Library Preparation Methods Research Articles

Abstract 2808: cfDNA multi-omics profiling and tissue of origin predictions in cancers of unknown primary

Abstract Cancers of Unknown Primary (CUP) comprise a heterogeneous group of metastatic cancers where the primary site is undetectable. It accounts for 2% of all new UK cancer diagnoses and is the 6th leading cause of cancer death. Favourable subsets of CUP exist, based on clinico-pathological features, and although these patients have improved clinical outcomes, they make up only 20% of patients with CUP. The evolution of molecular profiling and tissue-of-origin (TOO) classifiers has the potential to transform diagnosis and management of patients with CUP. Reliable molecular profiling requires good quality and quantity tumour tissue material, often scarce in patients with CUP. Liquid biopsies offer an alternative, minimally invasive approach. We developed a novel cell-free DNA (cfDNA)-based multi-omics assay combining methylation profiling with mutation and copy number alterations (CNA) detection, to enable TOO prediction and biomarker discovery to aid treatment stratification. Methods: Two novel library preparation methods were applied to 41 CUP cfDNA samples, 80 non-cancer controls and 80 cfDNA samples from known tumour types (breast, lung, colorectal cancer): 1) Targeted (641 gene panel) next generation sequencing (NGS); 2) A multiplex genome-wide methylation capture assay (T7-MBDSeq). Both sequencing outputs can estimate CNA. Cancer Genome Interpreter (CGI) was used to evaluate the potential actionability of molecular alterations detected. A novel TOO classifier, generated utilising in silico dilution mixture sets derived from The Cancer Genome Atlas (TCGA) methylation data, demonstrated an AUROC of 0.96 across 15 different cancer groups. This was applied to cfDNA methylation data from known tumour types to test performance accuracy and subsequently applied to CUP cfDNA samples. Results: Multi-omics profiling from cfDNA was completed for 34/41 patients with CUP. cfDNA mutation profiling and estimated CNA analysis so far revealed >350 alterations across 225 genes. 17/34 (50%) of patients harboured potentially actionable alterations by CGI and, where performed, 68% of tumour mutations were concordant in the cfDNA. cfDNA methylation profiling revealed tumour-specific methylation changes in breast, lung and colorectal cancers. Our preliminary TOO classifier performance in these tumour types had an overall sensitivity and specificity of 85% and 98%, respectively. In patients with CUP, a predicted TOO was made in 26/41 (63%) patients and for 6 patients, where a subsequent primary tumour diagnosis was made, the TOO prediction was correct. Conclusions: cfDNA multi-omics profiling revealed potential therapeutic benefit in 77% of this retrospective CUP cohort and illustrates the potential to re-classify patients to primary tumour types where alternative therapies may improve clinical outcomes. Further multi-omics cfDNA profiling of the CUP cohort and validation in known primary cancer types are ongoing. Citation Format: Alicia-Marie Conway, Alexandra Clipson, Francesca Chemi, Simon Pearce, Katarzyna Kamieniecka, Saba Ferdous, Sophie Richardson, Elaine Kilgour, Matthew G. Krebs, Alastair Kerr, Dominic Rothwell, Natalie Cook, Caroline Dive. cfDNA multi-omics profiling and tissue of origin predictions in cancers of unknown primary [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2808.

Abstract 58: Novel enzymatic fragmentation for challenging samples and methods

Abstract Next Generation Sequencing (NGS) requires fragmentation of DNA molecules upstream of sequencing. Current methods for fragmentation include mechanical shearing and enzymatic fragmentation for NGS library preparation. Mechanical shearing requires costly instruments, can be difficult to automate for high throughput labs, and results in sample loss. In comparison, enzymatic fragmentation methods do not require expensive instruments and are automation friendly. However, current enzymatic fragmentation methods on the market can remove DNA modifications such as methylation, cement DNA damage resulting from formalin fixation in final libraries and can introduce sequencing artifacts or bias. Therefore, while many fragmentation methods are commercially available, challenges remain for sequencing samples such as FFPE DNA or for detecting DNA modification (e.g., 5-methylcytosine). We have developed a novel enzymatic fragmentation method that can be used upstream of library preparation for DNA methylation assessment or FFPE DNA. The novel enzymatic fragmentation method is quick and robust, taking as little as 20 minutes. It is automation-friendly and can be used to generate DNA fragments ranging from as small as 50 bp up to over 1000 bp. Here we demonstrate the use of the novel enzymatic fragmentation method upstream of 5mC library preparation methods. This fragmentation method maintained the methylation marks. These libraries showed improvements in GC bias, library yield, library complexity and other sequencing metrics over libraries generated with mechanically sheared DNA. The use of the novel enzymatic fragmentation method with FFPE DNA library preparation resulted in improvements in sequencing metrics (increased proper pairs, etc.). There was reduced FFPE-damage-derived mutations compared to mechanical shearing or other enzymatic fragmentation methods. Fragmenting DNA to defined sizes for diverse applications and sample types remains a challenging aspect of NGS library preparation. This new, robust enzymatic fragmentation method overcomes the limitations of some traditional mechanical and enzymatic fragmentation methods and improves the library preparation and sequencing for both DNA modification assessment studies and FFPE DNA. Citation Format: Brittany S. Sexton, Maggie Heider, Louise Williams, Bradley Langhorst, Eileen Dimalanta, Lynne Apone. Novel enzymatic fragmentation for challenging samples and methods [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 58.

MET Exon 14 Skipping Mutations: Essential Considerations for Current Management of Non–Small-Cell Lung Cancer

MET Exon 14 Skipping Mutations: Essential Considerations for Current Management of Non–Small-Cell Lung Cancer

A multiplex platform for small RNA sequencing elucidates multifaceted tRNA stress response and translational regulation.

Small RNAs include tRNA, snRNA, micro-RNA, tRNA fragments and others that constitute > 90% of RNA copy numbers in a human cell and perform many essential functions. Popular small RNA-seq strategies limit the insights into coordinated small RNA response to cellular stress. Small RNA-seq also lacks multiplexing capabilities. Here, we report a multiplex small RNA-seq library preparation method (MSR-seq) to investigate cellular small RNA and mRNA response to heat shock, hydrogen peroxide, and arsenite stress. Comparing stress-induced changes of total cellular RNA and polysome-associated RNA, we identify a coordinated tRNA response that involves polysome-specific tRNA abundance and synergistic N3-methylcytosine (m3C) tRNA modification. Combining tRNA and mRNA response to stress we reveal a mechanism of stress-induced down-regulation in translational elongation. We also find that native tRNA molecules lacking several modifications are biased reservoirs for the biogenesis of tRNA fragments. Our results demonstrate the importance of simultaneous investigation of small RNAs and their modifications in response to varying biological conditions.

Enhanced DNA and RNA pathogen detection via metagenomic sequencing in patients with pneumonia

BackgroundMetagenomic next-generation sequencing (mNGS) is an important supplement to conventional tests for pathogen detections of pneumonia. However, mNGS pipelines were limited by irregularities, high proportion of host nucleic acids, and lack of RNA virus detection. Thus, a regulated pipeline based on mNGS for DNA and RNA pathogen detection of pneumonia is essential.MethodsWe performed a retrospective study of 151 patients with pneumonia. Three conventional tests, culture, loop-mediated isothermal amplification (LAMP) and viral quantitative real-time polymerase chain reaction (qPCR) were conducted according to clinical needs, and all samples were detected using our optimized pipeline based on the mNGS (DNA and RNA) method. The performances of mNGS and three other tests were compared. Human DNA depletion was achieved respectively by MolYsis kit and pre-treatment using saponin and Turbo DNase. Three RNA library preparation methods were used to compare the detection performance of RNA viruses.ResultsAn optimized mNGS workflow was built, which had only 1-working-day turnaround time. The proportion of host DNA in the pre-treated samples decreased from 99 to 90% and microbiome reads achieved an approximately 20-fold enrichment compared with those without host removal. Meanwhile, saponin and Turbo DNase pre-treatment exhibited an advantage for DNA virus detection compared with MolYsis. Besides, our in-house RNA library preparation procedure showed a more robust RNA virus detection ability. Combining three conventional methods, 76 (76/151, 50.3%) cases had no clear causative pathogen, but 24 probable pathogens were successfully detected in 31 (31/76 = 40.8%) unclear cases using mNGS. The agreement of the mNGS with the culture, LAMP, and viral qPCR was 60%, 82%, and 80%, respectively. Compared with all conventional tests, mNGS had a sensitivity of 70.4%, a specificity of 72.7%, and an overall agreement of 71.5%.ConclusionsA complete and effective mNGS workflow was built to provide timely DNA and RNA pathogen detection for pneumonia, which could effectively remove the host sequence, had a higher microbial detection rate and a broader spectrum of pathogens (especially for viruses and some pathogens that are difficult to culture). Despite the advantages, there are many challenges in the clinical application of mNGS, and the mNGS report should be interpreted with caution.

Long-read genotyping with SLANG (Simple Long-read loci Assembly of Nanopore data for Genotyping).

PremiseMost phylogenomic library preparation methods and bioinformatic analysis tools in restriction site–associated DNA sequencing (RADseq)/genotyping‐by‐sequencing (GBS) studies are designed for use with Illumina data. The lack of alternative bioinformatic pipelines hinders the exploration of long‐read multi‐locus data from other sequencing platforms. The Simple Long‐read loci Assembly of Nanopore data for Genotyping (SLANG) pipeline enables locus assembly, orthology estimation, and single‐nucleotide polymorphism (SNP) calling using Nanopore‐sequenced multi‐locus data.Methods and ResultsTwo test libraries (Leucanthemum spp., Senecio spp.; Compositae) were prepared using an amplified fragment length polymorphism (AFLP)‐based method to reduce genome complexity, then Nanopore‐sequenced, and analyzed with SLANG. We identified 704 and 448 orthologous loci with 12,368 and 10,048 SNPs, respectively. The constructed phylogenetic networks were identical to a GBS network produced using Leucanthemum Illumina data and were consistent with Senecio species circumscriptions based on morphology.ConclusionsSLANG identifies orthologous loci and extracts SNPs from long‐read multi‐locus Nanopore data for phylogenetic inference, population genetics, or phylogeographical studies. Combined with an AFLP‐based library preparation, SLANG provides an easily scalable, cost‐effective, and affordable alternative to Illumina‐based RADseq/GBS procedures.

A comparison of mRNA sequencing (RNA-Seq) library preparation methods for transcriptome analysis

BackgroundmRNA sequencing is a powerful technique, which is used to investigate the transcriptome status of a gene of interest, such as its transcription level and splicing variants. Presently, several RNA sequencing (RNA-Seq) methods have been developed; however, the relative advantage of each method has remained unknown. Here we used three commercially available RNA-Seq library preparation kits; the traditional method (TruSeq), in addition to full-length double-stranded cDNA methods (SMARTer and TeloPrime) to investigate the advantages and disadvantages of these three approaches in transcriptome analysis.ResultsWe observed that the number of expressed genes detected from the TeloPrime sequencing method was fewer than that obtained using the TruSeq and SMARTer. We also observed that the expression patterns between TruSeq and SMARTer correlated strongly. Alternatively, SMARTer and TeloPrime methods underestimated the expression of relatively long transcripts. Moreover, genes having low expression levels were undetected stochastically regardless of any three methods used. Furthermore, although TeloPrime detected a significantly higher proportion at the transcription start site (TSS), its coverage of the gene body was not uniform. SMARTer is proposed to be yielded for nonspecific genomic DNA amplification. In contrast, the detected splicing event number was highest in the TruSeq. The percent spliced in index (PSI) of the three methods was highly correlated.ConclusionsTruSeq detected transcripts and splicing events better than the other methods and measured expression levels of genes, in addition to splicing events accurately. However, although detected transcripts and splicing events in TeloPrime were fewer, the coverage at TSS was highest. Additionally, SMARTer was better than TeloPrime with regards to the detected number of transcripts and splicing events among the understudied full-length double-stranded cDNA methods. In conclusion, for short-read sequencing, TruSeq has relative advantages for use in transcriptome analysis.

Automation enables high-throughput and reproducible single-cell transcriptomics library preparation.

Next-generation sequencing (NGS) has revolutionized genomics, decreasing sequencing costs and allowing researchers to draw correlations between diseases and DNA or RNA changes. Technical advances have enabled the analysis of RNA expression changes between single cells within a heterogeneous population, known as single-cell RNA-seq (scRNA-seq). Despite resolving transcriptomes of cellular subpopulations, scRNA-seq has not replaced RNA-seq, due to higher costs and longer hands-on time. Here, we developed an automated workflow to increase throughput (up to 48 reactions) and to reduce by 75% the hands-on time of scRNA-seq library preparation, using the 10X Genomics Single Cell 3' kit. After gel bead-in-emulsion (GEM) generation on the 10X Genomics Chromium Controller, cDNA amplification was performed, and the product was normalized and subjected to either the manual, standard library preparation method or a fully automated, walk-away method using a Biomek i7 Hybrid liquid handler. Control metrics showed that both quantity and quality of the single-cell gene expression libraries generated were equivalent in size and yield. Key scRNA-seq downstream quality metrics, such as unique molecular identifiers count, mitochondrial RNA content, and cell and gene counts, further showed high correlations between automated and manual workflows. Using the UMAP dimensionality reduction technique to visualize all cells, we were able to further correlate the results observed between the manual and automated methods (R=0.971). The method developed here allows for the fast, error-free, and reproducible multiplex generation of high-quality single-cell gene expression libraries.

QitanTech Nanopore Long-Read Sequencing Enables Rapid Resolution of Complete Genomes of Multi-Drug Resistant Pathogens.

Advancement of novel sequencing technologies facilitates modern life science and medicine unprecedentedly. Exploring complete genome sequences of bacteria by long-read sequencing technology is significant for microbial genomics research. However, third-generation long-read sequencing technologies are available with limited choices, which generate technological barrier to scientific research. Recently, a novel QitanTech nanopore long-read sequencing technology has emerged in China, but the potential application and performance were unexplored. Herein, we comprehensively evaluated the feasibility of the emerging sequencing technology in assembling complete genomes of MDR pathogens. The results showed that 500 Mbp QitanTech nanopore sequencing data could be generated within 8 h in one flow cell with the standard library preparation method. The mean read length, longest read length, and mean read-level accuracy of QitanTech sequencing data were 6,041 bp, 57,037 bp, and 81.50% (LAST)/81.40% (Minimap2), respectively. Two routine assembly strategies including long-read assembly and hybrid assembly enable the achievement of complete bacterial genomes. The accuracy of assembled draft bacterial genomes with QitanTech long-read data could be improved up to 99.9% dramatically by polishing using accurate short-read data. Furthermore, the assembled bacterial genomes cover accurate structures of complex resistance plasmids harboring critical resistance genes such as tet(X), tmexCD-toprJ, and blaVIM–2, even the complex fusion MDR plasmid generated from homologous recombination. In conclusion, QitanTech nanopore sequencing, as a nanopore long-read sequencing technology launched in China, could be a good option for investigation of complex bacterial genomes. More potential applications based on this novel platform warrant investigations.

Research perspectives-Pipelines to human tendon transcriptomics.

Tendon transcriptomics is a rapidly growing field in musculoskeletal biology. The ultimate aim of many current tendon transcriptomic studies is characterization of in vitro, ex vivo, or in vivo, healthy, and diseased tendon microenvironments to identify the underlying pathways driving human tendon pathology. The transcriptome interfaces between genomic, proteomic, and metabolomic signatures of the tendon cellular niche and the response of this niche to stimuli. Some of the greatest bottlenecks in tendon transcriptomics relate to the availability and quality of human tendon tissue, hence animal tissues are frequently used even though human tissue is most translationally relevant. Here, we review the variability associated with human donor and procurement factors, such as whether the tendon is cadaveric or a clinical remnant, and how these variables affect the quality and relevance of the transcriptomes obtained. Moreover, age, sex, and health demographic variables impact the human tendon transcriptome. Tendons present tissue‐specific challenges for cell, nuclei, and RNA extraction that include a dense extracellular matrix, low cellularity, and therefore low RNA yield of variable quality. Consideration of these factors is particularly important for single‐cell and single‐nuclei resolution transcriptomics due to the necessity for unbiased and representative cell or nuclei populations. Different cell, nuclei, and RNA extraction methods, library preparation, and quality control methods are used by the tendon research community and attention should be paid to these when designing and reporting studies. We discuss the different components and challenges of human tendon transcriptomics, and propose pipelines, quality control, and reporting guidelines for future work in the field.

Protocol variations in run-on transcription dataset preparation produce detectable signatures in sequencing libraries

BackgroundA variety of protocols exist for producing whole genome run-on transcription datasets. However, little is known about how differences between these protocols affect the signal within the resulting libraries.ResultsUsing run-on transcription datasets generated from the same biological system, we show that a variety of GRO- and PRO-seq preparation methods leave identifiable signatures within each library. Specifically we show that the library preparation method results in differences in quality control metrics, as well as differences in the signal distribution at the 5 ′ end of transcribed regions. These shifts lead to disparities in eRNA identification, but do not impact analyses aimed at inferring the key regulators involved in changes to transcription.ConclusionsRun-on sequencing protocol variations result in technical signatures that can be used to identify both the enrichment and library preparation method of a particular data set. These technical signatures are batch effects that limit detailed comparisons of pausing ratios and eRNAs identified across protocols. However, these batch effects have only limited impact on our ability to infer which regulators underlie the observed transcriptional changes.

Automation of high-throughput mRNA-seq library preparation: a robust, hands-free and time efficient methodology.

Over the last decade, whole transcriptome profiling, also known as RNA-sequencing (RNA-seq), has quickly gained traction as a reliable method for unbiased assessment of gene expression. Integration of RNA-seq expression data into other omics datasets (e.g., proteomics, metabolomics, or epigenetics) solidifies our understanding of cell-specific regulatory patterns, yielding pathways to investigate the key rules of gene regulation. A limitation to efficient, at-scale utilization of RNA-seq is the time-demanding library preparation workflows, which is a 2-day or longer endeavor per cohort/sample size. To tackle this bottleneck, we designed an automated workflow that increases throughput capacity, while minimizing human error to enhance reproducibility. To this end, we converted the manual protocol of the NEBNext Directional Ultra II RNA Library Prep Kit for Illumina on the Beckman Coulter liquid handler, Biomek i7 Hybrid workstation. A total of 84 RNA samples were isolated from two human cell lines and subjected to comparative manual and automated library preparation methods. Qualitative and quantitative results indicated a high degree of similarity between libraries generated manually or through automation. Yet, there was a significant reduction in both hands-on and assay time from a 2-day manual to a 9-hour automated workflow. Using linear regression analysis, we found the Pearson correlation coefficient between libraries generated manually or by automation to be almost identical to a sample being sequenced twice (R²= 0.985 vs 0.983). This demonstrates that high-throughput automated workflows can be of great benefit to genomic laboratories by enhancing efficiency of library preparation, reducing hands-on time and increasing throughput potential.

Whole Genome DNA Methylation Profiling of D2 Medium Spiny Neurons in Mouse Nucleus Accumbens Using Two Independent Library Preparation Methods.

DNA methylation plays essential roles in various cellular processes. Next-generation sequencing has enabled us to study the functional implication of DNA methylation across the whole genome. However, this approach usually requires a substantial amount of genomic DNA, which limits its application to defined cell types within a discrete brain region. Here, we applied two separate protocols, Accel-NGS Methyl-Seq (AM-seq) and Enzymatic Methyl-seq (EM-seq), to profile the methylome of D2 dopamine receptor-expressing medium spiny neurons (D2-MSNs) in mouse nucleus accumbens (NAc). Using 40 ng DNA extracted from FACS-isolated D2-MSNs, we found that both methods yielded comparably high-quality methylome data. Additionally, we identified numerous unmethylated regions (UMRs) as cell type-specific regulatory regions. By comparing the NAc D2-MSN methylome with the published methylomes of mouse prefrontal cortex excitatory neurons and neural progenitor cells (NPCs), we identified numerous differentially methylated CpG and non-CpG regions. Our study not only presents a comparison of these two low-input DNA whole genome methylation profiling protocols, but also provides a resource of DNA methylome of mouse accumbal D2-MSNs, a neuron type that has critical roles in addiction and other neuropsychiatric disorders.

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

Despite the recent precipitous decline in the cost of genome sequencing, library preparation for RNA-seq is still laborious and expensive for applications such as high throughput screening. Limited availability of RNA generated by some experimental workflows poses an additional challenge and increases the cost of RNA library preparation. In a search for low cost, automation-compatible RNA library preparation kits that maintain strand specificity and are amenable to low input RNA quantities, we systematically tested two recent commercial technologies—Swift RNA and Swift Rapid RNA, presently offered by Integrated DNA Technologies (IDT) —alongside the Illumina TruSeq stranded mRNA, the de facto standard workflow for bulk transcriptomics. We used the Universal Human Reference RNA (UHRR) (composed of equal quantities of total RNA from 10 human cancer cell lines) to benchmark gene expression in these kits, at input quantities ranging between 10 to 500 ng. We found normalized read counts between all treatment groups to be in high agreement. Compared to the Illumina TruSeq stranded mRNA kit, both Swift RNA library kits offer shorter workflow times enabled by their patented Adaptase technology. We also found the Swift RNA kit to produce the fewest number of differentially expressed genes and pathways directly attributable to input mRNA amount.

Optimization of enzymatic fragmentation is crucial to maximize genome coverage: a comparison of library preparation methods for Illumina sequencing

BackgroundNovel commercial kits for whole genome library preparation for next-generation sequencing on Illumina platforms promise shorter workflows, lower inputs and cost savings. Time savings are achieved by employing enzymatic DNA fragmentation and by combining end-repair and tailing reactions. Fewer cleanup steps also allow greater DNA input flexibility (1 ng-1 μg), PCR-free options from 100 ng DNA, and lower price as compared to the well-established sonication and tagmentation-based DNA library preparation kits.ResultsWe compared the performance of four enzymatic fragmentation-based DNA library preparation kits (from New England Biolabs, Roche, Swift Biosciences and Quantabio) to a tagmentation-based kit (Illumina) using low input DNA amounts (10 ng) and PCR-free reactions with 100 ng DNA. With four technical replicates of each input amount and kit, we compared the kits’ fragmentation sequence-bias as well as performance parameters such as sequence coverage and the clinically relevant detection of single nucleotide and indel variants. While all kits produced high quality sequence data and demonstrated similar performance, several enzymatic fragmentation methods produced library insert sizes which deviated from those intended. Libraries with longer insert lengths performed better in terms of coverage, SNV and indel detection. Lower performance of shorter-insert libraries could be explained by loss of sequence coverage to overlapping paired-end reads, exacerbated by the preferential sequencing of shorter fragments on Illumina sequencers. We also observed that libraries prepared with minimal or no PCR performed best with regard to indel detection.ConclusionsThe enzymatic fragmentation-based DNA library preparation kits from NEB, Roche, Swift and Quantabio are good alternatives to the tagmentation based Nextera DNA flex kit from Illumina, offering reproducible results using flexible DNA inputs, quick workflows and lower prices. Libraries with insert DNA fragments longer than the cumulative sum of both read lengths avoid read overlap, thus produce more informative data that leads to strongly improved genome coverage and consequently also increased sensitivity and precision of SNP and indel detection. In order to best utilize such enzymatic fragmentation reagents, researchers should be prepared to invest time to optimize fragmentation conditions for their particular samples.

Using synthetic chromosome controls to evaluate the sequencing of difficult regions within the human genome

BackgroundNext-generation sequencing (NGS) can identify mutations in the human genome that cause disease and has been widely adopted in clinical diagnosis. However, the human genome contains many polymorphic, low-complexity, and repetitive regions that are difficult to sequence and analyze. Despite their difficulty, these regions include many clinically important sequences that can inform the treatment of human diseases and improve the diagnostic yield of NGS.ResultsTo evaluate the accuracy by which these difficult regions are analyzed with NGS, we built an in silico decoy chromosome, along with corresponding synthetic DNA reference controls, that encode difficult and clinically important human genome regions, including repeats, microsatellites, HLA genes, and immune receptors. These controls provide a known ground-truth reference against which to measure the performance of diverse sequencing technologies, reagents, and bioinformatic tools. Using this approach, we provide a comprehensive evaluation of short- and long-read sequencing instruments, library preparation methods, and software tools and identify the errors and systematic bias that confound our resolution of these remaining difficult regions.ConclusionsThis study provides an analytical validation of diagnosis using NGS in difficult regions of the human genome and highlights the challenges that remain to resolve these difficult regions.

Ancient DNA Methods Improve Forensic DNA Profiling of Korean War and World War II Unknowns.

The integration of massively parallel sequencing (MPS) technology into forensic casework has been of particular benefit to the identification of unknown military service members. However, highly degraded or chemically treated skeletal remains often fail to provide usable DNA profiles, even with sensitive mitochondrial (mt) DNA capture and MPS methods. In parallel, the ancient DNA field has developed workflows specifically for degraded DNA, resulting in the successful recovery of nuclear DNA and mtDNA from skeletal remains as well as sediment over 100,000 years old. In this study we use a set of disinterred skeletal remains from the Korean War and World War II to test if ancient DNA extraction and library preparation methods improve forensic DNA profiling. We identified an ancient DNA extraction protocol that resulted in the recovery of significantly more human mtDNA fragments than protocols previously used in casework. In addition, utilizing single-stranded rather than double-stranded library preparation resulted in increased attainment of reportable mtDNA profiles. This study emphasizes that the combination of ancient DNA extraction and library preparation methods evaluated here increases the success rate of DNA profiling, and likelihood of identifying historical remains.

Circular Chromosome Conformation Capture Sequencing (4C-Seq ) in Primary Adherent Cells.

The three-dimensional structure of the genome is highly organized and is an important aspect of gene regulation. Chromatin interactions can be identified using chromosome conformation capture-based techniques, which rely on proximity ligation. Of these techniques, circular chromosome conformation capture sequencing (4C-seq) is used to identify all chromatin interactions occurring with a single chromosomal location (one versus all). Here we describe a 4C-seq protocol that has been optimized for primary adherent cells, for which the first digestion step is inefficient using standard 4C-seq protocols. It can, however, also be applied to other cell or tissue types. This protocol utilizes a standard DNA library preparation method using a commercial kit, and includes a description of the data processing steps.

Comparison of Two Illumina Whole Transcriptome RNA Sequencing Library Preparation Methods Using Human Cancer FFPE Specimens.

Objective: RNA extraction and library preparation from formalin-fixed, paraffin-embedded (FFPE) samples are crucial pre-analytical steps towards achieving optimal downstream RNA sequencing (RNASeq) results. In this study, we assessed 2 Illumina library preparation methods for RNA-Seq analysis using archived FFPE samples from human cancer indications at 2 independent vendors. Methods: Twenty-five FFPE samples from 5 indications (non-small cell lung cancer, colorectal cancer, renal carcinoma, breast cancer, and hepatocellular carcinoma) were included, covering a wide range of sample storage durations (3-25 years-old), sample qualities, and specimen types (resection vs core needle biopsy). Each sample was processed independently by both vendors. Total RNA was isolated using the Qiagen miRNeasy FFPE kit followed by library construction using either TruSeq Stranded Total RNA library preparation kit with Ribo-Zero Gold, or TruSeq RNA Access library preparation kit. Libraries were normalized to 20 pM and sequenced on an Illumina HiSeq 2500 using V3 chemistry in paired-end mode with a read length of 2 × 50 bp. The data were processed through a standard RNASeq pipeline to produce counts and transcripts per millions for each gene in each sample to compare 2 library kits at 2 different vendors. Results: Our data showed that TruSeq RNA Access libraries yield over 80% exonic reads across different quality samples, indicating higher selectivity of the exome pull down by the capture approach compared to the random priming of the TruSeq Stranded Total kit. The overall QC data for FFPE RNA extraction, library preparation, and sequencing generated by the 2 vendors are comparable, and downstream gene expression quantification results show high concordance as well. With the TruSeq Stranded Total kit, the mean Spearman correlation between vendors was 0.87 and the mean Pearson correlation was 0.76. With the TruSeq RNA Access kit, the mean Spearman correlation between vendors was 0.89 and the mean Pearson correlation was 0.73. Interestingly, examination of the cross-vendor correlations compared to various common QC statistics suggested that library concentration is better correlated with consistency between vendors than is the RNA quantity. Conclusions: Our analyses provide evidence to guide selection of sequencing methods for FFPE samples in which the sample quality may be severely compromised.

Development and extensive analytical validation of deep amplicon sequencing for detecting KRAS and NRAS mutations in metastatic colorectal cancer samples.

The presence of wild-type RAS alleles, as determined by genotyping codons 12, 13, 59, 61, 117, and 146, is a prerequisite for personalized anti-EGFR treatment of metastatic colorectal cancer (mCRC) patients. Here we describe analytical validation of in-house developed massively parallel sequencing technology (MPS) in comparison to the in vitro diagnostics (IVD) certified qPCR method. DNA extracted from FFPE samples from CRC patients (n=703) and reference standards (n=33) were tested for KRAS and NRAS mutations in 6 codons of exons 2, 3, and 4 using deep amplicon sequencing (DAS) on a MiSeq benchtop sequencer (Illumina). Two different amplicon lengths and two different library preparation methods (long-RAS and short-RAS) were tested in order to evaluate their impact on DAS performance. In parallel, identical tumor DNA was tested by the following IVD assays: therascreen KRAS RGQ PCR Kit (Qiagen), cobas® KRAS Mutation Test (Roche Diagnostics), and SNaPshot assay (Thermo Fisher Scientific). Both DAS assays detected all the mutations present in reference standards and external quality control samples, except for the artificially generated KRAS codon 146 mutation. The DAS assays performed sufficient analytical specificity and sensitivity (≥0.95). The use of shorter amplicons prolonged the preparation steps but significantly improved the sequencing success rate of FFPE-derived DNA. RAS mutation frequencies in the Czech CRC patients were similar to previous reports, although rare mutations were also detected. DAS with short amplicons is a good strategy for routine assessment of somatic mutations in low-quality FFPE-derived DNA.