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Ribo-depletion in RNA-Seq – Which ribosomal RNA depletion method works best?

Ribo-depletion in RNA-Seq – Which ribosomal RNA depletion method works best?

Summary: This blogpost is focussed on ribosomal RNA (rRNA) depletion methods frequently applied to improve and economize RNA-Seq experiments.

The Rise of RNA-Seq

RNA-Seq Overtakes Microarrays

The use of Next-Generation RNA Sequencing (RNA-Seq) has recently overtaken that of DNA-based microarrays to detect and quantify changes in gene expression.

Why? RNA-Seq can detect novel coding and non-coding genes, splice isoforms, single nucleotide variants and gene fusions. Its broader dynamic range also enables sensitive detection of low abundance transcripts.

RNA-Seq vs Microarray

Also, technological advancements in single cell isolation, ribosome profiling and pulse-labelling techniques can now be multiplexed with RNA-Seq to widen the scope of scientific interrogation. Now, one can study the transcriptome, translotome and epitranscriptome with added spatial and temporal resolution. Studies of RNA structure and  RNA-protein/nucleic acid interactions with the use of nuclease digestion and biochemical pulldown approaches have also increasingly employed RNA-Seq. This excellent review describes all these latest advances.

A Major Challenge in RNA-Seq

A major limitation encountered in RNA-Seq however is the massive abundance of ribosomal RNA (rRNA) that can occupy up to 90% of RNA-Seq reads.  This necessitates additional steps for ribo-depletion or rRNA depletion to economize an RNA-Seq experiment.

Ribo-Depletion Methods

1) Poly-A selection

The most common method of rRNA depletion is poly-A selection, which relies on the use of oligo (dT) primers attached to a solid support (e.g. magnetic beads) to isolate protein-coding polyadenylated RNA transcripts. The main disadvantage though is one misses out on non-polyadenylated transcripts which include microRNAs, small nucleolar RNAs (snoRNAs), some long non-coding RNAs (lncRNA), and even some protein-coding RNAs (histones) which lack polyA tails. As a result, one fails to capture biologically relevant insights on these RNAs which make up a substantial proportion of the transcriptome.

Poly-A Selection - Advantages and Disadvantages

Curiously, polyadenylated transcripts are more abundant in eukaryotes as opposed to prokaryotes with both groups using polyadenylation in entirely different ways! Hence, polyA selection cannot be applied for sequencing of bacteria and archaebacteria, excluding its use in metagenomic RNA-Seq.

Poly-A selection also relies on transcripts being largely intact and tend to over-represent 3′ regions of transcripts. Studies comparing physical rRNA depletion methods and polyA selection show polyA selection did not work well for degraded RNA samples. A lower number of reads were also obtained with formalin-fixed paraffin-embedded (FFPE) tissues though analysis of fresh frozen tissues was not compromised.

Despite this, polyA selection still provides greater exonic coverage than physical rRNA depletion which tend to produce more intronic reads.  Further, a lower sequencing depth is typically needed for polyA selection, making it a respectable choice if one is focused only on protein-coding genes.

2) Physical Ribosomal RNA (rRNA) removal

Ribosomal rRNA can also be removed by hybridization to complementary biotinylated oligo probes, followed by extraction with streptavidin-coated magnetic beads. riboPOOLs developed by siTOOLs Biotech efficiently removes rRNA through this route, with a workflow similar to Ribo-Zero from Illumina.

Physical rRNA removal workflow
Workflow for rRNA removal with biotinylated probes and streptavidin-coated magnetic beads

Compared to polyA selection methods, rRNA removal enables detection of non-polyadenylated transcripts and small RNAs.  Comparisons between differential gene expression detected with both methods were typically well-correlated. The rRNA removal method however could detect both long and short transcripts showing less of a 3′ bias than polyA selection.

Physical rRNA removal also performs better for degraded and FFPE samples, and can also be applied for metagenomic samples that contain microbes. The Pan-Prokaryote riboPOOL by siTOOLs for example, functions effectively to remove rRNA from a diverse range of prokaryotic species, and can be used in combination with human and mouse/rat riboPOOLs to deplete rRNA from complex samples containing multiple species.

Physical rRNA Removal - Advantages and Disadvantages

By using targeted probes, one can also flexibly deplete abundant RNAs that take up expensive RNA-Seq reads. For example, globin, found in high amounts in RNA isolated from blood samples, can be efficiently depleted by globin mRNA-specific probes.

Ribosomal RNA can also be removed by selective degradation where enzyme RNase H is used to specifically degrade DNA-RNA hybrids formed between DNA probes and complementary rRNA (e.g. NEBNext rRNA depletion kit by New England Biolabs). This method was reported to produce consistent results, working as well on degraded samples though there was a bias against detecting transcripts of shorter length compared to Ribo-Zero.

3) Targeted amplification

An alternative method to deplete rRNA involves the use of  “not so random” hexamer/heptamer primers with a decreased affinity for rRNA during first strand cDNA synthesis. This is employed by the Ovation RNA-Seq kits from NuGen. Though the kit can be used to detect non-polyA RNAs and can be applied to prokaryotes, the additional incorporation of oligo(dT) still contributes to a bias towards  detecting 3′ regions.

A recent ribosome profiling study comparing library preparation methods reported fewer reads obtained and greater intronic reads for Nugen kits compared to polyA-selection methods. As Nugen also incorporated an RNase-mediated degradation of unwanted transcripts during final library construction steps, this indicates targeted amplification alone cannot totally remove rRNA. The method does however work with low input amounts and degraded samples.

 Targeted Amplification with not so random primers - Advantages and Disadvantages

So which ribo-depletion method works best?

And the answer as always? It depends. Depending on the ribo-depletion method chosen in RNA-Seq library preparation, some differences in genes detected and their expression levels will certainly be observed.

Poly-A selection might be the most efficient method when only focussed on protein-coding genes, but one loses significant information on non-polyadenylated RNAs and immature transcripts. In instances such as microbial sequencing or in sequencing degraded or FFPE samples, poly-A selection cannot even be applied or may perform poorly.

Physical rRNA removal offers the advantage of retrieving more transcriptomic information but comes at a cost of greater intronic/intergenic reads that necessitates a greater sequencing depth. However, it offers greater flexibility and better performance in sequencing of challenging sample types.

Targeted amplification with “not so random” primers though effective for low input material, comes also at a cost of greater sequencing depth required.

All methods are subject to some extent of non-specificity and detection bias. Further variability can also arise from different methods of sequence alignment in RNA-Seq data analysis. It is therefore always advisable to validate sequencing data obtained by real-time quantitative PCR (rtqPCR) or other methods.

 

References:

1. Song, Y., Milon, B., Ott, S., Zhao, X., Sadzewicz, L., Shetty, A., Boger, E. T., Tallon, L. J., Morell, R. J., Mahurkar, A., and Hertzano, R. (2018) A comparative analysis of library prep approaches for sequencing low input translatome samples. BMC Genomics. 19, 696
2. O’Neil, D., Glowatz, H., and Schlumpberger, M. (2013) Ribosomal RNA Depletion for Efficient Use of RNA-Seq Capacity. in Current Protocols in Molecular Biology, p. 4.19.1-4.19.8, John Wiley & Sons, Inc., Hoboken, NJ, USA, 103, 4.19.1-4.19.8
3. Stark, R., Grzelak, M., and Hadfield, J. (2019) RNA sequencing: the teenage years. Nat. Rev. Genet. 10.1038/s41576-019-0150-2
4. Cui, P., Lin, Q., Ding, F., Xin, C., Gong, W., Zhang, L., Geng, J., Zhang, B., Yu, X., Yang, J., Hu, S., and Yu, J. (2010) A comparison between ribo-minus RNA-sequencing and polyA-selected RNA-sequencing. Genomics. 96, 259–265
5. Zhao, S., Zhang, Y., Gamini, R., Zhang, B., and von Schack, D. (2018) Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion. Sci. Rep. 8, 4781
6. Herbert, Z. T., Kershner, J. P., Butty, V. L., Thimmapuram, J., Choudhari, S., Alekseyev, Y. O., Fan, J., Podnar, J. W., Wilcox, E., Gipson, J., Gillaspy, A., Jepsen, K., BonDurant, S. S., Morris, K., Berkeley, M., LeClerc, A., Simpson, S. D., Sommerville, G., Grimmett, L., Adams, M., and Levine, S. S. (2018) Cross-site comparison of ribosomal depletion kits for Illumina RNAseq library construction. BMC Genomics. 19, 199

 

Featured Image is an artist’s rendition of a ribosome. Credit: C. BICKLE/SCIENCE

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Tips for optimizing RNA affinity purification

Tips for optimizing RNA affinity purification

RNA affinity purification (RAP) experiments enable the isolation and analysis of interacting molecules with an RNA of interest. Often performed to gain insight into RNA function, it is gaining popularity in the study of lncRNAs but can also be applied to coding RNAs.

The general workflow involves preserving nucleic acid and protein interactions with a cross-linking reagent, followed by lysis and sonication to shear nucleic acids to sizes amenable for pulldown. Biotin-labelled DNA probes (which we offer, see raPOOLs) are added to the lysates and hybridize with the RNA of interest. This enables the isolation of the RNA and its associated molecules through the high affinity biotin-streptavidin interaction between biotinylated probes within the complex and streptavidin-coated magnetic beads. The complexes are then disrupted and individual components analysed by various methods: western blotting/mass spectrometry (for proteins), sequencing/northern and southern blots/PCR detection (for nucleic acids). A detailed protocol can be found here.

Despite the seemingly simple workflow, there are a number of parameters requiring optimization when applying the protocol to your RNA of interest. We break them down into the following sections:

1. Input material

If trying to detect protein partners of the target RNA, sufficient amounts of target RNA have to be isolated as unlike nucleic acids, proteins cannot be amplified. It is always advisable to determine the number of copies of the target RNA per cell to examine how much input material is required. As a guide, XIST is expressed at < 2000 copies/cell and required 50-250 million cells (depending on cell type) per pulldown condition to visualize proteins by immunoblotting/MS (Chu et al., 2015). For some lowly expressed lncRNAs, up to 1 billion cells may be required per pulldown! If your RNA is too lowly expressed and RAP is not feasible, other methods involving FISH and immunofluorescence imaging or protein arrays might be explored.

2. Cross-linking

Cross-linking reagents produce covalent bonds between nucleic acids and proteins in close proximity with each other, stabilizing these interactions for subsequent analysis. Formaldehyde (CH2O) and glutaraldehyde (C5H8O2) are most commonly used and cross-link direct and indirect associations between proteins-proteins, nucleic acids- nucleic acids and nucleic acids-proteins. Compared to formaldehyde, glutaraldehyde has two reactive groups, making it a stronger cross-linker. It also fixes long range interactions compared to formaldehyde, a zero-length cross-linker. Formaldehyde fixation can be reversed by heating at 65◦C for 6 h, while glutaraldehyde fixation is irreversible. Alternatively, UV irradiation produces irreversible cross-links only between nucleic acids and proteins.

There are a whole range of other cross-linking chemicals one could use in combination that can cross-link different reactive groups and at different ranges, but take note that the activity of cross-linking chemicals is highly determined by pH and buffer conditions, so be sure to follow given protocols closely and ensure reagents used are fresh. Note also that the longer cross-linking is carried out, the harder it is to sonicate nucleic acids down to smaller fragments.

3. Sonication and lysis

Sonication is an effective way to randomly shear nucleic acids to increase efficiency of their pulldown, hence improving detection sensitivity. Ideally, fragments should be sheared down to ~100-500 bases. If using PCR detection, be aware that your amplicon size should be small enough to lie within these sheared fragments.

Factors affecting sonication efficiency include volume of sample, sonication strength, frequency and duration and if using probe sonicators, probe position/depth. Follow the instrument manufacturer’s instructions closely and optimize duration of sonication by collecting samples at time-points and studying the extent of fragmentation. If using probe sonicators, ensure the probe is inserted into the lysate deep enough as frothing tends to occur during the sonication process. Always make sure to wipe the probe clean carefully each time. Due to the length of the protocol, take the usual precautions to avoid RNA degradation i.e. use RNase inhibitors, filter tips, and ensure temperatures are kept < 10°C. Lysates should be non-sticky and clear after sonication, which may take several hours. Pauses between sonications should be incorporated to avoid overheating of the sample.

If you are more focused on isolating chromatin, take note that lysis buffer conditions may vary to ensure efficient lysis of nuclei. In this case, swelling buffers may be incorporated and additional lysis steps might be required. Refer Chu et al., 2011.

4. Probe hybridization

The amount of biotinylated probes (raPOOL) should exceed the copy number of target RNA present in the lysate. With a recommended addition of 100 pmol of raPOOL per ml of lysate,

the number of copies of raPOOL =100 x 10^-12 * 6×10^23 (Avogadro’s constant) = 6 x 10^13 copies

and the number of copies of each probe (30 probes/raPOOL) = 6 x 10^13/30 = 2 x 10^12 copies

which is usually more than sufficient. However one can perform the hybridization with a range of probe concentrations to determine the optimal condition. Hybridization temperatures can also be varied with higher temperatures known to increase stringency of probe association.

5. Elution of components

As mentioned before, detection sensitivity is lowest for proteins, hence aliquot the beads in a proportion where most are used for protein analsis with a small proportion for nucleic acid detection. Benzonase is used to remove nucleic acids leaving proteins intact which can then be precipitated with TCA in the presence of deoxycholate. An acetone wash usually follows to remove the deoxycholate. Alternatively, biotin elution can be performed to compete out streptavidin binding sites and release complexes. It is recommended to separate the isolated proteins by PAGE to simplify the sample for MS analysis.

6. How much pulldown is enough?

The efficiency of RNA enrichment is determined by the difference in amounts of target RNA in the pulldown fraction as compared to the input fraction (i.e. lysate post-sonication and prior to probe hybridization). Be sure to account for the fraction of input used in the analysis. For a calculation guide, download this sheet. Fold enrichment is obtained by comparing against a negative/background condition. This may be performed using a negative control raPOOL which targets sequences not found in the cell. Non-target genes such as GAPDH/Cyclophilin A can also be analysed in the pulldown and input conditions to indicate pulldown is specific for the target RNA.

As a guide to how much pulldown is enough, Chu et al. retrieved ~60% of their target RNA and were able to analyse isolated proteins by western blotting and MS. One could also measure target RNA in lysates that have been subjected to pulldown, and a corresponding depletion of the target RNA should be observed.

We hope this helps you in your RAP optimization. For more questions and raPOOL requests, please feel free to email us at info@sitools.de

 

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