Dataset Information

Genome Assembly of the A-Group Wolbachia in Nasonia oneida Using Linked-Reads Technology.

ABSTRACT: Wolbachia are obligate intracellular bacteria which commonly infect various nematode and arthropod species. Genome sequences have been generated from arthropod samples following enrichment for the intracellular bacteria, and genomes have also been assembled from arthropod whole-genome sequencing projects. However, these methods remain challenging for infections that occur at low titers in hosts. Here we report the first Wolbachia genome assembled from host sequences using 10× Genomics linked-reads technology. The high read depth attainable by this method allows for recovery of intracellular bacteria that are at low concentrations. Based on the depth differences (714× for the insect and 59× for the bacterium), we assembled the genome of a Wolbachia in the parasitoid jewel wasp species Nasonia oneida. The final draft assembly consists of 1,293, 06 bp in 47 scaffolds with 1,114 coding genes and 97.01% genome completeness assessed by checkM. Comparisons of the five Multi Locus Sequence Typing genes revealed that the sequenced Wolbachia genome is the A1 strain (henceforth wOneA1) previously reported in N. oneida. Pyrosequencing confirms that the wasp strain lacks A2 and B types previously detected in this insect, which were likely lost during laboratory culturing. Assembling bacterial genomes from host genome projects can provide an effective method for sequencing bacterial genomes, even when the infections occur at low density in sampled tissues.

SUBMITTER: Wang X

PROVIDER: S-EPMC6821208 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundGenome sequencing yields the sequence of many short snippets of DNA (reads) from a genome. Genome assembly attempts to reconstruct the original genome from which these reads were derived. This task is difficult due to gaps and errors in the sequencing data, repetitive sequence in the underlying genome, and heterozygosity. As a result, assembly errors are common. In the absence of a reference genome, these misassemblies may be identified by comparing the sequencing data to the assembly and looking for discrepancies between the two. Once identified, these misassemblies may be corrected, improving the quality of the assembled sequence. Although tools exist to identify and correct misassemblies using Illumina paired-end and mate-pair sequencing, no such tool yet exists that makes use of the long distance information of the large molecules provided by linked reads, such as those offered by the 10x Genomics Chromium platform. We have developed the tool Tigmint to address this gap.ResultsTo demonstrate the effectiveness of Tigmint, we applied it to assemblies of a human genome using short reads assembled with ABySS 2.0 and other assemblers. Tigmint reduced the number of misassemblies identified by QUAST in the ABySS assembly by 216 (27%). While scaffolding with ARCS alone more than doubled the scaffold NGA50 of the assembly from 3 to 8 Mbp, the combination of Tigmint and ARCS improved the scaffold NGA50 of the assembly over five-fold to 16.4 Mbp. This notable improvement in contiguity highlights the utility of assembly correction in refining assemblies. We demonstrate the utility of Tigmint in correcting the assemblies of multiple tools, as well as in using Chromium reads to correct and scaffold assemblies of long single-molecule sequencing.ConclusionsScaffolding an assembly that has been corrected with Tigmint yields a final assembly that is both more correct and substantially more contiguous than an assembly that has not been corrected. Using single-molecule sequencing in combination with linked reads enables a genome sequence assembly that achieves both a high sequence contiguity as well as high scaffold contiguity, a feat not currently achievable with either technology alone.

Dataset Information

Genome Assembly of the A-Group Wolbachia in Nasonia oneida Using Linked-Reads Technology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets