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

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

doi:10.1016/j.dib.2019.104402

Cited by 4 publications

(3 citation statements)

References 16 publications

(26 reference statements)

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“…The previous BnVIR database integrated 10,090,561 genetic variations and 21 phenotypes of 2,311 core B. napus accessions (Yang et al, 2022a). On this basis, we newly collected 216 published phenotype datasets from 13 studies (Bus et al, 2011; Sun et al, 2016b; Sun et al, 2016a; Chen et al, 2018; Kittipol et al, 2019; Wu et al, 2019; Song et al, 2020; Xuan et al, 2020; Liu et al, 2021c; Liu et al, 2021b; Wang et al, 2021; Zhang et al ., 2021; Zhang et al ., 2022a) (Supplementary Table S3). These datasets cover a variety of phenotypic traits, such as agronomic traits under abiotic stress conditions and seed quality traits, and have been integrated into the Phenotype and Variation portals.…”

Section: Resultsmentioning

confidence: 99%

“…Rapeseed is the second most important oilseed crop widely planted in the world. The traits including yield, seed oil content (SOC), oil quality, disease resistance and stress resistance largely determine its production and economic value (Friedt et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Due to its special origin and evolutionary history, rapeseed has a polyploid genome and therefore a more complex sequence composition and regulatory mechanism than diploid crops, which increases the difficulty in fine mapping of the candidate loci and genes (Chalhoub et al, 2014;Friedt et al, 2018). Recently, a large number of genetic loci and candidate genes associated with important traits have been efficiently identified using powerful multi-omics techniques and analysis tools (Lu et al, 2019;Tang et al, 2021;He et al, 2022;Hu et al, 2022;Zhang et al, 2022b).…”

Section: Introductionmentioning

confidence: 99%

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BnIR: a multi-omics database with various tools for Brassica napus research and breeding

Yang

Wang

et al. 2023

Preprint

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In the post-GWAS era, multi-omics techniques have shown great power and potential for candidate gene mining and functional genomics research. However, due to the lack of effective data integration and multi-omics analysis platforms, such techniques have not still been applied widely in rapeseed, an important oil crop worldwide. Here, we constructed a rapeseed multi-omics database (BnIR; http://yanglab.hzau.edu.cn/BnIR), which provides datasets of six omics including genomics, transcriptomics, variomics, epigenetics, phenomics and metabolomics, as well as numerous "variation-gene expression-phenotype" associations by using multiple statistical methods. In addition, a series of multi-omics search and analysis tools are integrated to facilitate the browsing and application of these datasets. BnIR is the most comprehensive multi-omics database for rapeseed so far, and two case studies demonstrated its power to mine candidate genes associated with specific traits and analyze their potential regulatory mechanisms.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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BnIR: a multi-omics database with various tools for Brassica napus research and breeding

Yang

Wang

et al. 2023

Preprint

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Fine mapping and candidate gene analysis of a seed glucosinolate content QTL, qGSL-C2, in rapeseed (Brassica napus L.)

et al. 2019

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Genetic architecture of glucosinolate variation in Brassica napus

Kittipol

Wang

et al. 2019

Journal of Plant Physiology

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The diverse biological activities of glucosinolate (GSL) hydrolysis products play significant biological and economical roles in the defense system and nutritional qualities of Brassica napus (oilseed rape). Yet, genomic-based study of the B. napus GSL regulatory mechanisms are scarce due to the complexity of working with polyploid species. To address these challenges, we used transcriptome-based GWAS approach, Associative Transcriptomics (AT), across a diversity panel of 288 B. napus genotypes to uncover the underlying genetic basis controlling quantitative variation of GSLs in B. napus vegetative tissues. Single nucleotide polymorphism (SNP) markers and gene expression markers (GEMs) associations identify orthologues of MYB28/HAG1 (AT5G61420), specifically the copies on chromosome A9 and C2, to be the key regulators of aliphatic GSL variation in leaves. We show that the positive correlation observed between aliphatic GSLs in seed and leaf is due to the amount synthesized, as controlled by Bna.HAG1.A9 and Bna.HAG1.C2, rather than by variation in the transport processes. In addition, AT and differential expression analysis in root tissues implicate an orthologue of MYB29/HAG3 (AT5G07690), Bna.HAG3.A3, as controlling root aromatic GSL variation. Based on the root expression data we also propose Bna.MAM3.A3 to have a role in controlling phenylalanine chain elongation for aromatic GSL biosynthesis. This work uncovers a regulator of homophenylalanine-derived aromatic GSLs and implicates the shared biosynthetic pathways between aliphatic and aromatic GSLs.

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

Cited by 4 publications

References 16 publications

BnIR: a multi-omics database with various tools for Brassica napus research and breeding

BnIR: a multi-omics database with various tools for Brassica napus research and breeding

Fine mapping and candidate gene analysis of a seed glucosinolate content QTL, qGSL-C2, in rapeseed (Brassica napus L.)

Genetic architecture of glucosinolate variation in Brassica napus

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