A DNA sequencer is a scientific instrument used to automate the DNA sequencing process. Given a sample of DNA, a DNA sequencer is used to determine the order of the four bases: G (guanine), C (cytosine), A (adenine) and T (thymine). This is then reported as a text string, called a read. Some DNA sequencers can be also considered optical instruments as they analyze light signals originating from fluorochromes attached to nucleotides.
In bioinformatics, sequence analysis is the process of subjecting a DNA, RNA or peptide sequence to any of a wide range of analytical methods to understand its features, function, structure, or evolution. It can be performed on the entire genome, transcriptome or proteome of an organism, and can also involve only selected segments or regions, like tandem repeats and transposable elements. Methodologies used include sequence alignment, searches against biological databases, and others.
In bioinformatics, sequence assembly refers to aligning and merging fragments from a longer DNA sequence in order to reconstruct the original sequence. This is needed as DNA sequencing technology might not be able to 'read' whole genomes in one go, but rather reads small pieces of between 20 and 30,000 bases, depending on the technology used. Typically, the short fragments (reads) result from shotgun sequencing genomic DNA, or gene transcript (ESTs).
DNA sequencing is the process of determining the nucleic acid sequence – the order of nucleotides in DNA. It includes any method or technology that is used to determine the order of the four bases: adenine, guanine, cytosine, and thymine. The advent of rapid DNA sequencing methods has greatly accelerated biological and medical research and discovery.
Sanger sequencing is a method of DNA sequencing that involves electrophoresis and is based on the random incorporation of chain-terminating dideoxynucleotides by DNA polymerase during in vitro DNA replication. After first being developed by Frederick Sanger and colleagues in 1977, it became the most widely used sequencing method for approximately 40 years. It was first commercialized by Applied Biosystems in 1986. More recently, higher volume Sanger sequencing has been replaced by next generation sequencing methods, especially for large-scale, automated genome analyses. However, the Sanger method remains in wide use for smaller-scale projects and for validation of deep sequencing results. It still has the advantage over short-read sequencing technologies in that it can produce DNA sequence reads of > 500 nucleotides and maintains a very low error rate with accuracies around 99.99%. Sanger sequencing is still actively being used in efforts for public health initiatives such as sequencing the spike protein from SARS-CoV-2 as well as for the surveillance of norovirus outbreaks through the Center for Disease Control and Prevention's (CDC) CaliciNet surveillance network.
DNA sequencing theory is the broad body of work that attempts to lay analytical foundations for determining the order of specific nucleotides in a sequence of DNA, otherwise known as DNA sequencing. The practical aspects revolve around designing and optimizing sequencing projects, predicting project performance, troubleshooting experimental results, characterizing factors such as sequence bias and the effects of software processing algorithms, and comparing various sequencing methods to one another. In this sense, it could be considered a branch of systems engineering or operations research. The permanent archive of work is primarily mathematical, although numerical calculations are often conducted for particular problems too. DNA sequencing theory addresses physical processes related to sequencing DNA and should not be confused with theories of analyzing resultant DNA sequences, e.g. sequence alignment. Publications sometimes do not make a careful distinction, but the latter are primarily concerned with algorithmic issues. Sequencing theory is based on elements of mathematics, biology, and systems engineering, so it is highly interdisciplinary. The subject may be studied within the context of computational biology.
Phred is a computer program for base calling, that is to say, identifying a nucleobase sequence from fluorescence "trace" data generated by an automated DNA sequencer that uses electrophoresis and 4-fluorescent dye method. When originally developed, Phred produced significantly fewer errors in the data sets examined than other methods, averaging 40–50% fewer errors. Phred quality scores have become widely accepted to characterize the quality of DNA sequences, and can be used to compare the efficacy of different sequencing methods.
Phrap is a widely used program for DNA sequence assembly. It is part of the Phred-Phrap-Consed package.
The Staden Package is computer software, a set of tools for DNA sequence assembly, editing, and sequence analysis. It is open-source software, released under a BSD 3-clause license.
FASTQ format is a text-based format for storing both a biological sequence and its corresponding quality scores. Both the sequence letter and quality score are each encoded with a single ASCII character for brevity.
In bioinformatics, hybrid genome assembly refers to utilizing various sequencing technologies to achieve the task of assembling a genome from fragmented, sequenced DNA resulting from shotgun sequencing. Genome assembly presents one of the most challenging tasks in genome sequencing as most modern DNA sequencing technologies can only produce reads that are, on average, 25–300 base pairs in length. This is orders of magnitude smaller than the average size of a genome. This assembly is computationally difficult and has some inherent challenges, one of these challenges being that genomes often contain complex tandem repeats of sequences that can be thousands of base pairs in length. These repeats can be long enough that second generation sequencing reads are not long enough to bridge the repeat, and, as such, determining the location of each repeat in the genome can be difficult. Resolving these tandem repeats can be accomplished by utilizing long third generation sequencing reads, such as those obtained using the PacBio RS DNA sequencer. These sequences are, on average, 10,000–15,000 base pairs in length and are long enough to span most repeated regions. Using a hybrid approach to this process can increase the fidelity of assembling tandem repeats by being able to accurately place them along a linear scaffold and make the process more computationally efficient.
High-throughput sequencing technologies have led to a dramatic decline of genome sequencing costs and to an astonishingly rapid accumulation of genomic data. These technologies are enabling ambitious genome sequencing endeavours, such as the 1000 Genomes Project and 1001 Genomes Project. The storage and transfer of the tremendous amount of genomic data have become a mainstream problem, motivating the development of high-performance compression tools designed specifically for genomic data. A recent surge of interest in the development of novel algorithms and tools for storing and managing genomic re-sequencing data emphasizes the growing demand for efficient methods for genomic data compression.
Philip Palmer Green is a theoretical and computational biologist noted for developing important algorithms and procedures used in Gene mapping and DNA sequencing. He earned his doctorate from Berkeley in mathematics in 1976 with a dissertation on C*-algebra under the direction of Marc Rieffel, but transitioned from pure mathematics into applied work in biology and bioinformatics. Green has obtained numerous important results, including in developing Phred, a widely used DNA trace analyzer, in mapping techniques, and in genetic analysis. Green was elected to the National Academy of Sciences in 2001 and won the Gairdner Award in 2002.
Ladeana Hillier is a biomedical engineer and computational biologist. She was one of the earliest scientists involved in the Human Genome Project and is noted for her work in various branches of DNA sequencing, as well as for having co-developed Phred, a widely used DNA trace analyzer.
Michael Christopher Wendl is a mathematician and biomedical engineer who has worked on DNA sequencing theory, covering and matching problems in probability, theoretical fluid mechanics, and co-wrote Phred. He was a scientist on the Human Genome Project and has done bioinformatics and biostatistics work in cancer. Wendl is of ethnic German heritage and is the son of the aerospace engineer Michael J. Wendl.
Base calling is the process of assigning nucleobases to chromatogram peaks, light intensity signals, or electrical current changes resulting from nucleotides passing through a nanopore. One computer program for accomplishing this job is Phred, which is a widely used base calling software program by both academic and commercial DNA sequencing laboratories because of its high base calling accuracy.
In DNA sequencing, a read is an inferred sequence of base pairs corresponding to all or part of a single DNA fragment. A typical sequencing experiment involves fragmentation of the genome into millions of molecules, which are size-selected and ligated to adapters. The set of fragments is referred to as a sequencing library, which is sequenced to produce a set of reads.
SNV calling from NGS data is any of a range of methods for identifying the existence of single nucleotide variants (SNVs) from the results of next generation sequencing (NGS) experiments. These are computational techniques, and are in contrast to special experimental methods based on known population-wide single nucleotide polymorphisms. Due to the increasing abundance of NGS data, these techniques are becoming increasingly popular for performing SNP genotyping, with a wide variety of algorithms designed for specific experimental designs and applications. In addition to the usual application domain of SNP genotyping, these techniques have been successfully adapted to identify rare SNPs within a population, as well as detecting somatic SNVs within an individual using multiple tissue samples.
Sequence Alignment Map (SAM) is a text-based format originally for storing biological sequences aligned to a reference sequence developed by Heng Li and Bob Handsaker et al. It was developed when the 1000 Genomes Project wanted to move away from the MAQ mapper format and decided to design a new format. The overall TAB-delimited flavour of the format came from an earlier format inspired by BLAT’s PSL. The name of SAM came from Gabor Marth from University of Utah, who originally had a format under the same name but with a different syntax more similar to a BLAST output. It is widely used for storing data, such as nucleotide sequences, generated by next generation sequencing technologies, and the standard has been broadened to include unmapped sequences. The format supports short and long reads (up to 128 Mbp) produced by different sequencing platforms and is used to hold mapped data within the Genome Analysis Toolkit (GATK) and across the Broad Institute, the Wellcome Sanger Institute, and throughout the 1000 Genomes Project.
In genetics, coverage is one of several measures of the depth or completeness of DNA sequencing, and is more specifically expressed in any of the following terms:
