The Plant JournalGenomicsPeer-reviewed journal article
Structural variation discovery in wheat using PacBio high-fidelity sequencing
Zhiliang ZhangiD, Jijin ZhangiD, Lipeng KangiD, Xuebing Qiu, Song Xu, Jun Qiang XuiD, Yafei GuoiD, Zelin Niu, Beirui NiuiD, Aoyue BiiD, Xuebo ZhaoiD, Daxing XuiD, Jing WangiD, Changbin YiniD, Fei LüiD
Abstract
BackgroundStructural variations (SVs) pervade plant genomes and contribute substantially to the phenotypic diversity. However, most SVs were ineffectively assayed because of their complex nature and the limitations of early genomic technologies. The recent advance in third-generation sequencing, particularly the PacBio high-fidelity (HiFi) sequencing technology, produces highly accurate long-reads and offers an unprecedented opportunity to characterize SVs structure and functionality. As HiFi sequencing is relatively new to population genomics, it is imperative to evaluate and optimize HiFi sequencing based SV detection before applying the technology at scale. ResultsWe sequenced wheat genomes using HiFi reads, followed by a comprehensive evaluation of mainstream long-read aligners and SV callers in SV detection. The results showed that the accuracy of deletion discovery is markedly influenced by callers, which account for 87.73% of the variance, while both aligners (38.25%) and callers (49.32%) contributed substantially to the accuracy variance for insertions. Among the aligners, Winnowmap2 and NGMLR excelled in detecting deletions and insertions, respectively. For SV callers, SVIM achieved the best performance. We demonstrated that combining the aligners and callers mentioned above is optimal for SV detection. Furthermore, we evaluated the effect of sequencing depth on the accuracy of SV detection, showing that low-coverage HiFi sequencing is sufficiently robust for high-quality SV discovery. ConclusionsThis study thoroughly evaluated SV discovery approaches using HiFi reads, establishing optimal workflows to investigate structural variations in the wheat genome. The notable accuracy of SV discovery from low-coverage HiFi sequencing indicates that skim HiFi sequencing is effective and preferable to characterize SVs at the population level. This study will help advance SV discovery and decipher the biological functions of SVs in wheat and many other plants.
- organism: plant (other)
- assay: long-read sequencing
- research focus: variant calling
- research focus: benchmarking
- approach: statistical model
- approach: benchmark study
- Citations
- 10
- FWCI
- 2.38
- Field percentile
- top 11%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Genotyping of structural variation using PacBio high-fidelity sequencing
Zhiliang Zhang, Jijin Zhang, … Fei Lü·bioRxiv·Oct 28, 2021
- Improved structural variant discovery in hard-to-call regions using sample-specific string detection from accurate long reads
Luca Denti, Parsoa Khorsand, … Rayan Chikhi·bioRxiv·Feb 12, 2022
- A comprehensive benchmarking of WGS-based structural variant callers
Varuni Sarwal, Sebastian Niehus, … Serghei Mangul·bioRxiv·Apr 16, 2020
- NextSV: a meta-caller for structural variants from low-coverage long-read sequencing data
Fang Li, Jiang Yong Hu, … Kai Wang·BMC BioinformaticsPeer-reviewed·May 23, 2018
- Sawfish: Improving long-read structural variant discovery and genotyping with local haplotype modeling
Christopher T. Saunders, James Holt, … Michael A. Eberle·BioinformaticsPeer-reviewed·Mar 29, 2025
- VISTA: An integrated framework for structural variant discovery
Varuni Sarwal, Seungmo Lee, … Serghei Mangul·Briefings in BioinformaticsPeer-reviewed·Jul 25, 2024