Summary of Study ST002168

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001379. The data can be accessed directly via it's Project DOI: 10.21228/M8G70N This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST002168
Study TitleMulti-omics analyses of 398 foxtail millet accessions reveal genomic regions associated with domestication, metabolite traits and anti-inflammatory effects
Study SummaryFoxtail millet, domesticated from the wild species green foxtail, provides a rich source of phytonutrients for humans. To evaluate how breeding changed the metabolome of foxtail millet grains, we generated and analyzed datasets encompassing genomes, transcriptomes, metabolomes and anti-inflammatory indices from 398 foxtail millet accessions. We identified hundreds of common variants that influence numerous secondary metabolites, with significant heterogeneity in the natural variation of metabolites and their underlying genetic architectures between different sub-groups of foxtail millet. The combined results from variations in genome, transcriptome and metabolome illustrated how breeding has altered foxtail millet metabolite content. Selection for alleles of genes associated with yellow grains led to altered metabolite profiles, such as carotenoids and endogenous hormones. The importance of PSY1 (phytoene synthase 1) for millet color was validated using CRISPR-Cas9. The in vitro cell inflammation assay showed that 83 metabolites have anti-inflammatory effects. This multi-omics study illustrates how the breeding history of foxtail millet has impacted metabolites. It provides some fundamental resources for understanding how grain quality could be associated with different metabolites, and highlights future perspectives on millet genetic research and metabolome-assisted improvement.
Institute
Shanxi Agricultural University
DepartmentCollege of Life Sciences
LaboratoryShanxi Key Laboratory of Minor Crop Germplasm Innovation and Molecular Breeding
Last NameLi
First NameXukai
AddressMingxiannan No.1, Jinzhong, Shanxi, 030801, China
Emailxukai_li@sxau.edu.cn
Phone+86 15340810703
Submit Date2022-05-09
Raw Data AvailableYes
Raw Data File Type(s)mzML
Analysis Type DetailLC-MS
Release Date2022-05-31
Release Version1
Xukai Li Xukai Li
https://dx.doi.org/10.21228/M8G70N
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR001379
Project DOI:doi: 10.21228/M8G70N
Project Title:Multi-omics analyses of 398 foxtail millet accessions reveal genomic regions associated with domestication, metabolite traits and anti-inflammatory effects
Project Type:metabolite traits
Project Summary:Foxtail millet, domesticated from the wild species green foxtail, provides a rich source of phytonutrients for humans. To evaluate how breeding changed the metabolome of foxtail millet grains, we generated and analyzed datasets encompassing genomes, transcriptomes, metabolomes and anti-inflammatory indices from 398 foxtail millet accessions. We identified hundreds of common variants that influence numerous secondary metabolites, with significant heterogeneity in the natural variation of metabolites and their underlying genetic architectures between different sub-groups of foxtail millet. The combined results from variations in genome, transcriptome and metabolome illustrated how breeding has altered foxtail millet metabolite content. Selection for alleles of genes associated with yellow grains led to altered metabolite profiles, such as carotenoids and endogenous hormones. The importance of PSY1 (phytoene synthase 1) for millet color was validated using CRISPR-Cas9. The in vitro cell inflammation assay showed that 83 metabolites have anti-inflammatory effects. This multi-omics study illustrates how the breeding history of foxtail millet has impacted metabolites. It provides some fundamental resources for understanding how grain quality could be associated with different metabolites, and highlights future perspectives on millet genetic research and metabolome-assisted improvement.
Institute:Shanxi Agricultural University
Department:College of Life Sciences
Laboratory:Shanxi Key Laboratory of Minor Crop Germplasm Innovation and Molecular Breeding
Last Name:Li
First Name:Xukai
Address:Mingxiannan No.1, Jinzhong, Shanxi, 030801, China
Email:xukai_li@sxau.edu.cn
Phone:+86 15340810703
Funding Source:the National Key R&D Program of China (2019YFD1000700 and 2019YFD1000702)

Subject:

Subject ID:SU002254
Subject Type:Plant
Subject Species:Foxtail millet (Setaria italica)
Taxonomy ID:4555

Factors:

Subject type: Plant; Subject species: Foxtail millet (Setaria italica) (Factor headings shown in green)

mb_sample_id local_sample_id Genotype Treatment
SA207638B313_1Wild-type Control
SA207639B312_3Wild-type Control
SA207640B312_2Wild-type Control
SA207641B313_2Wild-type Control
SA207642B313_3Wild-type Control
SA207643B314_2Wild-type Control
SA207644B314_1Wild-type Control
SA207645B312_1Wild-type Control
SA207646B311_3Wild-type Control
SA207647B310_1Wild-type Control
SA207648B309_3Wild-type Control
SA207649B310_2Wild-type Control
SA207650B310_3Wild-type Control
SA207651B311_2Wild-type Control
SA207652B311_1Wild-type Control
SA207653B314_3Wild-type Control
SA207654B317_2Wild-type Control
SA207655B324_3Wild-type Control
SA207656B324_2Wild-type Control
SA207657B324_1Wild-type Control
SA207658B325_1Wild-type Control
SA207659B325_2Wild-type Control
SA207660B326_1Wild-type Control
SA207661B325_3Wild-type Control
SA207662B323_3Wild-type Control
SA207663B323_2Wild-type Control
SA207664B317_3Wild-type Control
SA207665B309_2Wild-type Control
SA207666B321_1Wild-type Control
SA207667B321_2Wild-type Control
SA207668B323_1Wild-type Control
SA207669B321_3Wild-type Control
SA207670B317_1Wild-type Control
SA207671B308_3Wild-type Control
SA207672B299_3Wild-type Control
SA207673B299_2Wild-type Control
SA207674B299_1Wild-type Control
SA207675B301_1Wild-type Control
SA207676B301_2Wild-type Control
SA207677B302_1Wild-type Control
SA207678B301_3Wild-type Control
SA207679B298_3Wild-type Control
SA207680B298_2Wild-type Control
SA207681B295_3Wild-type Control
SA207682B295_2Wild-type Control
SA207683B297_1Wild-type Control
SA207684B297_2Wild-type Control
SA207685B298_1Wild-type Control
SA207686B297_3Wild-type Control
SA207687B302_2Wild-type Control
SA207688B302_3Wild-type Control
SA207689B306_2Wild-type Control
SA207690B306_1Wild-type Control
SA207691B305_3Wild-type Control
SA207692B306_3Wild-type Control
SA207693B308_1Wild-type Control
SA207694B326_2Wild-type Control
SA207695B308_2Wild-type Control
SA207696B305_2Wild-type Control
SA207697B305_1Wild-type Control
SA207698B303_2Wild-type Control
SA207699B303_1Wild-type Control
SA207700B303_3Wild-type Control
SA207701B304_1Wild-type Control
SA207702B304_3Wild-type Control
SA207703B304_2Wild-type Control
SA207704B309_1Wild-type Control
SA207705B328_1Wild-type Control
SA207706B347_3Wild-type Control
SA207707B347_2Wild-type Control
SA207708B347_1Wild-type Control
SA207709B348_1Wild-type Control
SA207710B348_2Wild-type Control
SA207711B349_1Wild-type Control
SA207712B348_3Wild-type Control
SA207713B346_3Wild-type Control
SA207714B346_2Wild-type Control
SA207715B342_3Wild-type Control
SA207716B342_2Wild-type Control
SA207717B343_1Wild-type Control
SA207718B343_2Wild-type Control
SA207719B346_1Wild-type Control
SA207720B343_3Wild-type Control
SA207721B349_2Wild-type Control
SA207722B349_3Wild-type Control
SA207723B354_2Wild-type Control
SA207724B354_1Wild-type Control
SA207725B352_3Wild-type Control
SA207726B354_3Wild-type Control
SA207727B355_1Wild-type Control
SA207728B355_3Wild-type Control
SA207729B355_2Wild-type Control
SA207730B352_2Wild-type Control
SA207731B352_1Wild-type Control
SA207732B350_2Wild-type Control
SA207733B350_1Wild-type Control
SA207734B350_3Wild-type Control
SA207735B351_1Wild-type Control
SA207736B351_3Wild-type Control
SA207737B351_2Wild-type Control
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Collection:

Collection ID:CO002247
Collection Summary:Plant growth conditions. The 398 accessions were grown at Shanxi Agricultural University experiment station (Shanxi, China, 37° 25′ N, 112° 34′ E). The experimental design and replicates were the same as described above, except those two different plants per accession were collected for metabolite extraction.
Sample Type:Seeds
Collection Location:Shanxi Agricultural University experiment station (Shanxi, China, 37° 25′ N, 112° 34′ E)
Storage Conditions:Room temperature

Treatment:

Treatment ID:TR002266
Treatment Summary:None.
Plant Growth Location:Shanxi Agricultural University experiment station (Shanxi, China, 37° 25′ N, 112° 34′ E).

Sample Preparation:

Sampleprep ID:SP002260
Sampleprep Summary:Sample preparation and extraction. We carried out metabolic profiling using mature grains. For each sample, 5 g well-grown grains were randomly harvested from at least three individual plants. The de-hulled grains were ground using a mixer mill (MM 400, Retsch) with zirconia beads for 2 min at 30 Hz. After grinding, the powder was partitioned into two sample sets and stored at -80 °C until use. For each set, 100 mg powder was extracted overnight at 4 °C with 1.0 mL absolute methanol (for lipid-soluble metabolites) or 70% methanol (for water-soluble metabolites) containing 0.1 mg/L lidocaine. The extract was centrifuged at 10,000 g for 10 min, and the supernatant was purified by CNWBOND Carbon-GCB SPE Cartridge (250 mg, 3 mL; ANPEL, Shanghai, China) and filtered (SCAA-104, 0.22 μm pore size; ANPEL, Shanghai, China) before injection for UPLC-MS/MS analysis (Chen et al., 2013).
Processing Storage Conditions:Described in summary
Extract Storage:-80℃

Combined analysis:

Analysis ID AN003552
Analysis type MS
Chromatography type Reversed phase
Chromatography system Thermo Dionex Ultimate 3000
Column VP-ODS, 5 μm particle size, 2 mm, 150 mm
MS Type ESI
MS instrument type QTRAP
MS instrument name Thermo Scientific TSQ Altis Triple Quadrupole Mass Spectrometer
Ion Mode UNSPECIFIED
Units peak area

Chromatography:

Chromatography ID:CH002624
Chromatography Summary:The UPLC conditions were C18 reverse-phase column (VP-ODS, 5 μm particle size, 2 mm, 150 mm); two solvents system, solvent A-water (0.04% acetic acid), solvent B-acetonitrile (0.04% acetic acid); solvent gradients (A/B, v/v), 98:2 at 0 min, 98:2 at 1.0 min, 80:20 at 4.0 min, 2:98 at 12.0 min, 2:98 at 15.0 min, 98:2 at 15.1 min, 98:2 at 18.0 min; flow rate, 0.25 ml/min; temperature, 40 °C; injection volume: 10 μL. The effluent was alternatively connected to a triple quadrupole mass spectrometer.
Instrument Name:Thermo Dionex Ultimate 3000
Column Name:VP-ODS, 5 μm particle size, 2 mm, 150 mm
Injection Temperature:40
Sample Injection:10 μL
Solvent A:water (0.04% acetic acid)
Solvent B:acetonitrile (0.04% acetic acid)
Chromatography Type:Reversed phase

MS:

MS ID:MS003309
Analysis ID:AN003552
Instrument Name:Thermo Scientific TSQ Altis Triple Quadrupole Mass Spectrometer
Instrument Type:QTRAP
MS Type:ESI
MS Comments:The effluent was alternatively connected to a triple quadrupole mass spectrometer. Metabolite (m-trait) raw data were assessed and corrected for peak area by QC sample runs and internal standard (lidocaine, 0.1 mg/L) (Matsuda et al., 2015) using MetaboDrift (v1.1) (Thonusin et al., 2017), and then log2-transformed for statistical analysis to improve normality and normalized (Chen et al., 2013).
Ion Mode:UNSPECIFIED
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