Large-scale DNA sequencing

Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment

A multitude of algorithms for sequence comparison, short-read assembly and whole-genome alignment have been developed in the general context of molecular biology, to support technology development for high-throughput sequencing, numerous applications in genome biology and fundamental research on comparative genomics. The computational complexity of these algorithms has been previously reported in original research papers, yet this often neglected property has not been reviewed previously in a systematic manner and for a wider audience. We provide a review of space and time complexity of key sequence analysis algorithms and highlight their properties in a comprehensive manner, in order to identify potential opportunities for further research in algorithm or data structure optimization. The complexity aspect is poised to become pivotal as we will be facing challenges related to the continuous increase of genomic data on unprecedented scales and complexity in the foreseeable future, when robust biological simulation at the cell level and above becomes a reality.

High-throughput DNA sequencing: a genomic data manufacturing process

The progress trends in automated DNA sequencing operation are reviewed. Technological development in sequencing instruments, enzymatic chemistry and robotic stations has resulted in ever-increasing capacity of sequence data production. This progress leads to a higher demand on laboratory information management and data quality assessment. High-throughput laboratories face the challenge of organizational management, as well as technology management. Engineering principles of process control should be adopted in this biological data manufacturing procedure. While various systems attempt to provide solutions to automate different parts of, or even the entire process, new technical advances will continue to change the paradigm and provide new challenges.

Solid-phase cloning to create sublibraries suitable for DNA sequencing

A solid-phase method is described to create subclones, suitable for DNA sequencing, from lambda or cosmid libraries. The purified target DNA is sonicated and two linkers, with one oligonucleotide biotinylated in the 5'-end, are ligated to the ends of the fragments produced by sonication. After size separation, the fragments are immobilised onto a solid support and the non-biotinylated strand of each immobilised fragment is eluted. In this way, a library of single-stranded fragments is obtained. All fragments contain 'universal' flanking sequences of 22 bases introduced by the linker ligation. These flanking sequences can subsequently be used for solid-phase cloning into a single-stranded vector containing the complementary sequences. Thus, cloning can be achieved without the use of ligase or restriction enzymes. The resulting subclones are used for direct solid-phase sequencing and the immobilised strand can be used to selectively remove homologous DNA from the library of single-stranded fragments. Thus, a sublibrary of non-sequenced fragments can be created. Here, we show that a library of clones, suitable for direct solid-phase sequencing, can be obtained starting with lambda DNA. The efficiency of selective hybridisation of homologous and non-homologous fragments was investigated. The possibility of using this approach for automated cloning strategies for large-scale genomic and cDNA sequencing is discussed.

Nucleotide sequence analysis of 95 kb near the 3' end of the murine T-cell receptor alpha/delta chain locus: strategy and methodology

The nucleotide sequence of a region at the 3' terminus of the murine T-cell receptor alpha/delta chain locus is presented. This region, which encodes the constant region genes for alpha and delta chain polypeptides and all 50 joining gene segments for the alpha chain polypeptide, spans 94,647 bp and includes more than 50 noncoding sequence elements important for T-cell receptor gene rearrangement and expression. DNA sequencing of this region included complete analysis of two cosmid clones and five additional restriction fragments using a random subcloning approach with various manual and automated sequencing strategies. The automated sequencing strategies hold considerable promise for future large-scale DNA sequencing efforts.

Sequence accuracy of large DNA sequencing projects

Very little information has been accumulated regarding the likely accuracy of final or consensus DNA sequence data. With the large-scale efforts anticipated for the Human Genome Project, the subjective determination of final sequence must eventually be replaced with more objective, automatic methods. This will require a much better understanding of the nature of error in raw sequencing data and its impact on the determination of the final sequence. This paper describes a start at defining the error model of large-scale sequencing efforts based on random subcloning strategies.

Model genomes: The benefits of analysing homologous human and mouse sequences

The human genome initiative has provided the motivating force for launching sequencing projects suitable for testing various DNA-sequencing strategies, as well as motivating the development of mapping and sequencing technologies. In addition to projects targeting selected regions of the human genome, other projects are based on model organisms such as yeast, nematode and mouse. The sequencing of homologous regions of human and mouse genomes is a new approach to genome analysis, and is providing insights into gene evolution, function and regulation which could not be determined so easily from the analysis of just one species.

Large-scale and automated DNA sequence determination

DNA sequence analysis is a multistage process that includes the preparation of DNA, its fragmentation and base analysis, and the interpretation of the resulting sequence information. New technological advances have led to the automation of certain steps in this process and have raised the possibility of large-scale DNA sequencing efforts in the near future [for example, 1 million base pairs (Mb) per year]. New sequencing methodologies, fully automated instrumentation, and improvements in sequencing-related computational resources may render genome-size sequencing projects (100 Mb or larger) feasible during the next 5 to 10 years.