E. coli 36 bp

Escherichia coli K12 MG1655. The E. coli MG1655 consists of a circular chromosome of 4,639,675 bp in length.

Read source

The illuminia read data of E. coli (Paired-end 36 bp sequencing library with 200 bp inserts) were downloaded from Sequence Read Archive (SRA). More than 20.8 M reads

Sequence assembly

• Set1 (Different Assemblers)

Merged File: Set1_Contig

The above assemblers together with the parameter setting have been selected for de novo assembling of E. coli. After assembly, we discarded contigs with less than 100bp and evaluated the accuracy of the assemblies based on the Mauve Assembly Matrices (the results are shown below). In this set of data, we have different sequence assemblies, each was generated by the different assembler. Because the same assembler performs differently over varying parameter settings, such as kmer, we have tried different parameters for Abyss and SOAPdenovo in the following sets.

• Set2 (Different parameters for Abyss - the assembler provides the lowest number of contigs in Set1)

Merged File: Set2_Contig

• Set3 (Different parameters for SOAPdenovo - the assembler provides the largest number of contigs in Set1)

Merged File: Set3_Contig

Contig integrator

• CISA

The input file for CISA is an assembled set of contigs, e.g., the set1 contains the contigs obtained from Abyss, CLC, Edena, SOAPdenovo, and Velvet.

The integrated contigs generated by CISA can be directly downloaded via the Download link.

• MAIA

  maia('./assembly_list.txt','./NC_000913.fna')
  

assembly_list.txt:

Edena	./Edena_contigs.fa	2
SOAP    ./SOAP_contigs.fa   2
Velvet  ./Velvet.fa 2
CLC ./CLC.fa    2
Abyss	./Abyss_contigs.fa	3

A file named maia_assembly.fa was generated, containing a draft genome of 4640055 bp with 126761 uncalled bases (Ns). We split the genome into contigs (at >10Ns) and got the set of contigs maia.fa.

In using MAIA for other examples, we found that Matlab crashed while the recursion reached its limitation. We therefore split the reference genome into several parts, and then performed MAIA.

 maia('./assembly_list.txt','./NC_000913_1.fna')
 maia('./assembly_list.txt','./NC_000913_2.fna')
 maia('./assembly_list.txt','./NC_000913_3.fna')

The split references and the integrated results can be downloaded maia_ecoli_36.

• minimus2 and GAA

All_M2_GAA
Beacuase minimus2 and GAA merge two assemblies at a time, we iteratively integrate the five assemblies in random order.
minimus2: C_S_V_A_E, A_C_V_S_E, S_V_E_C_A, A_E_C_V_S, A_E_S_C_V, E_V_S_C_A, E_V_C_A_S, V_E_S_A_C, V_S_E_A_C, A_E_V_C_S
GAA: E_S_C_V_A, V_S_E_C_A, V_S_C_E_A, S_V_C_E_A, V_E_A_S_C, E_C_V_S_A, V_A_S_C_E, V_C_E_S_A, A_S_C_V_E, S_C_V_E_A

Evaluation

• Benchmark genome

Eshcherichia coli K12 MG1655

• Evaluated by Mauve Assembly Metrics to calculate the values for the left columns of "Blast_IntactCDS"

How to score genome assemblies using the Mauve system

• Evaluated by Blast with Features
• Evaluated by GAGE to calculate the values for the right columns of "Blast_IntactCDS"

Gage

• Score with Mauve Assembly Metrics, N50, Blast and GAGE:

Set1

[^] Please note that the ContigN50 calculated by Mauve Assembly Metrics is incorrect (off-by-one error). We have followed the definition of N50 (A contig N50 is calculated by first ordering every contig by length from longest to shortest. Next, starting from the longest contig, the lengths of each contig are summed, until this running sum equals one-half of the total length of all contigs in the assembly. The contig N50 of the assembly is the length of the shortest contig in this list.) [ref to calculate N50s.

[^#] Please note that GAA and minimus2 were designed to merge two assemblies at a time, we thus performed all runs and took the average scores.

[*] Please note that the scores of minimus2 and GAA were taken from the average of ten random combinations (details).

CISA integrates the five assemblies (Abyss, CLC, Edena, SOAPdenovo and Velvet from the outer to the inner) and sequentially generates the processed contigs after phase (1), (2), (3) and (4):

We have visually inspected the assemblies against the reference genome (NC_000913) by using graphic representations, e.g. dot plots. Therefore, we knew that the largest contig generated by minimus2(A,C,E,S,V) was misassembled. Moreover, we found that the merging order dramatically influences the result of minimus2.

Minimus2 firstly merges SOAPdenovo (the inner) with CLC (the outer), then merges the output (the inner) with Velvet (the outer) in the second run, merges the output (the inner) with Edena (the outer) in the third run, finally merges the output (the inner) with Abyss (the outer) in the fourth run and generates the integrated contigs.

Set2-Set3

As can be seen here, CISA can successfully integrate the sets of contigs and reduce the number of contigs. However, in comparison with integrating assemblies generated from different assemblers (Set 1), varying assemble parameters is less efficient (in the case of Set 2 or Set3) in completing the genome.