Developing bioinformatics pipeline for processing environmental DNA metabarcoding sequencing data
Autori
Sabolić, IvaMarkulin, Lucija
Muha, Teja Petra
Jenko, Barbara
Prosenc Zmrzljak, Uršula
Ostala autorstva
Morić, IvanaĐorđević, Valentina
Konferencijski prilog (Objavljena verzija)
,
© 2023 Institute of Molecular Genetics and Genetic Engineering, University of Belgrade
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Environmental DNA (eDNA) is DNA present in an environmental sample, originating from
any biological material released from organisms living in that environment. This DNA can
be isolated, amplified, sequenced, and analyzed in order to examine the taxonomic richness
and abundance of different organism groups in the targeted environment. Methods of
eDNA metabarcoding thus offer a unique opportunity to systematically streamline and
scale-up regular biological assessments across many different environments of interest.
Recently, as a part of the project funded by European structural and investment funds,
Labena d.o.o. company established a modern laboratory in Zagreb focused on the research
and provision of services in the field of eDNA. In collaboration with the Institute Ruđer
Bošković we have been working on developing tests for analysis of water quality based on
the eDNA and, as part of the standardization and optimization of sample-to-results eDNA
analysis process, we develo...ped a custom bioinformatics pipeline to facilitate efficient and
effective eDNA sequencing data analysis.
The pipeline was was written in Bash and utilizes several different algorithms to filter,
trim, merge, denoise and classify targeted eDNA sequences. Python-based scripts which
allow automatically download, filter, and format the data available on various online
platforms were included in the pipeline to facilitate the curation of custom reference
databases needed for taxonomic classification of targeted organism groups. User-friendly
and interactive pipeline report generation, comprised of both wet- and dry-lab step-bystep
sample statistics and graphical representations or the main results, is supported
using Rmarkdown and Plotly and DataTables libraries. The pipeline is containerized in
Docker, allowing for easier environment building and pipeline deployment.
Ključne reči:
environmental DNA / pipeline / reference databases / containerizationIzvor:
4th Belgrade Bioinformatics Conference, 2023, 4, 100-100Izdavač:
- Belgrade : Institute of molecular genetics and genetic engineering
Napomena:
- Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 2023
Kolekcije
Institucija/grupa
Institut za molekularnu genetiku i genetičko inženjerstvoTY - CONF AU - Sabolić, Iva AU - Markulin, Lucija AU - Muha, Teja Petra AU - Jenko, Barbara AU - Prosenc Zmrzljak, Uršula PY - 2023 UR - https://belbi.bg.ac.rs/ UR - https://imagine.imgge.bg.ac.rs/handle/123456789/2045 AB - Environmental DNA (eDNA) is DNA present in an environmental sample, originating from any biological material released from organisms living in that environment. This DNA can be isolated, amplified, sequenced, and analyzed in order to examine the taxonomic richness and abundance of different organism groups in the targeted environment. Methods of eDNA metabarcoding thus offer a unique opportunity to systematically streamline and scale-up regular biological assessments across many different environments of interest. Recently, as a part of the project funded by European structural and investment funds, Labena d.o.o. company established a modern laboratory in Zagreb focused on the research and provision of services in the field of eDNA. In collaboration with the Institute Ruđer Bošković we have been working on developing tests for analysis of water quality based on the eDNA and, as part of the standardization and optimization of sample-to-results eDNA analysis process, we developed a custom bioinformatics pipeline to facilitate efficient and effective eDNA sequencing data analysis. The pipeline was was written in Bash and utilizes several different algorithms to filter, trim, merge, denoise and classify targeted eDNA sequences. Python-based scripts which allow automatically download, filter, and format the data available on various online platforms were included in the pipeline to facilitate the curation of custom reference databases needed for taxonomic classification of targeted organism groups. User-friendly and interactive pipeline report generation, comprised of both wet- and dry-lab step-bystep sample statistics and graphical representations or the main results, is supported using Rmarkdown and Plotly and DataTables libraries. The pipeline is containerized in Docker, allowing for easier environment building and pipeline deployment. PB - Belgrade : Institute of molecular genetics and genetic engineering C3 - 4th Belgrade Bioinformatics Conference T1 - Developing bioinformatics pipeline for processing environmental DNA metabarcoding sequencing data EP - 100 SP - 100 VL - 4 UR - https://hdl.handle.net/21.15107/rcub_imagine_2045 ER -
@conference{ author = "Sabolić, Iva and Markulin, Lucija and Muha, Teja Petra and Jenko, Barbara and Prosenc Zmrzljak, Uršula", year = "2023", abstract = "Environmental DNA (eDNA) is DNA present in an environmental sample, originating from any biological material released from organisms living in that environment. This DNA can be isolated, amplified, sequenced, and analyzed in order to examine the taxonomic richness and abundance of different organism groups in the targeted environment. Methods of eDNA metabarcoding thus offer a unique opportunity to systematically streamline and scale-up regular biological assessments across many different environments of interest. Recently, as a part of the project funded by European structural and investment funds, Labena d.o.o. company established a modern laboratory in Zagreb focused on the research and provision of services in the field of eDNA. In collaboration with the Institute Ruđer Bošković we have been working on developing tests for analysis of water quality based on the eDNA and, as part of the standardization and optimization of sample-to-results eDNA analysis process, we developed a custom bioinformatics pipeline to facilitate efficient and effective eDNA sequencing data analysis. The pipeline was was written in Bash and utilizes several different algorithms to filter, trim, merge, denoise and classify targeted eDNA sequences. Python-based scripts which allow automatically download, filter, and format the data available on various online platforms were included in the pipeline to facilitate the curation of custom reference databases needed for taxonomic classification of targeted organism groups. User-friendly and interactive pipeline report generation, comprised of both wet- and dry-lab step-bystep sample statistics and graphical representations or the main results, is supported using Rmarkdown and Plotly and DataTables libraries. The pipeline is containerized in Docker, allowing for easier environment building and pipeline deployment.", publisher = "Belgrade : Institute of molecular genetics and genetic engineering", journal = "4th Belgrade Bioinformatics Conference", title = "Developing bioinformatics pipeline for processing environmental DNA metabarcoding sequencing data", pages = "100-100", volume = "4", url = "https://hdl.handle.net/21.15107/rcub_imagine_2045" }
Sabolić, I., Markulin, L., Muha, T. P., Jenko, B.,& Prosenc Zmrzljak, U.. (2023). Developing bioinformatics pipeline for processing environmental DNA metabarcoding sequencing data. in 4th Belgrade Bioinformatics Conference Belgrade : Institute of molecular genetics and genetic engineering., 4, 100-100. https://hdl.handle.net/21.15107/rcub_imagine_2045
Sabolić I, Markulin L, Muha TP, Jenko B, Prosenc Zmrzljak U. Developing bioinformatics pipeline for processing environmental DNA metabarcoding sequencing data. in 4th Belgrade Bioinformatics Conference. 2023;4:100-100. https://hdl.handle.net/21.15107/rcub_imagine_2045 .
Sabolić, Iva, Markulin, Lucija, Muha, Teja Petra, Jenko, Barbara, Prosenc Zmrzljak, Uršula, "Developing bioinformatics pipeline for processing environmental DNA metabarcoding sequencing data" in 4th Belgrade Bioinformatics Conference, 4 (2023):100-100, https://hdl.handle.net/21.15107/rcub_imagine_2045 .