Molecular Ecology Resources最新文献

Indigenous peoples have cultivated biodiverse agroecosystems since time immemorial. The rise of metagenomics and high-throughput sequencing technologies in biodiversity studies has rapidly expanded the scale of data collection from these lands. A respectful approach to the data life cycle grounded in the sovereignty of indigenous communities is imperative to not perpetuate harm. In this paper, we operationalize an indigenous data sovereignty (IDS) framework to outline realistic considerations for genomic data that span data collection, governance, and communication. As a case study for this framework, we use arthropod genomic data collected from diversified and simplified farm sites close to and far from natural habitats within a historic Kānaka 'Ōiwi (Indigenous Hawaiian) agroecosystem. Diversified sites had the highest Operational Taxonomic Unit (OTU) richness for native and introduced arthropods. There may be a significant spillover effect between forest and farm sites, as farm sites near a natural habitat had higher OTU richness than those farther away. We also provide evidence that management factors such as the number of Polynesian crops cultivated may drive arthropod community composition. Through this case study, we emphasize the context-dependent opportunities and challenges for operationalizing IDS by utilizing participatory research methods, expanding novel data management tools through the Local Contexts Hub, and developing and nurturing community partnerships-all while highlighting the potential of agroecosystems for arthropod conservation. Overall, the workflow and the example presented here can help researchers take tangible steps to achieve IDS, which often seems elusive with the expanding use of genomic data.

The unprecedented loss of global biodiversity is linked to multiple anthropogenic stressors. New conservation technologies are urgently needed to mitigate this loss. The rights, knowledge and perspectives of Indigenous peoples in biodiversity conservation-including the development and application of new technologies-are increasingly recognised. Advances in germplasm cryopreservation and germ cell transplantation (termed 'broodstock surrogacy') techniques offer exciting tools to preserve biodiversity, but their application has been underappreciated. Here, we use teleost fishes as an exemplar group to outline (1) the power of these techniques to preserve genome-wide genetic diversity, (2) the need to apply a conservation genomic lens when selecting individuals for germplasm cryobanking and broodstock surrogacy and (3) the value of considering the cultural significance of these genomic resources. We conclude by discussing the opportunities and challenges of these techniques for conserving biodiversity in threatened teleost fish and beyond.

We have developed a flexible undergraduate curriculum that leverages the place-based research of environmental microbiomes to increase the number of Indigenous researchers in microbiology, data science and scientific computing. Monitoring Environmental Microbiomes (MEM) provides a curriculum and research framework designed to integrate an Indigenous approach when conducting authentic scientific research and to build interest and confidence at the undergraduate level. MEM has been successfully implemented as a short summer workshop to introduce computing practices in microbiome analysis. Based on self-assessed student knowledge of topics and skills, increased scientific confidence and interest in genomics careers were observed. We propose MEM be incorporated in a scalable course-based research experience for undergraduate institutions, including tribal colleges and universities, community colleges and other minority serving institutions. This coupled curricular and research framework explicitly considers cultural perspectives, access and equity to train a diverse future workforce that is more informed to engage in microbiome research and to translate microbiome science to benefit community and environmental health.

Testing the association between objects is central in ecology, evolution, and quantitative sciences in general. Two types of variables can describe the relationships between objects: point variables (measured on individual objects), and distance variables (measured between pairs of objects). The Mantel test and derived methods have been extensively used for distance variables. Yet, these methods have been criticized due to low statistical power and inflated type I error when spatial autocorrelation is present. Here, we assessed the statistical power between different types of tested variables and the type I error rate over a wider range of autocorrelation intensities than previously assessed, both on univariate and multivariate data. We also illustrated the performance of distance matrix statistics through computational simulations of genetic diversity. We show that the Mantel test and derived methods are not affected by inflated type I error when spatial autocorrelation affects only one variable when investigating correlations, or when either the response or the explanatory variable(s) is affected by spatial autocorrelation while investigating causal relationships. As previously noted, with autocorrelation affecting more variables, inflated type I error could be reduced by modifying the significance threshold. Additionally, the Mantel test has no problem of statistical power when the hypothesis is formulated in terms of distance variables. We highlight that transformation of variable types should be avoided because of the potential information loss and modification of the tested hypothesis. We propose a set of guidelines to help choose the appropriate method according to the type of variables and defined hypothesis.

Advances in sequencing technologies and declining costs are increasing the accessibility of large-scale biodiversity genomic datasets. To maximize the impact of these data, a careful, considered approach to data management is essential. However, challenges associated with the management of such datasets remain, exacerbated by uncertainty among the research community as to what constitutes best practices. As an interdisciplinary team with diverse data management experience, we recognize the growing need for guidance on comprehensive data management practices that minimize the risks of data loss, maximize efficiency for stand-alone projects, enhance opportunities for data reuse, facilitate Indigenous data sovereignty and uphold the FAIR and CARE Guiding Principles. Here, we describe four fictional personas reflecting differing user experiences with data management to identify data management challenges across the biodiversity genomics research ecosystem. We then use these personas to demonstrate realistic considerations, compromises and actions for biodiversity genomic data management. We also launch the Biodiversity Genomics Data Management Hub (https://genomicsaotearoa.github.io/data-management-resources/), containing tips, tricks and resources to support biodiversity genomics researchers, especially those new to data management, in their journey towards best practice. The Hub also provides an opportunity for those biodiversity researchers whose expertise lies beyond genomics and are keen to advance their data management journey. We aim to support the biodiversity genomics community in embedding data management throughout the research lifecycle to maximize research impact and outcomes.

The rise of sedimentary ancient DNA (sedaDNA) studies has opened new possibilities for studying past environments. This groundbreaking area of genomics uses sediments to identify organisms, even in cases where macroscopic remains no longer exist. Managing this substrate in Indigenous Australian contexts, however, requires special considerations. Sediments and soils are often considered as waste by-products during archaeological and paleontological excavations and are not typically regulated by the same ethics guidelines utilised in mainstream 'western' research paradigms. Nevertheless, the product of sedaDNA work-genetic information from past fauna, flora, microbial communities and human ancestors-is likely to be of cultural significance and value for Indigenous peoples. This article offers an opinion on the responsibilities of researchers in Australia who engage in research related to this emerging field, particularly when it involves Indigenous communities. One aspect that deserves consideration in such research is the concept of benefit sharing. Benefit sharing refers to the practice of ensuring that the benefits that arise from research are shared equitably with the communities from which the research data were derived. This practice is particularly relevant in research that involves Indigenous communities, who may have unique cultural and spiritual connections to the research material. We argue that the integration of Traditional Knowledges into sedaDNA research would add enormous value to research and its outcomes by providing genomic outputs alongside and within the rich context of multimillennia oral histories.

Phytophthora agathidicida is a virulent soil pathogen of Aotearoa New Zealand's iconic kauri tree species (Agathis australis (D. Don) Lindl.) and the primary causal agent of kauri dieback disease. To date, only a few control options are available to treat infected kauri that are expressing symptoms of dieback disease. Previous research has identified strains of Penicillium and Burkholderia that inhibited the mycelial growth of P. agathidicida in vitro. However, the mechanisms of inhibition remain unknown. By performing whole genome sequencing, we screened the genomes of four Penicillium and five Burkholderia strains to identify secondary metabolite encoding biosynthetic gene clusters (SM-BGCs) that may be implicated in the production of antimicrobial compounds. We identified various types of SM-BGCs in the genome of each strain, including polyketide synthases (PKSs), non-ribosomal peptide synthetases (NRPSs), and terpenes. Across all four of the Penicillium strains, five SM-BGCs were detected that encoded the biosynthesis of napthopyrone, clavaric acid, pyranonigrin E, dimethyl coprogen and asperlactone. Across all five of the Burkholderia strains, three SM-BGCs were detected that encoded the biosynthesis of ornibactin, pyochelin and pyrrolnitin. Our analysis detected numerous SM-BGCs which could not be characterised. Further efforts should be made to identify the compounds encoded by these SM-BGCs so that we can explore their antimicrobial potential. The potential inhibitory effects of the compounds encoded by the SM-BGCs identified in this study may be worthy of further investigation for their effect on the growth and virulence of P. agathidicida.

Previous literature suggests that Indigenous cultural practices, specifically traditional medicine, are commonplace among urban communities contrary to the general conception that such practices are restricted to rural societies. We reviewed previous literature for records of herptiles (frog and reptile species) sold by traditional health practitioners in urban South Africa, then used visual confirmation surveys, DNA barcoding and folk taxonomy to identify the herptile species that were on sale. Additionally, we interviewed 11 IsiZulu and SePedi speaking traditional health practitioners to document details of the collection and pricing of herptile specimens along with the practitioners' views of current conservation measures for traditional medicine markets. The 34 herptile species recorded in previous literature on traditional medicine markets included endangered and non-native species. Spectrophotometry measurements of the DNA we extracted from the tissue of herptiles used in traditional medicine were an unreliable predictor of whether those extractions would be suitable for further experimental work. From our initial set of 111 tissue samples, 81 sequencing reactions were successful and 55 of those sequences had species-level matches to COI reference sequences on the NCBI GenBank and/or BOLD databases. Molecular identification revealed that traditional health practitioners correctly labelled 77% of the samples that we successfully identified with DNA barcoding in this study. Our mixed methodology approach is useful for conservation planning as it updates knowledge of animal use in Indigenous remedies and can accurately identify species of high conservation priority. Furthermore, this study highlights the possibility of collaborative conservation planning with traditional health practitioners.

The Aotearoa Genomic Data Repository (AGDR) is an initiative to provide a secure within-nation option for the storage, management and sharing of non-human genomic data generated from biological and environmental samples originating in Aotearoa New Zealand. This resource has been developed to follow the principles of Māori Data Sovereignty, and to enable the right of kaitiakitanga (guardianship), so that iwi, hapū and whānau (tribes, kinship groups and families) can effectively exercise their responsibilities as guardians over biological entities that they regard as taonga (precious or treasured). While the repository is designed to facilitate the sharing of data-making it findable by researchers and interoperable with data held in other genomic repositories-the decision-making process regarding who can access the data is entirely in the hands of those holding kaitiakitanga over each data set. No data are made available to the requesting researcher until the request has been approved, and the conditions for access (which can vary by data set) have been agreed to. Here we describe the development of the AGDR, from both a cultural perspective, and a technical one, and outline the processes that underpin its operation.