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Comparative evaluation of RNA-Seq library preparation methods for strand-specificity and low input.

ABSTRACT: Library preparation is a key step in sequencing. For RNA sequencing there are advantages to both strand specificity and working with minute starting material, yet until recently there was no kit available enabling both. The Illumina TruSeq stranded mRNA Sample Preparation kit (TruSeq) requires abundant starting material while the Takara Bio SMART-Seq v4 Ultra Low Input RNA kit (V4) sacrifices strand specificity. The SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Pico) by Takara Bio claims to overcome these limitations. Comparative evaluation of these kits is important for selecting the appropriate protocol. We compared the three kits in a realistic differential expression analysis. We prepared and sequenced samples from two experimental conditions of biological interest with each of the three kits. We report differences between the kits at the level of differential gene expression; for example, the Pico kit results in 55% fewer differentially expressed genes than TruSeq. Nevertheless, the agreement of the observed enriched pathways suggests that comparable functional results can be obtained. In summary we conclude that the Pico kit sufficiently reproduces the results of the other kits at the level of pathway analysis while providing a combination of options that is not available in the other kits.

SUBMITTER: Sarantopoulou D

PROVIDER: S-EPMC6748930 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Comparative evaluation of RNA-Seq library preparation methods for strand-specificity and low input

Project description:Library preparation is a key step in gene expression quantification. There are considerable advantages to both strand specific sequencing and the ability to sequence samples with very small amounts of starting material. Until recently there was no kit available that allowed both simultaneously. The standard Illumina-TruSeq stranded mRNA Sample Preparation kit requires abundant starting quantity while the Takara Bio-SMART-Seq® v4 Ultra® Low Input RNA kit allows for ultra low starting quantities but sacrifices strand specificity. Recently a kit that can do both, SMARTer® Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian by Takara Bio, has become available. Evaluating the performance and effects of these sample preparation kits is a critical determinant for selecting the appropriate sequencing protocol, but a comprehensive comparison is currently missing. To address this we performed a detailed comparative analysis of sequencing libraries prepared with the three kits. We prepared a set of samples representing two experimental conditions with each kit, allowing for comparison of the kits in a standard realistic differential expression analysis. We find substantial differences in the levels of alignment and differential gene expression. Using differential expression analysis we show that using Pico results in identifying 55% less differentially expressed genes than TruSeq. Nevertheless, using gene pathway enrichment analysis we find similar results for all three kits, indicating that ultimately comparable functional results can be reached.

2019-09-17 | GSE124167 | GEO

Comparative evaluation of RNA-Seq library preparation methods for strand-specificity and low input

Project description:Comparative evaluation of RNA-Seq library preparation methods for strand-specificity and low input

| PRJNA510931 | ENA

Systematic comparative analysis of strand-specific, cost-effective, RNA-seq library preparation methods for low input samples

Project description:Despite the precipitous decline in the cost of genome sequencing over the last few years, library preparation for RNA-seq is still laborious and expensive for high throughput screening for drug discovery. Limited availability of RNA generated by some experimental workflows poses an additional challenge and typically adds to the cost of RNA library preparation. In a search for low cost, automation-compatible RNA library preparation kits that also maintain strand specificity and are amenable to low input RNA quantities, we systematically tested two recent commercial technologies – Swift and Swift Rapid – using the Illumina TruSeq stranded mRNA, the de facto standard workflow for bulk transcriptomics, as our reference. We used the Universal Human Reference RNA (UHRR) (composed of equal quantities of total RNA from 10 human cancer cell lines) to benchmark differential gene expression in these kits, at input quantities ranging between 10 ng to 500 ng. Read quality and alignment metrics revealed high mapping efficiency and uniform read coverage through genes for all samples across all three kits. Normalized read counts between all treatment groups were in high agreement, with pairwise Pearson correlation coefficients >0.97. Compared to the Illumina TruSeq stranded mRNA kit, both Swift RNA library kits are cost effective and offer shorter workflow times enabled by their patented Adaptase technology. Furthermore, the Swift RNA kit allows for a relatively broader (and lower) input range, producing consistent results across diverse samples. The Swift Rapid RNA method is the fastest and most cost effective NGS workflow that is best suited for higher RNA yields, with the exact same RNA input range as the Illumina TruSeq kit. We also found the Swift RNA kit to produce the fewest number of differentially expressed genes and pathways attributable to input mRNA concentration.

2021-02-23 | GSE167300 | GEO

A comparative study of ChIP-seq sequencing library preparation methods.

Project description:BackgroundChIP-seq is the primary technique used to investigate genome-wide protein-DNA interactions. As part of this procedure, immunoprecipitated DNA must undergo "library preparation" to enable subsequent high-throughput sequencing. To facilitate the analysis of biopsy samples and rare cell populations, there has been a recent proliferation of methods allowing sequencing library preparation from low-input DNA amounts. However, little information exists on the relative merits, performance, comparability and biases inherent to these procedures. Notably, recently developed single-cell ChIP procedures employing microfluidics must also employ library preparation reagents to allow downstream sequencing.ResultsIn this study, seven methods designed for low-input DNA/ChIP-seq sample preparation (Accel-NGS® 2S, Bowman-method, HTML-PCR, SeqPlex™, DNA SMART™, TELP and ThruPLEX®) were performed on five replicates of 1 ng and 0.1 ng input H3K4me3 ChIP material, and compared to a "gold standard" reference PCR-free dataset. The performance of each method was examined for the prevalence of unmappable reads, amplification-derived duplicate reads, reproducibility, and for the sensitivity and specificity of peak calling.ConclusionsWe identified consistent high performance in a subset of the tested reagents, which should aid researchers in choosing the most appropriate reagents for their studies. Furthermore, we expect this work to drive future advances by identifying and encouraging use of the most promising methods and reagents. The results may also aid judgements on how comparable are existing datasets that have been prepared with different sample library preparation reagents.

| S-EPMC5073829 | biostudies-literature

Comparison of EM-seq and PBAT methylome library methods for low-input DNA.

Project description:DNA methylation is the most studied epigenetic mark involved in regulation of gene expression. For low input samples, a limited number of methods for quantifying DNA methylation genome-wide has been evaluated. Here, we compared a series of input DNA amounts (1-10ng) from two methylome library preparation protocols, enzymatic methyl-seq (EM-seq) and post-bisulfite adaptor tagging (PBAT) adapted from single-cell PBAT. EM-seq takes advantage of enzymatic activity while PBAT relies on conventional bisulfite conversion for detection of DNA methylation. We found that both methods accurately quantified DNA methylation genome-wide. They produced expected distribution patterns around genomic features, high C-T transition efficiency at non-CpG sites and high correlation between input amounts. However, EM-seq performed better in regard to library and sequencing quality, i.e. EM-seq produced larger insert sizes, higher alignment rates and higher library complexity with lower duplication rate compared to PBAT. Moreover, EM-seq demonstrated higher CpG coverage, better CpG site overlap and higher consistency between input series. In summary, our data suggests that EM-seq overall performed better than PBAT in whole-genome methylation quantification of low input samples.

| S-EPMC9542412 | biostudies-literature

Systematic comparative analysis of strand-specific, cost-effective, RNA-seq library preparation methods for low input samples

Project description:Systematic comparative analysis of strand-specific, cost-effective, RNA-seq library preparation methods for low input samples

| PRJNA704106 | ENA

Evaluation of commercially available small RNASeq library preparation kits using low input RNA.

Project description:BackgroundEvolving interest in comprehensively profiling the full range of small RNAs present in small tissue biopsies and in circulating biofluids, and how the profile differs with disease, has launched small RNA sequencing (RNASeq) into more frequent use. However, known biases associated with small RNASeq, compounded by low RNA inputs, have been both a significant concern and a hurdle to widespread adoption. As RNASeq is becoming a viable choice for the discovery of small RNAs in low input samples and more labs are employing it, there should be benchmark datasets to test and evaluate the performance of new sequencing protocols and operators. In a recent publication from the National Institute of Standards and Technology, Pine et al., 2018, the investigators used a commercially available set of three tissues and tested performance across labs and platforms.ResultsIn this paper, we further tested the performance of low RNA input in three commonly used and commercially available RNASeq library preparation kits; NEB Next, NEXTFlex, and TruSeq small RNA library preparation. We evaluated the performance of the kits at two different sites, using three different tissues (brain, liver, and placenta) with high (1 μg) and low RNA (10 ng) input from tissue samples, or 5.0, 3.0, 2.0, 1.0, 0.5, and 0.2 ml starting volumes of plasma. As there has been a lack of robust validation platforms for differentially expressed miRNAs, we also compared low input RNASeq data with their expression profiles on three different platforms (Abcam Fireplex, HTG EdgeSeq, and Qiagen miRNome).ConclusionsThe concordance of RNASeq results on these three platforms was dependent on the RNA expression level; the higher the expression, the better the reproducibility. The results provide an extensive analysis of small RNASeq kit performance using low RNA input, and replication of these data on three downstream technologies.

| S-EPMC5936030 | biostudies-literature

Systematic assessment of commercially available low-input miRNA library preparation kits

Project description:We compared the performance of six commercial kits (QIAseq, SMARTer, CATS, CleanTag, srLp, TailorMix) capable of handling <100ng total RNA input for miRNA detection sensitivity, reliability, titration response and ability to detect differentially expressed miRNAs at different amounts of synthetic miRNAs. We observed differences in detection sensitivity between the kits, but none were able to detect the full repertoire of expected miRNAs. The reliability within the replicates of all kits was good, while larger differences were observed between the kits, although none could accurately quantify the majority of miRNAs.

2019-09-27 | GSE133719 | GEO

spKAS-seq reveals R-loop dynamics using low-input materials by detecting single-stranded DNA with strand specificity.

Project description:R-loops affect transcription and genome stability. Dysregulation of R-loops is related to human diseases. Genome-wide R-loop mapping typically uses the S9.6 antibody or inactive ribonuclease H, both requiring a large number of cells with varying results observed depending on the approach applied. Here, we present strand-specific kethoxal-assisted single-stranded DNA (ssDNA) sequencing (spKAS-seq) to map R-loops by taking advantage of the presence of a ssDNA in the triplex structure. We show that spKAS-seq detects R-loops and their dynamics at coding sequences, enhancers, and other intergenic regions with as few as 50,000 cells. A joint analysis of R-loops and chromatin-bound RNA binding proteins (RBPs) suggested that R-loops can be RBP binding hotspots on the chromatin.

| S-EPMC9710868 | biostudies-literature

Systematic assessment of commercially available low-input miRNA library preparation kits.

Project description:High-throughput sequencing is increasingly favoured to assay the presence and abundance of microRNAs (miRNAs) in biological samples, even from low RNA amounts, and a number of commercial vendors now offer kits that allow miRNA sequencing from sub-nanogram (ng) inputs. Although biases introduced during library preparation have been documented, the relative performance of current reagent kits has not been investigated in detail. Here, six commercial kits capable of handling <100ng total RNA input were used for library preparation, performed by kit manufactures, on synthetic miRNAs of known quantities and human total RNA samples. We compared the performance of miRNA detection sensitivity, reliability, titration response and the ability to detect differentially expressed miRNAs. In addition, we assessed the use of unique molecular identifiers (UMI) sequence tags in one kit. We observed differences in detection sensitivity and ability to identify differentially expressed miRNAs between the kits, but none were able to detect the full repertoire of synthetic miRNAs. The reliability within the replicates of all kits was good, while larger differences were observed between the kits, although none could accurately quantify the relative levels of the majority of miRNAs. UMI tags, at least within the input ranges tested, offered little advantage to improve data utility. In conclusion, biases in miRNA abundance are heavily influenced by the kit used for library preparation, suggesting that comparisons of datasets prepared by different procedures should be made with caution. This article is intended to assist researchers select the most appropriate kit for their experimental conditions.

| S-EPMC6948978 | biostudies-literature

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