Haplotype assignment of longitudinal viral deep sequencing data using covariation of variant frequencies. Issue 2 (6th October 2022)

• Record Type: Journal Article
• Authors: Venturini, Cristina; Pang, Juanita; Tamuri, Asif U; Roy, Sunando; Atkinson, Claire; Griffiths, Paul; Breuer, Judith; Goldstein, Richard A
• Is Part Of: Virus evolution. Volume 8:Issue 2(2022)
• Publication Date: 2022-10-06
• Subjects: haplotype reconstruction -- next-generation sequencing -- human cytomegalovirus -- norovirus; Viruses -- Evolution -- Periodicals; 579.2138
• DOI: 10.1093/ve/veac093
• Languages: English
• ISSNs: 2057-1577

Abstract

Abstract: Longitudinal deep sequencing of viruses can provide detailed information about intra-host evolutionary dynamics including how viruses interact with and transmit between hosts. Many analyses require haplotype reconstruction, identifying which variants are co-located on the same genomic element. Most current methods to perform this reconstruction are based on a high density of variants and cannot perform this reconstruction for slowly evolving viruses. We present a new approach, HaROLD (HAplotype Reconstruction Of Longitudinal Deep sequencing data), which performs this reconstruction based on identifying co-varying variant frequencies using a probabilistic framework. We illustrate HaROLD on both RNA and DNA viruses with synthetic Illumina paired read data created from mixed human cytomegalovirus (HCMV) and norovirus genomes, and clinical datasets of HCMV and norovirus samples, demonstrating high accuracy, especially when longitudinal samples are available.