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Metagenomic analysis of biodiversity using eDNA from water and sediment samples from a lake and a river
University of Skövde, School of Bioscience.
2025 (English)Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Metagenomic analysis of eDNA is an alternative method of detection of species in the environment without the need of direct observation, capture, or biopsy of species of interest. This method optimises the process of species detection greatly by reducing costs and length of observation. One possible application of this method is the study of biodiversity of bodies of water populated by fish and molluscs. This study aims to study lake Lången and a river that flows into this lake to assess communities of fish and molluscs using eDNA analysis in comparison to previous traditional methods. The study also aims to find whether the biodiversity metrics obtained by eDNA analysis differ significantly between the two biome types. To reach the aim of the study, a workflow consisting of field- and laboratory work, as well as bioinformatic analysis, was developed and applied to obtain and study samples of biomaterial. The practical part of the study involved collection of samples, extraction of eDNA and sequencing. The bioinformatic part of the study involved classification of the sequencing data using custom reference sequence libraries, and statistical analysis of classification data using several statistical tests, such as Alpha- and Beta-Diversity, Principal Coordinate Analysis (PCoA), PERMANOVA and Dispersion tests. As was proven by the conducted bioinformatic analysis of sequencing data, it was possible to classify eDNA sequences belonging to most species of fish and molluscs that were previously reported to be present in lake Lången. As for comparative analysis of the lake and the river, there is no significant difference in species community compositions between the two neighbouring biomes. Results of all tests contributed to this conclusion, as p-values exceeded 0.05 by a large margin. Further research is possible with several improvements, such as bigger sample size, multi-omics analysis, and deeper bioinformatic analysis.

Place, publisher, year, edition, pages
2025. , p. 36
National Category
Genetics and Genomics
Identifiers
URN: urn:nbn:se:his:diva-25554OAI: oai:DiVA.org:his-25554DiVA, id: diva2:1985308
Subject / course
Bioscience
Educational program
Molekylär biodesign 180 hp
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Examiners
Available from: 2025-07-23 Created: 2025-07-23 Last updated: 2025-09-29Bibliographically approved

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