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Transcriptome-wide association and prediction for carotenoids and tocochromanols in fresh sweet corn kernels

dataset
posted on 2024-09-29, 06:42 authored by University of Georgia
Sweet corn is consistently one of the most highly consumed vegetables in the U.S., providing a valuable opportunity to increase nutrient intake through biofortification. Significant variation for carotenoid (provitamin A, lutein, zeaxanthin) and tocochromanol (vitamin E, antioxidants) levels is present in temperate sweet corn germplasm, yet previous genome-wide association studies (GWAS) of these traits have been limited by low statistical power and mapping resolution. Here, we employed a high-quality transcriptomic dataset collected from fresh sweet corn kernels to conduct transcriptome-wide association studies (TWAS) and transcriptome prediction studies for 39 carotenoid and tocochromanol traits. In agreement with previous GWAS findings, TWAS detected significant associations for four causal genes, beta-carotene hydroxylase (crtRB1), lycopene epsilon cyclase (lcyE), gamma-tocopherol methyltransferase (vte4), and homogentisate geranylgeranyltransferase (hggt1) on a transcriptome-wide level. Pathway-level analysis revealed additional associations for deoxy-xylulose synthase2 (dxs2), diphosphocytidyl methyl erythritol synthase2 (dmes2), cytidine methyl kinase1 (cmk1), and geranylgeranyl hydrogenase1 (ggh1), of which, dmes2, cmk1, and ggh1 have not previously been identified through maize association studies. Evaluation of prediction models incorporating genome-wide markers and transcriptome-wide abundances revealed a trait-dependent benefit to the inclusion of both genomic and transcriptomic data over solely genomic data, but both transcriptome- and genome-wide datasets outperformed a priori candidate gene-targeted prediction models for most traits. Altogether, this study represents an important step towards understanding the role of regulatory variation in the accumulation of vitamins in fresh sweet corn kernels.

Funding

Cornell University: Startup funds

USDA NIFA: AFRI EWD Predoctoral Fellowship 2019‐67011‐29606

USDA NIFA: Hatch 100397, 1010428, 1013637, 1013641, and 1023660

NSF: IOS-1546657

History

Data contact name

BioProject Curation Staff

Publisher

National Center for Biotechnology Information

Temporal Extent Start Date

2021-11-22

Theme

  • Non-geospatial

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

sequence analysis

Pending citation

  • No

Public Access Level

  • Public

Accession Number

PRJNA782659

Preferred dataset citation

It is recommended to cite the accession numbers that are assigned to data submissions, e.g. the GenBank, WGS or SRA accession numbers. If individual BioProjects need to be referenced, state that "The data have been deposited with links to BioProject accession number PRJNA782659 in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/)."

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