Dataset Information

Proteomic analysis of the taproot growth and development stage in Beta vulgaris

ABSTRACT: In order to understand the changes of proteins during the taproot growth and development of sugar beet, .the two cultivar (SD and BS) at two time points of taproot growth rate were performed proteomic sequencing using iTRAQ.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Beta Vulgaris (sugar Beet)

TISSUE(S): Root

SUBMITTER: Ningning Li

LAB HEAD: Ningning Li

PROVIDER: PXD031889 | Pride | 2022-08-12

REPOSITORIES: Pride

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Publications

Integration of Transcriptomic and Proteomic Profiles Reveals Multiple Levels of Genetic Regulation of Taproot Growth in Sugar Beet (<i>Beta vulgaris</i> L.).

Li Ningning N Zhang Yongfeng Y Wang Xuefeng X Ma Huailong H Sun Yaqing Y Li Guolong G Zhang Shaoying S

Frontiers in plant science 20220713

Sugar beet taproot growth and development is a complex biological process involving morphogenesis and dry matter accumulation. However, the molecular regulatory mechanisms underlying taproot growth and development remain elusive. We performed a correlation analysis of the proteome and transcriptome in two cultivars (SD13829 and BS02) at the start and the highest points of the taproot growth rate. The corresponding correlation coefficients were 0.6189, 0.7714, 0.6803, and 0.7056 in four compariso ...[more]

PMID: 35909753

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Project description:Background: Grape cultivars and wines are distinguishable by their color, flavor and aroma profiles. Omic analyses (transcripts, proteins and metabolites) are powerful tools for assessing biochemical differences in biological systems. Results: Berry skins of red- (Cabernet Sauvignon, Merlot, Pinot Noir) and white-skinned (Chardonnay, Semillon) wine grapes were harvested near optimum maturity from the same experimental vineyard and Ë?Brix-to-titratable acidity ratio. Identical sample aliquots were analyzed for transcripts by grapevine whole-genome oligonucleotide microarray and RNA-seq technologies, proteins by nano-liquid chromatography-mass spectroscopy, and metabolites by gas chromatography-mass spectroscopy and liquid chromatography-mass spectroscopy. Principal components analysis of each of five Omic technologies showed similar results across cultivars in all Omic datasets. Comparison of the processed data of genes mapped in RNA-seq and microarray data revealed a strong Pearson's correlation (0.80). The exclusion of probesets associated with genes with potential for cross-hybridization on the microarray improved the correlation to 0.93. The overall concordance of protein with transcript data was low with a Pearson's correlation of 0.27 and 0.24 for the RNA-seq and microarray data, respectively. Integration of metabolite with protein and transcript data produced an expected model of phenylpropanoid biosynthesis, which distinguished red from white grapes, yet provided detail of individual cultivar differences. Conclusions: The five Omic technologies were consistent in distinguishing cultivar variation. There was high concordance between transcriptomic technologies, but generally protein abundance did not correlate well with transcript abundance. The integration of multiple high-throughput Omic datasets revealed complex biochemical variation amongst five cultivars of an ancient and economically important crop species. Vitis vinifera L. cv. Cabernet Sauvignon, Chardonnay, Merlot, Pinot Noir, Semillon berries were harvested from Nevada Agricultural Experiment Station Valley Road Vineyard, Reno, NV, USA. Whole-genome microarray analysis was used to assess the transcriptomic response of berry skins at harvest, approximately 24 Â°Brix (2011 vintage). Vines were grown under water deficit and well-watered conditions. At least two clusters harvested from non-adjacent vines were used for each of five experimental replicates.

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