2020
DOI: 10.1101/2020.06.11.145623
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Prediction of complex phenotypes using theDrosophilametabolome

Abstract: Understanding the genotype -phenotype map and how variation at different levels of biological organization are associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at DNA level and on intermediate endophenotypes, such as RNA, proteins, metabolites. This facilitates our understanding of the link between genotypes and molecular and functional organismal phenotypes. Here, we use t… Show more

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Cited by 4 publications
(5 citation statements)
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“…The performance of GBLUP and MBLUP was investigated in Drosophila, where the prediction accuracy for two behavioral traits was below 0.1 when based on GBLUP and then increased to above 0.4 when using MBLUP. Such an increase have also been found for two environmental stress resistance traits in Drosophila 23 . In the plant field, metabolic information was introduced into prediction of complex traits by Riedelsheimer, et al 33 , where the authors presented a complementary approach to exploit large-scale genomic and metabolic information in hybrid testcrosses.…”
Section: Estimates Of Total Variance Of Malting Quality Traits Explained By Metabolomic Featuressupporting
confidence: 59%
See 1 more Smart Citation
“…The performance of GBLUP and MBLUP was investigated in Drosophila, where the prediction accuracy for two behavioral traits was below 0.1 when based on GBLUP and then increased to above 0.4 when using MBLUP. Such an increase have also been found for two environmental stress resistance traits in Drosophila 23 . In the plant field, metabolic information was introduced into prediction of complex traits by Riedelsheimer, et al 33 , where the authors presented a complementary approach to exploit large-scale genomic and metabolic information in hybrid testcrosses.…”
Section: Estimates Of Total Variance Of Malting Quality Traits Explained By Metabolomic Featuressupporting
confidence: 59%
“…With this information, it is worthwhile to investigate the role of MFs involved in the prediction of phenotypes for MQ traits. PLSR is a popular method used in the studies of metabolic profiles 22 , and using metabolomic BLUP (MBLUP) model gave better prediction accuracies than the BLUP model using genomic information for four of five quantitative traits investigated 23 .…”
Section: Introductionmentioning
confidence: 99%
“…Omics technologies provide an easy and effective way to measure thousands of endophenotypes in large mapping populations. Many research groups are using these approaches to improve prediction for complex traits (Guo et al, 2016 ; Westhues et al, 2017 ; Rincent et al, 2018 ; Schrag et al, 2018 ; Li et al, 2019 ; Xiang et al, 2019 ; Rohde et al, 2020 ; Zhou et al, 2020 ). While several studies have reported improvements in prediction accuracies when these data were used to create relationship matrices, the results are often mixed and inconsistent (Guo et al, 2016 ; Schrag et al, 2018 ; Zhou et al, 2020 ).…”
Section: Discussionmentioning
confidence: 99%
“…Using these frameworks, Morgante et al (2020) showed that BLUP models that included relationship matrices derived from transciptome data, as well as transcriptome and genome-wide marker data improved prediction accuracies compared to models that used only genome-wide markers. Several other studies have reported similar improvements in prediction accuracies when omics-based kernels are used for prediction, suggesting that these omics-based kernels capture some component of the phenotype that is not explained by genome-wide markers (environmental or non-additive genetic variance) (Westhues et al, 2017;Rincent et al, 2018;Schrag et al, 2018;Krause et al, 2019;Li et al, 2019;Rohde et al, 2020;Zhou et al, 2020). Despite these promising studies, these improv2gfgements seem to be dependent on the trait, methodologies and datatype (Guo et al, 2016;Schrag et al, 2018;Zhou et al, 2020).…”
Section: Introductionmentioning
confidence: 89%
“…While models including expression data could capture a greater amount of variance, their predictive ability was generally similar to GBLUP (Li et al 2019). Even more recently, two studies in Drosophila showed that using metabolites to predict a few complex traits can provide higher accuracy than genotypes (Zhou et al 2020;Rohde et al 2020).…”
Section: Introductionmentioning
confidence: 96%