Structural variation discovery in wheat using PacBio high‐fidelity sequencing

Structural variations (SVs) pervade plant genomes and contribute substantially to the phenotypic diversity. However, most SVs were ineffectively assayed due to their complex nature and the limitations of early genomic technologies. By applying the PacBio high-fidelity (HiFi) sequencing for wheat genomes, we performed a comprehensive evaluation of mainstream long-read aligners and SV callers in SV detection. The results indicated that the accuracy of deletion discovery is markedly influenced by callers, accounting for 87.73% of the variance, whereas 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, revealing that low-coverage HiFi sequencing is sufficiently robust for high-quality SV discovery. This study thoroughly evaluated SV discovery approaches and established optimal workflows for investigating structural variations using low-coverage HiFi sequencing in the wheat genome, which will advance SV discovery and decipher the biological functions of SVs in wheat and many other plants.

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Publication Details

Journal
The Plant Journal
Published
2024-09-06
DOI
https://doi.org/10.1111/tpj.17011
Citations
7
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
1.40

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article

Structural variation discovery in wheat using PacBio high‐fidelity sequencing

Beirui Niu, Daxing Xu, Jijin Zhang, Lipeng Kang et al.
7 citations
The Plant Journal
Genomics and Phylogenetic Studies
1.40
article

Structural variation discovery in wheat using PacBio high‐fidelity sequencing

Beirui Niu, Daxing Xu, Jijin Zhang, Lipeng Kang, Aoyue Bi, Yafei Guo, Fei Lü, Xuebing Qiu, Xuebo Zhao, Jun Xu, Jing Wang, Zhiliang Zhang, Changbin Yin, Xu Song, Zelin Niu
article en
7 citations

Abstract

Structural variations (SVs) pervade plant genomes and contribute substantially to the phenotypic diversity. However, most SVs were ineffectively assayed due to their complex nature and the limitations of early genomic technologies. By applying the PacBio high-fidelity (HiFi) sequencing for wheat genomes, we performed a comprehensive evaluation of mainstream long-read aligners and SV callers in SV detection. The results indicated that the accuracy of deletion discovery is markedly influenced by callers, accounting for 87.73% of the variance, whereas 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, revealing that low-coverage HiFi sequencing is sufficiently robust for high-quality SV discovery. This study thoroughly evaluated SV discovery approaches and established optimal workflows for investigating structural variations using low-coverage HiFi sequencing in the wheat genome, which will advance SV discovery and decipher the biological functions of SVs in wheat and many other plants.

The Plant JournalVol. 120(2)
Chinese Academy of Sciences (CN), Institute of Genetics and Developmental Biology (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, National Key Research and Development Program of China, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Institute of Genetics
Openalex Percentile: Top 19%
Genomics and Phylogenetic Studies
1.40
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