Hybrid Enterobacteriaceae assemblies using PacBio+Illumina or ONT+Illumina sequencing

Data associated with: De Maio, Shaw, et al. on behalf of the REHAB consortium (2019), Comparison of long-read sequencing technologies in the hybrid assembly of complex bacterial genomes. biorxiv 530824 Illumina sequencing allows rapid, cheap and accurate whole genome bacterial analyses, but short reads (<300 bp) do not usually enable complete genome assembly. Long read sequencing greatly assists with resolving complex bacterial genomes, particularly when combined with short-read Illumina data (hybrid assembly). However, it is not clear how different long-read sequencing methods impact on assembly accuracy. In this study, we compared hybrid assemblies for 20 bacterial isolates, including two reference strains, using Illumina sequencing and long reads from either Oxford Nanopore Technologies (ONT) or from SMRT Pacific Biosciences (PacBio) sequencing platforms. This set of files includes all hybrid assemblies produced using Unicycler with different sequencing approaches and strategies. Each isolate has 8 assemblies = 4 x ONT-Illumina + 4 x PacBio-Illumina. There are a total of 158 assemblies as two assemblies did not finish (8x20 - 2 = 160 - 2 = 158). Assemblies were produced from different long read preparation strategies:• Basic: no filtering or correction of reads (i.e. all long reads available used for assembly). • Corrected: Long reads were error-corrected and subsampled (preferentially selecting longest reads) to 30-40x coverage using Canu (v1.5, https://github.com/marbl/canu) with default options. • Filtered: long reads were filtered using Filtlong (v0.1.1, https://github.com/rrwick/Filtlong) by using Illumina reads as an external reference for read quality and either removing 10% of the worst reads or by retaining 500Mbp in total, whichever resulted in fewer reads. We also removed reads shorter than 1kb and used the --trim and --split 250 options. • Subsampled: we randomly subsampled long reads to leave approximately 600Mbp (corresponding to a long read coverage around 100x). Assembly file names have the following format: ${sample-name}_${preparation-strategy}_${long-read-sequencing}.fastae.g. for sample CFT073 the filtered PacBio-Illumina assembly is: CFT073_filtered_pacbio.fasta See the associated preprint for more details: https://doi.org/10.1101/530824

本数据集关联的文献为De Maio、Shaw等人代表REHAB联盟（REHAB consortium）于2019年发表在预印本平台bioRxiv的《复杂细菌基因组混合组装（hybrid assembly）中长读长测序（long-read sequencing）技术的比较》（编号：bioRxiv 530824）。
Illumina测序可实现快速、低成本且高精度的细菌全基因组分析，但短读长序列（short reads，<300 bp）通常无法完成完整的基因组组装。长读长测序技术可极大助力复杂细菌基因组的解析，尤其当与Illumina短读长数据结合时（即混合组装）。但目前尚不明确不同长读长测序方法对组装准确性的影响。
本研究采用Illumina测序结合牛津纳米孔科技（Oxford Nanopore Technologies, ONT）或PacBio单分子实时测序（SMRT Pacific Biosciences, PacBio）平台产出的长读长数据，对20株细菌分离株（包含2株参考菌株）开展混合组装对比分析。
本数据集包含所有通过Unicycler软件，采用不同测序方法与策略完成的混合组装结果。每个分离株对应8组组装结果：4组基于ONT-Illumina混合策略，4组基于PacBio-Illumina混合策略，总计应生成160组组装结果，但其中2组未完成组装，最终有效组装结果共158组（8×20 - 2 = 160 - 2 = 158）。
本次组装采用了四种不同的长读长制备策略：
1. 基础策略：未对读长进行过滤或校正（即使用所有可用的长读长序列开展组装）；
2. 校正策略：使用Canu（v1.5，https://github.com/marbl/canu）默认参数对长读长序列进行错误校正与二次采样，优先选取最长读长，将覆盖度调整至30~40×；
3. 过滤策略：使用Filtlong（v0.1.1，https://github.com/rrwick/Filtlong），以Illumina读长作为外部参考评估读长质量，过滤掉质量最差的10%读长，或保留总碱基量达500 Mbp的读长（以两者中读长数量更少的方案为准）；同时移除长度短于1 kb的读长，并启用--trim与--split 250参数；
4. 二次采样策略：随机对长读长序列进行二次采样，使其总碱基量约为600 Mbp（对应长读长覆盖度约100×）。
组装文件的命名格式为：${样本名称}_${制备策略}_${长读长测序平台}.fasta。例如，菌株CFT073的过滤策略PacBio-Illumina混合组装结果文件名为：CFT073_filtered_pacbio.fasta。
更多细节可参阅相关预印本：https://doi.org/10.1101/530824