Base-Calling for Bioinformaticians

Abstract Most quantitative geneticists are traditionally trained for data analysis in genetic evaluation and genomic prediction, but rarely have extensive knowledge of molecular genetics or experience in experimental labs. Recent products, such as those launched by Oxford Nanopore Technologies (ONT), give those quantitative geneticists a comprehensible and hands-on toolkit to explore DNA sequencing. The ‘MinION’, a small DNA sequencer, is of interest for quantitative geneticists due to both the minimal learning curve and the non-proprietary USB connectivity. This device is small enough to be portable, allowing for potential real-time, on-farm sequencing. The objective of this project is to compare the whole genome sequence (WGS) output of the MinION sequencer to that of the Illumina HiSeq 4000. Blood was collected from a 6-month-old Akaushi calf born on a Michigan State University farm. DNA was extracted from the sample using the QIAamp DNA Blood Kit from Qiagen, and library DNA ligation preparation (SQK-LSK109) from ONT was used. After base-calling with guppy software (provided by ONT), the data were preprocessed and experimental runs with the MinION were compared using quality control. Finally, the data were aligned with guppy software, and was compared to the aligned WGS obtained with Illumina HiSeq. Quality results from each MinION indicate that, despite the low amount of sequence collected in each run (~225,303 reads per run), the quality of bases sequenced was high (Q≥7). The aligned data from the Illumina sequencer provided 40x coverage of the genome, with a total of 739,339,742 reads. Although the amount of data obtained with MinION is much smaller than that of Illumina HiSeq, the high quality of MinION’s data combined with its ease of use give an opportunity of genomic sequencing for users who are either inexperienced or do not have access to large genomic sequencing devices.

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Manganese citrate improves base-calling accuracy in DNA sequencing reactions using rhodamine-based fluorescent dye-terminators

Nucleic Acids Research ◽

10.1093/nar/27.5.1405 ◽

1999 ◽

Vol 27 (5) ◽

pp. 1405-1407 ◽

Cited By ~ 5

Author(s):

C Korch

Keyword(s):

Dna Sequencing ◽

Fluorescent Dye ◽

Base Calling ◽

Dye Terminators

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naiveBayesCall: An Efficient Model-Based Base-Calling Algorithm for High-Throughput Sequencing

Lecture Notes in Computer Science - Research in Computational Molecular Biology ◽

10.1007/978-3-642-12683-3_15 ◽

2010 ◽

pp. 233-247 ◽

Cited By ~ 5

Author(s):

Wei-Chun Kao ◽

Yun S. Song

Keyword(s):

High Throughput ◽

High Throughput Sequencing ◽

Base Calling ◽

Model Based ◽

Calling Algorithm

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NanoSatellite: accurate characterization of expanded tandem repeat length and sequence through whole genome long-read sequencing on PromethION

Genome Biology ◽

10.1186/s13059-019-1856-3 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 10

Author(s):

Arne De Roeck ◽

Wouter De Coster ◽

Liene Bossaerts ◽

Rita Cacace ◽

Tim De Pooter ◽

...

Keyword(s):

Tandem Repeat ◽

Large Scale ◽

Tandem Repeats ◽

Current Data ◽

Flip Flop ◽

Base Calling ◽

Oxford Nanopore ◽

Long Read ◽

Technological Limitations ◽

Repeat Assessment

AbstractTechnological limitations have hindered the large-scale genetic investigation of tandem repeats in disease. We show that long-read sequencing with a single Oxford Nanopore Technologies PromethION flow cell per individual achieves 30× human genome coverage and enables accurate assessment of tandem repeats including the 10,000-bp Alzheimer’s disease-associated ABCA7 VNTR. The Guppy “flip-flop” base caller and tandem-genotypes tandem repeat caller are efficient for large-scale tandem repeat assessment, but base calling and alignment challenges persist. We present NanoSatellite, which analyzes tandem repeats directly on electric current data and improves calling of GC-rich tandem repeats, expanded alleles, and motif interruptions.

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Nanopore device-based fingerprinting of RNA oligos and microRNAs enhanced with an Osmium tag

Scientific Reports ◽

10.1038/s41598-019-50459-8 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 3

Author(s):

Madiha Sultan ◽

Anastassia Kanavarioti

Keyword(s):

Solid State ◽

Nucleotide Sequence ◽

Nucleic Acids ◽

Rna Sequencing ◽

Single Molecule ◽

Selective Labeling ◽

Base Calling ◽

Alpha Hemolysin ◽

Oxford Nanopore ◽

Single Molecule Analysis

Abstract Protein and solid-state nanopores are used for DNA/RNA sequencing as well as for single molecule analysis. We proposed that selective labeling/tagging may improve base-to-base resolution of nucleic acids via nanopores. We have explored one specific tag, the Osmium tetroxide 2,2′-bipyridine (OsBp), which conjugates to pyrimidines and leaves purines intact. Earlier reports using OsBp-tagged oligodeoxyribonucleotides demonstrated proof-of-principle during unassisted voltage-driven translocation via either alpha-Hemolysin or a solid-state nanopore. Here we extend this work to RNA oligos and a third nanopore by employing the MinION, a commercially available device from Oxford Nanopore Technologies (ONT). Conductance measurements demonstrate that the MinION visibly discriminates oligoriboadenylates with sequence A15PyA15, where Py is an OsBp-tagged pyrimidine. Such resolution rivals traditional chromatography, suggesting that nanopore devices could be exploited for the characterization of RNA oligos and microRNAs enhanced by selective labeling. The data also reveal marked discrimination between a single pyrimidine and two consecutive pyrimidines in OsBp-tagged AnPyAn and AnPyPyAn. This observation leads to the conjecture that the MinION/OsBp platform senses a 2-nucleotide sequence, in contrast to the reported 5-nucleotide sequence with native nucleic acids. Such improvement in sensing, enabled by the presence of OsBp, may enhance base-calling accuracy in enzyme-assisted DNA/RNA sequencing.

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From Sequence Data to Patient Result: A Solution for HIV Drug Resistance Genotyping With Exatype, End to End Software for Pol-HIV-1 Sanger Based Sequence Analysis and Patient HIV Drug Resistance Result Generation

Journal of the International Association of Providers of AIDS Care (JIAPAC) ◽

10.1177/2325958220962687 ◽

2020 ◽

Vol 19 ◽

pp. 232595822096268

Author(s):

Leonard Kingwara ◽

Muthoni Karanja ◽

Catherine Ngugi ◽

Geoffrey Kangogo ◽

Kipkerich Bera ◽

...

Keyword(s):

Drug Resistance ◽

Sequence Analysis ◽

Standard Method ◽

Sequence Data ◽

Scale Up ◽

Reference Laboratory ◽

Hiv Viral Load ◽

Hiv Drug Resistance ◽

Base Calling ◽

Hands On

Introduction: With the rapid scale-up of antiretroviral therapy (ART) to treat HIV infection, there are ongoing concerns regarding probable emergence and transmission of HIV drug resistance (HIVDR) mutations. This scale-up has to lead to an increased need for routine HIVDR testing to inform the clinical decision on a regimen switch. Although the majority of wet laboratory processes are standardized, slow, labor-intensive data transfer and subjective manual sequence interpretation steps are still required to finalize and release patient results. We thus set out to validate the applicability of a software package to generate HIVDR patient results from raw sequence data independently. Methods: We assessed the performance characteristics of Hyrax Bioscience’s Exatype (a sequence data to patient result, fully automated sequence analysis software, which consolidates RECall, MEGA X and the Stanford HIV database) against the standard method (RECall and Stanford database). Exatype is a web-based HIV Drug resistance bioinformatic pipeline available at sanger. exatype.com . To validate the exatype, we used a test set of 135 remnant HIV viral load samples at the National HIV Reference Laboratory (NHRL). Result: We analyzed, and successfully generated results of 126 sequences out of 135 specimens by both Standard and Exatype software. Result production using Exatype required minimal hands-on time in comparison to the Standard (6 computation-hours using the standard method versus 1.5 Exatype computation-hours). Concordance between the 2 systems was 99.8% for 311,227 bases compared. 99.7% of the 0.2% discordant bases, were attributed to nucleotide mixtures as a result of the sequence editing in Recall. Both methods identified similar (99.1%) critical antiretroviral resistance-associated mutations resulting in a 99.2% concordance of resistance susceptibility interpretations. The Base-calling comparison between the 2 methods had Cohen’s kappa (0.97 to 0.99), implying an almost perfect agreement with minimal base calling variation. On a predefined dataset, RECall editing displayed the highest probability to score mixtures accurately 1 vs. 0.71 and the lowest chance to inaccurately assign mixtures to pure nucleotides (0.002–0.0008). This advantage is attributable to the manual sequence editing in RECall. Conclusion: The reduction in hands-on time needed is a benefit when using the Exatype HIV DR sequence analysis platform and result generation tool. There is a minimal difference in base calling between Exatype and standard methods. Although the discrepancy has minimal impact on drug resistance interpretation, allowance of sequence editing in Exatype as RECall can significantly improve its performance.

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