De Novo Assembly of the Complete Genome of an Enhanced Electricity-Producing Variant of Geobacter sulfurreducens Using Only Short Reads

Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, California, USA.
PLoS ONE (Impact Factor: 3.23). 06/2010; 5(6):e10922. DOI: 10.1371/journal.pone.0010922
Source: PubMed


State-of-the-art DNA sequencing technologies are transforming the life sciences due to their ability to generate nucleotide sequence information with a speed and quantity that is unapproachable with traditional Sanger sequencing. Genome sequencing is a principal application of this technology, where the ultimate goal is the full and complete sequence of the organism of interest. Due to the nature of the raw data produced by these technologies, a full genomic sequence attained without the aid of Sanger sequencing has yet to be demonstrated.
We have successfully developed a four-phase strategy for using only next-generation sequencing technologies (Illumina and 454) to assemble a complete microbial genome de novo. We applied this approach to completely assemble the 3.7 Mb genome of a rare Geobacter variant (KN400) that is capable of unprecedented current production at an electrode. Two key components of our strategy enabled us to achieve this result. First, we integrated the two data types early in the process to maximally leverage their complementary characteristics. And second, we used the output of different short read assembly programs in such a way so as to leverage the complementary nature of their different underlying algorithms or of their different implementations of the same underlying algorithm.
The significance of our result is that it demonstrates a general approach for maximizing the efficiency and success of genome assembly projects as new sequencing technologies and new assembly algorithms are introduced. The general approach is a meta strategy, wherein sequencing data are integrated as early as possible and in particular ways and wherein multiple assembly algorithms are judiciously applied such that the deficiencies in one are complemented by another.

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Available from: Christian Barrett, Oct 09, 2015
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    • "However, each of the next-generation sequencing platforms has distinctive shortcomings. For instance, Illumina sequencing and SOLiD sequencing generate accurate but short tags that are difficult to be assembled (Nagarajan et al., 2010; Luo et al., 2012). PacBio sequencing generates long sequences, but its error rate is relatively high. "
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    ABSTRACT: Rapid advances of the next-generation sequencing technologies have allowed whole genome sequencing of many species. However, with the current sequencing technologies, the whole genome sequence assemblies often fall in short in one of the four quality measurements: accuracy, contiguity, connectivity, and completeness. In particular, small-sized contigs and scaffolds limit the applicability of whole genome sequences for genetic analysis. To enhance the quality of whole genome sequence assemblies, particularly the scaffolding capabilities, additional genomic resources are required. Among these, sequences derived from known physical locations offer great powers for scaffolding. In this mini-review, we will describe the principles, procedures and applications of physical-map-derived sequences, with the focus on physical map contig-specific sequences.
    Frontiers in Genetics 07/2014; 5:243. DOI:10.3389/fgene.2014.00243
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    • "With the advances of sequencing technologies, genomes of many species with biological or economic importance are currently under sequencing. With the exception of PacBio sequencing platform, several nextgen sequencing technologies such as 454 sequencing, Illumina sequencing, and SOLiD sequencing produce relatively short sequencing reads [1-3], making subsequent sequence assembly a great challenge. "
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    ABSTRACT: Along with the rapid advances of the nextgen sequencing technologies, more and more species are added to the list of organisms whose whole genomes are sequenced. However, the assembled draft genome of many organisms consists of numerous small contigs, due to the short length of the reads generated by nextgen sequencing platforms. In order to improve the assembly and bring the genome contigs together, more genome resources are needed. In this study, we developed a strategy to generate a valuable genome resource, physical map contig-specific sequences, which are randomly distributed genome sequences in each physical contig. Two-dimensional tagging method was used to create specific tags for 1,824 physical contigs, in which the cost was dramatically reduced. A total of 94,111,841 100-bp reads and 315,277 assembled contigs are identified containing physical map contig-specific tags. The physical map contig-specific sequences along with the currently available BAC end sequences were then used to anchor the catfish draft genome contigs. A total of 156,457 genome contigs (~79% of whole genome sequencing assembly) were anchored and grouped into 1,824 pools, in which 16,680 unique genes were annotated. The physical map contig-specific sequences are valuable resources to link physical map, genetic linkage map and draft whole genome sequences, consequently have the capability to improve the whole genome sequences assembly and scaffolding, and improve the genome-wide comparative analysis as well. The strategy developed in this study could also be adopted in other species whose whole genome assembly is still facing a challenge.
    PLoS ONE 10/2013; 8(10):e78872. DOI:10.1371/journal.pone.0078872 · 3.23 Impact Factor
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    • "Armed with this observation, a number of projects aim to take advantage of either different sources of sequencing data or different assembly tools. Indeed, cross-platform data merging is advantageous because sequencing platforms have different biases [4] and thus assemblies generated from different platforms' data can complement each other [5]; [6]. Several software packages were developed in order to capitalize on different advantages of existing assemblers. "
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    ABSTRACT: Motivation Among challenges that hamper reaping the benefits of genome assembly are both unfinished assemblies and the ensuing experimental costs. First, numerous software solutions for genome de novo assembly are available, each having its advantages and drawbacks, without clear guidelines as to how to choose among them. Second, these solutions produce draft assemblies that often require a resource intensive finishing phase. Methods In this paper we address these two aspects by developing Mix , a tool that mixes two or more draft assemblies, without relying on a reference genome and having the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a set of paths in the extension graph that maximizes the cumulative contig length. Results We evaluate the performance of Mix on bacterial NGS data from the GAGE-B study and apply it to newly sequenced Mycoplasma genomes. Resulting final assemblies demonstrate a significant improvement in the overall assembly quality. In particular, Mix is consistent by providing better overall quality results even when the choice is guided solely by standard assembly statistics, as is the case for de novo projects. Availability Mix is implemented in Python and is available at, novel data for our Mycoplasma study is available at
    BMC Bioinformatics 10/2013; 14(15). DOI:10.1186/1471-2105-14-S15-S16 · 2.58 Impact Factor
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