Computational and Experimental Tools to Monitor the Changes in Translation Efficiency of Plant mRNA on a Genome-Wide Scale: Advantages, Limitations, and Solutions

Abstract

The control of translation in the course of gene expression regulation plays a crucial role in plants’ cellular events and, particularly, in responses to environmental factors. The paradox of the great variance between levels of mRNAs and their protein products in eukaryotic cells, including plants, requires thorough investigation of the regulatory mechanisms of translation. A wide and amazingly complex network of mechanisms decoding the plant genome into proteome challenges researchers to design new methods for genome-wide analysis of translational control, develop computational algorithms detecting regulatory mRNA contexts, and to establish rules underlying differential translation. The aims of this review are to (i) describe the experimental approaches for investigation of differential translation in plants on a genome-wide scale; (ii) summarize the current data on computational algorithms for detection of specific structure–function features and key determinants in plant mRNAs and their correlation with translation efficiency; (iii) highlight the methods for experimental verification of existed and theoretically predicted features within plant mRNAs important for their differential translation; and finally (iv) to discuss the perspectives of discovering the specific structural features of plant mRNA that mediate differential translation control by the combination of computational and experimental approaches.

Transient Gene Expression is an Effective Experimental Tool for the Research into the Fine Mechanisms of Plant Gene Function: Advantages, Limitations, and Solutions

“…Several approaches have been designed and are used for delivering the gene constructs for transient expression: transfection of protoplasts using polyethylene glycol (PEG) or electroporation [ 20 ], biolistics [ 21 ], and agroinfiltration [ 7 ]. Numerous studies have convincingly demonstrated their efficacy for characterization of gene functions, including assessment of subcellular localization of protein products of the target genes, study of the signal transduction pathways, and protein–protein interaction [ 22 , 23 ], as well as for clarifying the functional properties of regulatory sequences in plants and so on [ 1 , 24 , 25 ]. Each system of transient gene expression in plants as well as the approaches to the delivery of gene constructs along with its specific advantages has its own limitations and bottlenecks depending on the goal of a particular research.…”

“…The first steps in the study of this problem were made owing to a deep insight into the mechanisms of transcription control as the first stage of gene expression and the easiest one for experiments in the methodical aspect. High-throughput technologies for transcriptome analysis, such as RNA-Seq and microarrays, have considerably clarified the key mechanisms underlying the regulation of gene transcription, expanded our knowledge about the transcriptional control of gene(s), and provided convincing experimental data demonstrating dynamic changes in transcriptomes of different plant species during their growth, development, and response to manifold environmental factors [ 1 , 2 ]. A large volume of data on gene expression obtained in comparative omic studies and, as a rule, meticulously processed with the help of available bioinformatics tools has made it possible to reveal the common transcriptome networks controlling a certain function and to predict the role of particular genes in cell processes [ 1 , 2 ].…”

“…High-throughput technologies for transcriptome analysis, such as RNA-Seq and microarrays, have considerably clarified the key mechanisms underlying the regulation of gene transcription, expanded our knowledge about the transcriptional control of gene(s), and provided convincing experimental data demonstrating dynamic changes in transcriptomes of different plant species during their growth, development, and response to manifold environmental factors [ 1 , 2 ]. A large volume of data on gene expression obtained in comparative omic studies and, as a rule, meticulously processed with the help of available bioinformatics tools has made it possible to reveal the common transcriptome networks controlling a certain function and to predict the role of particular genes in cell processes [ 1 , 2 ]. It should be emphasized that the approaches of in silico analysis mainly rely on the predictive functional classification of genes constructed based on the search for and comparative analysis of the known homologous genes, as a rule, orthologs [ 1 , 3 , 4 ].…”

“…A large volume of data on gene expression obtained in comparative omic studies and, as a rule, meticulously processed with the help of available bioinformatics tools has made it possible to reveal the common transcriptome networks controlling a certain function and to predict the role of particular genes in cell processes [ 1 , 2 ]. It should be emphasized that the approaches of in silico analysis mainly rely on the predictive functional classification of genes constructed based on the search for and comparative analysis of the known homologous genes, as a rule, orthologs [ 1 , 3 , 4 ]. However, all this is insufficient to clarify the function of a particular gene as well as the fine mechanism of its operation.…”

Translational gene regulation in plants: A green new deal

“…This review interrelates recent discoveries on translational gene regulation of cytosolic mRNAs in seed plants, building on previous excellent reviews on the same topic (Browning & Bailey-Serres, 2015;Goldenkova-Pavlova et al, 2018;Mazzoni-Putman & Stepanova, 2018;Merchante, Stepanova, & Alonso, 2017). We begin at the level of cellular "systems" physiology emphasizing, in order, metabolic control of global protein synthesis, genome-wide studies of translational control in response to environmental perturbations, and the role of ribonucleoprotein granules.…”