FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386458847> ?p ?o ?g. }

• W4386458847 abstract "Abstract Background Metabolomics measures an intermediate stage between genotype and phenotype, and may therefore be useful for breeding. Our objectives were to investigate genetic parameters and accuracies of predicted breeding values for malting quality (MQ) traits when integrating both genomic and metabolomic information. In total, 2430 plots of 562 malting spring barley lines from three years and two locations were included. Five MQ traits were measured in wort produced from each plot. Metabolomic features used were 24,018 nuclear magnetic resonance intensities measured on each wort sample. Methods for statistical analyses were genomic best linear unbiased prediction (GBLUP) and metabolomic-genomic best linear unbiased prediction (MGBLUP). Accuracies of predicted breeding values were compared using two cross-validation strategies: leave-one-year-out (LOYO) and leave-one-line-out (LOLO), and the increase in accuracy from the successive inclusion of first, metabolomic data on the lines in the validation population (VP), and second, both metabolomic data and phenotypes on the lines in the VP, was investigated using the linear regression (LR) method. Results For all traits, we saw that the metabolome-mediated heritability was substantial. Cross-validation results showed that, in general, prediction accuracies from MGBLUP and GBLUP were similar when phenotypes and metabolomic data were recorded on the same plots. Results from the LR method showed that for all traits, except one, accuracy of MGBLUP increased when including metabolomic data on the lines of the VP, and further increased when including also phenotypes. However, in general the increase in accuracy of MGBLUP when including both metabolomic data and phenotypes on lines of the VP was similar to the increase in accuracy of GBLUP when including phenotypes on the lines of the VP. Therefore, we found that, when metabolomic data were included on the lines of the VP, accuracies substantially increased for lines without phenotypic records, but they did not increase much when phenotypes were already known. Conclusions MGBLUP is a useful approach to combine phenotypic, genomic and metabolomic data for predicting breeding values for MQ traits. We believe that our results have significant implications for practical breeding of barley and potentially many other species." @default.
• W4386458847 created "2023-09-06" @default.
• W4386458847 creator A5003215392 @default.
• W4386458847 creator A5004797651 @default.
• W4386458847 creator A5017121787 @default.
• W4386458847 creator A5048229723 @default.
• W4386458847 creator A5062604888 @default.
• W4386458847 date "2023-09-05" @default.
• W4386458847 modified "2023-09-29" @default.
• W4386458847 title "Metabolomic-genomic prediction can improve prediction accuracy of breeding values for malting quality traits in barley" @default.
• W4386458847 cites W1593444788 @default.
• W4386458847 cites W1964338739 @default.
• W4386458847 cites W2023673366 @default.
• W4386458847 cites W2033670977 @default.
• W4386458847 cites W2040567872 @default.
• W4386458847 cites W2043695363 @default.
• W4386458847 cites W2049835150 @default.
• W4386458847 cites W2057828153 @default.
• W4386458847 cites W2058491411 @default.
• W4386458847 cites W2067715889 @default.
• W4386458847 cites W2130916293 @default.
• W4386458847 cites W2502184016 @default.
• W4386458847 cites W2564688219 @default.
• W4386458847 cites W2747969585 @default.
• W4386458847 cites W2753094459 @default.
• W4386458847 cites W2760544538 @default.
• W4386458847 cites W2899673678 @default.
• W4386458847 cites W3093098202 @default.
• W4386458847 cites W3093826010 @default.
• W4386458847 cites W3097022897 @default.
• W4386458847 cites W3198274722 @default.
• W4386458847 cites W4220986178 @default.
• W4386458847 cites W4280546327 @default.
• W4386458847 cites W4384699898 @default.
• W4386458847 doi "https://doi.org/10.1186/s12711-023-00835-w" @default.
• W4386458847 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37670243" @default.
• W4386458847 hasPublicationYear "2023" @default.
• W4386458847 type Work @default.
• W4386458847 citedByCount "0" @default.
• W4386458847 crossrefType "journal-article" @default.
• W4386458847 hasAuthorship W4386458847A5003215392 @default.
• W4386458847 hasAuthorship W4386458847A5004797651 @default.
• W4386458847 hasAuthorship W4386458847A5017121787 @default.
• W4386458847 hasAuthorship W4386458847A5048229723 @default.
• W4386458847 hasAuthorship W4386458847A5062604888 @default.
• W4386458847 hasBestOaLocation W43864588471 @default.
• W4386458847 hasConcept C103545067 @default.
• W4386458847 hasConcept C104317684 @default.
• W4386458847 hasConcept C104959735 @default.
• W4386458847 hasConcept C105795698 @default.
• W4386458847 hasConcept C135763542 @default.
• W4386458847 hasConcept C135870905 @default.
• W4386458847 hasConcept C150903083 @default.
• W4386458847 hasConcept C153209595 @default.
• W4386458847 hasConcept C154945302 @default.
• W4386458847 hasConcept C161890455 @default.
• W4386458847 hasConcept C197321923 @default.
• W4386458847 hasConcept C21565614 @default.
• W4386458847 hasConcept C2908647359 @default.
• W4386458847 hasConcept C2992444039 @default.
• W4386458847 hasConcept C33923547 @default.
• W4386458847 hasConcept C41008148 @default.
• W4386458847 hasConcept C48921125 @default.
• W4386458847 hasConcept C54355233 @default.
• W4386458847 hasConcept C60644358 @default.
• W4386458847 hasConcept C6557445 @default.
• W4386458847 hasConcept C70721500 @default.
• W4386458847 hasConcept C71924100 @default.
• W4386458847 hasConcept C81917197 @default.
• W4386458847 hasConcept C86803240 @default.
• W4386458847 hasConcept C99454951 @default.
• W4386458847 hasConceptScore W4386458847C103545067 @default.
• W4386458847 hasConceptScore W4386458847C104317684 @default.
• W4386458847 hasConceptScore W4386458847C104959735 @default.
• W4386458847 hasConceptScore W4386458847C105795698 @default.
• W4386458847 hasConceptScore W4386458847C135763542 @default.
• W4386458847 hasConceptScore W4386458847C135870905 @default.
• W4386458847 hasConceptScore W4386458847C150903083 @default.
• W4386458847 hasConceptScore W4386458847C153209595 @default.
• W4386458847 hasConceptScore W4386458847C154945302 @default.
• W4386458847 hasConceptScore W4386458847C161890455 @default.
• W4386458847 hasConceptScore W4386458847C197321923 @default.
• W4386458847 hasConceptScore W4386458847C21565614 @default.
• W4386458847 hasConceptScore W4386458847C2908647359 @default.
• W4386458847 hasConceptScore W4386458847C2992444039 @default.
• W4386458847 hasConceptScore W4386458847C33923547 @default.
• W4386458847 hasConceptScore W4386458847C41008148 @default.
• W4386458847 hasConceptScore W4386458847C48921125 @default.
• W4386458847 hasConceptScore W4386458847C54355233 @default.
• W4386458847 hasConceptScore W4386458847C60644358 @default.
• W4386458847 hasConceptScore W4386458847C6557445 @default.
• W4386458847 hasConceptScore W4386458847C70721500 @default.
• W4386458847 hasConceptScore W4386458847C71924100 @default.
• W4386458847 hasConceptScore W4386458847C81917197 @default.
• W4386458847 hasConceptScore W4386458847C86803240 @default.
• W4386458847 hasConceptScore W4386458847C99454951 @default.
• W4386458847 hasFunder F4320331737 @default.
• W4386458847 hasIssue "1" @default.
• W4386458847 hasLocation W43864588471 @default.
• W4386458847 hasLocation W43864588472 @default.

• next