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.

Boolean modelling of biological networks is a well-established technique for abstracting dynamical biomolecular regulation in cells. Specifically, decoding linkages between salient regulatory network states and corresponding cell fate outcomes can help uncover pathological foundations of diseases such as cancer. Attractor landscape analysis is one such methodology which converts complex network behavior into a landscape of network states wherein each state is represented by propensity of its occurrence. Towards undertaking attractor landscape analysis of Boolean networks, we propose an Attractor Landscape Analysis Toolbox (ATLANTIS) for cell fate discovery, from biomolecular networks, and reprogramming upon network perturbation. ATLANTIS can be employed to perform both deterministic and probabilistic analyses. It has been validated by successfully reconstructing attractor landscapes from several published case studies followed by reprogramming of cell fates upon therapeutic treatment of network. Additionally, the biomolecular network of HCT-116 colorectal cancer cell line has been screened for therapeutic evaluation of drug-targets. Our results show agreement between therapeutic efficacies reported by ATLANTIS and the published literature. These case studies sufficiently highlight thein silicocell fate prediction and therapeutic screening potential of the toolbox. Lastly, ATLANTIS can also help guide single or combinatorial therapy responses towards reprogramming biomolecular networks to recover cell fates.