FAIR Header Reference genome: a TRUSTworthy standard.

The lack of interoperable data standards among reference genome data-sharing platforms inhibits cross-platform analysis while increasing the risk of data provenance loss. Here, we describe the FAIR bioHeaders Reference genome (FHR), a metadata standard guided by the principles of Findability, Accessibility, Interoperability and Reuse (FAIR) in addition to the principles of Transparency, Responsibility, User focus, Sustainability and Technology. The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.

DATA RESOURCES AND ANALYSES FAIR Header Reference genome: A TRUSTworthy standard.

The lack of interoperable data standards among reference genome data-sharing platforms inhibits cross-platform analysis while increasing the risk of data provenance loss. Here, we describe the FAIR-bioHeaders Reference genome (FHR), a metadata standard guided by the principles of Findability, Accessibility, Interoperability, and Reuse (FAIR) in addition to the principles of Transparency, Responsibility, User focus, Sustainability, and Technology (TRUST). The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility, and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.

Vesicular Stomatitis Virus Elicits Early Transcriptome Response in Culicoides sonorensis Cells.

Viruses that are transmitted by arthropods, or arboviruses, have evolved to successfully navigate both the invertebrate and vertebrate hosts, including their immune systems. Biting midges transmit several arboviruses including vesicular stomatitis virus (VSV). To study the interaction between VSV and midges, we characterized the transcriptomic responses of VSV-infected and mock-infected Culicoides sonorensis cells at 1, 8, 24, and 96 h post inoculation (HPI). The transcriptomic response of VSV-infected cells at 1 HPI was significant, but by 8 HPI there were no detectable differences between the transcriptome profiles of VSV-infected and mock-infected cells. Several genes involved in immunity were upregulated (ATG2B and TRAF4) or downregulated (SMAD6 and TOLL7) in VSV-treated cells at 1 HPI. These results indicate that VSV infection in midge cells produces an early immune response that quickly wanes, giving insight into in vivo C. sonorensis VSV tolerance that may underlie their permissiveness as vectors for this virus.

An Outsider's Perspective on Why We Climb Mountains and Why Projects Like the i5k Matter.

Initiatives like the i5k are creating evermore genome assemblies. These initiatives are resource heavy, and their justifications and economics deserve attention. Scientifically, these initiatives are important, paving the way for cross-species analysis, requiring the building of new computational analysis and tools, and creating other new resources. However, an open question remains of how we quantitively measure the impact of genomes, and by extension these initiatives. This forum article discusses one such method which is to look at the publications about a species over time, however, this method does not show any signal from a published genome, leaving an open question of how to measure impact.

met v1: expanding on old estimations of biodiversity from eDNA with a new database framework.

A long-standing problem in environmental DNA has been the inability to compute across large number of datasets. Here we introduce an open-source software framework that can store a large number of environmental DNA datasets, as well as provide a platform for analysis, in an easily customizable way. We show the utility of such an approach by analyzing over 1400 arthropod metabarcode datasets. This article introduces a new software framework, met, which utilizes large numbers of metabarcode datasets to draw conclusions about patterns of diversity at large spatial scales. Given more accurate estimations on the distribution of variance in metabarcode datasets, this software framework could facilitate novel analyses that are outside the scope of currently available similar platforms. Database URL https://osf.io/spb8v/.

Combining natural language processing and metabarcoding to reveal pathogen-environment associations.

Cryptococcus neoformans is responsible for life-threatening infections that primarily affect immunocompromised individuals and has an estimated worldwide burden of 220,000 new cases each year-with 180,000 resulting deaths-mostly in sub-Saharan Africa. Surprisingly, little is known about the ecological niches occupied by C. neoformans in nature. To expand our understanding of the distribution and ecological associations of this pathogen we implement a Natural Language Processing approach to better describe the niche of C. neoformans. We use a Latent Dirichlet Allocation model to de novo topic model sets of metagenetic research articles written about varied subjects which either explicitly mention, inadvertently find, or fail to find C. neoformans. These articles are all linked to NCBI Sequence Read Archive datasets of 18S ribosomal RNA and/or Internal Transcribed Spacer gene-regions. The number of topics was determined based on the model coherence score, and articles were assigned to the created topics via a Machine Learning approach with a Random Forest algorithm. Our analysis provides support for a previously suggested linkage between C. neoformans and soils associated with decomposing wood. Our approach, using a search of single-locus metagenetic data, gathering papers connected to the datasets, de novo determination of topics, the number of topics, and assignment of articles to the topics, illustrates how such an analysis pipeline can harness large-scale datasets that are published/available but not necessarily fully analyzed, or whose metadata is not harmonized with other studies. Our approach can be applied to a variety of systems to assert potential evidence of environmental associations.

Yeast grown in continuous culture systems can detect mutagens with improved sensitivity relative to the Ames test.

Continuous culture systems allow for the controlled growth of microorganisms over a long period of time. Here, we develop a novel test for mutagenicity that involves growing yeast in continuous culture systems exposed to low levels of mutagen for a period of approximately 20 days. In contrast, most microorganism-based tests for mutagenicity expose the potential mutagen to the biological reporter at a high concentration of mutagen for a short period of time. Our test improves upon the sensitivity of the well-established Ames test by at least 20-fold for each of two mutagens that act by different mechanisms (the intercalator ethidium bromide and alkylating agent methyl methanesulfonate). To conduct the tests, cultures were grown in small, inexpensive continuous culture systems in media containing (potential) mutagen, and the resulting mutagenicity of the added compound was assessed via two methods: a canavanine-based plate assay and whole genome sequencing. In the canavanine-based plate assay, we were able to detect a clear relationship between the amount of mutagen and the number of canavanine-resistant mutant colonies over a period of one to three weeks of exposure. Whole genome sequencing of yeast grown in continuous culture systems exposed to methyl methanesulfonate demonstrated that quantification of mutations is possible by identifying the number of unique variants across each strain. However, this method had lower sensitivity than the plate-based assay and failed to distinguish the different concentrations of mutagen. In conclusion, we propose that yeast grown in continuous culture systems can provide an improved and more sensitive test for mutagenicity.

Uncovering Effects from the Structure of Metabarcode Sequences for Metagenetic and Microbiome Analysis.

The advent of next-generation sequencing has allowed for higher-throughput determination of which species live within a specific location. Here we establish that three analysis methods for estimating diversity within samples-namely, Operational Taxonomic Units; the newer Amplicon Sequence Variants; and a method commonly found in sequence analysis, minhash-are affected by various properties of these sequence data. Using simulations we show that the presence of Single Nucleotide Polymorphisms and the depth of coverage from each species affect the correlations between these approaches. Through this analysis, we provide insights which would affect the decisions on the application of each method. Specifically, the presence of sequence read errors and variability in sequence read coverage deferentially affects these processing methods.