Shotgun Sequence Assembly

Abstract

Shotgun sequencing is the most widely used technique for determining the DNA sequence of organisms. It involves breaking up the DNA into many small pieces that can be read by automated sequencing machines, then piecing together the original genome using specialized software programs called assemblers. Due to the large amounts of data being generated and to the complex structure of most organisms' genomes, successful assembly programs rely on sophisticated algorithms based on knowledge from such diverse fields as statistics, graph theory, computer science, and computer engineering. Throughout this chapter we will describe the main computational challenges imposed by the shotgun sequencing method, and survey the most widely used assembly algorithms.

Introduction

In 1982 Fred Sanger developed a new technique called shotgun sequencing and proved its worth by sequencing the complete genome of the bacteriophage Lambda [1]. This technique attempted to overcome the limitations of sequencing technologies by breaking up the DNA at random. Sequencing techniques were only able to “read” several hundred nucleotides at a time. The resulting pieces were assembled together based on the similarity between pieces derived from the same section of the original DNA molecule. The large amount of data produced by shotgun sequencing made it necessary to utilize computer programs to assist the assembly [2], [3]. Despite continued improvements in sequencing technology and the development of specialized assembly programs, it was unclear whether shotgun sequencing could be used to sequence genomes larger than those of viruses (typically 5000–100,000 nucleotides). For larger genomes it was thought that the complexity of the task would pose an insurmountable challenge to any computer program.

In 1995, however, researchers at The Institute for Genomic Research (TIGR) successfully used the shotgun sequencing technique to decipher the complete genome of the bacterium Haemophilus influenzae[4]. The sequencing of this 1.83 million base pair genome required the development of a specialized assembly program [5] as well as painstaking laboratory efforts to complete those regions that could not correctly be assembled by the software. The success of the Haemophilus project started a genomics revolution with the number of genomes being sequenced every year increasing at an exponential rate. At the moment the genomes of more than 1000 viruses, 100 bacteria, and several eukaryotes have been completed, while multiple other projects are well on the way to completion. In parallel with the large amounts of genomic data becoming available, the genomic revolution led to the birth of a new field—bioinformatics—bringing together an eclectic mix of scientific fields such as computer science and engineering, mathematics, physics, chemistry, and biology.

Critics of the shotgun sequencing approach continued to question its applicability to large genomes despite obvious successes in sequencing bacterial genomes. They argued the technique would be impractical in the case of large eukaryotic genomes because repeats—stretches of DNA that occur in two or more copies within the genome—would hopelessly confuse any assembler [6]. The standard procedure for handling large genomes was a hierarchical approach involving breaking up the DNA into large (50–150 kbp) pieces cloned in bacterial artificial chromosomes (BACs), and then sequencing each BAC through the shotgun method. Most such criticism was silenced in 2000 by the successful assembly at Celera of the genome of Drosophila melanogaster[7] from whole-genome shotgun (WGS) data. The assembly was performed with a new assembler [8] designed to handle the specific problems involved in assembling large complex genomes. The researchers from Celera went on to assemble the human genome using the same whole-genome shotgun sequencing technique [9]. Their results were published simultaneously with those from the International Human Genome Sequencing Consortium, who used the traditional hierarchical method [10]. Independent studies [11], [12] later showed that the two assemblies produced similar results and many of the differences between them could be explained by the draft-level quality of the data. The applicability of the WGS method to large genomes was thus proven though some continue to argue the validity of Celera's results (some opinions on this topic are presented in [13], [14], [15], [16], [17]).

Celera's success combined with the cost advantages of the WGS technique—Celera sequenced and assembled the human genome in a little over a year while the international consortium's efforts had been going on for more than 10 years—renewed interest in the WGS method and led to the development of several WGS assembly programs: Arachne [18], [19] at the Whitehead Institute, Phusion [20] at the Sanger Institute, Atlas [21] at the Baylor Human Genome Sequencing Center, and Jazz [22] at the DOE Joint Genome Institute. Most current sequencing projects have opted for a WGS approach instead of the hierarchical approach. For example the sequencing of the mouse [23], rat [24], dog [25], puffer fish [22], and sea squirt [26] all follow the WGS strategy.

The current issue of debate is the suitability of whole-genome shotgun sequencing as the starting point in the efforts to obtain the complete sequence for a genome. All sequencing strategies start by building a backbone, or rough draft, of the genome whose gaps need to be filled in through further laboratory experiments. It is still not clear which sequencing strategy will ultimately be the most efficient in obtaining the complete sequence of an organism, especially as none of the large eukaryotic projects have yet been finished, except for the 100 Mbp genome of the nematode Caenorhabditis elegans, finished in October 2002. (The genomes of Drosophila melanogaster and human are expected to be mostly finished before the end of 2003.)

Despite significant differences in the overall structuring of the sequencing process, all sequencing strategies rely on shotgun sequencing as a basic component. The reader is referred to [27], [28] for an in-depth discussion of current approaches to sequencing. The following sections represent a description of the shotgun sequencing technique, with a emphasis on the algorithmic challenges imposed by this technique.