomas W.J., Batley J., and Edwards D., 2024, The complex relationship between disease resistance and yield in crops, Plant Biotechnology Journal, 22: 2612-2623. https://doi.org/10.1111/pbi.14373 Ding Y., Hou K., Burch K., Lapinska S., Privé F., Vilhjálmsson B., Sankararaman S., and Pasaniuc B., 2021, Large uncertainty in individual polygenic risk score estimation impacts PRS-based risk stratification, Nature Genetics, 54: 30-39. https://doi.org/10.1038/s41588-021-00961-5 Evans L.M., Tahmasbi R., Vrieze S.I., Abecasis G.R., Das S., Gazal S., Bjelland D.W., de Candia T.R., Goddard M.E., Neale B.M., Yang J., Visscher P.M., and Keller M.C., 2017, Comparison of methods that use whole genome data to estimate the heritability and genetic architecture of complex traits, Nature Genetics, 50: 737-745. https://doi.org/10.1038/s41588-018-0108-x Fang X.J., and Wu W.R., 2026, Evolution of statistical genetic paradigms: from linkage analysis and candidate gene strategies to GWAS, Molecular Plant Breeding, 24(9): 2817-2829. Fang X.J., Wu W.R., and Tang J.L., (eds.), 2001, Crop DNA marker-assisted breeding, Science Press, Beijing, China, pp.1-84. Finucane H.K., Bulik-Sullivan B., Gusev A., Trynka G., Reshef Y., Loh P.R., Anttila V., Xu H., Zang C.Z., Farh K., Ripke S., Day F.R., Consortium R., Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Purcell S., Stahl E., Lindstrom S., Perry J.R.B., Okada Y., Raychaudhuri S., Daly M.J., Patterson N., Neale B.M., and Price A.L., 2015, Partitioning heritability by functional annotation using genome-wide association summary statistics, Nature Genetics, 47: 1228-1235. https://doi.org/10.1038/ng.3404 Forni S., Aguilar I., and Misztal I., 2011, Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information, Genetics Selection Evolution, 43: 1. https://doi.org/10.1186/1297-9686-43-1 Gazal S., Loh P.R., Finucane H.K., Ganna A., Schoech, A., Sunyaev, S., and Price A.L., 2018, Functional architecture of low-frequency variants highlights strength of negative selection across coding and noncoding annotations, Nature Genetics, 50: 1600-1607. https://doi.org/10.1038/s41588-018-0231-8 Gazal S., Weissbrod O., Hormozdiari F., Dey K., Nasser J., Jagadeesh K., Weiner D., Shi H., Fulco C., O'Connor L., Pasaniuc B., Engreitz J., and Price A., 2022, Combining SNP-to-gene linking strategies to identify disease genes and assess disease omnigenicity, Nature Genetics, 54: 827-836. https://doi.org/10.1038/s41588-022-01087-y Ge T., Chen C., Neale B., Sabuncu M., and Smoller J., 2016. Phenome-wide heritability analysis of the UK Biobank. PLoS Genetics, 13. https://doi.org/10.1371/journal.pgen.1006711 https://doi.org/10.1371/journal.pgen.1006711 Génin E., 2019, Missing heritability of complex diseases: case solved? Human Genetics, 139: 103-113. https://doi.org/10.1007/s00439-019-02034-4 Granato Í., Galli G., De Oliveira Couto E., Souza M., Mendonça L., and Fritsche-Neto R., 2018, snpReady: a tool to assist breeders in genomic analysis, Molecular Breeding, 38: 84. https://doi.org/10.1007/s11032-018-0844-8 Holland D., Frei O., Fan C., Shadrin A., Smeland O., Sundar V., Thompson P., Andreassen O., and Dale A., 2020, Beyond SNP heritability: Polygenicity and discoverability of phenotypes estimated with a univariate Gaussian mixture model, PLoS Genetics, 16(5): e1008612. https://doi.org/10.1371/journal.pgen.1008612 Hou K., Burch K., Majumdar A., Shi H., Mancuso N., Wu Y., Sankararaman S., and Pasaniuc B., 2019, Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture, Nature Genetics, 51: 1244-1251. https://doi.org/10.1038/s41588-019-0465-0 Jang S.K., Evans L., Fialkowski A., Arnett D.K., Ashley-Koch A.E., Barnes K.C., Becker D.M., Bis J.C., Blangero J., Bleecker E.R., Boorgula M.P., Bowden D.W., Brody J.A., Cade B.E., Jenkins B.W.C., Carson A.P., Chavan S., Cupples L.A., Custer B., Damrauer S.M., David S.P., de Andrade M., Dinardo C.L., Fingerlin T.E., Fornage M., Freedman B.I., Garrett M.E., Gharib S.A., Glahn D.C., Haessler J., Heckbert S.R., Hokanson J.E., Hou L.F., Hwang S.J., Hyman M.C., Judy R., Justice A.E., Kaplan R.C., Kardia S.L.R., Kelly S., Kim W., Kooperberg C., Levy D., Lloyd-Jones D.M., Loos R.J.F., Manichaikul A.W., Gladwin M.T., Martin L.W., Nouraie M., Melander O., Meyers D.A., Montgomery C.G., North K.E., Oelsner E.C., Palmer N.D., Payton M., Peljto A.L., Peyser P.A., Preuss M., Psaty B.M., Qiao D.D., Rader D.J., Rafaels N., Redline S., Reed R.M., Reiner A.P., Rich S.S., Rotter J.I., Schwartz D.A., Shadyab A.H., Silverman E.K., Smith N.L., Smith J.G., Smith A.V., Smith J.A., Tang W.H., Taylor K.D., Telen M.J., Vasan R.S., Gordeuk V.R., Wang Z., Wiggins K.L., Yanek L.R., Yang I.V., Young K.A., Young K.L., Zhang Y.Z., Liu D.J.J., Keller M.C., and Vrieze S. 2022, Rare genetic variants explain missing heritability, Nature Human Behaviour, 6: 1577-1586. https://doi.org/10.1038/s41562-022-01408-5
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