Genetic evaluation including intermediate omics features

被引:38
作者
Christensen, Ole F. [1 ]
Borner, Vinzent [1 ]
Varona, Luis [2 ]
Legarra, Andres [3 ]
机构
[1] Aarhus Univ, Ctr Quantitat Genet & Genom, Blichers Alle 20,Postboks 50, DK-8830 Tjele, Denmark
[2] Univ Zaragoza, Dept Anat Embriol & Genet Anim, Saragoza 50013, Spain
[3] INRA, GenPhySE Genet Physiol & Syst Elevage, F-31326 Castanet Tolosan, France
关键词
genetic evaluation; breeding value; mixed model equations; single-step method; transcriptomics; metabolomics; Genomic Prediction; GenPred; Shared Data Resource; GENOMIC PREDICTIONS; TRAITS;
D O I
10.1093/genetics/iyab130
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
In animal and plant breeding and genetics, there has been an increasing interest in intermediate omics traits, such as metabolomics and transcriptomics, which mediate the effect of genetics on the phenotype of interest. For inclusion of such intermediate traits into a genetic evaluation system, there is a need for a statistical model that integrates phenotypes, genotypes, pedigree, and omics traits, and a need for associated computational methods that provide estimated breeding values. In this paper, a joint model for phenotypes and omics data is presented, and a formula for the breeding values on individuals is derived. For complete omics data, three equivalent methods for best linear unbiased prediction of breeding values are presented. In all three cases, this requires solving two mixed model equation systems. Estimation of parameters using restricted maximum likelihood is also presented. For incomplete omics data, extensions of two of these methods are presented, where in both cases, the extension consists of extending an omics-related similarity matrix to incorporate individuals without omics data. The methods are illustrated using a simulated data set.
引用
收藏
页数:14
相关论文
共 28 条
  • [1] Genetic variance of metabolomic features and their relationship with body weight and body weight gain in Holstein cattle
    Aliakbari, Amir
    Ehsani, Alireza
    Torshizi, Rasoul Vaez
    Lovendahl, Peter
    Esfandyari, Hadi
    Jensen, Just
    Sarup, Pernille
    [J]. JOURNAL OF ANIMAL SCIENCE, 2019, 97 (09) : 3832 - 3844
  • [2] Host Genome Influence on Gut Microbial Composition and Microbial Prediction of Complex Traits in Pigs
    Camarinha-Silva, Amelia
    Maushammer, Maria
    Wellmann, Robin
    Vital, Marius
    Preuss, Siegfried
    Bennewitz, Joern
    [J]. GENETICS, 2017, 206 (03) : 1637 - 1644
  • [3] Campbell M, FRONT GENET, V12
  • [4] Genomic prediction when some animals are not genotyped
    Christensen, Ole F.
    Lund, Mogens S.
    [J]. GENETICS SELECTION EVOLUTION, 2010, 42
  • [5] Host genetics and the rumen microbiome jointly associate with methane emissions in dairy cows
    Difford, Gareth Frank
    Plichta, Damian Rafal
    Lovendahl, Peter
    Lassen, Jan
    Noel, Samantha Joan
    Hojberg, Ole
    Wright, Andre-Denis G.
    Zhu, Zhigang
    Kristensen, Lise
    Nielsen, Henrik Bjorn
    Guldbrandtsen, Bernt
    Sahana, Goutam
    [J]. PLOS GENETICS, 2018, 14 (10):
  • [6] Quantitative genetic models for describing simultaneous and recursive relationships between phenotypes
    Gianola, D
    Sorensen, D
    [J]. GENETICS, 2004, 167 (03) : 1407 - 1424
  • [7] Genetic Variance of Metabolomic Features and Their Relationship With Malting Quality Traits in Spring Barley
    Guo, Xiangyu
    Sarup, Pernille
    Jensen, Jens Due
    Orabi, Jihad
    Kristensen, Nanna Hellum
    Mulder, Frans A. A.
    Jahoor, Ahmed
    Jensen, Just
    [J]. FRONTIERS IN PLANT SCIENCE, 2020, 11
  • [8] Evaluation of the utility of gene expression and metabolic information for genomic prediction in maize
    Guo, Zhigang
    Magwire, Michael M.
    Basten, Christopher J.
    Xu, Zhanyou
    Wang, Daolong
    [J]. THEORETICAL AND APPLIED GENETICS, 2016, 129 (12) : 2413 - 2427
  • [9] Accelerating wheat breeding for end-use quality with multi-trait genomic predictions incorporating near infrared and nuclear magnetic resonance-derived phenotypes
    Hayes, B. J.
    Panozzo, J.
    Walker, C. K.
    Choy, A. L.
    Kant, S.
    Wong, D.
    Tibbits, J.
    Daetwyler, H. D.
    Rochfort, S.
    Hayden, M. J.
    Spangenberg, G. C.
    [J]. THEORETICAL AND APPLIED GENETICS, 2017, 130 (12) : 2505 - 2519
  • [10] SIMPLE METHOD FOR COMPUTING INVERSE OF A NUMERATOR RELATIONSHIP MATRIX USED IN PREDICTION OF BREEDING VALUES
    HENDERSON, CR
    [J]. BIOMETRICS, 1976, 32 (01) : 69 - 83