Application of the 3′ mRNA-Seq using unique molecular identifiers in highly degraded RNA derived from formalin-fixed, paraffin-embedded tissue

Background Archival formalin-fixed, paraffin-embedded (FFPE) tissue samples with clinical and histological data are a singularly valuable resource for developing new molecular biomarkers. However, transcriptome analysis remains challenging with standard mRNA-seq methods as FFPE derived-RNA samples are often highly modified and fragmented. The recently developed 3′ mRNA-seq method sequences the 3′ region of mRNA using unique molecular identifiers (UMI), thus generating gene expression data with minimal PCR bias. In this study, we evaluated the performance of 3′ mRNA-Seq using Lexogen QuantSeq 3′ mRNA-Seq Library Prep Kit FWD with UMI, comparing with TruSeq Stranded mRNA-Seq and RNA Exome Capture kit. The fresh-frozen (FF) and FFPE tissues yielded nucleotide sizes range from 13 to > 70% of DV200 values; input amounts ranged from 1 ng to 100 ng for validation. Results The total mapped reads of QuantSeq 3′ mRNA-Seq to the reference genome ranged from 99 to 74% across all samples. After PCR bias correction, 3 to 56% of total sequenced reads were retained. QuantSeq 3′ mRNA-Seq data showed highly reproducible data across replicates in Universal Human Reference RNA (UHR, R > 0.94) at input amounts from 1 ng to 100 ng, and FF and FFPE paired samples (R = 0.92) at 10 ng. Severely degraded FFPE RNA with ≤30% of DV200 value showed good concordance (R > 0.87) with 100 ng input. A moderate correlation was observed when directly comparing QuantSeq 3′ mRNA-Seq data with TruSeq Stranded mRNA-Seq (R = 0.78) and RNA Exome Capture data (R > 0.67). Conclusion In this study, QuantSeq 3′ mRNA-Seq with PCR bias correction using UMI is shown to be a suitable method for gene quantification in both FF and FFPE RNAs. 3′ mRNA-Seq with UMI may be applied to severely degraded RNA from FFPE tissues generating high-quality sequencing data.

Measuring and mitigating PCR bias in microbiota datasets

PCR amplification plays an integral role in the measurement of mixed microbial communities via high-throughput DNA sequencing of the 16S ribosomal RNA (rRNA) gene. Yet PCR is also known to introduce multiple forms of bias in 16S rRNA studies. Here we present a paired modeling and experimental approach to characterize and mitigate PCR NPM-bias (PCR bias from non-primer-mismatch sources) in microbiota surveys. We use experimental data from mock bacterial communities to validate our approach and human gut microbiota samples to characterize PCR NPM-bias under real-world conditions. Our results suggest that PCR NPM-bias can skew estimates of microbial relative abundances by a factor of 4 or more, but that this bias can be mitigated using log-ratio linear models.

Quantitating primer-template interactions using a deconstructed PCR methodology

When the polymerase chain reaction (PCR) is used to amplify simultaneously multiple templates, preferential amplification of certain templates (PCR bias) leads to a distorted representation of the original templates in the final amplicon pool. PCR selection, a type of PCR bias, is influenced by mismatches between primers and templates, the locations of mismatches, and the nucleotide pairing of mismatches. Direct measurement of primer-template interactions has not been possible, leading to uncertainty when attempting to optimize PCR reactions and degenerate primer pools. In this study, we developed an experimental system to systematically study primer-template interactions. We synthesized 10 double-stranded DNA templates with unique priming sites, as well as 64 primers with 0, 1, 2 or 3 mismatches with each of the 10 templates. By using a previously described deconstructed PCR (DePCR) methodology, we generated empirical data showing individual primer interactions with templates in complex template-primer amplification reactions. Standard PCR and DePCR amplification protocols were used to amplify templates in a series of 16 experiments in which templates, primers, and annealing temperature were varied. We observed that although perfect match primer-template interactions are important, the dominant type of interactions are mismatch amplifications, and that mismatched primer annealing and polymerase copying starts immediately during the first two cycle of PCR. In reactions with degenerate primer pools, multiple mismatches between primer and template are tolerated, and these do not have a strong effect on observed template ratios after amplification when employing the DePCR methodology. When employing the DePCR methodology, mismatched primer-template interactions were able to amplify source templates with significantly lower distortion relative to standard PCR. We establish here a quantitative experimental system for interrogating primer-template interactions and demonstrate the efficacy of the DePCR method for amplification of complex template mixtures with complex primer pools.

Quantitating primer-template interactions using a deconstructed PCR methodology

When the polymerase chain reaction (PCR) is used to amplify simultaneously multiple templates, preferential amplification of certain templates (PCR bias) leads to a distorted representation of the original templates in the final amplicon pool. PCR selection, a type of PCR bias, is influenced by mismatches between primers and templates, the locations of mismatches, and the nucleotide pairing of mismatches. Direct measurement of primer-template interactions has not been possible, leading to uncertainty when attempting to optimize PCR reactions and degenerate primer pools. In this study, we developed an experimental system to systematically study primer-template interactions. We synthesized 10 double-stranded DNA templates with unique priming sites, as well as 64 primers with 0, 1, 2 or 3 mismatches with each of the 10 templates. By using a previously described deconstructed PCR (DePCR) methodology, we generated empirical data showing individual primer interactions with templates in complex template-primer amplification reactions. Standard PCR and DePCR amplification protocols were used to amplify templates in a series of 16 experiments in which templates, primers, and annealing temperature were varied. We observed that although perfect match primer-template interactions are important, the dominant type of interactions are mismatch amplifications, and that mismatched primer annealing and polymerase copying starts immediately during the first two cycle of PCR. In reactions with degenerate primer pools, multiple mismatches between primer and template are tolerated, and these do not have a strong effect on observed template ratios after amplification when employing the DePCR methodology. When employing the DePCR methodology, mismatched primer-template interactions were able to amplify source templates with significantly lower distortion relative to standard PCR. We establish here a quantitative experimental system for interrogating primer-template interactions and demonstrate the efficacy of the DePCR method for amplification of complex template mixtures with complex primer pools.

Measuring and Mitigating PCR Bias in Microbiome Data

PCR amplification plays a central role in the measurement of mixed microbial communities via high-throughput sequencing. Yet PCR is also known to be a common source of bias in microbiome data. Here we present a paired modeling and experimental approach to characterize and mitigate PCR bias in microbiome studies. We use experimental data from mock bacterial communities to validate our approach and human gut microbiota samples to characterize PCR bias under real-world conditions. Our results suggest that PCR can bias estimates of microbial relative abundances by a factor of 2-4 but that this bias can be mitigated using simple Bayesian multinomial logistic-normal linear models.Author summaryHigh-throughput sequencing is often used to profile host-associated microbial communities. Many processing steps are required to transform a community of bacteria into a pool of DNA suitable for sequencing. One important step is amplification where, to create enough DNA for sequencing, DNA from many different bacteria are repeatedly copied using a technique called Polymerase Chain Reaction (PCR). However, PCR is known to introduce bias as DNA from some bacteria are more efficiently copied than others. Here we introduce an experimental procedure that allows this bias to be measured and computational techniques that allow this bias to be mitigated in sequencing data.

Targeted genome fragmentation with CRISPR/Cas9 improves hybridization capture, reduces PCR bias, and enables efficient high-accuracy sequencing of small targets

ABSTRACTCurrent next-generation sequencing techniques suffer from inefficient target enrichment and frequent errors. To address these issues, we have developed a targeted genome fragmentation approach based on CRISPR/Cas9 digestion. By designing all fragments to similar lengths, regions of interest can be size-selected prior to library preparation, increasing hybridization capture efficiency. Additionally, homogenous length fragments reduce PCR bias and maximize read usability. We combine this novel target enrichment approach with ultra-accurate Duplex Sequencing. The result, termed CRISPR-DS, is a robust targeted sequencing technique that overcomes the inherent challenges of small target enrichment and enables the detection of ultra-low frequency mutations with small DNA inputs.