Comparison of single cell sequencing data between two whole genome amplification methods on two sequencing platforms.
ABSTRACT: Research based on a strategy of single-cell low-coverage whole genome sequencing (SLWGS) has enabled better reproducibility and accuracy for detection of copy number variations (CNVs). The whole genome amplification (WGA) method and sequencing platform are critical factors for successful SLWGS (<0.1?×?coverage). In this study, we compared single cell and multiple cells sequencing data produced by the HiSeq2000 and Ion Proton platforms using two WGA kits and then comprehensively evaluated the GC-bias, reproducibility, uniformity and CNV detection among different experimental combinations. Our analysis demonstrated that the PicoPLEX WGA Kit resulted in higher reproducibility, lower sequencing error frequency but more GC-bias than the GenomePlex Single Cell WGA Kit (WGA4 kit) independent of the cell number on the HiSeq2000 platform. While on the Ion Proton platform, the WGA4 kit (both single cell and multiple cells) had higher uniformity and less GC-bias but lower reproducibility than those of the PicoPLEX WGA Kit. Moreover, on these two sequencing platforms, depending on cell number, the performance of the two WGA kits was different for both sensitivity and specificity on CNV detection. The results can help researchers who plan to use SLWGS on single or multiple cells to select appropriate experimental conditions for their applications.
Project description:With the development and clinical application of genomics, more and more concern is focused on single-cell sequencing. In the process of single-cell sequencing, whole genome amplification is a key step to enrich sample DNA. Previous studies have compared the performance of different whole genome amplification (WGA) strategies on Illumina sequencing platforms, but there is no related research aimed at Ion Proton platform, which is also a popular next-generation sequencing platform. Here by amplifying cells from six cell lines with different karyotypes, we estimated the data features of four common commercial WGA kits (PicoPLEX WGA Kit, GenomePlex Single Cell Whole Genome Amplification Kit, MALBAC Single Cell Whole Genome Amplification Kit, and REPLI-g Single Cell Kit), including median absolute pairwise difference, uniformity, reproducibility, and fidelity, and examined their performance of copy number variation detection. The results showed that both MALBAC and PicoPLEX could yield high-quality data and had high reproducibility and fidelity; and as for uniformity, PicoPLEX was slightly superior to MALBAC.
Project description:Single-cell sequencing is emerging as an important tool for studies of genomic heterogeneity. Whole genome amplification (WGA) is a key step in single-cell sequencing workflows and a multitude of methods have been introduced. Here, we compare three state-of-the-art methods on both bulk and single-cell samples of E. coli DNA: Multiple Displacement Amplification (MDA), Multiple Annealing and Looping Based Amplification Cycles (MALBAC), and the PicoPLEX single-cell WGA kit (NEB-WGA). We considered the effects of reaction gain on coverage uniformity, error rates and the level of background contamination. We compared the suitability of the different WGA methods for the detection of copy-number variations, for the detection of single-nucleotide polymorphisms and for de-novo genome assembly. No single method performed best across all criteria and significant differences in characteristics were observed; the choice of which amplifier to use will depend strongly on the details of the type of question being asked in any given experiment.
Project description:Whole genome amplification (WGA) is required for single cell genotyping. Effectiveness of currently available WGA technologies in combination with next generation sequencing (NGS) and material preservation is still elusive.In respect to the accuracy of SNP/mutation, indel, and copy number aberrations (CNA) calling, the HiSeq2000 platform outperformed IonProton in all aspects. Furthermore, more accurate SNP/mutation and indel calling was demonstrated using single tumor cells obtained from EDTA-collected blood in respect to CellSave-preserved blood, whereas CNA analysis in our study was not detectably affected by fixation. Although MDA-based WGA yielded the highest DNA amount, DNA quality was not adequate for downstream analysis. PCR-based WGA demonstrates superiority over MDA-PCR combining technique for SNP and indel analysis in single cells. However, SNP calling performance of MDA-PCR WGA improves with increasing amount of input DNA, whereas CNA analysis does not. The performance of PCR-based WGA did not significantly improve with increase of input material. CNA profiles of single cells, amplified with MDA-PCR technique and sequenced on both HiSeq2000 and IonProton platforms, resembled unamplified DNA the most.We analyzed the performance of PCR-based, multiple-displacement amplification (MDA)-based, and MDA-PCR combining WGA techniques (WGA kits Ampli1, REPLI-g, and PicoPlex, respectively) on single and pooled tumor cells obtained from EDTA- and CellSave-preserved blood and archival material. Amplified DNA underwent exome-Seq with the Illumina HiSeq2000 and ThermoFisher IonProton platforms.We demonstrate the feasibility of single cell genotyping of differently preserved material, nevertheless, WGA and NGS approaches have to be chosen carefully depending on the study aims.
Project description:Whole genome amplification (WGA) has become an invaluable tool to perform copy number variation (CNV) detection in single, or a limited number of cells. Unfortunately, current WGA methods introduce representation bias that limits the detection of small CNVs. New WGA methods have been introduced that might have the potential to reduce this bias. We compared the performance of PicoPLEX DNA-Seq (Picoseq), DOPlify, REPLI-g and Ampli-1 WGA for aneuploidy screening and copy number analysis using shallow whole genome massively parallel sequencing (MPS), starting from single or a limited number of cells. Although the four WGA methods perform differently, they are all suited for this application.
Project description:Single-cell genomic analysis has grown rapidly in recent years and finds widespread applications in various fields of biology, including cancer biology, development, immunology, pre-implantation genetic diagnosis, and neurobiology. To date, the amplification bias, amplification uniformity and reproducibility of the three major single cell whole genome amplification methods (GenomePlex WGA4, MDA and MALBAC) have not been systematically investigated using mammalian cells. In this study, we amplified genomic DNA from individual hippocampal neurons using three single-cell DNA amplification methods, and sequenced them at shallow depth. We then systematically evaluated the GC-bias, reproducibility, and copy number variations among individual neurons. Our results showed that single-cell genome sequencing results obtained from the MALBAC and WGA4 methods are highly reproducible and have a high success rate. The MALBAC displays significant biases towards high GC content. We then attempted to correct the GC bias issue by developing a bioinformatics pipeline, which allows us to call CNVs in single cell sequencing data, and chromosome level and sub-chromosomal level CNVs among individual neurons can be detected. We also proposed a metric to determine the CNV detection limits. Overall, MALBAC and WGA4 have better performance than MDA in detecting CNVs.
Project description:Here, we report a pilot study paving the way for further single cell genomics studies in Leishmania. First, the performances of two commercially available kits for Whole Genome Amplification (WGA), PicoPLEX and RepliG were compared on small amounts of Leishmania donovani DNA, testing their ability to preserve specific genetic variations, including aneuploidy levels and SNPs. We show here that the choice of WGA method should be determined by the planned downstream genetic analysis, PicoPLEX and RepliG performing better for aneuploidy and SNP calling, respectively. This comparison allowed us to evaluate and optimize corresponding bio-informatic methods. As PicoPLEX was shown to be the preferred method for studying single cell aneuploidy, this method was applied in a second step, on single cells of L. braziliensis, which were sorted by fluorescence activated cell sorting (FACS). Even sequencing depth was achieved in 28 single cells, allowing accurate somy estimation. A dominant karyotype with three aneuploid chromosomes was observed in 25 cells, while two different minor karyotypes were observed in the other cells. Our method thus allowed the detection of aneuploidy mosaicism, and provides a solid basis which can be further refined to concur with higher-throughput single cell genomic methods.
Project description:Sequencing analysis of circulating tumor cells (CTCs) enables "liquid biopsy" to guide precision oncology strategies. However, this requires low-template whole genome amplification (WGA) that is prone to errors and biases from uneven amplifications. Currently, quality control (QC) methods for WGA products, as well as the number of CTCs needed for reliable downstream sequencing, remain poorly defined. We sought to define strategies for selecting and generating optimal WGA products from low-template input as it relates to their potential applications in precision oncology strategies.Single pancreatic cancer cells (HPAF-II) were isolated using laser microdissection. WGA was performed using multiple displacement amplification (MDA), multiple annealing and looping based amplification (MALBAC) and PicoPLEX. Quality of amplified DNA products were assessed using a multiplex/RT-qPCR based method that evaluates for 8-cancer related genes and QC-scores were assigned. We utilized this scoring system to assess the impact of de novo modifications to the WGA protocol. WGA products were subjected to Sanger sequencing, array comparative genomic hybridization (aCGH) and next generation sequencing (NGS) to evaluate their performances in respective downstream analyses providing validation of the QC-score.Single-cell WGA products exhibited a significant sample-to-sample variability in amplified DNA quality as assessed by our 8-gene QC assay. Single-cell WGA products that passed the pre-analysis QC had lower amplification bias and improved aCGH/NGS performance metrics when compared to single-cell WGA products that failed the QC. Increasing the number of cellular input resulted in improved QC-scores overall, but a resultant WGA product that consistently passed the QC step required a starting cellular input of at least 20-cells. Our modified-WGA protocol effectively reduced this number, achieving reproducible high-quality WGA products from ?5-cells as a starting template. A starting cellular input of 5 to 10-cells amplified using the modified-WGA achieved aCGH and NGS results that closely matched that of unamplified, batch genomic DNA.The modified-WGA protocol coupled with the 8-gene QC serve as an effective strategy to enhance the quality of low-template WGA reactions. Furthermore, a threshold number of 5-10 cells are likely needed for a reliable WGA reaction and product with high fidelity to the original starting template.
Project description:Starting from only a few cells, current whole genome amplification (WGA) methods provide enough DNA to perform massively parallel sequencing (MPS). Unfortunately, all current WGA methods introduce representation bias which limits detection of copy number aberrations (CNAs) smaller than 3?Mb. A recent WGA method, called TruePrime single cell WGA, uses a recently discovered DNA primase, TthPrimPol, instead of artificial primers to initiate DNA amplification. This method could lead to a lower representation bias, and consequently to a better detection of CNAs. The enzyme requires no complementarity and thus should generate random primers, equally distributed across the genome. The performance of TruePrime WGA was assessed for aneuploidy screening and CNA analysis after MPS, starting from 1, 3 or 5 cells. Although the method looks promising, the single cell TruePrime WGA kit v1 is not suited for high resolution CNA detection after MPS because too much representation bias is introduced.
Project description:The growing interest in liquid biopsies for cancer research and cell-based non-invasive prenatal testing (NIPT) invigorates the need for improved single cell analysis. In these applications, target cells are extremely rare and fragile in peripheral circulation, which makes the genetic analysis very challenging. To overcome these challenges, cell stabilization and unbiased whole genome amplification are required. This study investigates the performance of four WGA methods on single or a limited number of cells after 24?hour of Streck Cell-Free DNA BCT preservation. The suitability of the DNA, amplified with Ampli1, DOPlify, PicoPLEX and REPLI-g, was assessed for both short tandem repeat (STR) profiling and copy number variant (CNV) analysis after shallow whole genome massively parallel sequencing (MPS). Results demonstrate that Ampli1, DOPlify and PicoPLEX perform well for both applications, with some differences between the methods. Samples amplified with REPLI-g did not result in suitable STR or CNV profiles, indicating that this WGA method is not able to generate high quality DNA after Streck Cell-Free DNA BCT stabilization of the cells.
Project description:<h4>Background</h4>Whole genome amplification (WGA) is currently a prerequisite for single cell whole genome or exome sequencing. Depending on the method used the rate of artifact formation, allelic dropout and sequence coverage over the genome may differ significantly.<h4>Results</h4>The largest difference between the evaluated protocols was observed when analyzing the target coverage and read depth distribution. These differences also had impact on the downstream variant calling. Conclusively, the products from the AMPLI1 and MALBAC kits were shown to be most similar to the bulk samples and are therefore recommended for WGA of single cells.<h4>Discussion</h4>In this study four commercial kits for WGA (AMPLI1, MALBAC, Repli-G and PicoPlex) were used to amplify human single cells. The WGA products were exome sequenced together with non-amplified bulk samples from the same source. The resulting data was evaluated in terms of genomic coverage, allelic dropout and SNP calling.