Dataset Information

A low cost and input tailing method of quality control on multiple annealing, and looping-based amplification cycles-based whole-genome amplification products.

ABSTRACT:

Background

Single-cell whole-genome sequencing provides novel insights into the nature of genetic heterogeneity in normal and diseased cells. However, amplification of formalin-fixed tissues with low cell numbers is still problematic and multiple annealing, and looping-based amplification cycles (MALBAC) is a commonly used whole-genome amplification (WGA) method with low cell numbers.

Methods

We developed a low-input tailing method to evaluate the MALBAC-based WGA from sub-nanogram or less quantities of input DNA. The tailing method uses 2100 BioAnalyzer to evaluate the size distribution of MALBAC products, and comparing the tailing with 10380 bp.

Results

Compared with a 22 loci qPCR panel, the tailing method provided a similar WGA evaluation efficiency in 13 samples on one set of study, with lower input, cheaper cost, shorter manual time, and a clear filtering cut off. Later, we demonstrated a strong correlation between tailing size and coverage breadth in another 29 samples on two sets of assays. As a result, the tailing method showed that it could predict whether a sequence breadth achieved 70% or not with 100% accuracy on these three sets of assays. Although further studies are needed, this tailing method is expected to be used as an excellent tool to select high-quality WGA products before library construction.

Conclusions

Our tailing method can provide a new WGA quality test to evaluate the WGA efficiency with 100% accuracy (42/42). Compared with qPCR panel, our tailing method needs lower input, cheaper cost, shorter manual time, a clear filtering cut off, and extendable high throughput as well as the same sensitivity.

SUBMITTER: Chen C

PROVIDER: S-EPMC6818575 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Publications

A low cost and input tailing method of quality control on multiple annealing, and looping-based amplification cycles-based whole-genome amplification products.

Chen Changyue C Li Jing J Wan JueFeng J Lu Yuan Y Zhang Zhen Z Xu ZengHui Z

Journal of clinical laboratory analysis 20181121 3

<h4>Background</h4>Single-cell whole-genome sequencing provides novel insights into the nature of genetic heterogeneity in normal and diseased cells. However, amplification of formalin-fixed tissues with low cell numbers is still problematic and multiple annealing, and looping-based amplification cycles (MALBAC) is a commonly used whole-genome amplification (WGA) method with low cell numbers.<h4>Methods</h4>We developed a low-input tailing method to evaluate the MALBAC-based WGA from sub-nanogra ...[more]

PMID: 30461059

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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.

Dataset Information

A low cost and input tailing method of quality control on multiple annealing, and looping-based amplification cycles-based whole-genome amplification products.

Background

Methods

Results

Conclusions

Publications

A low cost and input tailing method of quality control on multiple annealing, and looping-based amplification cycles-based whole-genome amplification products.

Similar Datasets

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