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.

Project description:BackgroundGenerating high-quality de novo genome assemblies is foundational to the genomics study of model and non-model organisms. In recent years, long-read sequencing has greatly benefited genome assembly and scaffolding, a process by which assembled sequences are ordered and oriented through the use of long-range information. Long reads are better able to span repetitive genomic regions compared to short reads, and thus have tremendous utility for resolving problematic regions and helping generate more complete draft assemblies. Here, we present LongStitch, a scalable pipeline that corrects and scaffolds draft genome assemblies exclusively using long reads.ResultsLongStitch incorporates multiple tools developed by our group and runs in up to three stages, which includes initial assembly correction (Tigmint-long), followed by two incremental scaffolding stages (ntLink and ARKS-long). Tigmint-long and ARKS-long are misassembly correction and scaffolding utilities, respectively, previously developed for linked reads, that we adapted for long reads. Here, we describe the LongStitch pipeline and introduce our new long-read scaffolder, ntLink, which utilizes lightweight minimizer mappings to join contigs. LongStitch was tested on short and long-read assemblies of Caenorhabditis elegans, Oryza sativa, and three different human individuals using corresponding nanopore long-read data, and improves the contiguity of each assembly from 1.2-fold up to 304.6-fold (as measured by NGA50 length). Furthermore, LongStitch generates more contiguous and correct assemblies compared to state-of-the-art long-read scaffolder LRScaf in most tests, and consistently improves upon human assemblies in under five hours using less than 23 GB of RAM.ConclusionsDue to its effectiveness and efficiency in improving draft assemblies using long reads, we expect LongStitch to benefit a wide variety of de novo genome assembly projects. The LongStitch pipeline is freely available at https://github.com/bcgsc/longstitch .

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