FLED: a full-length eccDNA detector for long-reads sequencing data.
FLED: a full-length eccDNA detector for long-reads sequencing data.
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FLED：用于长读长测序数据的全长 eccDNA 检测器。
DOI：
10.1093/bib/bbad388
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发表时间：
2023
影响因子：
9.5
通讯作者：
Bai,Yunfei
中科院分区：
文献类型：
--
作者：
Li,Fuyu;Ming,Wenlong;Lu,Wenxiang;Wang,Ying;Li,Xiaohan;Dong,Xianjun;Bai,Yunfei
考虑到eccDNA及其相应线性DNA的相似性，从短测序读段重建染色体外环状DNA（eccDNA）的全长序列已被证明具有挑战性。以前的测序方法无法实现全长eccDNA的高通量检测。本文提出了一种基于滚环扩增和纳米孔长读段测序技术相结合的eccDNA全长检测（Full-Length eccDNA Detection，FLED）算法。通过FLED分析了七个人上皮细胞和癌细胞系样品，每个样品鉴定了超过5000个全长eccDNA。通过聚合酶链反应（PCR）和桑格测序验证鉴定的eccDNA的结构。与其他已发表的基于纳米孔的eccDNA检测器相比，FLED表现出更高的灵敏度。在肿瘤细胞系中，与eccDNA重叠的基因在肿瘤相关通路中富集，在eccDNA分子上完整基因的上游或下游可预测到顺式调控元件，这些肿瘤相关基因在肿瘤细胞系中表达失调，表明eccDNA在生物学过程中的调控潜力。所提出的方法利用纳米孔长读段，并能够无偏地重建全长eccDNA序列。FLED是使用Python 3实现的，Python 3可以在GitHub（https：//github.com/FuyuLi/FLED）上免费获得。
Reconstructing the full-length sequence of extrachromosomal circular DNA (eccDNA) from short sequencing reads has proved challenging given the similarity of eccDNAs and their corresponding linear DNAs. Previous sequencing methods were unable to achieve high-throughput detection of full-length eccDNAs. Herein, a novel algorithm was developed, called Full-Length eccDNA Detection (FLED), to reconstruct the sequence of eccDNAs based on the strategy that combined rolling circle amplification and nanopore long-reads sequencing technology. Seven human epithelial and cancer cell line samples were analyzed by FLED and over 5000 full-length eccDNAs were identified per sample. The structures of identified eccDNAs were validated by both Polymerase Chain Reaction (PCR) and Sanger sequencing. Compared to other published nanopore-based eccDNA detectors, FLED exhibited higher sensitivity. In cancer cell lines, the genes overlapped with eccDNA regions were enriched in cancer-related pathways andcis-regulatory elements can be predicted in the upstream or downstream of intact genes on eccDNA molecules, and the expressions of these cancer-related genes were dysregulated in tumor cell lines, indicating the regulatory potency of eccDNAs in biological processes. The proposed method takes advantage of nanopore long reads and enables unbiased reconstruction of full-length eccDNA sequences. FLED is implemented using Python3 which is freely available on GitHub (https://github.com/FuyuLi/FLED).