Blocking Abundant RNA Transcripts by High-Affinity Oligonucleotides during Transcriptome Library Preparation

YRNA Blocking in Human Blood Plasma SamplesSamples and Sample Collection

For the healthy donor experiments, we drew venous blood from an elbow vein of two healthy donors in three EDTA tubes (BD Vacutainer Hemogard Closure Plastic K2-Edta Tube, 10 ml, #367525) using the BD Vacutainer Push blood collection set (21G needle). We collected the blood samples according to the Ethical Committee of Ghent University Hospital approval EC/2017/1207, following the ICH Good Clinical Practice rules, and obtained written informed consents from all donors. We inverted the tubes 5 times and centrifuged within 15 minutes after blood draw (400 g, 20 minutes, room temperature, without brake). Per donor, we pipetted the upper plasma fraction (leaving approximately 0.5 cm plasma above the buffy coat) and pooled in a 15 ml tube. After gently inverting, five aliquots of 220 μl platelet-rich plasma (PRP) were snap-frozen in 1.5 ml LoBind tubes (Eppendorf Protein LoBind microcentrifuge tubes Z666548 - DNA/RNA) in liquid nitrogen and stored at − 80 °C. We centrifuged the remaining plasma (800 g, 10 minutes, room temperature, without brake) and transferred to a new 15 ml tube, leaving approximately 0.5 cm plasma above the separation. Next, we centrifuged this plasma a 3rd time (2500 g, 15 minutes, room temperature, without brake), and transferred it to a 15 ml tube, leaving approximately 0.5 cm above the separation. The resulting platelet-free plasma (PFP) was gently inverted, snap-frozen in five aliquots of 220 μl and stored at − 80 °C. The entire plasma preparation protocol took less than 2 h. We isolated RNA from 200 μl PRP or PFP. For the spike-in RNA titration experiment, the protocol was identical, except for the fact 4 EDTA tubes of 10 ml were used and that the second centrifugation step was different (1500 g, 15 minutes, room temperature, without brake).

For the cancer patient experiment, plasma samples are acquired from ProteoGenex (Inglewood, United States of America) under EC/2017/1515 from Ghent University Hospital. Blood was collected in EDTA vacutainer tubes. After inversion (10 times), we centrifuged the vacutainer tubes at 4 °C for 10 minutes at 1500 g without brakes. The plasma is then transferred into a 15 mL centrifuge tube and centrifuged for a second time for 10 minutes at 1500 g. Finally, the plasma was transferred into cryovials and stored at − 80 °C until shipment. The cancer types included are colorectal cancer (CRC), lung adenocarcinoma (LUAD), and prostate cancer (PRAD).

RNA Isolation and Spike-in Controls

Total RNA was isolated from platelet-free (PFP) and platelet-rich plasma (PRP) using the miRNeasy Serum/Plasma Kit (Qiagen, Hilden, Germany, 217,184). We used 200 μl of plasma as input. For the cancer patient experiment, 2 μl of 1x RC PFP spikes were added to the plasma during isolation. The elution volume was 14 μl, and we added 2 μl of 1x LP PFP spikes (Thermo Fisher). Detailed descriptions of the spike-in controls can be found in the exRNAQC study [50]. From this total volume, we used 5 μl for the library preparation. For the healthy donor experiment, the eluate of multiple parallel extractions was pooled according to the original biofluid type (PRP or PFP) and split into six aliquots of 5 μl to minimize extraction bias. We did not include a gDNA removal step after RNA isolation. The input is volume-based since the RNA concentrations of PFP and PRP are below the limit of quantification.

YRNA LNA Design

The YNRA4 fragment (32 nucleotides) was tiled with 16 bp long complementary nucleotides resulting in 17 possible designs. We mapped the full set of antisense oligonucleotides to the human transcriptome (Ensembl v84) and miRBase. Oligonucleotides with no off-targets when 3 mismatches are allowed were retained. Of the retained LNAs, we chose the oligonucleotide with the highest melting temperature (Tm). The resulting fully modified LNA (ACCCACTACCATCGGA, targeting TCCGATGGTAGTGGGT) has a Tm of 89.9 °C. In addition to the fully LNA-modified oligo, for the same sequence we ordered 2′-O-methyl and 2′-methoxy-ethoxy modified nucleotides and half modified (alternating modified – non-modified nucleotides) oligos at Integrated DNA Technologies. Sequences are available in Supplemental Table 1.

TruSeq Small RNA Library Prep

We used the TruSeq small RNA library prep sequencing kit (Illumina, San Diego, CA, USA) for library preparation according to manufacturing instructions, except for the changes listed below. After adaptor ligation and before the reverse transcription step, 2 μl LNA with a concentration of 0.25 μM (LNA1x) or 2.5 μM (LNA10x) was added to 14 μl of the adaptor-ligated RNA. In the experiments with the cancer patient samples and alternative modifications, only the 0.25 μM (LNA1x) concentration was analyzed as we showed that the 10-fold higher concentration had no added value. As a negative control for LNA blocking (LNA0x), 2 μl of water was added to 14 μl of RNA. Next, we used 6 μl of each sample to start the reverse transcription and continue the library prep. Since the input amounts are low, the number of PCR cycles was set at 16 (the manufacturer recommends 11) during the final PCR step.

Pippin Prep and Sequencing

We performed a size selection for 125–163 bp on all libraries using 3% agarose dye-free marker H cassettes on a Pippin Prep (Sage Science, Beverly, MA, USA). Next, the libraries were purified by precipitation using ethanol and resuspended with 10 mM Tris-HCl buffer (pH 8.0) with Tween 20. After dilution, the libraries were quantified using the KAPA Library Quantification Kit (Roche Diagnostics, Diegem, Belgium, KK4854). Healthy donor samples were sequenced using a NextSeq 500 using the NextSeq 500 High Output Kit v2.5 (75 cycles) (Illumina, San Diego, CA, USA). We loaded the library at a concentration of 2.0 pM with 10% PhiX and obtained a total of 268 M reads. We loaded the cancer patient samples on one lane of a NovaSeq 6000 (Illumina, San Diego, CA, USA) instrument at a concentration of 300 pM with 10% PhiX using the NovaSeq 6000 SP Reagent Kit v1.5 (100 cycles) (Illumina, San Diego, CA, USA) (paired-end, 2 × 50 cycles, only the first read was used for subsequent analysis), resulting in 267 M reads. For the chemical modification comparison experiment, we used one lane of a NovaSeq 6000 SP Reagent Kit v1.5 (100 cycles) (Illumina, San Diego, CA, USA, 20028401) (Illumina, San Diego, CA, USA) (1 × 100 bp), loading 300 pM with 10% PhiX, resulting in a total of 548 M reads.

Quantification Analysis

We used a dedicated in-house small RNA-seq pipeline for the quantification of small RNAs. This pipeline starts with adaptor trimming using Cutadapt (v1.8.1) [51], which discards reads shorter than 15 nt, and those in which no adaptor was found. The reads with a low quality are discarded by using the FASTX-Toolkit (v0.0.14) [52] set at a minimum quality score of 20 in at least 80% of nucleotides. Next, we counted and filtered out reads belonging to our spike-in controls (both RC as LP). The spike reads are subtracted from the FASTA files, and reads are counted. For this comparison, the spike-in controls were not used for correction since the library preparation methods (adding LNA or not) differ. The spike-ins are, however, needed to correct for input concentration variation when all other parameters are equal, as the pooling is performed based on volume. Subsequently, we mapped the reads with Bowtie (v1.1.2) [53], allowing one mismatch. At the end of the pipeline, the mapped reads are annotated by matching the genomic coordinates of each read with genomic locations of miRNAs (obtained from miRBase, v20) and other small RNAs (obtained from UCSC GRCh37/hg19 and Ensembl v84). We submitted the original FASTQ-files and the count tables in EGA (EGAS00001006023). The samples are downsampled to the sequencing depth of the sample with the least number of reads per experiment, or respectively 13 M reads (concentration experiment), 6.5 M reads (modification experiment), and 7 M reads (cancer experiment).

Computational Analysis

We used R (v3.6.0) [54] for further data processing, using the following packages: tidyverse (v1.2.1) [55], biomaRt (v2.40.4) [56, 57], broom (v0.5.2) [58]. For differential expression analysis limma-voom (v3.40.6) [59] was used on a filtered matrix with at least 10 reads per million (RPM) per miRNA over all samples.

Mitochondrial Ribosomal RNA Blocking in Cell LysatesCell Culture and RNA Extraction

We used HEK293T cells that were grown in RPMI 1640 medium with GlutaMAX supplement (Thermo Fisher, Waltham, MA, USA) supplemented with 10% fetal calf serum (Merck, Germany) and were lysed with SingleShot lysis buffer (Bio-Rad, United States of America).

MtRNA LNA Design

From previous experiments, we identified three transcripts without poly(A) tail that are abundant (0.1–2% of all counts) in 3′ end sequencing data of HEK293T cells: MT-RNR1, MT-RNR2, and RNA45S. We visually inspected the RNA sequencing data using IGV_2.7.2 [60] and confirmed the presence of an adenosine-rich region flanking the abundant fragments observed in the sequencing library. For MT-RNR2, two different fragments were associated with an internal poly(A) stretch, contributing to the high number of gene counts. We investigated a design region of about 50 bases overlapping the abundant fragments and used Bowtie (v1.2.3) [53] to map several 16-base-long putative LNA sequences. We retained the oligos with the lowest number of off-target hits. We then checked their binding capacities and biochemical characteristics. Sequences are available in Supplemental Table 1.

LNA Treatment

We combined four different LNA mixes (MT-RNR2_1, MT-RNR2_2, MT-RNR1, and RNA24S) to have a final solution containing each LNA at 25 μM (100x). We mixed 2 μl of LNA to 3 μl of RNA sample. From this solution, we used 2.5 μl as input for the library preparation.

Library Preparation

For the library preparation, we used the QuantSeq 3′ mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, Austria). We performed the ‘low input’ version of the protocol.

Sequencing

We sequenced the libraries using the NovaSeq 6000 SP Reagent Kit v1.5 (100 cycles) (Illumina, San Diego, CA, USA) on a NovaSeq 6000 (Illumina, San Diego, CA, USA) instrument at a concentration of 300 pM with 10% PhiX.

Quantification Analysis

We used BBMap (v38.26) to trim off the poly(A) tails and adapter sequences and to perform quality trimming. Next, all FASTQ files were subsampled to 2,000,000 reads with Seqtk (v1.3) and mapped to the hg38 genome using STAR (v2.6.0). We used SAMtools (v1.9) to count the reads mapping to the LNA-targeted genomic regions. We used htseq-count (v0.11.0) [61] to generate the overall counts. Before initial trimming, before quality trimming, and after quality trimming, we used FastQC (v0.11.9) to investigate the quality of the reads.

Computational Analysis

We used R (v4.1.0) [54] and tidyverse (v1.3.1) [55] and biomaRt (v2.48.3) [56, 57] to analyze and visualize the computationally generated data.

Mitochondrial Ribosomal RNA Blocking in Direct-cDNA Long-Read SequencingCell Culture and Harvesting

We cultured HEK293T cells in RPMI medium supplemented with 10% fetal calf serum to 80% confluence in a T75. The cells were washed with 2 ml versene and incubated with 2 ml of trypsin for 3 minutes at 37 °C. We neutralized the mixture with 8 ml fresh medium. We centrifuged for 5 minutes at 2000 rcf at 4 °C and removed the supernatants. We resuspended the cells in 1 ml of QIAzol and flash-froze the mixture in liquid nitrogen.

RNA Extraction and Quality Control

We extracted RNA using the RNeasy Micro Kit (Qiagen, Hilden, Germany, 217,184) according to the manufacturer’s protocol. We checked the quality of the RNA (RQN = 10) using a Fragment Analyzer (Agilent, United States of America).

LNA Treatment

We combined four different LNA mixes (MT-RNR2_1, MT-RNR2_2, MT-RNR1 and RNA24S) to have a final solution containing each LNA at 25 μM. We then made a 10-fold dilution series to obtain three different LNA solutions: LNA1x (0.25 μM), LNA10x (2.5 μM) and LNA100x (25 μM). For each library preparation, 2 μg of total RNA was mixed with 2 μl of the corresponding LNA dilution. 1 μl of RNase-free water was added to 2 μg of total RNA as a non-treated sample (LNA0x). The samples are placed on ice for 5 minutes.

Library Preparation

We prepared direct-cDNA libraries using the SQK-DCS109 Kit (Oxford Nanopore Technologies, United Kingdom). The exact protocol was followed except for the following changes: the RNA-bead binding steps were performed for 5 minutes on a Hula Mixer and 5 minutes on the bench at room temperature; the RNA elution steps were performed for 5 minutes at 37 °C and 5 minutes on a Hula Mixer at room temperature; and 300 μl of 80% ethanol was used for the beads wash steps.

Oxford Nanopore Sequencing

We sequenced each library using two Flongle Flow Cells (Oxford Nanopore Technologies, United Kingdom) with a MinION Sequencer (Oxford Nanopore Technologies, United Kingdom). Sequencing was either stopped after 24 hours or when no more pores were available.

Quantification Analysis

We basecalled the raw fast5 files using Guppy (v3.5.2) [62] on a GPU. We grouped reads per sample and used Pychopper (v2.3.1) [63] to identify full-length transcripts containing both primer sequences. We mapped the reads with Minimap2 (v2.11) [64] and extracted reads mapping to the target fragment location using SAMtools (v1.11) [65]. We then used NanoComp (v1.12.0) [66] to check the read length and quality of each sample.

Computational Analysis

We used R (v4.1.0) [54] and tidyverse (v1.3.1) [55] and biomaRt (v2.48.3) [56, 57] to analyze and visualize the computationally generated data.

MALAT1 Blocking in Single-Cell 3′ End Sequencing for Peripheral Blood Mononuclear Cells (PBMCs)PBMCs Preparation

We collected whole blood in EDTA tubes. The blood was transferred to Leucosep filtered tubes (Greiner Bio-One) containing 15 ml of Ficoll Paque Plus (Cytiva, Washington, D.C., USA, 17144002) and diluted (1:2) with the same volume of 1X DPBS (Thermo Fisher, Waltham, MA, USA, 14190144). We centrifuged the samples at room temperature for 18 minutes at 800 rcf and extracted the PBMCs from the resulting buffy coat. The extracted PBMCs were centrifuged and washed twice with 1X DPBS (Thermo Fisher, Waltham, MA, USA, 14190144). We took a sample for counting, and assessed the cell viability and concentration with a Neubauer chamber, counting at least two different squares. PBMCs were then resuspended in freezing mix (complete medium (RPMI + 1% pen/strep + 10% FCS) + 10% DMSO) in cryovials with no more than 10 million cells. The vials were stored first at − 80 °C inside a freezing container for 24 h and then at − 150 °C. We thawed the vials just before live-death sorting.

MALAT1 LNA Design

After visually inspecting 3′ end sequencing data from PBMCs using IGV_2.7.2 [60], the optimal design space was identified (Supplemental Fig. 8). We identified two internal poly(A) sequences contributing to the high number of counts. Next, we designed and characterized the best LNA sequences following similar steps as before (see ‘mtRNA LNA design’, but with a length of 18 nucleotides). The sequences are available in Supplemental Table 1.

LNA Treatment

We diluted the LNAs at 125 μM of which 2 μl was used. This concentration is higher than the YRNA experiment, as we expect the total RNA concentration to be higher for this experiment. For the pre-RT blocking, 2 μl of the oligonucleotide mix was added to the master mix (including the RT reagent, template switching oligo, reducing reagent B, and RT enzyme C). The master mix is then combined with the cell suspension to a total volume of 80 μl. For the pre-cDNA amplification blocking, we added 2 μl of the oligonucleotide mix to the cDNA amplification mix (including Amp Mix and cDNA primers).

Library Preparation

Sorted single-cell suspensions were resuspended in PBS + 0.04% BSA at an estimated final concentration of 1000 cells/μl and loaded on a Chromium GemCode Single Cell Instrument (10x Genomics, Pleasonton, CA, USA, 1000204), Chip G (10x Genomics, Pleasonton, CA, USA, #2000177) to generate single-cell gel beads-in-emulsion (GEM). We prepared the scRNA-seq libraries using the GemCode Single Cell 3′ Gel Bead and Library kit, version NextGEM 3.1 (10x Genomics, Pleasonton, CA, USA, PN-1000121) according to the manufacturer’s instructions.

Sequencing

The Chromium libraries were equimolarly pooled and loaded on a NovaSeq 6000 (Illumina, San Diego, CA, USA) instrument in standard mode with a final loading concentration of 340 pM and 2% PhiX. We obtained a total of 952 M reads with q30 of 91.32% with an SP100 cycles (Illumina, San Diego, CA, USA, 20028401) kit. The number of (pre-filtered) cells per experiment were highly comparable, 13,841 cells for the noLNA sample, 13,279 cells pre-RT, and 13,893 cells post-RT. The FASTQ files were subsampled based on the number of cells to obtain a comparable number of reads/cell over all samples.

Quantification Analysis

Demultiplexing of the bcl files was performed with cellranger mkfastq (v6.0.1), after which gene counts per cell were obtained with cellranger count (v6.0.1).

Computational Analysis

The count matrixes were loaded into R (v4.1.0) [54] and further processed, including the integration and annotation, with Seurat (v4.0.3) [67]. We did not filter the cells. We analyzed and visualized the data using tidyverse (v1.2.1) [55].

LNA Blocking Simulation in Whole Blood 3′-End SequencingData Download

We downloaded one of the whole blood 3′-end RNA sequencing (QuantSeq) samples generated by Uellendahl-Werth et al. [68] (SRR11028518). This sample had a sequencing depth of 18,043,131 reads.

Quantification Analysis

We used BBMap (v38.26) to trim off the poly(A) tails and adapter sequences and to perform quality trimming. Next, we mapped the trimmed reads to the hg38 genome using STAR (v2.6.0). We used htseq-count (v0.11.0) [61] to quantify the uniquely mapped reads. We used FastQC (v0.11.9) to investigate the quality of the reads before quality trimming and after quality trimming.

Depletion Simulations

All simulations were run using R (4.1.0). First, we generated the sampling distribution by first removing the ENSG00000244734 (HBB) reads and calculating the fraction of reads appointed to each gene relative to the total amount of reads. We used this distribution to guide the subsampling. We then subsampled the count tables for a varying total number of counts (0.5 M, 1 M, 2 M, 4 M, 8 M), initial HBB abundance (0–90%, by 10% increments), and percentage of depletion (0–100%, by 2% increments). Last, we calculated the number of genes with 10 counts or larger. Finally, we analyzed and visualized (v1.2.1) [55].

Resource List

1X DPBS (Thermo Fisher, Waltham, MA, USA, 14190144).

RPMI 1640 medium with GlutaMAX supplement (Thermo Fisher, Waltham, MA, USA, 61870010

10% Fetal calf serum (Merck, Germany, F0804-500ML)

Chromium GemCode Single Cell Instrument (10x Genomics, Pleasonton, CA, USA, 1000204)

Direct cDNA sequencing kit (Oxford Nanopore Technologies, UK, SQK-DCS109)

Eppendorf Protein LoBind microcentrifuge tubes (Eppendorf, Hamburg, Germany, Z666548)

Ficoll Paque Plus (Cytiva, Washington, D.C., USA, 17144002

Flongle Flow cell (Oxford Nanopore Technologies, UK, FLO-FLG001)

Fragment Analyzer RNA Kit (Agilent, USA, DNF-471-0500)

GemCode Chip G (10x Genomics, Pleasonton, CA, USA, 2000177)

GemCode Single Cell 3′ Gel Bead and Library kit, version NextGEM 3.1 (10x Genomics, Pleasonton, CA, USA, PN-1000121)

KAPA Library Quantification Kit (Roche Diagnostics, Diegem, Belgium, KK4854)

MinION sequencer (Oxford Nanopore Technologies, UK, MIN-101B)

miRNeasy Serum/Plasma Kit (Qiagen, Hilden, Germany, 217,184).

NextSeq 500 High Output Kit v2.5 (75 cycles) (Illumina, San Diego, CA, USA, 20024906)

NextSeq 500 Sequencing System (Illumina, San Diego, CA, USA, SY-415-1001)

NovaSeq 6000 Sequencing System (Illumina, San Diego, CA, USA, 20012850)

NovaSeq 6000 SP Reagent Kit v1.5 (100 cycles) (Illumina, San Diego, CA, USA, 20028401)

Pippin Prep (Sage Science, Beverly, MA, USA, PIP0001).

QuantSeq 3′ mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, Austria, 139.96)

RNeasy Micro Kit (Qiagen, Hilden, Germany, 217,184)

SingleShot lysis buffer (Bio-Rad, United States of America, 1,725,080)

TruSeq small RNA library prep sequencing kit (Illumina, San Diego, CA, USA, RS-200)

Vacutainer Hemogard Closure Plastic K2-Edta Tube, 10 ml, (BD, Franklin Lakes, NJ, USA, 367525)

Vacutainer Push blood collection set (BD, Franklin Lakes, NJ, USA, 368657)

HEK293T (ATCC, Manassas, VA, USA)

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