Existing Sequencing Methods Research Articles

Long read mitochondrial genome sequencing using Cas9-guided adaptor ligation

The mitochondrial genome (mtDNA) is an important source of disease-causing genetic variability, but existing sequencing methods limit understanding, precluding phased measurement of mutations and clear detection of large sporadic deletions. We adapted a method for amplification-free sequence enrichment using Cas9 cleavage to obtain full length nanopore reads of mtDNA. We then utilized the long reads to phase mutations in a patient with an mtDNA-linked syndrome and demonstrated that this method can map age-induced mtDNA deletions. We believe this method will offer deeper insight into our understanding of mtDNA variation.

Nanopore Sequencing Accurately Identifies the Cisplatin Adduct on DNA.

Cisplatin, which selectively binds to N7 atoms of purines to inhibit normal replication and transcription, is a widely applied chemotherapeutic drug in the treatment of cancer. Though direct identification of cisplatin lesions on DNA is of great significance, existing sequencing methods have issues such as complications of preamplification or enrichment-induced false-positive reports. Direct identification of cisplatin lesions by nanopore sequencing (NPS) is in principle feasible. However, relevant investigations have never been reported. By constructing model sequences (83 nucleotides in length) containing a sole cisplatin lesion, identification of corresponding lesions by NPS is achieved with <10 ng of input sequencing library. Moreover, characteristic high-frequency noises caused by cisplatin lesions are consistently observed during NPS, clearly identifiable in corresponding high-pass filtered traces. This feature is, however, never observed in any other combinations of natural DNA bases and could be taken as a reference to identify cisplatin lesions on DNA. Further investigations demonstrate that cisplatin stalls the replication of phi29 DNA polymerase, which appears as a ∼5 pA level fluctuation in the single-molecule resolution. These results have confirmed the feasibility of NPS to identify cisplatin lesions at the genomic level and may provide new insights into understanding the molecular mechanism of platinum-based drugs.

Sequencing of Nucleic Acids: from the First Human Genome to Next Generation Sequencing in COVID-19 Pandemic

Despite being around for more than 40 years, DNA sequencing is regarded as young technology in clinical medicine. As sequencing is becoming cheaper, faster and more accurate, it is rapidly being incorporated into clinical laboratories. In 2003, the completion of the first human genome opened the door to personalized medicine. Ever since it has been expected for genomics to widely impact clinical care and public health. However, many years can pass for genomic discoveries to reflect back and benefit the patients. DNA sequencing represents a less biased approach to diagnostics. It is not only a diagnostic tool, but can also influence clinical management and therapy. As new technologies rapidly emerge it is important for researchers and health professionals to have basic knowledge about the capabilities and drawbacks of the existing sequencing methods, and their use in clinical setting and research. This review provides an overview of nucleic acid sequencing technologies from historical perspective and later focuses on clinical utilization of sequencing. Some of the most promising areas are presented with selected examples from Slovenian researchers.

Genome reconstruction and haplotype phasing using chromosome conformation capture methodologies.

Genomic analysis of individuals or organisms is predicated on the availability of high-quality reference and genotype information. With the rapidly dropping costs of high-throughput DNA sequencing, this is becoming readily available for diverse organisms and for increasingly large populations of individuals. Despite these advances, there are still aspects of genome sequencing that remain challenging for existing sequencing methods. This includes the generation of long-range contiguity during genome assembly, identification of structural variants in both germline and somatic tissues, the phasing of haplotypes in diploid organisms and the resolution of genome sequence for organisms derived from complex samples. These types of information are valuable for understanding the role of genome sequence and genetic variation on genome function, and numerous approaches have been developed to address them. Recently, chromosome conformation capture (3C) experiments, such as the Hi-C assay, have emerged as powerful tools to aid in these challenges for genome reconstruction. We will review the current use of Hi-C as a tool for aiding in genome sequencing, addressing the applications, strengths, limitations and potential future directions for the use of 3C data in genome analysis. We argue that unique features of Hi-C experiments make this data type a powerful tool to address challenges in genome sequencing, and that future integration of Hi-C data with alternative sequencing assays will facilitate the continuing revolution in genomic analysis and genome sequencing.

Quantum Point Contact Single-Nucleotide Conductance for DNA and RNA Sequence Identification.

Several nanoscale electronic methods have been proposed for high-throughput single-molecule nucleic acid sequence identification. While many studies display a large ensemble of measurements as "electronic fingerprints" with some promise for distinguishing the DNA and RNA nucleobases (adenine, guanine, cytosine, thymine, and uracil), important metrics such as accuracy and confidence of base calling fall well below the current genomic methods. Issues such as unreliable metal-molecule junction formation, variation of nucleotide conformations, insufficient differences between the molecular orbitals responsible for single-nucleotide conduction, and lack of rigorous base calling algorithms lead to overlapping nanoelectronic measurements and poor nucleotide discrimination, especially at low coverage on single molecules. Here, we demonstrate a technique for reproducible conductance measurements on conformation-constrained single nucleotides and an advanced algorithmic approach for distinguishing the nucleobases. Our quantum point contact single-nucleotide conductance sequencing (QPICS) method uses combed and electrostatically bound single DNA and RNA nucleotides on a self-assembled monolayer of cysteamine molecules. We demonstrate that by varying the applied bias and pH conditions, molecular conductance can be switched ON and OFF, leading to reversible nucleotide perturbation for electronic recognition (NPER). We utilize NPER as a method to achieve >99.7% accuracy for DNA and RNA base calling at low molecular coverage (∼12×) using unbiased single measurements on DNA/RNA nucleotides, which represents a significant advance compared to existing sequencing methods. These results demonstrate the potential for utilizing simple surface modifications and existing biochemical moieties in individual nucleobases for a reliable, direct, single-molecule, nanoelectronic DNA and RNA nucleotide identification method for sequencing.

Integrating human sequence data sets provides a resource of benchmark SNP and indel genotype calls

Clinical adoption of human genome sequencing requires methods that output genotypes with known accuracy at millions or billions of positions across a genome. Because of substantial discordance among calls made by existing sequencing methods and algorithms, there is a need for a highly accurate set of genotypes across a genome that can be used as a benchmark. Here we present methods to make high-confidence, single-nucleotide polymorphism (SNP), indel and homozygous reference genotype calls for NA12878, the pilot genome for the Genome in a Bottle Consortium. We minimize bias toward any method by integrating and arbitrating between 14 data sets from five sequencing technologies, seven read mappers and three variant callers. We identify regions for which no confident genotype call could be made, and classify them into different categories based on reasons for uncertainty. Our genotype calls are publicly available on the Genome Comparison and Analytic Testing website to enable real-time benchmarking of any method.

A high-throughput and quantitative method to assess the mutagenic potential of translesion DNA synthesis

Cellular genomes are constantly damaged by endogenous and exogenous agents that covalently and structurally modify DNA to produce DNA lesions. Although most lesions are mended by various DNA repair pathways in vivo, a significant number of damage sites persist during genomic replication. Our understanding of the mutagenic outcomes derived from these unrepaired DNA lesions has been hindered by the low throughput of existing sequencing methods. Therefore, we have developed a cost-effective high-throughput short oligonucleotide sequencing assay that uses next-generation DNA sequencing technology for the assessment of the mutagenic profiles of translesion DNA synthesis catalyzed by any error-prone DNA polymerase. The vast amount of sequencing data produced were aligned and quantified by using our novel software. As an example, the high-throughput short oligonucleotide sequencing assay was used to analyze the types and frequencies of mutations upstream, downstream and at a site-specifically placed cis–syn thymidine–thymidine dimer generated individually by three lesion-bypass human Y-family DNA polymerases.

An effective mixed‐model assembly line sequencing heuristic for just‐in‐time production systems

AbstractThe commonly accepted objective of sequencing a mixed‐model assembly line for a Just‐In‐Time (JIT) production system is to keep part usage rates at the assembly line close to constant. Sumichrast and Russell evaluated four existing sequencing methods and showed that the best method in achieving this objective is Miltenburg's algorithm 3 using heuristic 2 (M‐A3H2).This paper presents a much simpler heuristic procedure compared to M‐A3H2. The experiment on 9 problem sets conducted by Sumichrast and Russell is repeated for the new heuristic procedure and M‐A3H2. The results show that the new heuristic procedure is as good as M‐A3H2 in solution quality regarding the mean squared and absolute deviations and much more efficient in computation time. It is further noticed that the computation time required by M‐A3H2 increases much faster than the new heuristic procedure as the number of products increases. Nevertheless, the most important benefit of this new heuristic procedure is its simplicity which should make it very desirable for practitioners.

Sequencing of megabase plus DNA by hybridization: Theory of the method

A mismatch-free hybridization of oligonucleotides containing from 11 to 20 monomers to unknown DNA represents, in essence, a sequencing of a complementary target. Realizing this, we have used probability calculations and, in part, computer simulations to estimate the types and numbers of oligonucleotides that would have to be synthesized in order to sequence a megabase plus segment of DNA. We estimate that 95,000 specific mixes of 11-mers, mainly of the 5′ (A,T,C,G)(A,T,C,G)N8(A,T,C,G)3′ type, hybridized consecutively to dot blots of cloned genomic DNA fragments would provide primary data for the sequence assembly. An optimal mixture of representative libraries in M13 vector, having inserts of (i) 7kb, (ii) 0.5 kb genomic fragments randomly ligated in up to 10-kb inserts, and (iii) tandem “jumping” fragments 100 kb apart in the genome, will be needed. To sequence each million base pairs of DNA, one would need hybridization data from about 2100 separate hybridization sample dots. Inevitable gaps and uncertainties in alignment of sequenced fragments arising from nonrandom or repetitive sequence organization of complex genomes and difficulties in cloning “poisonous” sequences in Escherichia coli, inherent to large sequencing by any method, have been considered and minimized by choice of libraries and number of subclones used for hybridization. Because it is based on simpler biochemical procedures, our method is inherently easier to automate than existing sequencing methods. The sequence can be derived from simple primary data only by extensive computing. Phased experimental tests and computer simulations increasing in complexity are needed before accurate estimates can be made in terms of cost and speed of sequencing by the new approach. Nevertheless, sequencing by hybridization should show advantages over existing methods because of the inherent redundancy and parallelism in its data gathering.