Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

TY - JOUR

T1 - Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

AU - Cao, Chen

AU - He, Jingni

AU - Mak, Lauren

AU - Perera, Deshan

AU - Kwok, Devin

AU - Wang, Jia

AU - Li, Minghao

AU - Mourier, Tobias

AU - Gavriliuc, Stefan

AU - Greenberg, Matthew

AU - Morrissy, A. Sorana

AU - Sycuro, Laura K.

AU - Yang, Guang

AU - Jeffares, Daniel C.

AU - Long, Quan

N1 - Publisher Copyright: © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

PY - 2021/5/19

Y1 - 2021/5/19

N2 - DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or "haplotypes." However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

AB - DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or "haplotypes." However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

KW - haplotype reconstruction

KW - linkage disequilibrium

KW - regularization

KW - within-host evolution

UR - http://www.scopus.com/inward/record.url?scp=85107087559&partnerID=8YFLogxK

U2 - 10.1093/molbev/msab037

DO - 10.1093/molbev/msab037

M3 - Article

C2 - 33547786

SN - 0737-4038

VL - 38

SP - 2660

EP - 2672

JO - Molecular Biology and Evolution

JF - Molecular Biology and Evolution

IS - 6

ER -