Benchmarking of sequencing technologies defines optimal strategies for genetic variants detection in a human genome.
| Title: | Benchmarking of sequencing technologies defines optimal strategies for genetic variants detection in a human genome. |
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| Authors: | Eveleigh RJM; Canadian Centre for Computational Genomics, McGill University, Montreal, QC, H3A 1A4, Canada.; McGill Genome Centre, Victor Phillip Dahdaleh Institute of Genomic Medicine, Montreal, QC, H3A 1A4, Canada.; Reiling SJ; Department of Human Genetics, McGill University, Montreal, QC, H3A 0C7, Canada.; McGill Genome Centre, Victor Phillip Dahdaleh Institute of Genomic Medicine, Montreal, QC, H3A 1A4, Canada.; Galvez JH; Canadian Centre for Computational Genomics, McGill University, Montreal, QC, H3A 1A4, Canada.; McGill Genome Centre, Victor Phillip Dahdaleh Institute of Genomic Medicine, Montreal, QC, H3A 1A4, Canada.; Bourgey M; Canadian Centre for Computational Genomics, McGill University, Montreal, QC, H3A 1A4, Canada.; Department of Human Genetics, McGill University, Montreal, QC, H3A 0C7, Canada.; DNA to RNA - Health Data Science Platform, McGill University, Montreal, QC, H3A 2R7, Canada.; Ragoussis J; Department of Human Genetics, McGill University, Montreal, QC, H3A 0C7, Canada. ioannis.ragoussis@mcgill.ca.; McGill Genome Centre, Victor Phillip Dahdaleh Institute of Genomic Medicine, Montreal, QC, H3A 1A4, Canada. ioannis.ragoussis@mcgill.ca.; Bourque G; Canadian Centre for Computational Genomics, McGill University, Montreal, QC, H3A 1A4, Canada. guil.bourque@mcgill.ca.; Department of Human Genetics, McGill University, Montreal, QC, H3A 0C7, Canada. guil.bourque@mcgill.ca.; McGill Genome Centre, Victor Phillip Dahdaleh Institute of Genomic Medicine, Montreal, QC, H3A 1A4, Canada. guil.bourque@mcgill.ca.; DNA to RNA - Health Data Science Platform, McGill University, Montreal, QC, H3A 2R7, Canada. guil.bourque@mcgill.ca. |
| Source: | Genome biology [Genome Biol] 2026 Apr 08; Vol. 27 (1). Date of Electronic Publication: 2026 Apr 08. |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: BioMed Central Ltd Country of Publication: England NLM ID: 100960660 Publication Model: Electronic Cited Medium: Internet ISSN: 1474-760X (Electronic) Linking ISSN: 14747596 NLM ISO Abbreviation: Genome Biol Subsets: MEDLINE |
| Imprint Name(s): | Publication: London, UK : BioMed Central Ltd; Original Publication: London : Genome Biology Ltd., c2000- |
| MeSH Terms: | High-Throughput Nucleotide Sequencing*/methods ; High-Throughput Nucleotide Sequencing*/standards ; Sequence Analysis, DNA*/methods ; Sequence Analysis, DNA*/standards ; Genome, Human* ; Genetic Variation*; Genomics/methods ; Humans ; Benchmarking ; INDEL Mutation ; Polymorphism, Single Nucleotide |
| Abstract: | Background: Advances in sequencing technologies continue to improve the resolution and completeness with which human genetic variation can be characterized. Short-read sequencing remains widely used due to its high base accuracy, throughput, and cost efficiency; however, its limited ability to resolve repetitive and structurally complex regions has accelerated adoption of long-read sequencing platforms, including those from Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT).; Results: We systematically compared sequencing technologies and variant calling pipelines for small variants and structural variants across diverse genomic contexts and sequencing depths. Short-read sequencing combined with DRAGEN achieved high accuracy for single-nucleotide variants (SNVs) and indels in well-mapped and moderately complex regions but showed reduced sensitivity and completeness for structural variant detection. In contrast, long-read sequencing platforms demonstrated clear advantages in detecting structural variants and resolving small variants in difficult genomic regions, although challenges remain in specific indel-prone sequence contexts. Among long-read pipelines, PacBio Revio with DeepVariant achieved the highest SNV and indel accuracy genome-wide, while ONT R10 with DeepVariant performed particularly well in clinically relevant loci. Structural variant detection was dominated by long-read optimized callers, with SVIM and Sawfish performing best for PacBio, and Sniffles2 and CuteSV2 for ONT, consistently outperforming short-read-based methods across variant classes and sizes. Coverage analyses indicated that long-read sequencing reached accuracy saturation between 20 × and 45 × , whereas short-read sequencing required more than 60 × coverage to approach maximal genome completeness.; Conclusions: These results provide practical guidance for platform and pipeline selection. Long-read sequencing enables more comprehensive detection and resolution of structural variants and variation in complex genomic regions, while short-read sequencing remains a cost-effective and scalable solution for high-throughput genotyping and clinically focused applications.; (© 2026. The Author(s).) |
| Competing Interests: | Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. |
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| Grant Information: | PJT-191707 Canada Institute of Health Research (CIHR) project grant |
| Contributed Indexing: | Keywords: CMRG; Genome in a bottle; Human reference genome; ILMN; Illumina; LRS; MGI; Nanopore; ONT; PB; PacBio; SRS; Structural variants; T2T; Third generation sequencing; Variant calling; WGS |
| Entry Date(s): | Date Created: 20260409 Date Completed: 20260414 Latest Revision: 20260415 |
| Update Code: | 20260415 |
| PubMed Central ID: | PMC13072666 |
| DOI: | 10.1186/s13059-026-04048-4 |
| PMID: | 41952156 |
| Database: | MEDLINE |
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