The role of Bioinformatics in biodiversity conservation
Venkatesh Chellappa
Bioinformatics | Precision Medicine | AI | Genomics | ML | Cloud
Bioinformatics can help identify and track endangered species.
All of this bioinformatics information provides genomic insights to improve the monitoring, management and recovery of endangered wildlife. The latest DNA sequencing tools bring science to the field for real-time results and will one day enable data-based decision-making within an actionable time frame. Genomic insights are fundamental to a variety of biotechnology applications, including other tools that have followed [1].
A great deal of biodiversity is threatened, but some taxa are more accessible and better studied than others. How can we obtain high-quality DNA and generate genomic information from very rare and small (e.g. flies, meiotic groups, gastrochaetes) or difficult taxa (e.g. conifers or uncultured fungi due to large genome sizes)? [2].
Bioinformatics can help survey and assess the health of ecosystems.
Accurate assessments of biodiversity are crucial to advising ecosystem-monitoring programs and understanding ecosystem function. Nevertheless, a standard operating procedure to assess biodiversity accurately and consistently has not been established. This is especially true for meiofauna, a diverse community (20 phyla) of small benthic invertebrates that have fundamental ecological roles. Recent studies show that metabarcoding is a cost-effective and time-effective method to estimate meiofauna biodiversity, in contrast to morphological-based taxonomy. Here, we compare biodiversity assessments of a diverse meiofaunal community derived by applying multiple taxonomic methods based on comparative morphology, molecular phylogenetic analysis, DNA barcoding of individual specimens, and metabarcoding of environmental DNA. We show that biodiversity estimates are strongly biased across taxonomic methods and phyla. Such biases affect understanding of community structures and ecological interpretations. This study supports the urgency of improving aspects of environmental high-throughput sequencing and the value of taxonomists in correctly understanding biodiversity estimates[3].
The next step is to combine expert-based extent of occurrence data with ecological niche modeling. Ecological niche modeling is a rapidly emerging area that utilizes available presence only or presence–absence data along with environmental data (e.g. climate models and remote sensed data) to quickly output predictions about suitability of habitat in areas that have not been sampled (Soberón and Peterson, 2004) in GIS layer formats. As more data becomes available to global repositories, and as environmental data layers become finer scale, the more tractable finer scale ecological niche modeling becomes. Although niche modeling is both quantitative and repeatable, this approach does not yet take into account biotic interactions and other biogeographic factors that may limit species ranges (Guisan and Zimmerman, 2000; Soberón and Peterson, 2005). Thus it is the combination of modeling approaches and expert opinion information that will put us into the position to make accurate, scalable maps of species distributions (McPherson et al. 2006; Pearce et al. 2001) that can be easily visualized on flat maps or virtual globes. These modeled range maps represent a central information product for our global biodiversity map[4].
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Bioinformatics can help publicize the importance of biodiversity.
Motivation: Data about biodiversity have been scattered in different formats in natural history collections, survey reports and the literature. A central challenge for the biodiversity informatics community is to provide the means to share and rapidly synthesize these data and the knowledge they provide us to build an easily accessible, unified global map of biodiversity. Such a map would provide raw and summary data and information on biodiversity and its change across the world at multiple scales[4].
The availability of public genomic resources can greatly assist biodiversity assessment, conservation, and restoration efforts by providing evidence for scientifically informed management decisions. Here we survey the main approaches and applications in biodiversity and conservation genomics, considering practical factors, such as cost, time, prerequisite skills, and current shortcomings of applications. Most approaches perform best in combination with reference genomes from the target species or closely related species. We review case studies to illustrate how reference genomes can facilitate biodiversity research and conservation across the tree of life. We conclude that the time is ripe to view reference genomes as fundamental resources and to integrate their use as a best practice in conservation genomics[5].
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