Comparison of commercially available whole-genome sequencing kits for variant detection in circulating cell-free DNA

Abstract

circulating cell-free DnA (ccfDnA) has great potential for non-invasive diagnosis, prognosis and monitoring treatment of disease. However, a sensitive and specific whole-genome sequencing (WGS) method is required to identify novel genetic variations (i.e., SnVs, cnVs and inDeLS) on ccfDnA that can be used as clinical biomarkers. In this article, five WGS methods were compared: ThruPLEX Plasma-seq, QIAseq cfDNA All-in-One, NEXTFLEX Cell Free DNA-seq, Accel-NGS 2 S PCR FREE DNA and Accel-NGS 2 S PLUS DNA. The Accel PCR-free kit did not produce enough material for sequencing. The other kits had significant common number of SNVs, INDELs and CNVs and showed similar results for SnVs and cnVs. the detection of variants and genomic signatures depends more upon the type of plasma sample rather than the WGS method used. Accel detected several variants not observed by the other kits. ThruPLEX seemed to identify more low-abundant SNVs and SNV signatures were similar to signatures observed with the QIAseq kit. Accel and NEXTFLEX had similar CNV and SNV signatures. These results demonstrate the importance of establishing a standardized workflow for identifying noninvasive candidate biomarkers. Moreover, the combination of variants discovered in ccfDNA using WGS has the potential to identify enrichment pathways, while the analysis of signatures could identify new subgroups of patients. The analysis of circulating cell-free DNA (ccfDNA) from plasma bears great promise for diagnosis, prognosis and monitoring the treatment of cancer 1. In the context of precision medicine, the identification of novel non-invasive biomarkers is crucial but the analysis of ccfDNA is still a challenge. Indeed, ccfDNA is low concentrated, highly fragmented and the abundance depends on the type and the stage of cancer and the pre-analytical steps 2,3-5. Due to its properties, a complete workflow for sample preparation, library preparation, sequencing and data analysis should be performed to ensure standardization of sample analysis especially in the case of clinical cohorts 4,6,7. Pre-analytical steps including sample collection, storage, processing and extraction were compared to maximize the yield and size of ccfDNA 3,5,8-12. Furthermore, size analysis and quantification methods were used to evaluate the extracted ccfDNA. Sensitive approaches such as quantitative PCR, digital PCR, mass spectrometry and next generation sequencing (NGS) are commonly applied to analyze extracted ccfDNA 2. With the improvement of NGS analysis, whole-genome sequencing (WGS) is a great approach to identify all types of genomic alteration including single nucleotide variant (SNV), insertion and deletion (INDEL), copy number variation (CNV) and structural variant (SV) for the identification of candidate biomarkers in cancer 13. In particular, several specific and sensitive low-coverage sequencing approaches have been applied for the analysis of CNVs from cancer plasma samples 14-20. In addition, recent WGS studies allowed the analysis of nucleosome

A novel genomic DNA library preparation method with low GC bias

“…To assess the utility of the novel protocol for genomic DNA sequencing, we compared its performance to the commercially available kits TruSeq (Illumina) and ThruPLEX (Rubicon Genomics) using plant Arabidopsis thaliana ( A. thaliana ) DNA and fruit fly Drosophila melanogaster ( D. melanogaster ) DNA. These kits have been shown to perform well with low DNA input (Sato et al , 2019; Mauger et al ., 2020) and are popular for WGS or ChIP-Seq analysis.…”

“…For example, very low DNA yields are common in analyses such as chromatin immunoprecipitation (ChIP-seq; commonly performed for epigenomic analyses), degraded DNA from field samples (for example in forensic science, archaeology, and paleontology) (Gansauge and Meyer, 2013; Xavier and Parson, 2017), parasites and microorganisms that cannot be cultured (Nascimento et al ., 2016), viruses (Malboeuf et al ., 2013), very small insects (Cruaud et al , 2019), and metagenomics of environmental samples (Rinke et al , 2014). Low DNA input can also be an issue in single-cell analyses (Harada et al , 2019; Kaya-Okur et al , 2019), analyses using circulating fetal or tumor DNA (Mauger et al , 2020), and clinical studies with formalin-fixed paraffin-embedded tumor tissue samples (Munchel et al ., 2015; Kader et al , 2016; Zhang et al , 2019).…”

“…Nextera kits are also susceptible to the presence of contamination or duplicates (Rinke et al ., 2014), do not detect more variants than lower-cost alternatives (Pasquali et al ., 2019), and the limited control of fragment size can introduce biases (Adey et al ., 2010; Nascimento et al ., 2016). The Rubicon Genomics ThruPLEX kit (Takara Bio) has been shown to have relatively high sensitivity for de novo genome assembly and reliably detects variants in low-input DNA (Chung et al ., 2016; Nascimento et al ., 2016; Mauger et al , 2020) and ChIP-Seq samples (Sundaram et al , 2016).…”

Genomic diversity of Mycobacterium avium subsp. paratuberculosis: pangenomic approach for highlighting unique genomic features with newly constructed complete genomes

“…It is important to examine the genetic diversity of the population for epidemiological analysis or to observe various pathogenic properties. As advances in next-generation sequencing (NGS) methods have been made, it has become easier to obtain genomic information from organisms [ 42 ], which has led to the rise of bioinformatics [ 43 – 45 ]. Comparative genomics is a powerful method to identify genes that cause phenotypic differences and vice versa [ 16 , 39 , 46 ].…”

MAESTRO affords ‘breadth and depth’ for mutation testing

“…To further characterize performance, and explore the feasibility to detect trace levels of ultra-rare mutations via liquid biopsy, we compared MAESTRO to conventional duplex sequencing for tracking 438 mutations in 18 x replicate 1/100k dilutions and 17 x replicate negative control samples. We used sheared genomic DNA from the same two cell lines described in the previous section to mimic cfDNA 8,34,[38][39][40][41][42] and isolated 20 ng for each replicate to reflect the cfDNA in typical 10 mL blood samples. These were intended to model the scenario for which (i) a limited mass of cfDNA fragments is drawn from the bloodstream, and (ii) at sufficiently low tumor fraction such that mutations are sparsely partitioned into each blood tube.…”