Pond eDNA Species Placement

ISEF Category: Animal Sciences

Subcategory: Systematics and Evolution  ·  Difficulty: Advanced  ·  Setup: Home Setup  ·  Time: 1 to 2 Months

The Hook

A single DNA snippet from pond water can point to what lives there, even when you never see the organism itself. Your job is to place that snippet on the tree of life. That turns a mystery sample into a real evidence trail, and it gives you a clear way to test how database choices change the answer.

What Is It?

Environmental DNA, or eDNA, is genetic material organisms leave behind in water, soil, or air. In this project, you start with one unknown sequence from a pond and try to figure out which branch of life it belongs on. Think of it like matching a torn page to the right book.

BLAST stands for Basic Local Alignment Search Tool. It compares your sequence with sequences in public databases, then gives you likely matches. Phylogenomic placement goes one step farther, because you use shared DNA patterns to see where the unknown sequence fits among related species. If you use a Nanopore community dataset, you may work with long reads that need cleanup before analysis. If you stay fully in silico, you can still do real hypothesis testing with a public sequence file.

Why This Is a Good Topic

This is a good science fair topic because you can test the same sequence in more than one database, with more than one search setting, and get measurable differences. It connects to biodiversity monitoring, invasive species detection, and ecosystem health. You learn how scientists move from a raw DNA read to a defensible ID, which is a real research skill, not just a classroom exercise.

Research Questions

• How does the choice of reference database change the top taxonomic placement of the pond sequence?
• What is the effect of BLAST scoring settings on the best hit identity and coverage?
• Does trimming low-quality sequence ends change the nearest known relative?
• To what extent do tree-building methods agree on the sequence's position?
• Which taxonomic group stays stable across repeated runs with different search settings?
• How does adding more local reference sequences affect confidence in the final placement?

Basic Materials

• Laptop with at least 8 GB RAM.
• Stable internet connection.
• FASTA or FASTQ file from a free Nanopore community dataset or public eDNA source.
• Web browser with access to NCBI BLAST and NCBI Taxonomy Browser.
• Spreadsheet software such as Google Sheets or LibreOffice Calc.
• Free text editor that can open sequence files, such as VS Code or Notepad++;.

Advanced Materials

• Access to a Nanopore sequencer or archived raw read files.
• DNA extraction kit for environmental samples.
• PCR and library prep reagents for an eDNA marker.
• Benchmark reference DNA barcodes from known pond taxa.
• Access to a workstation for alignment and tree building.
• Sanger-verified reference sequences for local species.

Software & Tools

• NCBI BLAST: Compares your sequence against public databases and reports close matches.
• NCBI Taxonomy Browser: Checks lineage names and helps you read taxonomic labels correctly.
• MEGA: Aligns sequences and builds simple phylogenetic trees.
• IQ-TREE: Runs likelihood-based tree analysis and bootstrap support on aligned sequences.
• AliView: Lets you inspect and clean alignments by eye.

Experiment Steps

1. Define the exact sequence you will analyze and choose whether to use a raw read, a consensus, or a cleaned fragment.
2. Gather a small reference set that includes close relatives, known pond taxa, and an outgroup for rooting the tree.
3. Choose one search method for the main result, then set up a second method that can challenge it.
4. Build an alignment plan that keeps homologous regions lined up and removes noisy ends before tree building.
5. Decide how you will compare results using identity, coverage, e-value, and branch support.
6. Predefine the rule you will use when database results disagree, so your final placement stays consistent.

Common Pitfalls

• Treating the top BLAST hit as a final species ID, which ignores close matches with nearly equal scores.
• Using a sequence that is too short or noisy, which can move the sample into the wrong clade.
• Building a tree with too few reference taxa, which can make the unknown sequence look more certain than it is.
• Mixing unrelated marker genes in one analysis, which breaks the alignment and muddies the result.
• Ignoring coverage and query length, which can make a weak match look stronger than a real one.

What Makes This Competitive

A strong version of this project does more than name the closest match. It compares multiple databases, multiple placement methods, and the same sequence under different filtering rules. If you also report bootstrap support, coverage, and where the result stays unstable, you show real scientific judgment. That kind of uncertainty analysis turns a simple ID exercise into a research project.

Project Variations

• Compare a pond sequence with sequences from a nearby stream to see whether local habitat changes the placement.
• Test the same unknown sequence with BLAST, then with a phylogenetic tree, to see when the two methods agree.
• Add regional fish, amphibian, and invertebrate references to check whether the sequence settles into a different branch.

Learn More

• NCBI BLAST: Search the NCBI BLAST help pages for nucleotide and protein similarity searches.
• NCBI Taxonomy Browser: Look up species names, lineages, and synonyms in the NCBI Taxonomy Browser.
• NCBI Bookshelf: Search for free chapters on sequence alignment and phylogenetic trees.
• MEGA documentation: Find alignment and tree-building tutorials on the MEGA website.
• Oxford Nanopore Community: Look for public datasets and analysis guides on the Nanopore Community site.
• PubMed: Search for review articles on environmental DNA, DNA barcoding, and phylogenetic placement.