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Dataset . 2023
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Dataset . 2025
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Strawberry volatile organic compounds metabolomic data and QTL study

Authors: Thérèse Navarro, Alejandro; Zafra Delgado, Olga; Tikunov, Yury; Peeters, Carel; Willemsen, Johan; van Dijk, Thijs; Bourke, Peter M.; +3 Authors

Strawberry volatile organic compounds metabolomic data and QTL study

Abstract

This dataset contains the supplementary materials of the publication "Multivariate QTL approach reveals a major regulator of terpenoid production and other volatiles in strawberry" of the same authors. In this study we extracted volatile organic compounds from several strawberry samples and analysed their identity and abundance. We used this volatile data to perform an extensive multivariate QTL study, the results of which can be found in this dataset. All analysis, results and figures can be reproduced using the folder included in the supplementary data 1. If you want to reproduce part or all of our analysis, only download sup data 1. If you only need one of our results or data table you can download them individually: Sup data 2: abundances of volatile organic compounds from a biparental and diverse panel (GWAS) population. Sup data 3 and 4: p-value tables for several models and all metabolites as well as multivariate traits (see publication for more information). Sup tables 1 and 2: significant QTL signals for each trait individually and summarised per QTL locus. Sup table 3: previously reported VOC QTLs in strawberry, with positions imputed in the Royal Royce genome. Sup table 4: metadata about all the identified compounds on this and previous studies. Sup table 5: SNP array positions imputed in the "Royal Royce" genome assembly.

Country
Netherlands
Keywords

QTL analysis, volatile organic compounds, Volatile organic compounds, strawberry, metabolomics

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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