Mutations can occur throughout the virus genome and may be beneficial, neutral or deleterious. We are interested in mutations that yield a C next to a G, producing CpG sites. CpG sites are rare in eukaryotic and viral genomes. For the eukaryotes, it is thought that CpG sites are rare because they are prone to mutation when methylated. In viruses, we know less about why CpG sites are rare. A previous study in HIV suggested that CpG-creating transition mutations are more costly than similar non-CpG-creating mutations. To determine if this is the case in other viruses, we analyzed the allele frequencies of CpG-creating and non-CpG-creating mutations across various strains, subtypes, and genes of viruses using existing data obtained from Genbank, HIV Databases, and Virus Pathogen Resource. Our results suggest that CpG sites are indeed costly for most viruses. By understanding the cost of CpG sites, we can obtain further insights into the evolution and adaptation of viruses.
The interaction between human immunodeficiency virus (HIV) and the antibody repertoire (AbR) during chronic infection can provide important information for HIV vaccine research, yet has not been well-characterized on a systems level. We deeply sequenced the HIV population and the AbR of ten HIV-infected, antiretroviral (ART)-naïve individuals, each with 10-20 longitudinal samples spanning 4-14 years. Our unbiased sequencing approach identified partitions of AbRs showing evidence of interaction with autologous HIV populations. We show that these HIV-associated partitions are enriched for the V gene segments of known HIV broadly neutralizing antibodies (bnAbs), indicating that the HIVresponding component of the AbR can be identified via time-series genetic data. Despite this evidence for larger-scale AbR/HIV interactions at the sub-population level, we found little to no evidence for coevolution. This suggests that coevolution is either rare, or hard to detect, which has important vaccine design implications.
The societal challenges posed by a growing human population and climate change necessitate technical advances in plant science. Plant research makes vital contributions to society by advancing technologies that improve agricultural food production, biological energy capture and conversion, and human health. However, the plant biology community lacks a comprehensive understanding of molecular machinery, including their locations within cells, distributions and variations among different cell types, and real‐time dynamics. Fortunately, rapid advances in molecular methods, imaging, proteomics, and metabolomics made in the last decade afford unprecedented opportunities to develop a molecular‐level map of plant cells with high temporal and spatial resolution. The Plant Cell Atlas (PCA) initiative aims to generate a resource that will provide fresh insight into poorly understood aspects of plant cell structure and organization and enable the discovery of new cellular compartments and features. The PCA will be a community resource (http://www.plantcellatlas.org/) that describes the state of various plant cell types and integrates high‐resolution spatio‐temporal information of nucleic acids, proteins, and metabolites within plant cells. This first PCA initiative workshop convened scientists passionate about developing a comprehensive PCA to brainstorm about the state of the field, recent advances, the development of tools, and the future directions of this initiative. The workshop featured invited talks to share initial data, along with broader ideas for the PCA. Additionally, breakout sessions were organized around topics including the conceptual goals of the PCA, technical challenges, and community wants and needs. These activities connected scientists with diverse expertise and sparked important discussions about how to leverage and extend leading‐edge technologies and develop new techniques. A major outcome of the workshop was that the community wishes to redefine concepts of plant cell types and tissues quantitatively. A long‐term goal is to delineate all molecules within the cell at high spatio‐temporal resolution, obtain information about interacting molecular networks, and identify the contribution of these networks to development of the organism as a whole. As a first step, we wish to create comprehensive cellular and subcellular biomolecular maps of transcripts, proteins, and metabolites, track the dynamic interactions of these molecules intra‐ and intercellularly, discern complete states and transitions of specialized cell types, and integrate these disparate data points to generate testable models of cellular function. Ultimately, the PCA initiative will have a substantial positive impact by empowering a broad, diverse group of scientists to forge exciting paths in the field of plant science, facilitating connections with interested stakeholders beyond the scientific community, and enabling new agricultural technologies for a sustainable future.
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