Transcriptome analysis of table grapes (Vitis vinifera L.) identified a gene network module associated with berry firmness

PLoS One. 2020 Aug 17;15(8):e0237526. doi: 10.1371/journal.pone.0237526. eCollection 2020.

Abstract

Berry firmness is one of the main selection criteria for table grape breeding. However, the underlying genetic determinants and mechanisms involved in gene expression during berry development are still poorly understood. In this study, eighteen libraries sampled from Vitis vinifera L. cv. 'Red Globe' and 'Muscat Hamburg' at three developmental stages (preveraison, veraison and maturation) were analyzed by RNA sequencing (RNA-Seq). The firmness of 'Red Globe' was significantly higher than that of 'Muscat Hamburg' at the three developmental stages. In total, a set of 4,559 differentially expressed genes (DEGs) was identified between 'Red Globe' and 'Muscat Hamburg' in the preveraison (2,259), veraison (2030) and maturation stages (2682), including 302 transcription factors (TFs). Weighted gene coexpression network analysis (WGCNA) showed that 23 TFs were predicted to be highly correlated with fruit firmness and propectin content. In addition, the differential expression of the PE, PL, PG, β-GAL, GATL, WAK, XTH and EXP genes might be the reason for the differences in firmness between 'Red Globe' and 'Muscat Hamburg'. The results will provide new information for analysis of grape berry firmness and softening.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Gene Expression Profiling / methods*
  • Gene Expression Regulation, Developmental
  • Gene Expression Regulation, Plant
  • Gene Regulatory Networks*
  • High-Throughput Nucleotide Sequencing
  • Plant Proteins / genetics
  • Quantitative Trait Loci
  • Sequence Analysis, RNA
  • Vitis / genetics
  • Vitis / growth & development*

Substances

  • Plant Proteins

Associated data

  • figshare/10.6084/m9.figshare.12424475

Grants and funding

This study was supported by the National Key Research and Development Program(Grant No. 2019YFD1001904 and 2018YFD1000200), National Natural Science Foundation of China (Grant No. 31972368), Agriculture Research System of China (Grant No. CARS-29-yc-6), Natural Science Founds of Liaoning Province (Grant No. 2019-MS-280), Shenyang Science and Technology Bureau Funds (Grant No. 19-302-3-10) and the Department of Science and Technology of Liaoning Province (Grant No. 2020JH5/10100023).