Dynamics of the Pollen Sequestrome Defined by Subcellular Coupled Omics

Abstract

Reproduction success in angiosperm plants depends on robust pollen tube growth through the female pistil tissues to ensure successful fertilization. Accordingly, there is an apparent evolutionary trend to accumulate significant reserves during pollen maturation, including a population of stored mRNAs, that are utilized later for a massive translation of various proteins in growing pollen tubes. Here, we performed a thorough transcriptomic and proteomic analysis of stored and translated transcripts in three subcellular compartments of tobacco (Nicotiana tabacum), long-term storage EDTA/puromycin-resistant particles, translating polysomes, and free ribonuclear particles, throughout tobacco pollen development and in in vitro-growing pollen tubes. We demonstrated that the composition of the aforementioned complexes is not rigid and that numerous transcripts were redistributed among these complexes during pollen development, which may represent an important mechanism of translational regulation. Therefore, we defined the pollen sequestrome as a distinct and highly dynamic compartment for the storage of stable, translationally repressed transcripts and demonstrated its dynamics. We propose that EDTA/puromycin-resistant particle complexes represent aggregated nontranslating monosomes as the primary mediators of messenger RNA sequestration. Such organization is extremely useful in fast tip-growing pollen tubes, where rapid and orchestrated protein synthesis must take place in specific regions.

Figure 1.

Schematic representation of the experimental workflow.

Figure 2.

Definition of the pollen sequestrome. A, Quantification of expressed transcripts in total RNA, transcripts expressed in all three fractions, and the overlap of both sets. B, Overall expression signal in all three fractions during pollen development and the progamic phase. C, Relative distribution of the expression signal between subcellular fractions in four stages of pollen development and the progamic phase. D, Average expression signal in each subcellular fraction during pollen development and the progamic phase. E, PCA of transcripts present in all three subcellular fractions and total RNA in MPG. F, PCA of transcripts forming the sequestrome fraction during pollen development and the progamic phase. G, Hierarchical clustering of transcripts present in all three subcellular fractions and in total RNA in mature pollen.

Figure 3.

Expression profiles of selected transcripts in six stages of pollen development and the progamic phase. In each chart, relative expression signals are shown for each subcellular fraction. Blue represents the sequestrome, orange the translatome, and green the mRNPome. Expression profiles and accession numbers of selected genes are shown in Supplemental Table S3.

Figure 4.

Quantification of fraction proteomes. A, 1D SDS-PAGE electrophoretogram, 12.5% polyacrylamide gel, with Coomassie Brilliant Blue R250 staining. B, Number of proteins identified in each fraction in each MPG and two stages of the progamic phase (PT4 and PT24). C, PCA of proteins present in all three fractions in MPG, PT4, and PT24. D, Venn diagrams showing the number of unique and overlapping proteins in all fractions of MPG, PT4, and PT24. E, Average expression signal (area) of proteins unique for each fraction and proteins shared by two or all three fractions (see C). F, Distribution of expression signals of data presented in D. In E and F, the bottom whiskers show the 9th percentile and the top whiskers mark the 91st percentile.

Figure 5.

Gene Ontology (GO) summary of fraction proteomes. A, Top seven categories in each fraction (EPP, POL, and RNP) in all three developmental stages (MPG, PT4, and PT24). B, Expression dynamics of the 10 most abundant proteins present in each subcellular fraction and in each developmental stage.

Figure 6.

Dynamics of RPs, eukaryotic initiation factors (eIFs), PABPs, and TUDOR-SN (TSN) proteins during pollen development and the progamic phase. A, Overall abundance of RP transcripts. B, Abundance of RP transcripts present in 60S and 40S subunits. C, Overall abundance of eIF transcripts. D, Abundance of transcripts forming individual eIFs. E, Overall abundance of PABP transcripts. F, Overall abundance of TSN transcripts. G, Expression dynamics of seven protein groups associated with PABPs in all subcellular fractions during the progamic phase. H, Expression dynamics of six protein groups associated with TSN proteins in all subcellular fractions during the progamic phase. Transcriptomic data (A–F) were plotted as a sum of expression signals, and relative visualization of the same data is shown in the respective inlet. Proteomic data are plotted as protein abundance values (ppm).

Figure 7.

Dynamics of ribosomal proteins in fraction proteomes during the progamic phase. A, Sum of expression signals of ribosomal proteins in all fractions. B, Distribution of expression signals in 80S ribosomes as well as individually in small and large ribosomal subunits. C, Dynamics of individual small and large subunit ribosomal proteins between EPP and POL fractions during the progamic phase. The heat map intensity shows the predominant presence of the respective protein in the polysomal (orange) or EPP (blue) fraction.

Figure 8.

5′UTR and upstream open reading frames (uORF) analysis. Sequences were extracted from the Nicotiana tabacum TN90 cDNA database (Sierro et al., 2013, 2014). A, Box plots comparing 5′UTR length and number of uORFs between POL and EPP resident transcripts. All observed differences in the number of uORFs and 5′UTR length (with the exception of the uORF comparison at MPG) were statistically significant. B, Top three common motifs identified in the 5′UTRs of stored transcripts at the PT24 time point.

Figure 9.

Dynamics of stored transcripts from sperm cell-expressed and sperm cell-specific genes between POL and EPP up to 24 h of in vitro pollen tube growth. Data were derived from an Agilent 44K array chip and validated by qPCR. Error bars represent sd among replicates.

Figure 10.

Polysome profiling revealed that monosomes dominate at MPG. A, Experimental workflow. B, Polysome profiles from a subcellular fractionation-coupled Suc density gradient showing a dominant monosome peak in the MPG sample and only traces of polysomes. At the PT4 stage, the increase in polysome abundance is likely associated with high translation activities in pollen tubes. P/M represents a ratio of polysomes versus monosomes calculated per area of occupancy on the plot by the two fractions. C, Quantification of transcript occupancy in monosomes versus polysomes of five selected genes at the MPG stage and after 4 h of in vitro pollen tube growth (PT4). The P/M ratio represents the translatability rate of each transcript from the respective gene at each stage. Asterisks report a statistically significant difference (Welch’s t test, P < 0.05) between the P/M ratio at MPG versus PT4 as a metric of induced translation. Error bars represent sd among replicates. D, Quantification of the POL/EPP ratio for selected transcripts and the respective proteins during the progamic phase. Error bars represent sd among replicates.