Estimation of genetic diversity in viral populations from next generation sequencing data with extremely deep coverage

In this paper we propose a method and discuss its computational implementation as an integrated tool for the analysis of viral genetic diversity on data generated by high-throughput sequencing. Most methods for viral diversity estimation proposed so far are intended to take benefit of the longer reads produced by some NGS platforms in order to estimate a population of haplotypes. Our goal here is to take advantage of distinct virtues of a certain kind of NGS platform - the platform SOLiD (Life Technologies) is an example - that has not received much attention due to the short length of its reads, which renders haplotype estimation very difficult. However, this kind of platform has a very low error rate and extremely deep coverage per site and our method is designed to take advantage of these characteristics. We propose to measure the populational genetic diversity through a family of multinomial probability distributions indexed by the sites of the virus genome, each one representing the populational distribution of the diversity per site. The implementation of the method focuses on two main optimization strategies: a read mapping/alignment procedure that aims at the recovery of the maximum possible number of short-reads; the estimation of the multinomial parameters through a Bayesian approach, which, unlike simple frequency counting, allows one to take into account the prior information of the control population within the inference of a posterior experimental condition and provides a natural way to separate signal from noise, since it automatically furnishes Bayesian confidence intervals. The methods described in this paper have been implemented as an integrated tool called Tanden (Tool for Analysis of Diversity in Viral Populations).Comment: 30 pages, 5 figures, 2 tables, Tanden is written in C# (Microsoft), runs on the Windows operating system, and can be downloaded from: http://tanden.url.p

Estimation of genetic diversity in viral populations from next generation sequencing data with extremely deep coverage

Submitted by Nuzia Santos ([email protected]) on 2016-08-23T18:40:07Z No. of bitstreams: 1 ve_Zukurov_Jean_Estimation_CPqRR_2016.pdf: 2592734 bytes, checksum: 828bb4463862e79c125c937639dc1451 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2016-08-23T18:44:25Z (GMT) No. of bitstreams: 1 ve_Zukurov_Jean_Estimation_CPqRR_2016.pdf: 2592734 bytes, checksum: 828bb4463862e79c125c937639dc1451 (MD5)Made available in DSpace on 2016-08-23T18:44:25Z (GMT). No. of bitstreams: 1 ve_Zukurov_Jean_Estimation_CPqRR_2016.pdf: 2592734 bytes, checksum: 828bb4463862e79c125c937639dc1451 (MD5) Previous issue date: 2016Universidade Federal de São Paulo. Escola Paulista de Medicina. Departamento de Medicina. São Paulo, SP, Brasil.Universidade Federal de São Paulo. Escola Paulista de Medicina. Departamento de Microbiologia. São Paulo, SP, Brasil/ Universidade Federal Rural do Rio de Janeiro. Departamento de Microbiologia e Imunologia Veterinária. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Grupo de Genomica e Biologia Computacional. Belo Horizonte, MG, Brasil.Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Grupo de Genomica e Biologia Computacional. Belo Horizonte, MG, Brasil.Universidade Federal de São Paulo. Escola Paulista de Medicina. Departamento de Medicina. São Paulo, SP, Brasil/Universidade Federal de São Paulo. Escola Paulista de Medicina. Departamento de Microbiologia. São Paulo, SP, Brasil.Universidade Federal de São Paulo. Escola Paulista de Medicina. Departamento de Informática em Saúde. São Paulo, SP, Brasil/Universidade Federal de São Paulo. Escola Paulista de Medicina. Laboratório de Biocomplexidade e Genômica Evolutiva. São Paulo, SP, BrasilBACKGROUND: In this paper we propose a method and discuss its computational implementation as an integrated tool for the analysis of viral genetic diversity on data generated by high-throughput sequencing. The main motivation for this work is to better understand the genetic diversity of viruses with high rates of nucleotide substitution, as HIV-1 and Influenza. Most methods for viral diversity estimation proposed so far are intended to take benefit of the longer reads produced by some next-generation sequencing platforms in order to estimate a population of haplotypes which represent the diversity of the original population. The method proposed here is custom-made to take advantage of the very low error rate and extremely deep coverage per site, which are the main features of some neglected technologies that have not received much attention due to the short length of its reads, which precludes haplotype estimation. This approach allowed us to avoid some hard problems related to haplotype reconstruction (need of long reads, preliminary error filtering and assembly). RESULTS: We propose to measure genetic diversity of a viral population through a family of multinomial probability distributions indexed by the sites of the virus genome, each one representing the distribution of nucleic bases per site. Moreover, the implementation of the method focuses on two main optimization strategies: a read mapping/alignment procedure that aims at the recovery of the maximum possible number of short-reads; the inference of the multinomial parameters in a Bayesian framework with smoothed Dirichlet estimation. The Bayesian approach provides conditional probability distributions for the multinomial parameters allowing one to take into account the prior information of the control experiment and providing a natural way to separate signal from noise, since it automatically furnishes Bayesian confidence intervals and thus avoids the drawbacks of preliminary error filtering. CONCLUSIONS: The methods described in this paper have been implemented as an integrated tool called Tanden (Tool for Analysis of Diversity in Viral Populations) and successfully tested on samples obtained from HIV-1 strain NL4-3 (group M, subtype B) cultivations on primary human cell cultures in many distinct viral propagation conditions

Natural antibody--complement dependent neutralization of bovine herpesvirus 4 by human serum

In contrast to most gammaherpesviruses, Bovine herpesvirus 4 (BoHV-4) has a broad range of host species both in vitro and in vivo. Several in vitro studies demonstrated that some human cell lines are sensitive or even permissive to BoHV-4. These observations led to the hypothesis that cross-species transmission of BoHV-4 could lead to human infections. In the present study, we investigate the sensitivity of BoHV-4 to neutralization by naïve human sera in order to determine if humans exhibit innate anti-viral activities against this virus. Our results demonstrate that human sera from naïve individuals, in contrast to the sera of naïve subjects from various animal species, neutralize BoHV-4 efficiently. A series of complementary experiments were performed to unravel the mechanism(s) of this neutralization. The data obtained in this study demonstrates that human serum neutralizes BoHV-4 in a complement dependent manner activated by natural antibodies raised against the Galalpha1-3Galbeta1-4GlcNAc-R epitope expressed by bovine cell