| Literature DB >> 31671909 |
Henrik Krehenwinkel1, Aaron Pomerantz2,3, Stefan Prost4,5.
Abstract
We live in an era of unprecedented biodiversity loss, affecting the taxonomic composition of ecosystems worldwide. The immense task of quantifying human imprints on global ecosystems has been greatly simplified by developments in high-throughput DNA sequencing technology (HTS). Approaches like DNA metabarcoding enable the study of biological communities at unparalleled detail. However, current protocols for HTS-based biodiversity exploration have several drawbacks. They are usually based on short sequences, with limited taxonomic and phylogenetic information content. Access to expensive HTS technology is often restricted in developing countries. Ecosystems of particular conservation priority are often remote and hard to access, requiring extensive time from field collection to laboratory processing of specimens. The advent of inexpensive mobile laboratory and DNA sequencing technologies show great promise to facilitate monitoring projects in biodiversity hot-spots around the world. Recent attention has been given to portable DNA sequencing studies related to infectious organisms, such as bacteria and viruses, yet relatively few studies have focused on applying these tools to Eukaryotes, such as plants and animals. Here, we outline the current state of genetic biodiversity monitoring of higher Eukaryotes using Oxford Nanopore Technology's MinION portable sequencing platform, as well as summarize areas of recent development.Entities:
Keywords: portable sequencing, nanopore sequencing, biodiversity monitoring, local capacity building, MinION, DNA barcoding, long read sequencing
Mesh:
Year: 2019 PMID: 31671909 PMCID: PMC6895800 DOI: 10.3390/genes10110858
Source DB: PubMed Journal: Genes (Basel) ISSN: 2073-4425 Impact factor: 4.096
Figure 1(A) Schematic of different genetic biomonitoring approaches using the MinION platform. (B) Schematic of the application of the mobile sequencing laboratory. (A) Left panel: DNA barcoding involves extracting DNA and performing PCR amplification from individual specimens. Amplicons are tagged with unique dual indices and then pooled into a single library and sequenced. Middle panel: Metabarcoding involves DNA extraction and PCR amplification from a bulk community sample. Each individual metabarcoding library can be dual indexed to enable pooling of different bulk samples. Right panel: Metagenomics involves extracting DNA directly from a bulk environmental sample. The DNA is then sheared to small fragment sizes and an indexed library constructed, before sequencing. Due to its long read length, shearing is not necessary for MinION-based metagenomics. The application of the MinION platform for metabarcoding and metagenomics is currently restricted due to the high error rates of R9.x flow cells. Changes to the pores (discussed above) in R10 flow cells are supposed to lower its error rates considerably, potentially enabling the use of MinION for these applications. (B) Left photo: A typical portable laboratory or “lab in a backpack” setup. Middle photo: Due to its limited size and cost, the portable laboratory can be transported even to remote field locations. Right photo: The portable laboratory setup in the jungle of Panama.
Applications of the MinION sequencing platform for biomonitoring of higher eukaryote biodiversity.
| Citation | Purpose | |
|---|---|---|
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| [ | To test the feasibility of in-the-field DNA barcoding. The field-application was carried out in Tanzania. |
| [ | To test the feasibility of in-the-field DNA barcoding. The field-application was carried out in Ecuador. | |
| [ | To investigate the feasibility of using long-read DNA barcodes for biodiversity monitoring. The field-application was carried out in Peru. | |
| [ | Proof of concept study of in-the-field DNA barcoding. The field-application was carried out in Madagascar. | |
| [ | To document Phoridae (Diptera) biodiversity in the Kibale National Park in Uganda. | |
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| [ | To test the usability of long-read rDNA barcodes for metabarcoding applications. The field-application was carried out in Peru. |
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| [ | To test the feasibility of reverse metagenomics for species identification using the MinION platform. |
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| [ | To test the feasibility of genome skimming for species identification using the MinION platform. The field-application was carried out in Wales. |
| [ | To test the feasibility of genome skimming using the MinION platform for species identification of highly-traded shark species. |
Available pipelines for bioinformatic processing of genetic monitoring data generated with the MinION platform.
| Name | Genetic Monitoring Technique | Programs Used in the Pipeline | Citation |
|---|---|---|---|
| DNA barcoding | Based on de novo assembly using canu [ | [ | |
| DNA barcoding | Based on de novo assembly using Allele Wrangler ( | [ | |
| DNA barcoding | Based on alignments with MAFFT [ | [ | |
| ONTrack | DNA barcoding | Based on clustering using vsearch [ | [ |
| NanoAmpli-Seq | Metabarcoding | Extension of the intramolecular-ligated nanopore consensus sequencing (INC-Seq) protocol [ | [ |
| What’s in my pot? (WIMP) | Metabarcoding | Stand-alone tool | [ |
| MinION Detection Software (MINDS) | Metagenomics | Based on the based on the Centrifuge classification engine [ | [ |
| Nanopipe | Can be used for metagenomics | Based on LAST alignments [ | [ |
Figure 2Principle steps of bioinformatic pipelines for MinION-based biodiversity assessment approaches. Left panel: For DNA barcoding the reads are first base-called and demultiplexed. Next reads are filtered and depending on the applied pipeline either assembled de novo, or clustered and subsequently aligned. Lastly, the consensus sequences are polished and blasted against a database. Middle panel: For Metabarcoding applications the reads are first base-called and quality filtered. Next reads are clustered into OTUs and then blasted against a database directly or aligned to create individual consensus sequences. Right panel: For metagenomic applications reads are first base-called and filtered. Subsequently, reads are either blasted against a database directly, or assembled de novo into contigs and subsequently blasted against a database.