Diversifying maize genomic selection models

被引:13
作者
Rice, Brian R. [1 ]
Lipka, Alexander E. [1 ]
机构
[1] Univ Illinois, Dept Crop Sci, Urbana, IL 61801 USA
基金
美国国家科学基金会;
关键词
Genomic selection; Maize; Hybrid prediction; Omics; Multi-kernel; GBLUP; MARKER-ASSISTED SELECTION; GENETIC ARCHITECTURE; PREDICTION ACCURACY; STATISTICAL-METHODS; HYBRID PERFORMANCE; BREEDING POPULATIONS; QUANTITATIVE TRAIT; WIDE ASSOCIATION; COMPLEX TRAITS; PLANT;
D O I
10.1007/s11032-021-01221-4
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Genomic selection (GS) is one of the most powerful tools available for maize breeding. Its use of genome-wide marker data to estimate breeding values translates to increased genetic gains with fewer breeding cycles. In this review, we cover the history of GS and highlight particular milestones during its adaptation to maize breeding. We discuss how GS can be applied to developing superior maize inbreds and hybrids. Additionally, we characterize refinements in GS models that could enable the encapsulation of non-additive genetic effects, genotype by environment interactions, and multiple levels of the biological hierarchy, all of which could ultimately result in more accurate predictions of breeding values. Finally, we suggest the stages in a maize breeding program where it would be beneficial to apply GS. Given the current sophistication of high-throughput phenotypic, genotypic, and other -omic level data currently available to the maize community, now is the time to explore the implications of their incorporation into GS models and thus ensure that genetic gains are being achieved as quickly and efficiently as possible.
引用
收藏
页数:15
相关论文
共 156 条
  • [1] Alliance G, 2010, GENETICS 101 UNDERST, P22
  • [2] The Genetic Architecture of Maize (Zea mays L.) Kernel Weight Determination
    Alvarez Prado, Santiago
    Lopez, Cesar G.
    Lynn Senior, M.
    Borras, Lucas
    [J]. G3-GENES GENOMES GENETICS, 2014, 4 (09): : 1611 - 1621
  • [3] Directions for research and training in plant omics: Big Questions and Big Data
    Argueso, Cristiana T.
    Assmann, Sarah M.
    Birnbaum, Kenneth D.
    Chen, Sixue
    Dinneny, Jose R.
    Doherty, Colleen J.
    Eveland, Andrea L.
    Friesner, Joanna
    Greenlee, Vanessa R.
    Law, Julie A.
    Marshall-Colon, Amy
    Mason, Grace Alex
    O'Lexy, Ruby
    Peck, Scott C.
    Schmitz, Robert J.
    Song, Liang
    Stern, David
    Varagona, Marguerite J.
    Walley, Justin W.
    Williams, Cranos M.
    [J]. PLANT DIRECT, 2019, 3 (04)
  • [4] Comparing genomic selection and marker-assisted selection for Fusarium head blight resistance in wheat (Triticum aestivum L.)
    Arruda, M. P.
    Lipka, A. E.
    Brown, P. J.
    Krill, A. M.
    Thurber, C.
    Brown-Guedira, G.
    Dong, Y.
    Foresman, B. J.
    Kolb, F. L.
    [J]. MOLECULAR BREEDING, 2016, 36 (07)
  • [5] The interaction of plant biotic and abiotic stresses: from genes to the field
    Atkinson, Nicky J.
    Urwin, Peter E.
    [J]. JOURNAL OF EXPERIMENTAL BOTANY, 2012, 63 (10) : 3523 - 3543
  • [6] Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype x Environment Interaction
    Bandeira e Sousa, Massaine
    Cuevas, Jaime
    de Oliveira Couto, Evellyn Giselly
    Perez-Rodriguez, Paulino
    Jarquin, Diego
    Fritsche-Neto, Roberto
    Burgueno, Juan
    Crossa, Jose
    [J]. G3-GENES GENOMES GENETICS, 2017, 7 (06): : 1995 - 2014
  • [7] Hybrid Wheat Prediction Using Genomic, Pedigree, and Environmental Covariables Interaction Models
    Basnet, Bhoja Raj
    Crossa, Jose
    Dreisigacker, Susanne
    Perez-Rodriguez, Paulino
    Manes, Yann
    Singh, Ravi P.
    Rosyara, Umesh R.
    Camarillo-Castillo, Fatima
    Murua, Mercedes
    [J]. PLANT GENOME, 2019, 12 (01)
  • [8] Spontaneous epigenetic variation in the Arabidopsis thaliana methylome
    Becker, Claude
    Hagmann, Joerg
    Mueller, Jonas
    Koenig, Daniel
    Stegle, Oliver
    Borgwardt, Karsten
    Weigel, Detlef
    [J]. NATURE, 2011, 480 (7376) : 245 - U127
  • [10] Molecular markers and selection for complex traits in plants: Learning from the last 20 years
    Bernardo, Rex
    [J]. CROP SCIENCE, 2008, 48 (05) : 1649 - 1664