Easy and accurate reconstruction of whole HIV genomes from short-read sequence data with shiver

Title: Easy and accurate reconstruction of whole HIV genomes from short-read sequence data with shiver
Authors: Wymant, C
Blanquart, F
Golubchik, T
Gall, A
Bakker, M
Bezemer, D
Croucher, NJ
Hall, M
Hillebregt, M
Ong, SH
Ratmann, O
Albert, J
Bannert, N
Fellay, J
Fransen, K
Gourlay, A
Grabowski, MK
Gunsenheimer-Bartmeyer, B
Günthard, HF
Kivelä, P
Kouyos, R
Laeyendecker, O
Liitsola, K
Meyer, L
Porter, K
Ristola, M
Van Sighem, A
Berkhout, B
Cornelissen, M
Kellam, P
Reiss, P
Fraser, C
BEEHIVE Collaboration
Item Type: Journal Article
Abstract: Studying the evolution of viruses and their molecular epidemiology relies on accurate viral sequence data, so that small differences between similar viruses can be meaningfully interpreted. Despite its higher throughput and more detailed minority variant data, next-generation sequencing has yet to be widely adopted for HIV. The difficulty of accurately reconstructing the consensus sequence of a quasispecies from reads (short fragments of DNA) in the presence of large between- and within-host diversity, including frequent indels, may have presented a barrier. In particular, mapping (aligning) reads to a reference sequence leads to biased loss of information; this bias can distort epidemiological and evolutionary conclusions. De novo assembly avoids this bias by aligning the reads to themselves, producing a set of sequences called contigs. However contigs provide only a partial summary of the reads, misassembly may result in their having an incorrect structure, and no information is available at parts of the genome where contigs could not be assembled. To address these problems we developed the tool shiver to pre-process reads for quality and contamination, then map them to a reference tailored to the sample using corrected contigs supplemented with the user's choice of existing reference sequences. Run with two commands per sample, it can easily be used for large heterogeneous data sets. We used shiver to reconstruct the consensus sequence and minority variant information from paired-end short-read whole-genome data produced with the Illumina platform, for sixty-five existing publicly available samples and fifty new samples. We show the systematic superiority of mapping to shiver's constructed reference compared with mapping the same reads to the closest of 3,249 real references: median values of 13 bases called differently and more accurately, 0 bases called differently and less accurately, and 205 bases of missing sequence recovered. We also successfully applied shiver to whole-genome samples of Hepatitis C Virus and Respiratory Syncytial Virus. shiver is publicly available from
Issue Date: 1-Jan-2018
Date of Acceptance: 1-Jan-2018
ISSN: 2057-1577
Publisher: Oxford University Press (OUP)
Journal / Book Title: Virus Evolution
Volume: 4
Issue: 1
Copyright Statement: © 2018 The Author(s). Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Sponsor/Funder: Bill & Melinda Gates Foundation
Funder's Grant Number: GCAEN 511473
Keywords: HIV
genome assembly
next-generation sequencing
BEEHIVE Collaboration
Publication Status: Published
Conference Place: England
Article Number: vey007
Online Publication Date: 2018-05-18
Appears in Collections:Mathematics
Faculty of Medicine
Faculty of Natural Sciences
Epidemiology, Public Health and Primary Care

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