Detecting Selection in the HIV-1 Genome during Sexual Transmission Events.

Little is known about whether and how variation in the HIV-1 genome affects its transmissibility. Assessing which genomic features of HIV-1 are under positive or negative selection during transmission is challenging, because very few virus particles are typically transmitted, and random genetic drift can dilute genetic signals in the recipient virus population. We analyzed 30 transmitter-recipient pairs from the Zurich Primary HIV Infection Study and the Swiss HIV Cohort Study using near full-length HIV-1 genomes.

V-pipe: a computational pipeline for assessing viral genetic diversity from high-throughput data.

Motivation: High-throughput sequencing technologies are used increasingly not only in viral genomics research but also in clinical surveillance and diagnostics. These technologies facilitate the assessment of the genetic diversity in intra-host virus populations, which affects transmission, virulence and pathogenesis of viral infections. However, there are two major challenges in analysing viral diversity.

Intra- and Interchain Interactions in (CuAu)CN, (AgAu)CN, and (CuAgAu)CN and Their Effect on One-, Two-, and Three-Dimensional Order.

Mixed-metal cyanides (CuAu)CN, (AgAu)CN, and (CuAgAu)CN adopt an AuCN-type structure in which metal-cyanide chains pack on a hexagonal lattice with metal atoms arranged in sheets. The interactions between and within the metal-cyanide chains are investigated using density functional theory (DFT) calculations, C solid-state NMR (SSNMR), and X-ray pair distribution function (PDF) measurements. Long-range metal and cyanide order is found within the chains: (-Cu-NC-Au-CN-), (-Ag-NC-Au-CN-), and (-Cu-NC-Ag-NC-Au-CN-).

Recent advances in inferring viral diversity from high-throughput sequencing data.

Rapidly evolving RNA viruses prevail within a host as a collection of closely related variants, referred to as viral quasispecies. Advances in high-throughput sequencing (HTS) technologies have facilitated the assessment of the genetic diversity of such virus populations at an unprecedented level of detail. However, analysis of HTS data from virus populations is challenging due to short, error-prone reads.

A Comprehensive Analysis of Primer IDs to Study Heterogeneous HIV-1 Populations.

Determining the composition of viral populations is becoming increasingly important in the field of medical virology. While recently developed computational tools for viral haplotype analysis allow for correcting sequencing errors, they do not always allow for the removal of errors occurring in the upstream experimental protocol, such as PCR errors. Primer IDs (pIDs) are one method to address this problem by harnessing redundant template resampling for error correction.

Estimating Fitness of Viral Quasispecies from Next-Generation Sequencing Data.

The quasispecies model is ubiquitous in the study of viruses. While having lead to a number of insights that have stood the test of time, the quasispecies model has mostly been discussed in a theoretical fashion with little support of data. With next-generation sequencing (NGS), this situation is changing and a wealth of data can now be produced in a time- and cost-efficient manner.

A framework for inferring fitness landscapes of patient-derived viruses using quasispecies theory.

Fitness is a central quantity in evolutionary models of viruses. However, it remains difficult to determine viral fitness experimentally, and existing in vitro assays can be poor predictors of in vivo fitness of viral populations within their hosts. Next-generation sequencing can nowadays provide snapshots of evolving virus populations, and these data offer new opportunities for inferring viral fitness.