Transcriptome‐wide association and prediction for carotenoids and tocochromanols in fresh sweet corn kernels. Issue 2 (8th March 2022)

• Record Type: Journal Article
• Authors: Hershberger, Jenna; Tanaka, Ryokei; Wood, Joshua C.; Kaczmar, Nicholas; Wu, Di; Hamilton, John P.; DellaPenna, Dean; Buell, C. Robin; Gore, Michael A.
• Is Part Of: œplant genome. Volume 15:Issue 2(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-03-08
• Subjects: Plant genomes -- Periodicals; Plant genome mapping -- Periodicals; 572.862
• DOI: 10.1002/tpg2.20197
• Languages: English
• ISSNs: 1940-3372

Abstract

Abstract: Sweet corn ( Zea mays L.) is consistently one of the most highly consumed vegetables in the United States, 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, β‐carotene hydroxylase ( crtRB1 ), lycopene epsilon cyclase ( lcyE ), γ‐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 toward understanding the role of regulatory variation in the accumulation of vitamins in fresh sweet corn kernels. Core Ideas: Transcriptomic data aid the study of vitamin levels in fresh sweet corn kernels. crtRB1, lcyE, dxs2, dmes2, and cmk1 were associated with carotenoid traits. vte4, hggt1, and ggh1 were associated with tocochromanol traits. Transcriptomic data boosted predictive ability over genomic data alone for some traits. Joint transcriptome‐ and genome‐wide models achieved the highest predictive abilities.