In the July 19, 2013 issue of the journal Science, an interesting article describes the discovery and characterization of two “giant” viruses that are proposed to comprise the first members of the “Pandoravirus” genus.
Nadege Philippe and co-workers obtained the viruses from sediment samples in Chile and Australia and found that they have no morphological resemblance to any previously defined virus families. The investigators isolated the genomes of these viruses and sequenced them using a variety of NextGen methodologies. They then assembled the reads into contigs and characterized them using various sequence similarity algorithms (including NCBI’s BLAST and CD-Search). Interestingly, while related to each other, the genomes were not similar to those of any other organism or virus. Additionally, 93% of protein-coding sequences had no recognizable homologs.
What is a genome assembly?
The haploid human genome consists of 22 autosomal chromosomes and the Y and the X chromosomes. Each of the chromosomes represents a single DNA molecule, a sequence of millions of nucleotide bases. These molecules are linear, so one might expect that we should represent each chromosome by a single, continuous sequence.
Unfortunately, this is not the case for two main reasons: 1) because of the nature of genomic DNA and the limitations of our sequencing methods, some parts of the genome remain unsequenced, and 2) emerging evidence suggests that some regions of the genome vary so much between individual people that they cannot be represented as a single sequence.
In response to this, modern genomic data sets present a model of the genome known as a genome assembly. This post will introduce the basic concepts of how we produce such assemblies as well as some basic vocabulary.
Given the size of modern sequence databases, finding the complete genome sequence for a bacterium among the many other partial sequences can be a challenge. In addition, if you want to download sequences for many bacterial species, an automated solution might be preferable.
In this post we’ll discuss how to download bacterial genomes programmatically for a list of species using the E-utilities, the application programming interface (API) to NCBI’s Entrez system of databases. We’ll also take advantage of NCBI’s redesigned Genome database, which links all genome sequences for a given species to one record, making it easy to obtain the desired sequences once you find the right Genome record. In principle you can apply the procedure below to other simple genomes that are represented by a single sequence. Future posts will address additional considerations that apply to complex, eukaryotic genomes.