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1. Importance of timely metadata curation to the global surveillance of genetic diversity

   https://doi.org/10.1111/cobi.14061  

   Crandall, Eric D. ; Toczydlowski, Rachel H. ; Liggins, Libby ; Holmes, Ann E. ; Ghoojaei, Maryam ; Gaither, Michelle R. ; Wham, Briana E. ; Pritt, Andrea L. ; Noble, Cory ; Anderson, Tanner J. ; et al ( March 2023 , Conservation Biology)

   Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies produce large amounts of genome‐scale genetic diversity data for wild populations, but most (87%) do not include the associated spatial and temporal metadata necessary for them to be reused in monitoring programs or for acknowledging the sovereignty of nations or Indigenous peoples. We undertook a distributed datathon to quantify the availability of these missing metadata and to test the hypothesis that their availability decays with time. We also worked to remediate missing metadata by extracting them from associated published papers, online repositories, and direct communication with authors. Starting with 848 candidate genomic data sets (reduced representation and whole genome) from the International Nucleotide Sequence Database Collaboration, we determined that 561 contained mostly samples from wild populations. We successfully restored spatiotemporal metadata for 78% of these 561 data sets (n = 440 data sets with data on 45,105 individuals from 762 species in 17 phyla). Examining papers and online repositories was much more fruitful than contacting 351 authors, who replied to our email requests 45% of the time. Overall, 23% of our email queries to authors unearthed useful metadata. The probability of retrieving spatiotemporal metadata declined significantly as age of the data set increased. There was a 13.5% yearly decrease in metadata associated with published papers or online repositories and up to a 22% yearly decrease in metadata that were only available from authors. This rapid decay in metadata availability, mirrored in studies of other types of biological data, should motivate swift updates to data‐sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost to conservation science forever.

    

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2. Building a global genomics observatory: Using GEOME (the Genomic Observatories Metadatabase) to expedite and improve deposition and retrieval of genetic data and metadata for biodiversity research

   https://doi.org/10.1111/1755-0998.13269  

   Riginos, Cynthia ; Crandall, Eric D. ; Liggins, Libby ; Gaither, Michelle R. ; Ewing, Rodney B. ; Meyer, Christopher ; Andrews, Kimberly R. ; Euclide, Peter T. ; Titus, Benjamin M. ; Therkildsen, Nina Overgaard ; et al ( October 2020 , Molecular Ecology Resources)

   Genetic data represent a relatively new frontier for our understanding of global biodiversity. Ideally, such data should include both organismal DNA‐based genotypes and the ecological context where the organisms were sampled. Yet most tools and standards for data deposition focus exclusively either on genetic or ecological attributes. The Genomic Observatories Metadatabase (GEOME: geome‐db.org) provides an intuitive solution for maintaining links between genetic data sets stored by the International Nucleotide Sequence Database Collaboration (INSDC) and their associated ecological metadata. GEOME facilitates the deposition of raw genetic data to INSDCs sequence read archive (SRA) while maintaining persistent links to standards‐compliant ecological metadata held in the GEOME database. This approach facilitates findable, accessible, interoperable and reusable data archival practices. Moreover, GEOME enables data management solutions for large collaborative groups and expedites batch retrieval of genetic data from the SRA. The article that follows describes how GEOME can enable genuinely open data workflows for researchers in the field of molecular ecology.

    

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3. Privacy preserving identification of population stratification for collaborative genomic research

   https://doi.org/10.1093/bioinformatics/btad274  

   Dervishi, Leonard ; Li, Wenbiao ; Halimi, Anisa ; Jiang, Xiaoqian ; Vaidya, Jaideep ; Ayday, Erman ( June 2023 , Bioinformatics)

   The rapid improvements in genomic sequencing technology have led to the proliferation of locally collected genomic datasets. Given the sensitivity of genomic data, it is crucial to conduct collaborative studies while preserving the privacy of the individuals. However, before starting any collaborative research effort, the quality of the data needs to be assessed. One of the essential steps of the quality control process is population stratification: identifying the presence of genetic difference in individuals due to subpopulations. One of the common methods used to group genomes of individuals based on ancestry is principal component analysis (PCA). In this article, we propose a privacy-preserving framework which utilizes PCA to assign individuals to populations across multiple collaborators as part of the population stratification step. In our proposed client-server-based scheme, we initially let the server train a global PCA model on a publicly available genomic dataset which contains individuals from multiple populations. The global PCA model is later used to reduce the dimensionality of the local data by each collaborator (client). After adding noise to achieve local differential privacy (LDP), the collaborators send metadata (in the form of their local PCA outputs) about their research datasets to the server, which then aligns the local PCA results to identify the genetic differences among collaborators’ datasets. Our results on real genomic data show that the proposed framework can perform population stratification analysis with high accuracy while preserving the privacy of the research participants.

    

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4. Revisiting conservation units for the endangered mountain yellow-legged frog species complex (Rana muscosa, Rana sierrae) using multiple genomic methods

   https://doi.org/10.1007/s10592-023-01568-5  

   Byrne, Allison Q. ; Rothstein, Andrew P. ; Smith, Lydia L. ; Kania, Hannah ; Knapp, Roland A. ; Boiano, Daniel M. ; Briggs, Cheryl J. ; Backlin, Adam R. ; Fisher, Robert N. ; Rosenblum, Erica Bree ( September 2023 , Conservation Genetics)

   Insights from conservation genomics have dramatically improved recovery plans for numerous endangered species. However, most taxa have yet to benefit from the full application of genomic technologies. The mountain yellow-legged frog species complex, Rana muscosa and Rana sierrae, inhabits the Sierra Nevada mountains and Transverse/Peninsular Ranges of California and Nevada. Both species have declined precipitously throughout their historical distributions. Conservation management plans outline extensive ongoing recovery efforts but are still based on the genetic structure determined primarily using a single mitochondrial sequence. Our study used two different sequencing strategies – amplicon sequencing and exome capture – to refine our understanding of the population genetics of these imperiled amphibians. We used buccal swabs, museum tissue samples, and archived skin swabs to genotype frog populations across their range. Using the amplicon sequencing and exome capture datasets separately and combined, we document five major genetic clusters. Notably, we found evidence supporting previous species boundaries within Kings Canyon National Park with some exceptions at individual sites. Though we see evidence of genetic clustering, especially in the R. muscosa clade, we also found evidence of some admixture across cluster boundaries in the R. sierrae clade, suggesting a stepping-stone model of population structure. We also find that the southern R. muscosa cluster had large runs of homozygosity and the lowest overall heterozygosity of any of the clusters, consistent with previous reports of marked declines in this area. Overall, our results clarify management unit designations across the range of an endangered species and highlight the importance of sampling the entire range of a species, even when collecting genome-scale data. 

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5. Updating splits, lumps, and shuffles: Reconciling GenBank names with standardized avian taxonomies

   https://doi.org/10.1093/ornithology/ukac045  

   Hosner, Peter A ; Zhao, Min ; Kimball, Rebecca T ; Braun, Edward L ; Burleigh, J Gordon ( August 2022 , Ornithology)

   Abstract Biodiversity research has advanced by testing expectations of ecological and evolutionary hypotheses through the linking of large-scale genetic, distributional, and trait datasets. The rise of molecular systematics over the past 30 years has resulted in a wealth of DNA sequences from around the globe. Yet, advances in molecular systematics also have created taxonomic instability, as new estimates of evolutionary relationships and interpretations of species limits have required widespread scientific name changes. Taxonomic instability, colloquially “splits, lumps, and shuffles,” presents logistical challenges to large-scale biodiversity research because (1) the same species or sets of populations may be listed under different names in different data sources, or (2) the same name may apply to different sets of populations representing different taxonomic concepts. Consequently, distributional and trait data are often difficult to link directly to primary DNA sequence data without extensive and time-consuming curation. Here, we present RANT: Reconciliation of Avian NCBI Taxonomy. RANT applies taxonomic reconciliation to standardize avian taxon names in use in NCBI GenBank, a primary source of genetic data, to a widely used and regularly updated avian taxonomy: eBird/Clements. Of 14,341 avian species/subspecies names in GenBank, 11,031 directly matched an eBird/Clements; these link to more than 6 million nucleotide sequences. For the remaining unmatched avian names in GenBank, we used Avibase’s system of taxonomic concepts, taxonomic descriptions in Cornell’s Birds of the World, and DNA sequence metadata to identify corresponding eBird/Clements names. Reconciled names linked to more than 600,000 nucleotide sequences, ~9% of all avian sequences on GenBank. Nearly 10% of eBird/Clements names had nucleotide sequences listed under 2 or more GenBank names. Our taxonomic reconciliation is a first step towards rigorous and open-source curation of avian GenBank sequences and is available at GitHub, where it can be updated to correspond to future annual eBird/Clements taxonomic updates. 

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