Using novel next generation sequencing assembly approaches to reveal new insights into the evolutionary rate and selection of hepatitis B virus
Date Issued
2015
Date
2015
Author(s)
Lin, You-Yu
Abstract
Next-generation sequencing has become the mainstream method of obtaining high quantities of genomic data during the past decade. The increased accessibility of massive data sets has driven up the need for compatible analytic algorithms and software, whereas assembly is the initial and foremost important step when analyzing these data sets. Sequence assembly is especially critical for analyzing data sets generated by the Illumina platform, one of the two most commonly used next-generation sequencing platform along with the 454/Roche pyrosequencing platform. Illumina sequencing produces much larger data sets compared to pyrosequencing, but its shorter read length presents difficulties for de novo assembly. Pathogenic viruses, such as HIV, HBV, and HCV, can be both abundant and greatly diversified within a single host carrier. The high output capability of the Illumina platform is well suited for the detection of genetic variations within viral quasispecies, but its short read length impedes assembly efficiency while the high genetic variation itself also presents challenges for assembly algorithms. Most available de novo assembly algorithms, such as Velvet, were not originally intended for such metagenomic data sets and cannot efficiently assemble viral quasispecies NGS data sets. Therefore, we present a BLAST-based assembly pipeline, BBAP, developed for the assembly of metagenomic data sets. We also propose a hybrid de novo-reference assembly strategy which initially de novo assembles a partial data set, and the resulting scaffolds are then used as reference sequences to assemble the full data set through reference assembly. Previous studies have tried to understand the evolution of HBV, but estimations of long and short term mutation rates have been inconsistent. One possible reason for the observed ambiguity among HBV evolutionary rates is the distinct viral dynamics of HBV. There is limited host immune response during the early immunotolerance phase, and the evolutionary focus of viral quasispecies is on competition between viral variants (colonizers), whereas the host immune response increases during the following immunoclearance phase and shifts selection pressure back to evasion and adaptation of the host immune system (adaptors). Considering that HBV can be vertically transmitted from mother to infant, the HBV quasispecies constantly shifts between immunotolereance and immoclearance phases. We propose that the inconsistency among observed HBV evolutionary rates is due to the constant shifting between colonizer and adaptor roles resulting from rapid changing selection regimes. Furthermore, the relative small HBV genome size and complex genomic structure makes it extreme unlikely for a viral strain to reach dominant states in both phases, therefore a colonization-adaptation trade off (CAT) occurs. We sequenced 12 HBV samples from a three generation family, whom all have vertically transmitted chronic HBV, using next generation sequencing and Sanger sequencing. NGS data sets were assembled by BBAP, and evolutionary rates of both short- and long- term were both estimated while testing the CAT model. Frequent shifting between phases requires the virus to constantly adjust accordingly, which is provided by the error prone polymerase and high replication rate. During the course of chronic hepatitis B virus infection a huge amount of genetic variation is accumulated within the host. Revealing the processes that govern this diversification is also important to our understanding of the HBV evolution. Because BBAP is capable of detecting polymorphisms with frequencies as rare as 10-4, we compared the number of mutations with the expected number of mutations derived from simulations of different assumptions to examine the HBV quasispecies evolutionary dynamics. Overall, BBAP provides efficient and accurate assembly results compared to other assemblers, and results from the BBAP assembly of the study family NGS data sets suggests the CAT model to be able to account for the discrepancies observed among short- and long- term evolutionary rates with both positive and negative selection playing important roles shaping the HBV genome.
Subjects
Hepatitis B Virus
next generation sequencing
sequence assembly
evolutionary rate
natural selection
SDGs
Type
thesis
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