Translating ribosome affinity purification (TRAP) offers the possibility to dissect developmental programs with minimal processing of organs and tissues. The protocol yields high-quality RNA from cells targeted with a green fluorescent protein (GFP)-labeled ribosomal subunit. Downstream analysis tools, such as qRT-PCR or RNA-seq, reveal tissue and cell type-specific expression profiles.
In this article, we give hands-on instructions to obtain translatome data from different Arabidopsis thaliana root cell types via the translating ribosome affinity purification (TRAP) method and consecutive optimized low-input library preparation.
As starting material, we employ plant lines that express GFP-tagged ribosomal protein RPL18 in a cell type-specific manner by use of adequate promoters. Prior to immunopurification and RNA extraction, the tissue is snap frozen, which preserves tissue integrity and simultaneously allows execution of time series studies with high temporal resolution. Notably, cell wall structures remain intact, which is a major drawback in alternative procedures such as fluorescence-activated cell sorting-based approaches that rely on tissue protoplasting to isolate distinct cell populations. Additionally, no tissue fixation is necessary as in laser capture microdissection-based techniques, which allows high-quality RNA to be obtained.
However, sampling from subpopulations of cells and only isolating polysome-associated RNA severely limits RNA yields. It is, therefore, necessary to apply sufficiently sensitive library preparation methods for successful data acquisition by RNA-seq.
TRAP offers an ideal tool for plant research as many developmental processes involve cell wall-related and mechanical signaling pathways. The use of promoters to target specific cell populations is bridging the gap between organ and single-cell level that in turn suffer from little resolution or very high costs. Here, we apply TRAP to study cell-cell communication in lateral root formation.
Driven by the increasing application of next-generation sequencing techniques, spatial resolution in developmental biology could be augmented. Contemporary studies aim at dissecting tissues down to specialized cell types, if not single-cell level1,2,3,4. To this end, a plethora of different methods has been devised over the last fifty years (see Figure 1A)5,6,7,8,9,10,11,12,13,14,15.
Many tools in plant science have been adaptations of techniques that were pioneered in animal research. This is not the case for the method we are introducing in detail here. In 2005, equipped with a strong background in protein translation, the Bailey-Serres Lab set out to engineer ribosomal proteins for subsequent affinity purification16. Thus, they could avoid time-consuming and labor-intensive polysome profiling, which is based on ultracentrifugation with a sucrose gradient and was used to assess translating ribosomes since the 1960s17,18. The method has since been referred to as translational ribosome affinity purification (TRAP)16. After successful translatome studies in plants, Heiman et al. adapted TRAP for animals19 and others extended its application to yeast20, Drosophila21, Xenopus22 and zebrafish23,24.
Although genetic modification of the model system is a prerequisite for TRAP, which limits its application to species amenable to genetic transformation, one can simultaneously harness this objection to target subsets of cells that are of special interest and otherwise extremely difficult to isolate from the intact tissue/organ25 (e.g., highly branched dendritic cells in a mouse brain or fungal hyphae in infected plant tissue). In plants, all cells are held in place via cell walls that form the basis of the hydrostatic skeleton26. To free a plant cell from this matrix, scientists have either physically cut the cell out of its surrounding tissue through laser capture microdissection (LCM)27 or performed enzymatic digestion of the cell walls28. Among the latter cells, so-called protoplasts, the population of interest is fluorescently labeled and can be separated via fluorescence-activated cell sorting (FACS)7. LCM usually requires a sample to be fixed and embedded in wax, which ultimately deteriorates the quality of its RNA29. FACS-based methods yield high-quality RNA, but the process of protoplasting itself introduces differences in gene expression30 and tissues with modified and thick secondary cell walls are notoriously difficult to treat. Moreover, many developmental processes in plants are assumed to rely on mechanically transmitted signals and therefore the integrity of the cell wall is of paramount importance31. Two methods, which use a shortcut to circumvent cell isolation by operating on the level of nucleii, are fluorescence-activated nuclear sorting (FANS) and isolation of nuclei tagged in specific cell types (INTACT). As in TRAP, they use cell type-specific promoters to mark nuclei, that subsequently get enriched via sorting or pull down, respectively8,15. A major challenge for all these approaches is to get sufficient RNA material from subsets of cells in a tissue. As TRAP captures only a fraction of the cellular RNAs, sample collection is a considerable bottleneck. Therefore, especially sensitive library preparation protocols are needed to produce high-quality data from low input amounts.
Since its establishment, TRAP has been either used in combination with DNA microarrays or, as sequencing costs dropped significantly in recent years, RNA-seq10,32,33. A multitude of research questions has already been elucidated as reviewed in Sablok et al.34. We are convinced that more reports will follow in coming years as the technique is very versatile when combining different promoters to target specific cell types. Eventually, this will be done even in an inducible way, and may be combined with probing the plant's reaction to many biotic and abiotic stress factors. Additionally, where stable transgenic lines are not available, hairy root expression systems have also been successfully used to perform TRAP in tomato and medicago35,36.
Figure 1: Translating ribosome affinity purification (TRAP) complements the "omics" analysis portfolio. A. Increasing levels of analytical precision, down to single-cell or even subcellular resolution can be achieved by a plethora of methods or combinations thereof. The scheme gives an overview of currently available tools in the plant and animal field. Tissue collection at cellular resolution can be achieved by protocols like LCM or FACS, which are then coupled to standard transcriptome or polysome profiling/translatome analysis. TRAP and INTACT integrate both tissue capture and RNA isolation as they are based on epitope-tagging. However, INTACT samples only cell nuclei and constitutes, therefore, a special case of transcriptome analysis. A small rabbit icon marks newly developed methods in the animal field: While SLAM-ITseq and Flura-seq rely on metabolic targetting of nascent RNAs with modified uracil bases in cells expressing the permissive enzyme, Slide-seq makes use of a coated glass slide with DNA barcodes that provide positional information in the cellular range. A proximity-labeling approach is followed in APEX-seq to sample RNAs in specific subcellular compartments. Notably, increased resolution often requires the generation of transgenic material (asterisks) and these methods are thus predominantly used for model species. TRAP is especially suited for plant science studies involving cell wall (CW) or mechanic signaling as well as cell species that are difficult to release from their CW matrix. B. Detailed wet-lab steps of the TRAP procedure: Seedlings expressing GFP-tagged ribosomal protein in distinct cell types (e.g. root endodermis) are grown on Petri dishes for seven days and root material harvested by snap freezing. A total RNA control sample is collected from the homogenized crude extract before pelleting the debris via centrifugation. Magnetic anti-GFP beads are added to the cleared extract to perform immunoprecipitation. After incubation and three wash steps, the polysome-associated RNA (TRAP/polysome RNA) is directly obtained via phenol-chloroform extraction. LCM: laser capture microdissection, FACS/FANS: fluorescence-activated cell/nuclear sorting, APEX-seq: method based on engineered ascorbate peroxidase, INTACT: isolation of nuclei tagged in specific cell types, SLAM-ITseq: thiol(SH)-linked alkylation for the metabolic sequencing of RNA in tissue, Flura-seq: fluorouracil-labeled RNA sequencing (Created with Biorender.com) Please click here to view a larger version of this figure.
The goal of this article is to supply a detailed description of the TRAP method, to highlight critical steps and to provide guidance for a possible library preparation method.
A generic TRAP experiment will essentially consist of the following steps (see also Figure 1B): (1) Preparation of plant material including cloning of ribosome-tagging construct, transgenic line production and selection, growing and bulking up of seeds, sterilization and plating, and stress application/treatment (optional) and tissue harvesting; (2) immunopurification including tissue homogenization and clearing of the crude extract, bead wash and immunopurification, and wash steps; (3) RNA extraction and quality assessment; and (4) library preparation.
The Arabidopsis root has been a model system to study plant development ever since its introduction as a model plant37,38. Here, the application of TRAP is showcased in the context of plant lateral root development. In plants, the buildup of the entire root system relies on the execution of this program and is therefore very important for the survival of the organism39. In Arabidopsis, lateral roots originate from pericycle tissue that resides next to xylem vessels and therefore is termed xylem pole pericycle (XPP; see Figure 2C)40. Some XPP cells, which are located deep inside the root, acquire a founder cell identity and, upon a local hormonal trigger, start to proliferate by swelling and dividing anticlinally41. However, due to the presence of a rigid cell wall matrix, this process exerts mechanical stress on the surrounding tissues. In particular, the overlying endodermis is affected, as it is in the way of the lateral root growth axis42,43,44. Indeed, the newly forming primordium will have to grow through the overlying endodermis cell (Figure 2C2) whereas cortex and epidermis cells are just pushed aside for the primordium to finally emerge45,46. Recent work in our lab has shown that the endodermis is actively contributing to accommodate the proliferation in the pericycle. Targeted blocking of endodermal hormonal signaling is sufficient to inhibit even the very first division in the XPP cells47. Hence, pericycle-endodermis communication constitutes a very early checkpoint for lateral root development in Arabidopsis. It is, however, not known how this crosstalk is performed. To unravel this mystery, we chose the TRAP-seq approach to target XPP and endodermal cells. To enrich for cells in the lateral root program, we mimicked the hormonal trigger by exogenously applying an auxin analog (1-naphthaleneacetic acid, NAA)48, which at the same time allowed to temporally resolve the initial phase of lateral root formation.
1. Cloning of transgene, transgenic line production and selection
2. Propagation and sterilization
3. Plating
4. Tissue treatment (optional)
NOTE: In this protocol, we outline the exogenous treatment of Arabidopsis roots with the synthetic auxin variant NAA. Depending on the experimental question at hand, this part needs to be adjusted or can be omitted entirely.
5. Harvesting
6. Immunopurification
NOTE: This step aims to obtain high-quality TRAP/polysome RNA. Therefore, strictly follow good practice advice for RNA handling. Perform all steps in this section in a sterile bench and clean all equipment and labware with an RNase-removing solution (Table of Materials). Wear gloves and change them immediately when contaminated with sample, ice, or other sources that have not been cleaned. Since this is a very crucial aspect, a section on equipment reuse together with waste disposal advice is included.
Ingredients | Stock concentration | Add volume in mL for 50 mL of WB* | Add volume in mL for 50 mL of PEB* | ||
1 | Tris, pH 9 | A | 2 M | 5 | 5 |
2 | KCl | A | 2 M | 5 | 5 |
3 | EGTA | A | 0.5 M | 2.5 | 2.5 |
4 | MgCl2 | A | 1 M | 1.75 | 1.75 |
5 | PTE | A | 20% (v/v) | 0 | 2.5 |
6 | detergent mix | A | 0 | 2.5 | |
Tween 20 | 20% (v/v) | ||||
Triton-X 100 | 20% (v/v) | ||||
Brij-35 | 20% (w/v) | ||||
Igepal | 20% (v/v) | ||||
7 | DTT | ₳ | 0.5 M | 0.1 | 0.1 |
8 | PMSF | ₳ | 0.1 M (isopropanol) | 0.5 | 0.5 |
9 | Cycloheximide | ₳ | 25 mg/mL (EtOH) | 0.1 | 0.1 |
10 | Chloramphenicol | ₳ | 50 mg/mL (EtOH) | 0.05 | 0.05 |
Table 1: Buffer composition and mixing advice. Ingredients with the given stock concentrations mixed in the given amounts yield 50 mL of WB or PEB. Tris: tris-(hydroxymethyl)-aminomethane, EGTA: ethylene glycol-bis(β-aminoethyl ether)-N,N,N',N'-tetra-acetic acid, PTE: Polyoxyethylene-(10)-tridecyl ether, A: autoclave, ₳: filter-sterilize; *fill up to 50 mL with RNase-free water.
7. RNA extraction and QC
8. Library preparation
For quality assessment, the above-mentioned procedure should be probed at several intermediate steps: expression pattern validation in planta, quality control of the isolated polysomal RNA as well as of the final libraries. qRT-PCR using known marker genes can, in addition, be performed to confirm the response to the treatment condition or to fine-tune the experimental conditions.
Confocal analysis of GFP signal distribution
To check for both endodermal and XPP expression patterns, we analyzed homozygous lines of pELTP::GFP-RPL18 and pXPP::GFP-RPL18 by confocal microscopy. Figure 2A and Figure 2B show representative plants with GFP signals (green) that have been counterstained with propidium iodide (magenta) to outline cell walls. The cross-section in Figure 2A1 shows a concentric ring in the third cell layer from the outside, which corresponds to the endodermis. The endodermal GFP signal initiates shortly above the meristematic zone (Figure 2A2) and appears both in the cytosol and around the nuclei of the cells, which corresponds to ribosomes. In contrast, the XPP line exhibits two distinct poles, which corresponds to the XPP (Figure 2B1). Approximately three cells at each pole start above the meristematic zone to exhibit a GFP signal. Thus, both lines comply with the localization pattern of endodermis and XPP, respectively (Figure 2C)53.
Polysome RNA validation
To determine the quality of the obtained polysome RNA we performed quality control measurements, using two automated electrophoresis systems (Table of Materials) that work with µL input amounts and also calculate an RNA integrity number (RIN)54. The proprietary algorithm assigns a RIN value between 1 and 10 to each electropherogram and is a robust and reproducible measure for RNA quality (i.e., degradation) – the lower the value the more degraded is the sample. Figure 3 shows examples of the measurements we obtained from polysome RNA. Most samples show hardly any apparent degradation with RIN values ranging from 9-10, which is in accordance with previous reports55,56. Any improper handling, especially periods of prolonged elevated temperatures (e.g., room temperature) or RNase contamination would be evident at this stage. Both instruments also calculate sample concentrations from their electropherograms (Figure 3A). These can vary substantially and are mostly at the lower detection limit. We, therefore, advise using fluorometric measurements to accurately quantify concentrations.
Library QC
As most labs do not perform the RNA sequencing in house, quality controls are often run at specialized facilities with high throughput devices (Table of Materials). They routinely assess the quality and quantify concentrations by qPCR and fluorometric assays (Table of Materials) as accurate measurements are prerequisite for library pooling. Nevertheless, if library preparation is not outsourced, one can sample the outcome with specialized equipment (Table of Materials). Figure 4 shows traces of successfully prepared libraries with our recommended protocol (A) and highlights the robustness of the procedure despite scaled-down reaction volumes (B). Part C illustrates sub-standard samples that can result from over-/underfragmentation, material loss during clean up or unsuccessful adapter removal. In the latter case, another clean up with a more stringent sample-bead-ratio could help eliminate the contamination. Completely failed samples were extremely rare in our hands and could originate at multiple points (e.g., too high input for the stochiometric tagmentation reaction).
The performance of sequenced libraries is exemplified in Figure 4D for samples from the endodermis in our mutant background. Libraries from WT and/or pericycle perform similar or even better. Ribosomal reads were on average around 2% with only few samples above 3%. Reads with an average quality score above 30 were consistently above 90% already before the filtering. The mapping ability of the sequenced reads was equally high ranging on average at 85%. To determine the correlation between biological replicates pairwise Spearman coefficients were calculated for each time point. All tests resulted in high coefficient values.
Treatment response and enrichment analysis
Before a genome-spanning dataset is produced, TRAP RNA from a pilot experiment can be probed by qRT-PCR to validate treatment success and/or experimental conditions. We performed this type of analysis to assess auxin responses after 2 h of treatment in the XPP samples (Figure 5A). Three different auxin-responsive genes (GH3.3, LBD29 and GATA23) were tested via the ∆∆Ct method57. Very strong induction was observed in all three cases after the incubation period, which suggests that the exogenous NAA application was successful.
If newly developed promoters are utilized one should at this point also perform enrichment analysis with qRT-PCR. To this end, a known marker gene (i.e., the gene driven by the promoter used) is amplified in the TRAP and total RNA sample and expression levels normalized to the total RNA level. If the isolation of TRAP RNA from the specific tissue was successful a significant fold change increase should be obtained. Alternatively, equivalent information can be retrieved from the sequencing data (see Figure 5B). Expression of two suberin-related genes, GPAT5 and HORST, is present in all endodermis samples and notably absent from the XPP tissues. On the contrary, pericycle-expressed genes (PHO1 and SKOR) are only very lowly expressed in the endodermis and enriched in the XPP probes with an auxin-induced down-regulation over the examined time frame.
Figure 2: Cell type-specific expression of GFP-RPL18 in the Arabidopsis root. A-B. Confocal microscopy images of pELTP::GFP-RPL18 (A) and pXPP::GFP-RPL18 (B) expressing roots at six days post germination. Cell wall outlines were obtained through staining with propidium iodide (magenta). Cross-sections A1 and B1 are from the positions denoted with dashed lines in A2 and B2, respectively. The latter images show maximum projections (MAX) of the recorded z-stacks. C. Schematic representation of the tissue types composing the Arabidopsis root in longitudinal (C1) and cross-section (C3) as well as in a lateral root primordium (C2). The image was modified with permission from F. Bouché. Scale bars: 100 µm. Please click here to view a larger version of this figure.
Figure 3: TRAP/polysome RNA quality assessment. A. Tapestation – Representative results from 14 measured samples in gel picture representation with their respective RINe values (top left). Electropherogram representation is shown for sample A1 (highlighted in blue). The table on the right informs about the sample concentrations. B. Similar traces as in A are obtained with the Bioanalyzer. The panels on the right show samples with increasing levels of degradation, which reflects in their decreasing RIN values. Please click here to view a larger version of this figure.
Figure 4: Library profiles from TRAP/polysome samples. A. Two representative TRAP samples (left) correspond very well with the traces for successful libraries recommended by the Nextera XT user guide. B. Differing reaction volumes yield robust library preparation outcomes. C. Libraries with suboptimal outcomes: very short fragments (top left), extremely long fragments (bottom left), low concentration (top right) or complete fail (bottom right). Note also residual short fragments (blue ellipse), that have to be removed before sequencing. Bioanalyzer: red traces, LabChip: blue traces. D. Selected quality measures for sequenced TRAP samples (endodermis of our lateral root-free mutant) at different time points and distribution of Spearman correlation coefficients calculated between pairwise comparisons of all samples within a time point (n=65). Please click here to view a larger version of this figure.
Figure 5: qRT-PCR and RNA-seq show auxin-responsiveness and tissue type enrichment, respectively. A. Expression levels of three known auxin-responsive genes were assessed after 2 h of auxin treatment via qRT-PCR. Strong induction was observed in all samples. RT-PCR was performed on 3 independent biological replicates and normalized to the non-treated samples with UBC21 as internal reference gene. Error bars represent the SEM. GH3.3: Gretchen Hagen 3.3, LDB29: LATERAL BOUNDARY DOMAIN 29, GATA23: GATA-motif binding transcription factor 23, UBC21: UBIQUITIN-CONJUGATING ENZYME 21 B. Expression levels of four marker genes from the TRAP-seq dataset. Samples on the left are endodermis-derived (green shades), while samples on the right are XPP-derived (blue shades). Numbers represent the auxin incubation intervals in hours. Negative z-scores reflect low expression levels and vice versa. Endodermal marker genes (GPAT5, HORST) are differentially expressed with high levels in endodermis samples. On the contrary, pericycle markers (PHO1, SKOR) have high expression levels in XPP cells and show down-regulation upon auxin treatment. GPAT5: glycerol-3-phosphate 2-O-acyltransferas (suberin biosynthsis), HORST: hydroxylase of root suberized tissue, PHO1: phosphate 1, SKOR: stelar K+ outward rectifier. Please click here to view a larger version of this figure.
Figure 6: Non-constitutive pUBQ10::GFP-RPL18 localization patterns. Confocal microscopy of six-day-old seedlings. Cell wall outlines were obtained through staining with propidium iodide (magenta). Cross-sections A2 and C1 are from the positions denoted with dashed lines in A3 and C2, respectively. Images marked MAX show maximum projections of the recorded z-stacks. A1-A3. Uniform localization patterns of the UBQ10-driven construct. B1-C2. Notable decrease in the signal strength in outer tissue layers. A, B and C are recorded in three different plants. Scale bars: 100 µm. Please click here to view a larger version of this figure.
Verification of RPL18 localization pattern
Crucial to avoid misinterpretation of data from any TRAP experiment is the proper expression pattern of the tagged ribosomal subunit. Therefore, the incorporation of GFP as an epitope tag to RPL18 very elegantly allows verification of the desired expression pattern and consecutively, pulldown of the polysome fraction from the same tissue. More invasive approaches to assure proper promoter patterns are followed by Jiao and Mayerowitz 2010, which requires GUS-staining and in Tian et al. 2019 that relies on immunostaining with anti-FLAG antibodies58,59.
We strongly advise to check the localization pattern in each generation as T-DNA transgenic lines can be prone to silencing and thus signal strength can deteriorate or the proportion of expressing seeds decreases. With the GFP-tag incorporated in the construct, these frequent controls are easily performed via microscopy.
However, even thorough confocal analysis can in some instances lead to false conclusions. We would like to highlight this with our failed attempt to produce a control TRAP line. So far, the plant science community has not been able to create a plant line with a uniform RPL18 distribution throughout all cell layers. Even the initially employed 35S promoter was attributed to only show "near constitutive" distribution with a non-uniform localization pattern10. Our approach was to use the promoter of UBIQUITIN10 (UBQ10) to drive the GFP-RPL18 construct. Screening in the T1 generation offered very promising localization and thus was chosen to be propagated (Figure 6A). However, data of a test sequencing run did not show enrichment in comparisons between ELTP– and UBQ10-driven lines for known endodermis specific genes. Upon closer inspection of those plants, indeed we found a decrease in signal in the outer tissue layers whereas stele tissue showed strong expression (Figure 6B). Future studies should search the promoter landscape for more suitable candidates and complement the TRAP method.
Total RNA as control sample
The establishment of a better TRAP control line is still pending and will be highly anticipated by the field. With this in mind, so far the only way to obtain a tissue-wide uniform distribution of mRNAs is to collect total RNA. As, in this case, a transcriptome is sampled, this needs to be accounted for in the further bioinformatic analysis. Notably, both total RNA and polysome RNA fractions are now correlated as they originate from the same tissue sample.
In search for a TRAP library preparation method
As mentioned previously, a major drawback of the TRAP approach are the varying and mostly low yields that can be achieved. With samples ranging from few ng to sometimes up to 100 ng a standard approach with the Illumina TruSeq kit (100 ng input requirement) was judged as too insensitive for construction of libraries of sufficient quality. A market search revealed several commercially available library preparation kits, that were specified to work with as low as 5-10 ng starting material. We did not test the protocol used by Reynoso et al. 2019, which works for their TRAP samples from tomato, rice and Medicago and uses the BrAD-seq approach60.
All our trials, however, with subsequent test sequencing yielded dissatisfactory results. Despite the use of polyA-enrichment steps, the TRAP samples suffered from high ribosomal contaminations (up to 30% of reads). Furthermore, the success rate for the library preparation was variable and especially low for samples with critically low concentrations or relatively lower RIN values. Our extensive testing lead us to the conclusion, that the specific RNA composition of a TRAP sample, with very high rRNA content and presumably minute mRNA concentrations, requires a more sensitive approach to obtain reliable libraries. Thus, we turned to state-of-the-art solutions for ultra-low input amounts: SMARTer v4 and Nextera XT. Reassuringly, Song et al. also found this library preparation approach to outperform their competitors when they tested several methods and their sequencing output on TRAPed liver tissue61. The quality metrics we have presented in Figure 4D exhibit high quality reads (Q>30) at low rRNA-mapping rates (<3%) concurrent with high gene mapping rates. Additionally, consistently high Spearman correlation coefficients show that replicates have indeed very similar expression profiles. The usage of both kits was straightforward with modest cycle numbers and yielded robust and reliable results. Sequencing data were of high quality with 1.5 ng starting material. With the SMARTer kit tolerating as low as 200 pg input, the amount of plant starting material can be optimized. The applicability for rarer cell types will ultimately be determined by the feasibility to accrue enough RNA.
TRAP complements the plant science toolkit
The TRAP method has become increasingly popular with plant scientists34 and we are confident that it will acquire the status of a standard technique due to several reasons.
None of the steps in the TRAP protocol need specialized equipment, like a cell sorting machine or a dedicated laser-capture microscope, which makes it possible for many labs to perform the experiments. To date, the most costly factors are library preparation and downstream sequencing. Nevertheless, with the dynamic advancement of next-generation sequencing techniques and increasing demand for single-cell sequencing, we anticipate that costs will decrease significantly.
Furthermore, the isolation of polysome-associated RNAs means that information is gathered on the active translation status of those RNAs (translatome). Therefore, TRAP captures the output of all regulatory steps that are upstream of translation and represents a more direct proxy for the cellular protein composition. Of course, stalled ribosomes and post-translational modifications still remain elusive and need to be addressed by other approaches (e.g. proteomics).
As stated previously, a clear advantage that TRAP has in a plant context is the preservation of CW structures and mechanical properties of the cells. As we only begin to understand the intricate connections and regulatory functions that arise through CW- and mechanical signaling31,62, approaches that preserve these structures will become more important in many different developmental contexts.
Especially for well-established model species, TRAP can profit from a wealth of different promoters, that have been characterized. In Arabidopsis, it was thus possible to map the entire root in a cell type-specific manner by using 19 different marker gene promoters30,63. With each RNA-seq experiment, these selections will be improved and new, more specific promoters will arise and refine the cellular resolution.
TRAP is additionally applicable in a combinatorial use with many promoters for cell populations where no markers are yet known. This is the case for specialized cells in the root endodermis. The so-called passage cells are characterized by the absense of the suberin layer that coats mature endodermis cells53. Combining suitable promoters and subsequent in silico subtraction of the distinct expression profiles will enrich for regions that harbor passage cells. Transcriptional reporter analysis will then help identify passage cell marker genes. However, whether TRAP can be used to then analyze the rare cell population on this basis remains to be determined.
In this article, we have provided a detailed description of the translating-ribosome affinity purification method, its advantages and limitations, and highlighted potential applications thereof. In the portfolio of "omics" studies, it occupies an important niche and will help to answer many biological questions.
The authors have nothing to disclose.
We would like to thank Jean-Claude Walser of the Genetic Diversity Center Zurich for crucial expert advice in the early phase of this project. Work in the Vermeer lab was supported by an SNF Professorship grant (PP00P3_157524) and a R'EQUIP equipment grant (316030_164086) from the Swiss National Science Foundation (SNSF) awarded to JEMV.
Sterilization | |||
bleach, 13% | Sigma | 71696 | |
beaker | VWR | 214-1172/74/75 | |
desiccator with porcelaine plate (DURAN) | Sigma/Merck | Z317454-1EA/Z317594-1EA | |
EtOH, p.a. | Honeywell | 02860-1L | |
HCl, 37% | Roth | 4625.1 | |
Tween 20 | Sigma | P9416 | |
Plate growth + harvesting | |||
MS salts, basal salt mixture, incl. MES buffer | Duchefa | M0254 | |
agar plant for cell culture | Applichem/Panreac | A2111.1000 | |
DMSO | Sigma | D4540 | |
forcepts | Rubis Switzerland | 5-SA model | |
KOH | Fluka | 60370 | |
micropore/surgical tape | 3M | 1530-0 | |
NAA | Duchefa | N0903 | |
petri dishes 120×120 mm | Greiner bio-one | 688102 | |
scalpel | VWR/Swann-Morton | 233-5454 | |
tissues, neutral, two-layered | any supplier of your choice | ||
Immunoprecipitation | |||
GFP-beads: gtma-100 GFP-Trap_MA | Chromotek | e.g. gtma-100 | |
Brij-35 | Sigma | P1254-500G | |
centrifuge tubes (in accordance with centrifuge) | Beckman Coulter | 357001 | |
Chloramphenicol | Applichem | C0378-25G | |
cotton gloves | VWR | 113-7355 | |
Cycloheximide, HPLC grade | Sigma | 01810-1G | |
DEPC | VWR | E174 | might have long delivery times |
DTT | Fluka | 43815 | |
EGTA | Sigma | 3054.3 | |
homogenizers DUALL 23 | KONTES GLASS CO (via VWR) | SCERSP885450-0023 (set) | SCERSP885451-0023 pestle only – SCERSP885452-0023 cylinder only; long delivery times |
Igepal CA-360 | Sigma | I3021-100ml | |
KCl | Sigma | 60130 | |
MgCl2 hexahydrat | Roth | 2189.2 | |
mortar and pestle | VWR | 470148-960 & 470019-978 | |
PMSF | Roche | 10 837 091 001 | |
Polyoxyethylene-(10)-tridecylether/PTE | Sigma | P2393-500G | |
RNase-free water | Roth | T143.3 | |
RNAZap | Thermo Fisher | AM9780/AM9782 | for cleaning surfaces |
Tris, >99.3% | Roth | AE15.3 | |
Triton X-100 | Fluka | T8787-250ml | |
Tween 20 | Sigma | P9416-100ml | |
RNA extraction | |||
2-Propanol, p.a. | Sigma | 33539-1L-GL-R | |
Chloroform, HPLC grade | Scharlau | CL02181000 | |
EtOH, p.a. | Honeywell | 02860-1L | |
low-retention microcentrifuge tubes, 1.5 ml | Eppendorf/Sigma | Z666548-250EA | LoBind |
RNase-free DNase set | Qiagen | 79254 | |
RNeasy MiniElute Cleanup Kit | Qiagen | 74204 | |
TRIzol reagent | ThermoFisher/Ambion | 15596018 | |
Library preparation | |||
15/50 mL Tube Magnetic Separator | Abraxis | PN 472250 | |
AMPure beads | Beckman Coulter | A63881 | |
Index Kit A | Illumina | FC-131-2001 | |
Index Kit D | Illumina | FC-131-2004 | |
neodymium magnets | Amazon/other | 6 x 1.5 mm range: N42 (NdFeB) | |
Nextera XT kit | Illumina | FC-131-1024/1096 | https://emea.support.illumina.com/ |
PCR strips | ThermoScientific | AB-0266 | |
SMARTer v4 kit | Takara Bioscience | 634892 | https://www.takarabio.com/ |
Bioanalyzer | Agilent | 2100 Bioanalyzer Instrument | specialized equipment for RNA/DNA quality control |
Tapestation | Agilent | 4200 Tapestation Instrument | specialized equipment for RNA/DNA quality control |
Fragment Analyzer | Agilent | 5400 Fragment Analyzer System | specialized equipment for RNA/DNA quality control (high throughput) |
LabChip | PerkinElmer | LabChip GX Touch Nucleic Acid Analyzer | specialized equipment for RNA/DNA quality control (high throughput) |
Qubit 4 Fluorometer | ThermoFisher | Q33239 | specialized equipment for RNA/DNA concentration determination |
qRT-PCR | |||
GATA23 | Microsynth | fwd: AGTGAGAATGAA AGAAGAGAAGGG; rev: GTGGCTGCGAAT AATATGAATACC |
|
GH3.3 | Microsynth | fwd: CAAACCAATCCT CCAAATGAC; rev: ACTTATCCGCAA CCCGACT |
|
LBD29 | Microsynth | fwd: TCTCCAACAACA GGTTGTGAAT; rev: AAGGAGCCTTAG TAGTGTCTCCA |
|
UBC21 | Microsynth | fwd: TGCGACTCAGGG AATCTTCT; rev: TCATCCTTTCTT AGGCATAGCG |
|
SsoAdvanced Universal SYBR Green | Bio-Rad | #172-5270 | |
iScript Adv cDNA Kit | Bio-Rad | #172-5038 | |
miscellaneous | |||
Falcon tubes 15 ml, Cellstar | Greiner bio-one | 188261 | |
Falcon tubes 50 ml, Cellstar | Greiner bio-one | 210261 | |
filter tips 1 ml | Axygen | TF-1000-R-S | |
filter tips 10 µl | Axygen | TF-10-R-S | |
filter tips 100 µl | Axygen | TF-100-R-S | |
filter tips 20 µl | Axygen | TF-20-R-S | |
filter tips 200 µl | Axygen | TF-200-R-S | |
microcentrifuge tubes 1.5 ml | SARSTEDT | 72.690.001 | |
Propidium iodide | Sigma | P4170-100MG | |
sequencing company | Novogene | en.novogene.com |