Detection of mosaic and population-level structural variants with Sniffles2.

TitleDetection of mosaic and population-level structural variants with Sniffles2.
Publication TypeJournal Article
Year of Publication2024
AuthorsSmolka, M, Paulin, LF, Grochowski, CM, Horner, DW, Mahmoud, M, Behera, S, Kalef-Ezra, E, Gandhi, M, Hong, K, Pehlivan, D, Scholz, SW, Carvalho, CMB, Proukakis, C, Sedlazeck, FJ
JournalNat Biotechnol
Date Published2024 Jan 02

Calling structural variations (SVs) is technically challenging, but using long reads remains the most accurate way to identify complex genomic alterations. Here we present Sniffles2, which improves over current methods by implementing a repeat aware clustering coupled with a fast consensus sequence and coverage-adaptive filtering. Sniffles2 is 11.8 times faster and 29% more accurate than state-of-the-art SV callers across different coverages (5-50×), sequencing technologies (ONT and HiFi) and SV types. Furthermore, Sniffles2 solves the problem of family-level to population-level SV calling to produce fully genotyped VCF files. Across 11 probands, we accurately identified causative SVs around MECP2, including highly complex alleles with three overlapping SVs. Sniffles2 also enables the detection of mosaic SVs in bulk long-read data. As a result, we identified multiple mosaic SVs in brain tissue from a patient with multiple system atrophy. The identified SV showed a remarkable diversity within the cingulate cortex, impacting both genes involved in neuron function and repetitive elements.

Alternate JournalNat Biotechnol
PubMed ID38168980
PubMed Central ID6868818
Grant ListDP2 MH119424 / MH / NIMH NIH HHS / United States
K23 NS125126 / NS / NINDS NIH HHS / United States
F31 HG011205 / HG / NHGRI NIH HHS / United States
R01 GM132589 / GM / NIGMS NIH HHS / United States
K08 HG008986 / HG / NHGRI NIH HHS / United States