Minimum virtual dataset for reproducible triploid de novo genome assembly

Despite technological advancements, whole-genome sequencing remains technically challenging for organisms with higher-ploidy genomes. Therefore, the use of short-read sequencing platforms for this purpose has been attempted, but the conditions that result in poor-quality genomes have not been elucidated. Therefore, in the present study, simulated sequences mimicking the accumulation of insertion/deletion mutations were created to clarify the permissible differences between homologous chromosomes and the k-mer sizes for good-quality genome assembly from short-read sequencing data for triploid species. The results illustrated that a narrow range of k-mers permits the generation of high-quality assemblies for any level of difference between homologous chromosomes.
This dataset consists of the virtual haploid genome (O.fasta), triploid genome data (reference_sequense), NGS read data (NGS_reads), and assembly results (all_contigs) created in this study.

尽管测序技术已取得长足进步，但针对高倍性基因组生物体的全基因组测序仍具有较高技术难度。因此，已有研究尝试采用短读长测序平台开展此类工作，但导致基因组组装质量不佳的具体条件仍未阐明。为此，本研究构建了模拟插入/缺失突变累积过程的序列，以厘清三倍体物种利用短读长测序数据实现高质量基因组组装时，同源染色体间的允许差异范围与k元组（k-mer）的最优取值区间。研究结果显示，无论同源染色体间的差异程度如何，仅需选择狭窄区间内的k元组即可获得高质量的基因组组装结果。
本数据集涵盖本研究生成的虚拟单倍体基因组（O.fasta）、三倍体基因组数据（reference_sequense）、NGS读段数据（NGS_reads）以及组装结果（all_contigs）。