Changes in Polysome Association of mRNA Throughout Growth and Development in Arabidopsis thaliana

Feature selection for RNA cleavage efficiency at specific sites using the LASSO regression model in Arabidopsis thaliana

BACKGROUND

RNA degradation is important for the regulation of gene expression. Despite the identification of proteins and sequences related to deadenylation-dependent RNA degradation in plants, endonucleolytic cleavage-dependent RNA degradation has not been studied in detail. Here, we developed truncated RNA end sequencing in Arabidopsis thaliana to identify cleavage sites and evaluate the efficiency of cleavage at each site. Although several features are related to RNA cleavage efficiency, the effect of each feature on cleavage efficiency has not been evaluated by considering multiple putative determinants in A. thaliana.

RESULTS

Cleavage site information was acquired from a previous study, and cleavage efficiency at the site level (CS_site value), which indicates the number of reads at each cleavage site normalized to RNA abundance, was calculated. To identify features related to cleavage efficiency at the site level, multiple putative determinants (features) were used to perform feature selection using the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. The results indicated that whole RNA features were important for the CS_site value, in addition to features around cleavage sites. Whole RNA features related to the translation process and nucleotide frequency around cleavage sites were major determinants of cleavage efficiency. The results were verified in a model constructed using only sequence features, which showed that the prediction accuracy was similar to that determined using all features including the translation process, suggesting that cleavage efficiency can be predicted using only sequence information. The LASSO regression model was validated in exogenous genes, which showed that the model constructed using only sequence information can predict cleavage efficiency in both endogenous and exogenous genes.

CONCLUSIONS

Feature selection using the LASSO regression model in A. thaliana identified 155 features. Correlation coefficients revealed that whole RNA features are important for determining cleavage efficiency in addition to features around the cleavage sites. The LASSO regression model can predict cleavage efficiency in endogenous and exogenous genes using only sequence information. The model revealed the significance of the effect of multiple determinants on cleavage efficiency, suggesting that sequence features are important for RNA degradation mechanisms in A. thaliana.

Improved computational analysis of ribosome dynamics from 5'P degradome data using fivepseq

In eukaryotes, 5′–3′ co-translation degradation machinery follows the last translating ribosome providing an in vivo footprint of its position. Thus, 5′ monophosphorylated (5′P) degradome sequencing, in addition to informing about RNA decay, also provides information regarding ribosome dynamics. Multiple experimental methods have been developed to investigate the mRNA degradome; however, computational tools for their reproducible analysis are lacking. Here, we present fivepseq: an easy-to-use application for analysis and interactive visualization of 5′P degradome data. This tool performs both metagene- and gene-specific analysis, and enables easy investigation of codon-specific ribosome pauses. To demonstrate its ability to provide new biological information, we investigate gene-specific ribosome pauses in Saccharomyces cerevisiae after eIF5A depletion. In addition to identifying pauses at expected codon motifs, we identify multiple genes with strain-specific degradation frameshifts. To show its wide applicability, we investigate 5′P degradome from Arabidopsis thaliana and discover both motif-specific ribosome protection associated with particular developmental stages and generally increased ribosome protection at termination level associated with age. Our work shows how the use of improved analysis tools for the study of 5′P degradome can significantly increase the biological information that can be derived from such datasets and facilitate its reproducible analysis.

Ribosomal Protein RPL10A Contributes to Early Plant Development and Abscisic Acid-Dependent Responses in Arabidopsis

Plant ribosomal proteins play universal roles in translation, although they are also involved in developmental processes and hormone signaling pathways. Among Arabidopsis RPL10 family members, RPL10A exhibits the highest expression during germination and early development, suggesting that RPL10A is the main contributor to these processes. In this work, we first analyzed RPL10A expression pattern in Arabidopsis thaliana using transgenic RPL10A_pro:GUS plants. The gene exhibits a ubiquitous expression pattern throughout the plant, but it is most strongly expressed in undifferentiated tissues. Interestingly, gene expression was also detected in stomatal cells. We then examined protein function during seedling establishment and abscisic acid (ABA) response. Heterozygous rpl10A mutant plants show decreased ABA-sensitivity during seed germination, are impaired in early seedling and root development, and exhibit reduced ABA-inhibition of stomatal aperture under light conditions. Overexpression of RPL10A does not affect the germination and seedling growth, but RPL10A-overexpressing lines are more sensitive to ABA during early plant development and exhibit higher stomatal closure under light condition both with and without ABA treatment than wild type plants. Interestingly, RPL10A expression is induced by ABA. Together, we conclude that RPL10A could act as a positive regulator for ABA-dependent responses in Arabidopsis plants.

Multiplexing polysome profiling experiments to study translation in Escherichia coli

Polysome profiling is a widely used method to monitor the translation status of mRNAs. Although it is theoretically a simple technique, it is labor intensive. Repetitive polysome fractionation rapidly generates a large number of samples to be handled in the downstream processes of protein elimination, RNA extraction and quantification. Here, we propose a multiplex polysome profiling experiment in which distinct cellular extracts are pooled before loading on the sucrose gradient for fractionation. We used the multiplexing method to study translation in E. coli. Multiplexing polysome profiling experiments provided similar mRNA translation status to that obtained with the non-multiplex method with comparable distribution of mRNA copies between the polysome profiling fractions, similar ribosome occupancy and ribosome density. The multiplexing method was used for parallel characterization of gene translational responses to changing mRNA levels. When the mRNA level of two native genes, cysZ and lacZ was increased by transcription induction, their global translational response was similar, with a higher ribosome load leading to increased ribosome occupancy and ribosome densities. However the pattern and the magnitude of the translational response were gene specific. By reducing the number of polysome profiling experiments, the multiplexing method saved time and effort and reduced cost and technical bias. This method would be useful to study the translational effect of mRNA sequence-dependent parameters that often require testing multiple samples and conditions in parallel.

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

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.

Emerging Roles and Landscape of Translating mRNAs in Plants

Plants use a wide range of mechanisms to adapt to different environmental stresses. One of the earliest responses displayed under stress is rapid alterations in stress responsive gene expression that has been extensively analyzed through expression profiling such as microarrays and RNA-sequencing. Recently, expression profiling has been complemented with proteome analyses to establish a link between transcriptional and the corresponding translational changes. However, proteome profiling approaches have their own technical limitations. More recently, ribosome-associated mRNA profiling has emerged as an alternative and a robust way of identifying translating mRNAs, which are a set of mRNAs associated with ribosomes and more likely to contribute to proteome abundance. In this article, we briefly review recent studies that examined the processes affecting the abundance of translating mRNAs, their regulation during plant development and tolerance to stress conditions and plant factors affecting the selection of translating mRNA pools. This review also highlights recent findings revealing differential roles of alternatively spliced mRNAs and their translational control during stress adaptation. Overall, better understanding of processes involved in the regulation of translating mRNAs has obvious implications for improvement of stress tolerance in plants.

Differential Expression of Genes of the Calvin-Benson Cycle and its Related Genes During Leaf Development in Rice

To understand how the machinery for photosynthetic carbon assimilation is formed and maintained during leaf development, changes in the mRNA levels of the Calvin-Benson cycle enzymes, ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) activase and two key enzymes for sucrose synthesis were determined in rice (Oryza sativa L.). According to the patterns of changes in the mRNA levels, these genes were categorized into three groups. Group 1 included most of the genes involved in the carboxylation and reduction phases of the Calvin-Benson cycle, as well as three genes in the regeneration phase. The mRNA levels increased and reached maxima during leaf expansion and then rapidly declined, although there were some variations in the residual mRNA levels in senescent leaves. Group 2 included a number of genes involved in the regeneration phase, one gene in the reduction phase of the Calvin-Benson cycle and one gene in sucrose synthesis. The mRNA levels increased and almost reached maxima before full expansion and then gradually declined. Group 3 included Rubisco activase, one gene involved in the regeneration phase and one gene in sucrose synthesis. The overall pattern was similar to that in group 2 genes except that the mRNA levels reached maxima after the stage of full expansion. Thus, genes of the Calvin-Benson cycle and its related genes were differentially expressed during leaf development in rice, suggesting that such differential gene expression is necessary for formation and maintenance of the machinery of photosynthetic carbon assimilation.