De Novo Assembly of the Complete Genome of an
Enhanced Electricity-Producing Variant of Geobacter
sulfurreducens Using Only Short Reads
Harish Nagarajan1,2, Jessica E. Butler3, Anna Klimes3¤, Yu Qiu2, Karsten Zengler2, Joy Ward3, Nelson D.
Young3, Barbara A. Methe ´4, Bernhard Ø. Palsson2, Derek R. Lovley3, Christian L. Barrett2*
1Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, California, United States of America, 2Department of Bioengineering,
University of California San Diego, La Jolla, California, United States of America, 3Department of Microbiology, University of Massachusetts, Amherst, Massachusetts,
United States of America, 4Department of Microbial and Environmental Genomics, J. Craig Venter Institute, Rockville, Maryland, United States of America
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.
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.
We have successfully developed a four-phase strategy
Citation: Nagarajan H, Butler JE, Klimes A, Qiu Y, Zengler K, et al. (2010) De Novo Assembly of the Complete Genome of an Enhanced Electricity-Producing Variant
of Geobacter sulfurreducens Using Only Short Reads. PLoS ONE 5(6): e10922. doi:10.1371/journal.pone.0010922
Editor: Niyaz Ahmed, University of Hyderabad, India
Received February 5, 2010; Accepted April 29, 2010; Published June 8, 2010
Copyright: ? 2010 Nagarajan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This research was supported by the Office of Science, Biological and Environmental Research (BER), United States Department of Energy, Cooperative
Agreement No.DE-FC02-02ER63446. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com
¤ Current address: Department of Physical and Biological Sciences, Western New England College, Springfield, Massachusetts, United States of America
The sequencing of the first bacterial genome in 1995 has left a
lasting impact on the field of prokaryotic genomics. The next
revolution in the field of genomics has been the development and
progress of high-throughput sequencing technologies. These next-
generation sequencers, mainly those from Illumina and 454 Life
Sciences (454), generate millions of short reads that are more
error-prone than the traditional Sanger sequencing. However,
these technologies have greatly reduced the cost of sequencing per
base and thus have opened up a wide range of applications. The
major applications include resequencing of closely related
individuals for personalized genomics and de novo sequencing of
new microbial genomes.
De novo sequencing using next-generation technologies has
necessitated the development of new algorithms for assembling
the short and more error-prone reads that they generate. Several
de novo assembly algorithms based on de-Bruijn graphs (EULER-
SR  and Velvet ), hash-extension (VCAKE) , overlap
layout (EDENA)  and for paired-end reads (ALLPATHS) 
have been recently developed. These algorithms are capable of
assembling millions of short-reads from next-generation sequenc-
ing technologies into thousands of contigs with varying degrees of
While 454 reads are longer than Illumina reads (,250–450 bp
compared to ,36–100 bp), they have a higher indel error rate
when compared to Illumina reads. The longer 454 reads, though,
inherently offer advantages over the shorter Illumina reads for de
novo assembly. Illumina reads, despite being much shorter, provide
a higher depth of coverage than 454 reads. This complementary
nature of Illumina and 454 reads has been exploited by some
recent methods that have produced an assembly of P. syringae
pathovar oryzae, consisting of 126 scaffolds, 2002 unincorporated
contigs, and an N50 of 91.5 kb . Another report integrated
these two data types using a different approach to assemble an
Acinetobacter baylyi strain into 10 scaffolds with an N50 of 1Mb .
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Salzberg and colleagues assembled a virulent strain of P. aeruginosa
PA01 into a large 6.3 Mb scaffold  using a mixed comparative
and de novo approach that included a gene-boosted strategy.
However, this approach heavily relied on comparative information
and thus cannot be classified as de novo.
Despite these recent reports that indicate significant progress by
integrating Illumina and 454 technologies, complete de novo
assembly of microbial genomes from only short reads and without
aid from Sanger sequencing still remains an unsolved challenge.
This challenge is critically important , for a single, circular
nucleotide sequence of the complete chromosome is a necessary
prerequisite for confident and complete research based on a
genome. As an answer to this challenge, we have developed a
strategy (Meta-Assembly) for complete, whole-genome de novo
assembly and applied it to a novel Geobacter variant (KN400) that is
capable of unprecedented current production at an electrode .
Our Meta-Assembly strategy adopts a bi-level integrative ap-
proach that leverages the different and complementary results
provided by multiple assembly programs over and above the
integration of complementary data types to obtain a complete,
whole-genome assembly. We have applied this strategy using 506
Illumina GA1 singleton reads and 166454 GS-FLX paired-end
sequencing reads and assessed our finished assembly by sequenc-
ing nearly 1% of the genome by Sanger sequencing and by a
comparison to the genome of a highly related strain.
Meta-Assembly strategy results in the complete genome
of KN400 from a mixture of short reads
Our Meta-Assembly approach (Figure 1) consists of four distinct
phases: Hybrid Assembly, Scaffold Bridging and Finishing,
Scaffold Ordering and Genome Finishing.
In the Hybrid Assembly phase (Figure 1A), we first filtered and
assembled the Illumina reads alone using the de-Bruijn graph
based algorithm EULER-SR . This assembly consisted of 4233
contigs with an N50 of 1.48 Kb. We then assembled these contigs,
along with all of the reads not assembled by EULER-SR  and
all of the 454 reads (i.e. neglecting the pair information) using
solutions/analysis-tools/gs-de-novo-assembler.asp). This combin-
ing step was a critical aspect in maximizing the complementary
information in Illumina and 454 reads, as shown by the resulting
assembly of 270 hybrid contigs with an N50 of 92.67 kb (Table 1).
We then leveraged the mate pair information by combining these
270 ‘‘hybrid’’ contigs with the paired 454 reads using Newbler’s
scaffolder. The contigs that did not form part of one of the output
scaffolds (unscaffolded contigs) were utilized later in the final
Finishing phase. This scaffolding step resulted in a greatly
improved assembly, giving three de novo scaffolds of lengths
3.18 Mb, 5.7 kb and 524 kb (respectively scaffolds A, B, and C in
Figure 1a.) with a total length of 3.7 Mb.
algorithms significantly improves the quality of the de
The de novo scaffolds A and C from the Hybrid
Assembly phase contained numerous stretches of degenerate
nucleotides, and to resolve them we applied a post-processing step
that exploited the coverage provided by short-reads. We developed
a Scaffold Bridging and Finishing phase for the purpose of linking
the de novo scaffolds and for resolving the intra-scaffold degenerate
nucleotide positions that were introduced by the scaffolder
(Figure 1B). In this phase, we leveraged the complementary
nature of the assemblies generated by programs like EULER-SR
, Velvet  and Newbler. Since EULER-SR  and Newbler
generate slightly different sets of contigs, we created a second set of
hybrid contigs from Illumina and 454 reads using EULER-SR.
We aligned these hybrid contigs against the de novo scaffolds using
NUCMER and analyzed the alignment for the threes scenarios
that could potentially bridge the scaffolds and resolve the
degenerate nucleotides (Methods and Fig S2). We found that
none of the hybrid EULER-SR  contigs aligned in such a way
that they bridged any pair of de novo scaffolds (Fig. S2A). We were
able to resolve all intra-scaffold degenerate nucleotide positions by
either substituting the corresponding bases from hybrid EULER-
SR  contigs that overlapped with flanking regions of Ns in the de
novo scaffolds (Fig S2B), or by removing the degenerate bases when
the regions flanking them aligned to contiguous regions on the
hybrid EULER-SR contigs (Fig S2C). (We implemented the same
approach using hybrid contigs generated by Velvet  as the
complementary set instead of EULER-SR  and obtained a
similar result.) At this stage, our assembly could contain small
indels due to 454 sequencing or due to our custom program. To
correct these, we aligned the Illumina reads using the Smith-
Waterman capabilities of MosaikAligner (Stromberg and Marth in
preparation). We also analyzed these scaffolds for potential
repeats/duplications by examining the read coverage and also
the multiplicity of the vertices in the repeat graph that is part of
EULER-SR’s output. This analysis revealed that scaffold B was
indeed duplicated and a BLAST  search identified it as an
rRNA gene. At the end of this phase, then, our assembly consisted
of four scaffolds, identified in Figure 1B as A (3.15 Mb), B (5.7 Kb)
occurring twice, and C (518 Kb).
An efficient PCR-based search strategy results in the
correct orientationof the
In the Scaffold Ordering phase, we considered the
KN400 genome to be a signed circular permutation of the four
scaffolds–giving 24 unique possible permutations (Figure 1C). To
determine the correct relative orientation of the scaffolds, we
employed a polymerase chain reaction (PCR)-based search
strategy. Our approach consisted of nine PCRs, six of which
serially eliminated 23 possible permutations. The orientation
ABcB was confirmed by the remaining three PCRs (Figure 1C).
This PCR-based ordering approach enabled us to link the four
scaffolds into one circular chromosome of 3.71 Mb. This
approach must not be confused with the standard gap-closing
approaches adopted, because we do not use PCRs to fill gaps but
only to confirm the relative orientation of the scaffolds and just link
them up. That is, there were no intervening nucleotides between
the four scaffolds. In fact, our approach goes a step further in
validating the sequence by accounting for the reverse complement
rearrangements that might be introduced in the assembly.
Depth of coverage offered by Illumina reads corrects the
indels introduced by 454 and scaffold finishing and
We corrected for indels and any errors introduced
during our scaffold finishing and scaffold ordering phase by
aligning the Illumina reads to the ordered scaffold ABcB using
MosaikAligner (Stromberg and Marth in preparation). The result
was a complete circular genome consisting of 3,714,272 bp. The
statistics of changes made by this alignment are provided in
Table 2. The genome can be accessed from GenBank under the
accession number CP002031.
Sanger sequencing of selected regions of KN400 genome
validates the de novo assembly
To validate the de novo assembly approach adopted here and to
estimate the accuracy of the obtained genome sequence, we
amplified 32kb (,1% of the genome) of KN400 and performed
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Sanger sequencing on both the forward and reverse strands
(Figure 2A). We compared these sequenced regions to the
corresponding genomic region obtained from Meta-Assembly
using megaBLAST  alignment algorithm.We found that out of
the 32680 bp sequenced by Sanger sequencing, there were 32675
perfect matches, four SNPs and one 1 bp insertion with respect to
the assembled KN400 genome sequence. All of these differences
occur in a 30 bp region of the genome that is covered by just one
454 read. This means that the accuracy of this short region is a
direct reflection of the quality of the single overlapping read. For
Figure 1. Assembly Strategy. A) Hybrid Assembly Phase; B) Scaffold Bridging and Finishing Phase; C) Scaffold Ordering Phase: The left branch of
the decision tree consists of permutations that can be confirmed by the PCR performed while the right branch consists of those permutations that
cannot be confirmed by the particular PCR. The faded permutations are those which have been eliminated by the PCRs while those in bold are those
that are remaining. (Gel Inset: Showing PCR products for all the 9 PCRs performed in the search strategy to confirm the correct orientation of the
scaffolds); D) Genome Finishing Phase.
Table 1. Summary and statistics of different stages of Meta-Assembly.
Phase Assembler Number of Contigs/Scaffolds N50(kb)Degenerate PositionsAssembly Length(Mb)
A EULER-SR(Illumina Alone)4233 1.4870 3.51
A Newbler(454 Reads+Illumina) 27092.670 3.72
A Newbler Scaffolder (Mate Pairs)3 3184.3 41421 3.71
B Scaffold Bridger/Finisher4 3184.30 3.71
C Scaffold Ordering1 3714.20 3.71
D Finisher1 3714.20 3.71
De Novo Genome Assembly
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this work, we utilized first generation short read technologies, and
read quality and quantity have dramatically improved thereafter.
Such low coverage regions are rare even in our assembly, and with
contemporary data output they would likely be nonexistent. That
is, investigators using our approach with the improved read data
would almost certainly not have such assembly errors because 1)
there would likely be no such regions since data output is so high
and 2) the accuracy of individual reads is so much higher. It is
worth pointing out that any approach based on short reads would
be limited by the single 454 reads spanning this region, but what
sets our approach apart is that we were able to actually place this
single read in the context of assembling a circularly-closed
KN400 is the first microbial genome that has been
completely assembled de novo using only next-
generation sequencing technologies
We predicted 3356 ORFs and 54 RNAs in the KN400 genome
using the RAST pipeline  and manual curation. We found the
completed KN400 genome to be collinear over its entire length
with no major rearrangements (Figure 3)–and approximately 97%
identical at the sequence level to Geobacter sulfurreducens PCA .
Because the genomes were so similar, we evaluated the correctness
of our de novo assembly by assessing the commonalities and the
differences between PCA and KN400 genomes. We adopted a
comparative genomics approach at the ORF level to assess the
differences and similarities between KN400 and PCA (Figure 2B).
Meta-Assembly approach facilitates accurate prediction
of genomic regions unique to PCA.
primary genomic regions that were specific to the PCA strain and
had no correspondence with the KN400 genome: a 32kb region
between GSU0039 and GSU0064 (in KN400) (Region 1), a 78kb
region between GSU2105 and GSU2183 (Region 2), and a 16 kb
region between GSU2588 and GSU2601 (Region 3) (Table S3).
The largest region, GSU2105-GSU2183, had 79 genes in PCA
between the orthologs to ORFs KN400_2161 and KN400_2163.
Forty-six of these genes were hypothetical, and 11 were
remaining genes were predicted to encode several sensors and
regulators and a DNA-binding repair protein (region 2 in Table
S3). The deletion of this region was confirmed by performing a
PCR over the break (Figure 4). The second largest region,
GSU0039-GSU0064, had 26 genes in PCA between the orthologs
to KN400_0039 and KN400_0040. Fifteen of these were
hypothetical and 4 were transposases (region 1 in Table S3). In
addition, there were 3 CRISPR-associated proteins. The third
region, GSU2588-GSU2601, had 11 genes in PCA between the
orthologs to KN400_2568 and KN400_2571. Four of these were
transposases and seven hypothetical proteins (region 3 in Table
S3). The abundance of transposons in these PCA-strain-specific
We identified three
genetic elements. The
Table 2. Changes made due to alignment of Illumina reads in
the genome-finishing phase.
Changes Number of Changes
Figure 2. Assembly validation approaches. A) Sanger sequencing approach; B) Comparative Genomics approach.
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regions suggests that they resulted from the activity of mobile
genetic elements within the Geobacter sulfurreducens genome since the
time the two strains diverged. None of these regions encoded any
protein predicted to be required for growth in the PCA strain .
Genomic Regions unique to KN400 relative to PCA
provides insights into possible evolutionary paths for
Of the 3356 ORFs predicted in KN400, we found
that 3088 (92%) had complete reciprocal orthologs with the same
relative ordering in PCA. Conservation of the orthologs between
the two genomes was quantified by the ratio of the bit scores from
a KN400-PCA to a KN400-KN400 BLAST alignment. The
orthologs had an average bit score ratio of 93.0% (Table S4).
We compared the remaining 268 proteins in KN400 that did
not have reciprocal orthology in PCA to all proteins in the NCBI
RefSeq database  to determine the organism which encoded
the protein with the highest sequence similarity (Table S4). Fifty-
six proteins had no significant match in the database, indicating
they were specific to the KN400 genome, and were annotated as
hypothetical proteins (Table S4). Thirty-six proteins were most
similar to PCA, and 90 were most similar to other Geobacteraceae,
indicating that they were vertically inherited (Table S4). This left
86 proteins that were found in the KN400 but were most similar to
a non-Geobacteraceae species (Table S4). These 86 genes were found
primarily in 12 small regions in KN400 that aligned poorly with
the PCA genome (Table S4). These regions ranged in size from 3.3
to 21.2kb, and seven of them included genes for at least one
transposase or integrase. In particular, copies of the two-subunit
transposase ISGsu7 were associated with strain-specific islands in
both PCA and KN400 (Tables S3 and S4). This supports the idea
that these regions may also have been produced by the activity of
mobile genetic elements since the two strains diverged.
C-type cytochromes play a key role in the transfer of electrons
from central metabolism to external electron acceptors like Fe(III)
and electrodes . Comparative analysis of KN400 and PCA
showed that several genes encoding cytochromes contain single
nucleotide polymorphisms between the strains, including the gene
for the outer-membrane cytochrome OmcS (GSU2504), which
has been shown to be required for electron transfer to insoluble
Figure 3. Genome-level comparison of KN400 and PCA. Shown in this figure is a dot-plot of the genome-wide alignment of KN400 and PCA.
Along the X-Axis is the KN400 genome and the PCA genome is shown along the Y axis.
De Novo Genome Assembly
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Fe(III) . In addition, analysis of the genes specific to the
KN400 strain also shows that there are at least three transport
proteins that are not found in the PCA strain (Table S4). Further
analysis of the link between these types of genetic differences and
the phenotype of the KN400 strain during electricity production is
underway (Butler J.E. et al, in prep).
Genomic characteristics of KN400 are typical of microbial
genomes at large
To assess whether KN400 was a particularly fortuitous choice
for attempting a de novo assembly using only short reads, we
assessed its genome complexity by performing a comparative
analysis using five different genomic properties that have been
characterized using 895 microbial genomes. We obtained data
relating to the GC content, genome size, number of replicons,
number of rRNAs and number of tRNAs for a sample of 895
microbial genomes from the Genome Atlas Database (http://
www.cbs.dtu.dk/services/GenomeAtlas-3.0/). We computed the
percentile ranks for KN400 genome to evaluate its relative
complexity in the space of all microbial genomes across these five
dimensions (Figure 5). Based on size and GC content, the KN400
genome has percentile ranks of 53 (3.71 Mb) and 75 (61% G+C).
Furthermore, about 60% of the microbial genomes consisted of a
single replicon – as is the case with KN400. KN400 has two
ribosomal RNA operons, which is the most frequent number of
rRNA operons among the 895 microbial genomes. Apart from
large repeats like the rRNA operons, local inverted repeats like
transposases also characterize genomic complexity and thus have
an effect on the assembly process. To evaluate the transposase
content of KN400, we relied on a recent survey  of the
transposases present in all available microbial genomic and
metagenomic databases. This survey found that the average
genome contains 11 transposases per 1kb. Based on this result, a
genome the size of KN400 would be expected to contain 38
transposases. Our analysis indicated that KN400 contains 30
transposases. Based on these comparisons, we concluded that
KN400 is a typical microbial genome and not an outlying
De novo assembly of complete microbial genomes using new
DNA sequencing technologies and without the aid of Sanger
sequencing has been an unsolved challenge. We have developed a
bi-level integrative approach, the Meta-Assembly, that answers
Our Meta-Assembly strategy is composed of four key phases. In
phase one we integrated Illumina and 454 reads at the very
beginning of our assembly process to generate hybrid contigs,
instead of using Illumina reads only for error correction of an
assembly generated from just 454 reads . This early integration
step was very important for reducing the number of degenerate
nucleotide positions (Tables 1 and 3) and thus for the overall
quality of the assembly. Incorporating the Illumina reads early in
the assembly process significantly reduced the number of
degenerate nucleotides in the assembly (,41000 N’s) compared
to when they are used for just error correction of the assembly
generated by Newbler (,90,000 N’s). In addition, we used
EULER-SR  instead of VCAKE  as the short read
assembler–in distinction from an earlier report . The fact that
de-Bruijn graph based algorithms like EULER-SR  and Velvet
 outperform VCAKE  has been documented in an earlier
study , and we found the same trend with our data as well.
Since assembly of Illumina reads is the first step of the hybrid
assembly phase, the quality of the initial assembly has the greatest
impact on the outcome of the entire process. Moreover, EULER-
SR  is also capable of performing a de novo assembly with a
mixture of Illumina and 454 reads, but its performance does not
degrade with increasing read length (). This proved to be a
significant advantage, for we were able to exploit the comple-
mentary nature of EULER-SR  and Newbler to develop the
Scaffold Bridging and Finishing Phase–enabling us to resolve all of
the degenerate nucleotides.
In the second phase, we maximized the complementary
information provided by different assembly algorithms. This
component of our strategy is a key distinguishing aspect of our
approach. Although Newbler alone was able to assemble the reads
into five scaffolds, the resulting assembly had a considerable
number of degenerate positions which could not be resolved just
from an error correction step using Illumina reads (Table 3).
Similarly, while EULER-SR  and Velvet  both generated
high quality contigs, they do not perform as well as Newbler with
respect to leveraging the paired-end information in the 454 reads.
Our results clearly show that integrating more than one assembly
algorithm is very important for enhancing the quality of the
In the third phase, the simple PCR-based search strategy
allowed us to quickly order and orient the scaffolds into a circular
genome. This is another unique aspect of our approach in that we
address the problem of relative orientation of the scaffolds as well
as their ordering with just a few PCRs. While we use the PCRs to
order the scaffolds into a circular genome, we did not fill any gaps
as no sequence information is obtained from the PCRs. We note
that as technology improvements allow paired-end sequencing
reads with longer inserts, the necessity of this PCR step will
Figure 4. Gel picture confirming the 79 kb deletion (Region2) in KN400. PCR was performed with primer sets in order to amplify over the
break (shown in panel B). The expected product size is 207bp. Panel A shows that we can amplify over the break only in KN400 and not in PCA,
confirming the deletion of region 2 in KN400.
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In the fourth and final phase, we aligned Illumina reads against
the ordered scaffold to account for indels and errors induced
during the scaffold finishing phase.
To our knowledge this is the first reported de novo assembly of a
complete genome using next generation sequencing technologies.
Furthermore, our comprehensive comparative analysis of genomic
characteristics of 895 microbial genomes reveals that KN400 is a
characteristic microbial genome and is not an outlier in the space
of all microbial genomes. We view our result as the demonstration
of general a strategy for assembling genomes, wherein multiple
data types are integrated at specific steps in the process to
maximize the potential of their complementary nature and
wherein multiple assembly programs are utilized such that
deficiencies in one algorithmic approach are compensated by the
strengths of another algorithmic approach. As new sequencing
technologies and new assembly programs become available, they
can be readily incorporated in this framework. Genome assembly
will remain challenging for the foreseeable future, and we view the
idea of such a readily extensible meta approach as one of the most
promising ways to meet this challenge.
Figure 5. Density of five different genomic properties in the space of microbial genomes. A) GC Content B) Genome Size C)Number of
rRNAs D) Number of Replicons E) Number of tRNAs. Shown in red circle, is the value of KN400’s genomic property.
Table 3. Comparison of Meta-Assembly to other assembly programs.
Assembler Number of Contigs/ScaffoldsN50(kb) Degenerate PositionsAssembly Length(Mb)
Meta-Assembly1 3714.20 3.71
Newbler alone5 3184.3904493.72
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Materials and Methods
We utilized an electrode isolated strain of a rare variant of
Geobacter sulfurreducens KN400that exhibits enhanced current
production relative to Geobacter sulfurreducens PCA . For the
purpose of a de novo assembly, we carried out both Illumina
sequencing and 454 Life Sciences pyrosequencing (shotgun and
paired end) for KN400. The details of the sequence data used are
shown in the Table S1. The paired end reads had an average
insert size of 3020 bp and the distribution of the fragment size is
given in Supplementary Figure S1.
Hybrid Assembly Phase.
reads using the de-Bruijn graph based short-read assembler
EULER-SR  with the vertex size parameter set to 25. Prior
to assembling the short-reads, we filtered them for obvious failure
modes using the filterIlluminaReads script as part of the EULER-
SR package . We took all of the 454 reads as singletons (i.e.
neglecting the paired end information) and assembled them using
Roche’s assembler (Newbler) with default parameters (minimum
overlap length 40, minimum overlap identity 90%). In order to
integrate the Illumina and 454 technologies, we combined the
contigs generated from the EULER-SR  and Newbler
assemblies using the incremental assembly option in Newbler to
generate a set of hybrid contigs. At this stage, we leveraged the
mate-pair information provided by the 454 reads in order to build
scaffolds from these hybrid contigs.
Scaffold Bridging and Finishing Phase.
maximize the complementary nature of the assembly algorithms,
we developed a meta-approach that reconciles the assemblies
produced by either EULER-SR  or Velvet  and Newbler.
The de novo scaffolds generated from phase A are largely due to
Newbler and contain a lot of degenerate nucleotides. We created a
second set of hybrid contigs from both the Illumina and 454 reads
using EULER-SR with a vertex-size of 25. Using the NUCMER
alignment tool of MUMMER package , we aligned these
hybrid EULER-SR  contigs against the de novo scaffolds with the
break length parameter of 10,000. We further implemented a
custom program (Supplementary Figure S2) which accounted for
the following three scenarios, in order to link up the de novo
scaffolds and resolve the degenerate nucleotides.
N If any of these contigs aligned in such a way that they were
bridging any two of the de novo scaffolds, those scaffolds were
linked up (Figure S2A).
N In the event that these contigs overlapped with the flanking
regions of degenerate nucleotides (N’s), we replaced the N’s
with the corresponding region of the contig.(Figure S2B)
N If the regions flanking the degenerate positions aligned to
contiguous regions in the contig set, we removed that stretch of
degenerate nucleotides (Figure S2C).
We assembled Illumina GA1
In order to
We further augmented this custom program with an alignment
of Illumina reads against these scaffolds in order to account for the
indel errors due to 454 sequencing. We used the MosaikAligner in
the ‘‘all’’ alignment mode with a hash size of 13 and 20 bp as
alignment candidate threshold, allowing a maximum of 4
Scaffold Ordering Phase.
genome as a signed circular permutation of the finished scaffolds
and adopted a PCR based scaffold ordering approach in order to
orient them into a circular genome. We designed a search strategy
We considered the KN400
comprised of nine PCRs in order to determine the correct
orientation. For performing the PCRs, total G. sulfurreducens
(KN400) genomic DNA was prepared using the MasterPure
Complete DNA Purification kit (Epicentre Biotechnologies,
Madison, WI) according to manufacturer’s directions. Taq DNA
polymerase (QIAGEN Inc., Valencia, CA) was used for all PCR
amplifications. The sequence and the location details of the primer
sets used for the PCRs are provided in Table S2A, while the
combinations of the primer pairs for each PCR and the expected
amplicon size are given in Table S2B.
Genome Finishing Phase.
possible indel errors due to the 454 sequencing as well as our
Meta-Assembly approach, we re-aligned all of the Illumina reads
to the ordered scaffold using MosaikAligner (Stromberg and
Marth in preparation) with the same parameters as described in
Phase B of the Meta-Assembly approach.
In order to account for any
Validation by Sanger Sequencing
We validated our assembly approach and computed error rates
by performing Sanger sequencing of about 1% of the KN400
genome. The regions that were selected for sequencing along with
the details of the primers used for PCR amplification are shown in
Gene Prediction and Comparative Analysis
At each step of the finishing process, we predicted open reading
frames (ORFs) in the KN400 draft genome using the Rapid
Annotation by Subsystem Technology (RAST) pipeline  in
order to check if the standard properties like gene density were
characteristic of a bacterial genome. We performed a whole
genome alignment of KN400 and PCA using Mauve (Darling
et al., 2004) with a seed-weight of 15, a minimum island size of 50,
and the Muscle 3.6 algorithm in order to check for completeness of
all the homologous gene sequence. We further confirmed the
absence of any genes with respect to PCA by aligning the Illumina
reads to the corresponding region.
Comparative Genomics Analysis.
genome sequence, translated ORFs, and functional annotation
from NCBI (RefSeq ID NC_002939) and the RefSeq database
 and performed an alignment using BLAST . We
extracted the Identifiers, functional annotations, and organism
names for the closest matches for all ORFs. We calculated bit
score ratios as the bit score of the best match in a KN400-PCA or
KN400-RefSeq BLASTp or tBLASTn comparison adjusted by
the bit score of the KN400 protein aligned to itself or its own
genome. Orthologs were defined as reciprocal best matches in
whole-genome KN400-PCA BLASTp comparisons . We also
performed a bidirectional Smith-Waterman alignment of the
ORFs of KN40 and PCA using the ssearch35 program of the
FASTAv3.5 package .
We obtained the PCA
Found at: doi:10.1371/journal.pone.0010922.s001 (0.44 MB TIF)
Distribution of fragment sizes from 454 paired end
Found at: doi:10.1371/journal.pone.0010922.s002 (0.56 MB TIF)
Custom program used in the Scaffold Bridging and
assembly of KN400.
Found at: doi:10.1371/journal.pone.0010922.s003 (0.02 MB
Next generation sequencing data used for de novo
De Novo Genome Assembly
PLoS ONE | www.plosone.org8 June 2010 | Volume 5 | Issue 6 | e10922
Table S2 Download full-text
denotes reverse complement.) B: Primer pairs and product analysis
of each PCR.
Found at: doi:10.1371/journal.pone.0010922.s004 (0.03 MB
A: Sequence and location of primers. (Lower case
Found at: doi:10.1371/journal.pone.0010922.s005 (0.04 MB
Genomic regions absent in KN400 but present in
Found at: doi:10.1371/journal.pone.0010922.s006 (0.95 MB
All predicted KN400 genes with annotation and
and primer details.
Selected regions for Sanger sequencing, coordinates
Found at: doi:10.1371/journal.pone.0010922.s007 (0.05 MB
We would like to thank Nicholas Webster for providing access to Newbler
and the data analysis cluster and Mark Chaisson and Pavel Pevzner for
discussions on genome assembly and EULER-SR. We would also like to
acknowledge Nathan E. Lewis for his valuable inputs on representation of
Conceived and designed the experiments: HN CLB. Performed the
experiments: HN AK JW CLB. Analyzed the data: HN JEB CLB.
Contributed reagents/materials/analysis tools: HN JEB AK YQ KZ JW
NDY BAM BP DL CLB. Wrote the paper: HN JEB AK CLB.
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PLoS ONE | www.plosone.org9 June 2010 | Volume 5 | Issue 6 | e10922