Genome-Wide Identification and Expression Profiling of the Polygalacturonase (PG) and Pectin Methylesterase (PME) Genes in Grapevine (Vitis vinifera L.)

Abstract

In pectin regulation, polygalacturonases (PGs) and pectin methylesterases (PMEs) are critical components in the transformation, disassembly network, and remodeling of plant primary cell walls. In the current study, we identified 36 PG and 47 PME genes using the available genomic resources of grapevine. Herein, we provide a comprehensive overview of PGs and PMEs, including phylogenetic and collinearity relationships, motif and gene structure compositions, gene duplications, principal component analysis, and expression profiling during developmental stages. Phylogenetic analysis of PGs and PMEs revealed similar domain composition patterns with Arabidopsis. The collinearity analysis showed high conservation and gene duplications with purifying selection. The type of duplications also varied in terms of gene numbers in PGs (10 dispersed, 1 proximal, 12 tandem, and 13 segmental, respectively) and PMEs (23 dispersed, 1 proximal, 16 tandem, and 7 segmental, respectively). The tissue-specific response of PG and PME genes based on the reported transcriptomic data exhibited diverged expression patterns in various organs during different developmental stages. Among PGs, VvPG8, VvPG10, VvPG13, VvPG17, VvPG18, VvPG19, VvPG20, VvPG22, and VvPG23 showed tissue- or organ-specific expression in majority of the tissues during development. Similarly, in PMEs, VvPME3, VvPME4, VvPME5, VvPME6, VvPME19, VvPME21, VvPME23, VvPME29, VvPME31, and VvPME32 suggested high tissue-specific response. The gene ontology (GO), Kyoto Encyclopedia of Genes and Genomics (KEGG) enrichment, and cis-elements prediction analysis also suggested the putative functions of PGs and PMEs in plant development, such as pectin and carbohydrate metabolism, and stress activities. Moreover, qRT-PCR validation of 32 PG and PME genes revealed their role in various organs of grapevines (i.e., root, stem, tendril, inflorescence, flesh, skins, and leaves). Therefore, these findings will lead to novel insights and encourage cutting-edge research on functional characterization of PGs and PMEs in fruit crop species.

Comprehensive Sequence Analysis of IQD Gene Family and their Expression Profiling in Grapevine (Vitis vinifera)

“…Specific forward and reverse primers of all the identified (49) VvIQD genes were designed using Beacan Designer 7.9 ( Table S1). The RT-PCR analysis of all VvIQD genes using the cDNA was performed following the guidelines as described in previous studies [28], and actin genes were used as a reference for qRT-PCR [29]. CT-values were used to calculate the relative fold-change.…”

Construction of a High-Density Genetic Map and Mapping of Firmness in Grapes (Vitis vinifera L.) Based on Whole-Genome Resequencing

“…Grape berries are widely used as table grapes and to produce wine, raisins, and juice [1]. Grapes have a high nutritional value and provide health benefits [2]. Berry firmness is one of the main factors affecting consumers' acceptance [3][4][5].…”

Genome-wide Identification of ATP Binding Cassette (ABC) Transporter and Heavy Metal Associated (HMA) Gene Families in Flax (Linum usitatissimum L.)

“…Synonymous (Ks) and non-synonymous substitution (Ka) rates were also calculated for duplicated gene pairs as previously described [47]. Also, a substitution rate of 1.5 × 10 −8 substitutions per synonymous site per year [62] was used to estimate divergence time of duplicated genes.…”

“…In flax, a total of four different types of gene duplications were observed from 210 ABC transporter and HMA genes, having 162 WGD or segmental, 29 dispersed, 14 tandem, 4 proximal duplicated genes. Segmental duplications (77.14%) contributed the most to the expansion of the two gene families in flax, a common mode of expansion for many gene families across various plant species[47][48][49]. The selection pressure analysis of duplicated gene pairs based on three categories (i.e., purifying, positive, and neutral selection) tends to provide valuable information regarding protein-coding genes[50].…”