scholarly journals Reliable Multiplex Sequencing with Rare Index Mis-Assignment on DNB-Based NGS Platform

2018 ◽  
Author(s):  
Qiaoling Li ◽  
Xia Zhao ◽  
Wenwei Zhang ◽  
Lin Wang ◽  
Jingjing Wang ◽  
...  
Keyword(s):  
Massively Parallel Sequencing ◽  
Massively Parallel ◽  
Rolling Circle Replication ◽  
Linear Amplification ◽  
Preparation Methods ◽  
Rolling Circle ◽  
Quality Issue ◽  
Error Accumulation ◽  
Sequencing Platforms ◽  
Multiplex Sequencing

AbstractBackgroundMassively-parallel-sequencing, coupled with sample multiplexing, has made genetic tests broadly affordable. However, intractable index mis-assignments (commonly exceeds 1%) were repeatedly reported on some widely used sequencing platforms.ResultsHere, we investigated this quality issue on BGI sequencers using three library preparation methods: whole genome sequencing (WGS) with PCR, PCR-free WGS, and two-step targeted PCR. BGI’s sequencers utilize a unique DNB technology which uses rolling circle replication for DNA-nanoball preparation; this linear amplification is PCR free and can avoid error accumulation. We demonstrated that single index mis-assignment from free indexed oligos occurs at a rate of one in 36 million reads, suggesting virtually no index hopping during DNB creation and arraying. Furthermore, the DNB-based NGS libraries have achieved an unprecedentedly low sample-to-sample mis-assignment rate of 0.0001% to 0.0004% under recommended procedures.ConclusionsSingle indexing with DNB technology provides a simple but effective method for sensitive genetic assays with large sample numbers.

scholarly journals CoolMPS™: Advanced massively parallel sequencing using antibodies specific to each natural nucleobase

2020 ◽  
Author(s):  
Snezana Drmanac ◽  
Matthew Callow ◽  
Linsu Chen ◽  
Ping Zhou ◽  
Leon Eckhardt ◽  
...  
Keyword(s):  
Massively Parallel Sequencing ◽  
Low Cost ◽  
Massively Parallel ◽  
Read Length ◽  
Sequencing Error ◽  
Rolling Circle Replication ◽  
Parallel Sequencing ◽  
Rolling Circle ◽  
Comprehensive Health ◽  
Sequence Quality

AbstractMassively parallel sequencing (MPS) on DNA nanoarrays provides billions of reads at relatively low cost and enables a multitude of genomic applications. Further improvement in read length, sequence quality and cost reduction will enable more affordable and accurate comprehensive health monitoring tests. Currently the most efficient MPS uses dye-labeled reversibly terminated nucleotides (RTs) that are expensive to make and challenging to incorporate. Furthermore, a part of the dye-linker (scar) remains on the nucleobase after cleavage and interferes with subsequent sequencing cycles. We describe here the development of a novel MPS chemistry (CoolMPS™) utilizing unlabeled RTs and four natural nucleobase-specific fluorescently labeled antibodies with fast (30 sec) binding. We implemented CoolMPS™ on MGI’s PCR-free DNBSEQ MPS platform using arrays of 200nm DNA nanoballs (DNBs) generated by rolling circle replication and demonstrate 3-fold improvement in signal intensity and elimination of scar interference. Single-end 100-400 base and pair-end 2×150 base reads with high quality were readily generated with low out-of-phase incorporation. Furthermore, DNBs with less than 50 template copies were successfully sequenced by strong-signal CoolMPS™ with 3-times higher accuracy than in standard MPS. CoolMPS™ chemistry based on natural nucleobases has potential to provide longer, more accurate and less expensive MPS reads, including highly accurate “4-color sequencing” on the most efficient dye-crosstalk-free 2-color imagers with an estimated sequencing error rate of 0.00058% (one error in 170,000 base calls) in a proof-of-concept demonstration.

scholarly journals Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms

2017 ◽  
Author(s):  
Maura Costello ◽  
Mark Fleharty ◽  
Justin Abreu ◽  
Yossi Farjoun ◽  
Steven Ferriera ◽  
...  
Keyword(s):  
Best Practices ◽  
Massively Parallel Sequencing ◽  
Massively Parallel ◽  
Preparation Methods ◽  
Multiple Sample ◽  
Cluster Generation ◽  
Sequencing Platforms ◽  
Insight Into ◽  
Swap Rates

ABSTRACTHere, we present an in-depth characterization of the index swapping mechanism on Illumina instruments that employ the ExAmp chemistry for cluster generation (HiSeqX, HiSeq4000, and NovaSeq). We discuss best practices for eliminating the effects of index swapping on data integrity by utilizing unique dual indexing for complete filtering of index swapped reads. We calculate mean swap rates across multiple sample preparation methods and sequencer models, demonstrating that different methods can have vastly different swap rates, and show that even non-ExAmp chemistry instruments display trace levels of index swapping. Finally, using computational methods we provide a greater insight into the mechanism of index swapping.

scholarly journals Comparison of Pre-Analytical FFPE Sample Preparation Methods and Their Impact on Massively Parallel Sequencing in Routine Diagnostics

PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e104566 ◽  
Author(s):  
Carina Heydt ◽  
Jana Fassunke ◽  
Helen Künstlinger ◽  
Michaela Angelika Ihle ◽  
Katharina König ◽  
...  
Keyword(s):  
Sample Preparation ◽  
Massively Parallel Sequencing ◽  
Ffpe Sample ◽  
Massively Parallel ◽  
Preparation Methods ◽  
Routine Diagnostics ◽  
Parallel Sequencing ◽  
Sample Preparation Methods

scholarly journals Visualization tools for human structural variations identified by whole-genome sequencing

2019 ◽  
Vol 65 (1) ◽  
pp. 49-60 ◽  
Author(s):  
Toshiyuki T. Yokoyama ◽  
Masahiro Kasahara
Keyword(s):  
Massively Parallel Sequencing ◽  
Massively Parallel ◽  
Visualization Tool ◽  
Structural Variations ◽  
Long Read ◽  
Comprehensive Survey ◽  
Visualization Tools ◽  
Sequencing Platforms ◽  
Near Future ◽  
Individual Human

Abstract Visualizing structural variations (SVs) is a critical step for finding associations between SVs and human traits or diseases. Given that there are many sequencing platforms used for SV identification and given that how best to visualize SVs together with other data, such as read alignments and annotations, depends on research goals, there are dozens of SV visualization tools designed for different research goals and sequencing platforms. Here, we provide a comprehensive survey of over 30 SV visualization tools to help users choose which tools to use. This review targets users who wish to visualize a set of SVs identified from the massively parallel sequencing reads of an individual human genome. We first categorize the ways in which SV visualization tools display SVs into ten major categories, which we denote as view modules. View modules allow readers to understand the features of each SV visualization tool quickly. Next, we introduce the features of individual SV visualization tools from several aspects, including whether SV views are integrated with annotations, whether long-read alignment is displayed, whether underlying data structures are graph-based, the type of SVs shown, whether auditing is possible, whether bird’s eye view is available, sequencing platforms, and the number of samples. We hope that this review will serve as a guide for readers on the currently available SV visualization tools and lead to the development of new SV visualization tools in the near future.

scholarly journals Robustness of Massively Parallel Sequencing Platforms

PLoS ONE ◽  
2015 ◽  
Vol 10 (9) ◽  
pp. e0138259 ◽  
Author(s):  
Pınar Kavak ◽  
Bayram Yüksel ◽  
Soner Aksu ◽  
M. Oguzhan Kulekci ◽  
Tunga Güngör ◽  
...  
Keyword(s):  
Massively Parallel Sequencing ◽  
Massively Parallel ◽  
Parallel Sequencing ◽  
Sequencing Platforms

scholarly journals Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms

BMC Genomics ◽  
2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Maura Costello ◽  
Mark Fleharty ◽  
Justin Abreu ◽  
Yossi Farjoun ◽  
Steven Ferriera ◽  
...  
Keyword(s):  
Massively Parallel Sequencing ◽  
Massively Parallel ◽  
Parallel Sequencing ◽  
Sequencing Platforms
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