Accurate assembly of minority viral haplotypes from next-generation sequencing through efficient noise reduction

Abstract

Rapidly evolving RNA viruses continuously produce minority haplotypes that can become dominant if they are drug-resistant or can better evade the immune system. Therefore, early detection and identification of minority viral haplotypes may help to promptly adjust the patient’s treatment plan preventing potential disease complications. Minority haplotypes can be identified using next-generation sequencing, but sequencing noise hinders accurate identification. The elimination of sequencing noise is a non-trivial task that still remains open. Here we propose CliqueSNV based on extracting pairs of statistically linked mutations from noisy reads. This effectively reduces sequencing noise and enables identifying minority haplotypes with the frequency below the sequencing error rate. We comparatively assess the performance of CliqueSNV using an in vitro mixture of nine haplotypes that were derived from the mutation profile of an existing HIV patient. We show that CliqueSNV can accurately assemble viral haplotypes with frequencies as low as 0.1% and maintains consistent performance across short and long bases sequencing platforms.

Strainline: full-length de novo viral haplotype reconstruction from noisy long reads

“…In addition, we also benchmarked reference-guided methods such as PredictHaplo [ 11 ] and CliqueSNV [ 12 ], which can reconstruct haplotypes from long-read sequencing data. However, we failed to run PredictHaplo on our long-read data sets (we have reported the so far unresolved issue at https://github.com/cbg-ethz/PredictHaplo/issues/1 ).…”

“…So far, existing methods for viral quasispecies assembly can be classified into reference-based approaches on the one hand and de novo (reference free) approaches on the other hand; see [ 9 ] for a recent review of related approaches. Reference-based methods such as ShoRAH [ 10 ], PredictHaplo [ 11 ] and CliqueSNV [ 12 ] require high quality reference for reliable reconstruction of strains and, apart from rare exceptions [ 11 , 12 ], mainly have been specializing in processing relatively error-free short read data. Importantly, high quality reference genomes may not be available precisely when they are needed the most: very often, new outbreaks of known viruses are caused by virus variants that significantly deviate from curated reference sequence [ 13 , 14 ].…”

Reduced and highly diverse peripheral HIV-1 reservoir in virally suppressed patients infected with non-B HIV-1 strains in Uganda

“…*** p < 0.001, **** p < 0.0001, n.s., not significant. B Genetic diversity of the inducible cell-associated spliced HIV-1 RNA and proviral DNA based on the number of viral haplotypes using CliqueSNV ( 103 ). Unpaired t test was used to compare the number of unique HIV-1 variants (viral haplotypes) between the reservoir diversity in both cohorts of patients and between individuals infected with subtype B (U.S.) and non-B (Uganda) HIV-1 subtypes.…”

“…Implemented in the DEEPGEN™ Software Tool Suite [ 51 ], p-distance measures the proportion of different nucleotide sites between two pair of sequences (reads). Next, the number and frequency of unique HIV-1 variants (viral haplotypes) within each clinical sample was determined using CliqueSNV [ 103 ], which accurately assemblies both majority and minority (i.e., frequencies as low as 0.1%) haplotypes and estimate their frequencies within the viral population.…”

Rescuing Low Frequency Variants within Intra-Host Viral Populations directly from Oxford Nanopore sequencing data

“…Strainline uses a combination of local De Bruijn graph assembly and overlap extending to generate haplotype genomes 19 . CliqueSNV constructs haplotype sequences by recognizing linked SNVs that are supported by a single read 21 . While both methods claim to assemble genomes at strain level resolution, haplotype phasing from ONT sequencing protocols for SARS-CoV-2 is challenging due to the limited read length from amplicon sequencing (250bp-500bp) 22 , uneven coverage, and susceptibility to bias from single nucleotide variation.…”