Sequencing of samples, de novo assembly of the genomes, and scaffolding

Programming language, systems, and external programs

ContigScape was developed based on Cytoscape, which is available for Linux, Windows and MacOS X. The core programming language of ContigScape is Java. Users are provided with a comprehensive manual that explains all functions (see Additional file 1).

Counting contig abundance and copy number, and display

Our interest lies in estimating the abundance of repeat contigs. We define a repeat contig as one at least having twice as much read coverage than the average genome coverage. Average genome coverage is the ratio of the total bases of reads assembled into contigs and the total size of all contigs. When users input Contig Relationship Scape (CRS) file in our plugin without original assembly result, the default arithmetic for genome coverage is to count the average coverage of all contigs with size bigger than 20 kb (In our experience, the repeat contig bigger than 20 kb is rare in microbial genome except plasmid). Each copy number is calculated as the ratio of contig abundance and average genomic coverage, which represents the corresponding repetition rate of the contigs. Contig abundance is the ratio of total bases of reads assembled into this contig and the contig size. We define a specific contig as one having read coverage less than 1.5 fold average (default value is 1.5, which can be set by users). So, the contigs whose coverage is greater than 1.5 and less than 2 are probable repeats. They need to be confirmed by counting the connections at the end of the contig or PCR method. Like Figure 1B7, 106S-106E is a repeat contig verified by two linkages in each end. PCR needs to be used to determine the relationship “37S-37E-106S-106E-41S-41E-106E-106S-42E-42S” or “37S-37E-106S-106E-41E-41S-106E-106S-42E-42S”.

Meanwhile, the average number of linkages between contigs can be computed by $\mathrm{Z}={\displaystyle {\sum }_1^{\mathrm{n}}\mathrm{linkNum}}\mathrm{between}\mathrm{largecontigs}\left(\mathrm{size}\ge 20\mathrm{Kb}\right)/\mathrm{n}$, where Z is the average number of linkages and n is the number of relationships conforming to the requirements. As above, the ratio of link number and Z indicates the width of edge representing linkage in CytoScape.

Principles of displaying Roche 454 genome assembly results

Roche 454 reads now exceed 700 base pairs in length and thus can be used to resolve gaps caused by small repeats. The ‘Newbler Assembler’ may produce a ‘454Contigs.ace’ file, which contains all assembly information and can be shown by ‘Consed’ [5]. As indicated in Supporting Figure 2, when a read was separated into two contigs, the coordinate of the read in each contig was shown after the read name, followed by the contig number with which this read was linked. The general principle to label the reads spanning the linked contigs is to use ‘fmX’ to represent the 5’ end of the reads located in contigX and ‘toY’ to represent the 3’ end of the reads located in contigY. This unique feature of the ‘Newbler Assembler’ labeling system in conjunction with long reads from 454 enables us to extract all the information of ‘fm’ and ‘to’ from the ‘454Contigs.ace’ file. This information can then be arranged into a relationship table (Figure 2C, D), such as ‘5’-end-Contig1’ linked to ‘3’-end-Contig2’. This relationship table can then be displayed by ContigScape as shown in Figure 3D.

Principles of displaying scaffolds constructed by mate-pair reads

A scaffold is a consensus sequence formed by ordered contigs using ‘N’ to fill any gaps. The most common method uses the mate-pair information to assemble contigs into scaffolds. Scaffolding programs can determine the separation of two contigs depending on the fragment size of the mate-pair reads. For example, if two contigs were separately mapped by a pair of 3-kb mate-pair reads, the two contigs could be joined into a scaffold, and the gap size would be 3 kb minus the distance between the mapping loci and the end of contigs. This method would allow repeat regions less than 3 kb in length to be bridged. However, ambiguous linkages can occur if the repeat region was longer than the fragment size of the mate-pair library (Figure 4). Similar to the results from ‘Newbler’ for 454 reads, ContigScape can display a relationship network within scaffolds by counting the number of mate-pair reads linking to large contigs (>500 bp).

Visualization

Repeats are usually assembled into single contigs and thus cause gaps. After sequencing, two repeat regions (R1 and R2, Figure 3A) were assembled into the R1/R2 repeat contig (Figure 3B), and ContigScape reported all of its possible linkages with other regions (1–4, Figure 3C–D). Further PCR validation guided by this predicted linkage would exclude the incorrect relationships and result in a final correct consensus sequence. The repeat contigs in ContigScape are shown in red (Figure 3D) to distinguish them from the normal contigs shown in dark blue (default setting). In addition, the number of reads connecting two contigs is labeled with linkage edges, and the linkage reliability is illustrated by variable edge thickness.

The key feature of ContigScape is to determine the linkage of two contigs assembled from 454 or Illumina reads. An ‘Ace’ file can be opened directly by ContigScape and the relationship of contigs can be saved as a CRS format (see sample, tabbed.txt, tabbedCov.txt, Additional file 1). The CRS format includes two files, and each contains three columns. ‘tabbed.txt’ contains the number of connections among contigs, and ‘tabbedCov.txt’ describes the length and coverage of contigs. The ‘tabbed.txt’ is similar to AGP file and describes how the chromosomes and scaffolds were assembled from the component contigs, but does not require contigs to be sorted in advance. It will produce an original graph after loading the two files, and a final graph needed for the layout function of Cytoscape. Researchers can also obtain the CRS information by converting the results from GRASS, SSPACE, OPERA and MIP scaffolders.

Another prominent characteristic of ContigScape is the calculation of the coverage of contigs and the subsequent definition of the contig whose coverage exceeded two fold above the average, denoted as ‘repeat contig’. Each contig is represented by one edge and two nodes, with ‘XS’ and ‘XE’ indicating the 5’ end (Start) and 3’ end (End) of contigX (X represents a number), respectively. The linkage (reads) is represented by a sole edge whose thickness varies based on the number of supporting reads. The number on the edge of contigs indicates the contig length, whereas the number on the edge of linkages indicates the number of linking reads.

Application of technology to display 454 contigs and scaffolding by mate-pair reads

We have used this tool for the visualization of eleven genomes (Table 2, Figure 5), accelerating the completion of these genomes (nine of them have been published). After de novo assembly by 454 Newbler, researchers can estimate the complexity of specific genomes and the difficulty of gap closing with global views. In Figure 5, we see significant differences in the assembly of eleven genomes due to variance in the number of total contigs and repeat contigs. In addition, ContigScape has been applied to gap closing of an additional 40 genomes (Figure 6); the network of contigs in Streptomyces, Leptospira and Ralstonia is complex, whereas the contig graphs of Brucella, Mycoplasma and Ketogulonicigeniumis is simple. These genomes comprised bacteria, archaea, virus and fungi. It was clear that the gap closing for A. hospitalis W1 was easy. In the graph of A. hospitalis W1, we saw that the 28-kb contig3 was a tandem repeat, which had previously been identified as an integrated plasmid [26]. It is easy to determine if the plasmid is circular and if the copy number exceeds two, such as A. orientalis HCCB10007 and E.tarda EIB202 [25]. The 24th graph of Figure 6 shows four circular plasmids composed of only one contig. There was also a high-copy-number contig in the graph of Mycobacterium tuberculosis CCDC5079, and BLAST identified it as IS6110, an insertion element. The 14 rRNA operons of Bacillus thuringiensis BMB171 [24], each of approximately 5 kb in length, can also be clearly displayed (Figure 5). There were also many independent and closed rings in the assembly graph of Cotesia vestalis Bracovirus[27], which were identified as 35 non-redundant circular genome segments. The number of contigs in the fungus Cordyceps militaris[29] exceeded 2,000, therefore the contigs need further scaffolding.

We applied ContigScape to a recently assembled Streptomyces sp genome with 111 contigs sequenced by Roche 454 without scaffolding. We added seven contigs (contig140, 141, 142, 143, 144, 145 and 146) into the two CRS files to show different plasmids (Figure 1B). After processing, we found 25 repeat contigs, constituting six plasmids, 8 rRNA operons and one telomere (contig28, Figure 1B2). The remaining repeats include IS elements, phage or other sequences. Figure 1A shows that 52 nodes have no linkage, and they need additional scaffolding information. Therefore, PCR is necessary to fill the remaining gaps. Any relationships requiring validation are indicated by a green edge.

Judging whether a repeat contig was from chromosome or plasmid mainly depended on the linkage information of two ends of this contig. Four different types were shown in Figure 1B: 1). Repeat contigs connected in a circular fashion (Panel 3), 2). Individual contig connected itself without anyone else (Panel 4 and 6), 3). One end of repeat contig having no linkage to any other contigs, usually representing linear chromosome telomere or linear plasmid end (Panel 1 and 2), 4). A linear plasmid composed of only one repeat contig without connections to any contigs (Panel 5). While if a plasmid is linear and single copy, ContigScape cannot distinguish it. We can estimate whether or not a contig was a plasmid effectively based on above described situation in our experience. Of course researcher must confirm whether it is a plasmid or not by PCR, sequencing and annotation.

In Figure 1B, 143E has connections with 142E and 144E (Panel 3). But the number of connections (800) between 143E and 142E is more than that (10) between 143E and 144E. In this case, the latter might be a nonspecific connection caused by little overlap among the reads. Additionally, Figure 1B shows that contig78 in the linear plasmid 80E-80S-78E-78S-54E-54S also has another copy in the chromosome (Panel 1).

We also applied this program to another Streptomyces sp genome with 145 contigs sequenced by Roche 454 with mate-pair information (Figure 7). We can better interpret the relationship between contigs by using mate-pair reads. Figure 7C represents a linear chromosome with an 18 kb repeat at the ends (telomeres).

Display functionality of ContigScape

There are several unique features of ContigScape for microbial genome analysis (Figure 1). In particular, the “find genomic features” function may identify contigs belonging to plasmid/terminal repeats, determine whether the plasmid was linear or circular, and counting the read coverage of this plasmid (Figure 1B). Second, ContigScape may determine the locations of the ends of linear chromosomes based on a repeat contig where in one end has two edges and the other has none. After the ‘Ace’ file is loaded, the genomic structure network can be displayed, including the linkage of contigs, contig size and number of repeats. Meanwhile, another plugin called Network Analyzer [30] can be used to determine the complexity of the network (genome), and thus estimate the amount of work required to complete the genome. When viewing the graph, the 1,000 base pairs of both 5’-end and 3’-end can be loaded, with 20 “N” linking them representing the middle sequences. Clicking the edge of two contigs, the sequence containing corresponding contigs’ ends can also be displayed. The displayed sequence can be used to design primers in ContigScape and perform blast against NCBI database. In addition, the user can open “edit panel” to edit the connections of the network. In addition to gap closing in bacterial genomes, complete BAC or plasmid sequences can also be finished using ContigScape. It can also display if a CRS file, converted from scaffolding results using different methods, was imported. The workflow of ContigScape is shown in Figure 8. Other functions of ContigScape are described in an Additional file 1 (see ContigScape manual).