Briefings in BioinformaticsBioinformaticsPeer-reviewed journal article
NASTRA: Accurate analysis of short tandem repeat markers by nanopore sequencing with repeat-structure-aware algorithm
Zilin ReniD, Jiarong ZhangiD, Yixiang Zhang, Tingting YangiD, Pingping SuniD, Jiguo Xue, Xiaochen BoiD, Bo Zhou, Jiangwei YaniD, Ming NiiD
Abstract
Forensic short-tandem repeats (STR) genetic markers are multi-allelic and widely utilized for individual identification, kinship testing, and cell-line authentication. Nanopore sequencing, known for its portability, is emerging as a promising approach for STR typing, facilitating real-time and in-field testing. However, its efficacy is often hampered by sequencing noise. Previous methods rely on alignment-based genotyping, necessitating known alleles, which limits their applicability to unknown alleles. Here, we introduced NASTRA, an innovative allele reference-free tool for precise germline analysis of STR genetic markers. NASTRA incorporates a recursive algorithm to infer repeat structures of allele sequences using only known repeat motifs. Our tests, conducted on 80 individual samples and 8 DNA standards, have demonstrated NASTRAs exceptional 100% accuracy in genotyping nearly all diploid STRs across various multiplex kits and flow cells. It surpasses alignment-based methods in accuracy and speed. In a paternity testing case study, NASTRA accurately identified three relationships among six individuals within an 18-minute sequencing duration. These results underscore NASTRAs ability to perform STR analysis on both NGS and nanopore sequencing platforms, significantly enhancing the utility of nanopore sequencing in relevant applications. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/565630v3_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@296e89org.highwire.dtl.DTLVardef@180b6forg.highwire.dtl.DTLVardef@96bf21org.highwire.dtl.DTLVardef@de1b1d_HPS_FORMAT_FIGEXP M_FIG C_FIG
- assay: long-read sequencing
- research focus: variant calling
- approach: statistical model
- approach: experimental assay
- Citations
- 11
- FWCI
- 1.49
- Field percentile
- top 18%
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