Prediction of malting quality traits in barley based on genome-wide marker data to assess the potential of genomic selection

被引:45
|
作者
Schmidt, Malthe [1 ]
Kollers, Sonja [1 ]
Maasberg-Prelle, Anja [1 ]
Grosser, Joerg [1 ]
Schinkel, Burkhard [1 ]
Tomerius, Alexandra [1 ,2 ]
Graner, Andreas [3 ]
Korzun, Viktor [1 ]
机构
[1] KWS LOCHOW GMBH, D-29303 Bergen, Norway
[2] AIB Dr Alexandra Tomerius, D-38304 Wolfenbuttel, Germany
[3] Leibniz Inst Plant Genet & Crop Plant Res IPK Gat, D-06466 Stadt Seeland, Germany
关键词
ASSISTED SELECTION; RESISTANCE; ASSOCIATION; POPULATIONS; ACCURACY; WHEAT; LOCI; OPTIMIZATION; STRATEGIES; COMPONENTS;
D O I
10.1007/s00122-015-2639-1
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Key message Genomic prediction of malting quality traits in barley shows the potential of applying genomic selection to improve selection for malting quality and speed up the breeding process. Genomic selection has been applied to various plant species, mostly for yield or yield-related traits such as grain dry matter yield or thousand kernel weight, and improvement of resistances against diseases. Quality traits have not been the main scope of analysis for genomic selection, but have rather been addressed by marker-assisted selection. In this study, the potential to apply genomic selection to twelve malting quality traits in two commercial breeding programs of spring and winter barley (Hordeum vulgare L.) was assessed. Phenotypic means were calculated combining multilocational field trial data from 3 or 4 years, depending on the trait investigated. Three to five locations were available in each of these years. Heritabilities for malting traits ranged between 0.50 and 0.98. Predictive abilities (PA), as derived from cross validation, ranged between 0.14 to 0.58 for spring barley and 0.40-0.80 for winter barley. Small training sets were shown to be sufficient to obtain useful PAs, possibly due to the narrow genetic base in this breeding material. Deployment of genomic selection in malting barley breeding clearly has the potential to reduce cost intensive phenotyping for quality traits, increase selection intensity and to shorten breeding cycles.
引用
收藏
页码:203 / 213
页数:11
相关论文
共 50 条
  • [41] Genome-wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing
    Yang, Ruifei
    Xu, Zhenqiang
    Wang, Qi
    Zhu, Di
    Bian, Cheng
    Ren, Jiangli
    Huang, Zhuolin
    Zhu, Xiaoning
    Tian, Zhixin
    Wang, Yuzhe
    Jiang, Ziqin
    Zhao, Yiqiang
    Zhang, Dexiang
    Li, Ning
    Hu, Xiaoxiang
    GENETICS SELECTION EVOLUTION, 2021, 53 (01)
  • [42] Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus
    Muller, Barbara S. F.
    Neves, Leandro G.
    de Almeida Filho, Janeo E.
    Resende, Marcio F. R., Jr.
    Munoz, Patricio R.
    dos Santos, Paulo E. T.
    Paludzyszyn Filho, Estefano
    Kirst, Matias
    Grattapaglia, Dario
    BMC GENOMICS, 2017, 18
  • [43] Genome-wide Association Study and Genomic Prediction for Fusarium graminearum Resistance Traits in Nordic Oat (Avena sativa L.)
    Haikka, Hanna
    Manninen, Outi
    Hautsalo, Juho
    Pietila, Leena
    Jalli, Marja
    Vetelainen, Merja
    AGRONOMY-BASEL, 2020, 10 (02):
  • [44] Genome wide association study and genomic prediction for stover quality traits in tropical maize (Zea mays L.)
    Vinayan, M. T.
    Seetharam, K.
    Babu, Raman
    Zaidi, P. H.
    Blummel, M.
    Nair, Sudha K.
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [45] Multi-model genome-wide association study on key organic naked barley agronomic, phenological, diseases, and grain quality traits
    Paire, Laura
    Mccabe, Cathal
    Mccabe, Tomas
    EUPHYTICA, 2024, 220 (07)
  • [46] The first application of genomic selection for tree morphological traits in Pinus koraiensis using markers identified through a genome-wide association study
    Jeon, Donghyun
    Kang, Yuna
    Lim, Yoonho
    Lee, Kyungmi
    Cheon, Kyeong-seong
    Lee, Tae-ho
    Shim, Donghwan
    Kim, Changsoo
    FORESTRY, 2025,
  • [47] Genome-Wide Association Study of Meat Quality Traits in Hanwoo Beef Cattle Using Imputed Whole-Genome Sequence Data
    Bedhane, Mohammed
    van der Werf, Julius
    Gondro, Cedric
    Duijvesteijn, Naomi
    Lim, Dajeong
    Park, Byoungho
    Park, Mi Na
    Hee, Roh Seung
    Clark, Samuel
    FRONTIERS IN GENETICS, 2019, 10
  • [48] Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection
    McElroy, Michel S.
    Navarro, Alberto J. R.
    Mustiga, Guiliana
    Stack, Conrad
    Gezan, Salvador
    Pena, Geover
    Sarabia, Widem
    Saquicela, Diego
    Sotomayor, Ignacio
    Douglas, Gavin M.
    Migicovsky, Zoe
    Amores, Freddy
    Tarqui, Omar
    Myles, Sean
    Motamayor, Juan C.
    FRONTIERS IN PLANT SCIENCE, 2018, 9
  • [49] Genome-wide association mapping and genomic prediction of agronomical traits and breeding values in Iranian wheat under rain-fed and well-watered conditions
    Rabieyan, Ehsan
    Bihamta, Mohammad Reza
    Moghaddam, Mohsen Esmaeilzadeh
    Mohammadi, Valiollah
    Alipour, Hadi
    BMC GENOMICS, 2022, 23 (01)
  • [50] A new strategy for using historical imbalanced yield data to conduct genome-wide association studies and develop genomic prediction models for wheat breeding
    Chu, Chenggen
    Wang, Shichen
    Rudd, Jackie C.
    Ibrahim, Amir M. H.
    Xue, Qingwu
    Devkota, Ravindra N.
    Baker, Jason A.
    Baker, Shannon
    Simoneaux, Bryan
    Opena, Geraldine
    Dong, Haixiao
    Liu, Xiaoxiao
    Jessup, Kirk E.
    Chen, Ming-Shun
    Hui, Kele
    Metz, Richard
    Johnson, Charles D.
    Zhang, Zhiwu S.
    Liu, Shuyu
    MOLECULAR BREEDING, 2022, 42 (04)