Data in support of genetic architecture of glucosinolate variations in Brassica napus

Varanya Kittipol; Zhesi He; Lihong Wang; Timothy Doheny-Adams; Swen Langer; Ian Bancroft

doi:10.1016/j.dib.2019.104402

Data in support of genetic architecture of glucosinolate variations in Brassica napus

Varanya Kittipol, Zhesi He, Lihong Wang, Timothy Doheny-Adams, Swen Langer, Ian Bancroft

Biology

Research output: Contribution to journal › Article › peer-review

Abstract

The transcriptome-based GWAS approach, Associative Transcriptomics (AT), which was employed to uncover the genetic basis controlling quantitative variation of glucosinolates in Brassica napus vegetative tissues is described. This article includes the phenotypic data of leaf and root glucosinolate (GSL) profiles across a diversity panel of 288 B. napus genotypes, as well as information on population structure and levels of GSLs grouped by crop types. Moreover, data on genetic associations of single nucleotide polymorphism (SNP) markers and gene expression markers (GEMs) for the major GSL types are presented in detail, while Manhattan plots and QQ plots for the associations of individual GSLs are also included. Root genetic association are supported by differential expression analysis generated from root RNA-seq. For further interpretation and details, please see the related research article entitled ‘Genetic architecture of glucosinolate variation in Brassica napus’ [1].

Original language	English
Article number	104402
Number of pages	7
Journal	Data in Brief
Volume	25
DOIs	https://doi.org/10.1016/j.dib.2019.104402
Publication status	Published - Aug 2019

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This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

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Cite this

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title = "Data in support of genetic architecture of glucosinolate variations in Brassica napus",

abstract = "The transcriptome-based GWAS approach, Associative Transcriptomics (AT), which was employed to uncover the genetic basis controlling quantitative variation of glucosinolates in Brassica napus vegetative tissues is described. This article includes the phenotypic data of leaf and root glucosinolate (GSL) profiles across a diversity panel of 288 B. napus genotypes, as well as information on population structure and levels of GSLs grouped by crop types. Moreover, data on genetic associations of single nucleotide polymorphism (SNP) markers and gene expression markers (GEMs) for the major GSL types are presented in detail, while Manhattan plots and QQ plots for the associations of individual GSLs are also included. Root genetic association are supported by differential expression analysis generated from root RNA-seq. For further interpretation and details, please see the related research article entitled {\textquoteleft}Genetic architecture of glucosinolate variation in Brassica napus{\textquoteright} [1].",

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AU - He, Zhesi

AU - Wang, Lihong

AU - Doheny-Adams, Timothy

AU - Langer, Swen

AU - Bancroft, Ian

N1 - This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

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AB - The transcriptome-based GWAS approach, Associative Transcriptomics (AT), which was employed to uncover the genetic basis controlling quantitative variation of glucosinolates in Brassica napus vegetative tissues is described. This article includes the phenotypic data of leaf and root glucosinolate (GSL) profiles across a diversity panel of 288 B. napus genotypes, as well as information on population structure and levels of GSLs grouped by crop types. Moreover, data on genetic associations of single nucleotide polymorphism (SNP) markers and gene expression markers (GEMs) for the major GSL types are presented in detail, while Manhattan plots and QQ plots for the associations of individual GSLs are also included. Root genetic association are supported by differential expression analysis generated from root RNA-seq. For further interpretation and details, please see the related research article entitled ‘Genetic architecture of glucosinolate variation in Brassica napus’ [1].

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