Silva Catarina, Ferrão José, Marques Bárbara, Pedro Sónia, Correia Hildeberto, Valente Ana, Rodrigues António Sebastião, Vieira Luís
Technology and Innovation Unit, Human Genetics Department, National Institute of Health, Avenida Padre Cruz, 1649-016, Lisbon, Portugal.
Comprehensive Health Research Centre, NOVA Medical School, Universidade NOVA de Lisboa, Campo Dos Mártires da Pátria, 130, 1169-056, Lisbon, Portugal.
Mol Cytogenet. 2025 Jul 23;18(1):18. doi: 10.1186/s13039-025-00721-8.
Nanopore sequencing is a technology that holds great promise for identifying all types of human genome variations, particularly structural variations. In this work, we used nanopore sequencing technology to sequence 2 human cell lines at low depth of coverage to call copy number variations (CNV), and compared the results variant by variant with chromosomal microarray (CMA) results.
We analysed sequencing data using CuteSV and Sniffles2 variant callers, compared breakpoints based on hybrid-SNP microarray, nanopore sequencing and Sanger sequencing, and analysed CNV coverage. From a total of 48 high confidence variants (truth set), variant calling detected 79% of the truth set variants, increasing to 86% for interstitial CNV. Simultaneous use of the 2 callers slightly increased variant calling. Both callers performed better when calling CNV losses than gains. Variant sizes from CMA and nanopore sequencing showed an excellent correlation, with breakpoints determined by nanopore sequencing differing by only 20 base pairs on average from Sanger sequencing. Nanopore sequencing also revealed that four variants concealed genomic inversions undetectable by CMA. In the 10 CNV not called in nanopore sequencing, 8 showed coverage evidence of genomic loss or gain, highlighting the need to improve SV calling algorithms performance.
Nanopore sequencing offers advantages over CMA for structural variant detection, including the identification of multiple variant types and their breakpoints with increased precision. However, further improvements in variant calling algorithms are still needed for nanopore sequencing to become a highly robust and standardized approach for a comprehensive analysis of genomic structural variation.
纳米孔测序是一项在识别所有类型的人类基因组变异,尤其是结构变异方面极具潜力的技术。在本研究中,我们使用纳米孔测序技术对2个人类细胞系进行低深度测序以检测拷贝数变异(CNV),并将逐个变异的结果与染色体微阵列(CMA)结果进行比较。
我们使用CuteSV和Sniffles2变异检测工具分析测序数据,基于杂交SNP微阵列、纳米孔测序和桑格测序比较断点,并分析CNV覆盖情况。在总共48个高置信度变异(真值集)中,变异检测发现了79%的真值集变异,对于间质CNV,这一比例增至86%。同时使用这两种检测工具可略微提高变异检测率。在检测CNV缺失时,两种检测工具的表现均优于检测CNV增益时。CMA和纳米孔测序的变异大小显示出极佳的相关性,纳米孔测序确定的断点与桑格测序确定的断点平均仅相差20个碱基对。纳米孔测序还揭示,有四个变异隐藏了CMA无法检测到的基因组倒位。在纳米孔测序未检测到的10个CNV中,有8个显示出基因组缺失或增益的覆盖证据,这突出表明需要提高结构变异检测算法的性能。
在结构变异检测方面,纳米孔测序比CMA具有优势,包括能够识别多种变异类型及其断点,且精度更高。然而,纳米孔测序要成为一种用于全面分析基因组结构变异的高度稳健且标准化的方法,仍需要进一步改进变异检测算法。