Reconstructing Local Insect Biodiversity with DNA Barcodes

ISEF Category: Animal Sciences

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

The Hook

A tiny insect can carry a DNA tag that helps you place it on a family tree. That means a backyard sample can turn into a map of local biodiversity, not just a jar of bugs. You can compare species from different habitats, or see how well public sequence databases sort them. The same idea can work with new specimens or public GenBank records.

What Is It?

Phylogenetic reconstruction means building a family tree from DNA differences. For insects, a common starting point is a barcode sequence, a short stretch of DNA that often separates species the way a store barcode separates products. If two insects share many matching bases, they usually sit closer together on the tree.

You can gather your own specimens, use citizen-collected vouchers, or skip wet lab work and download public records from GenBank. BOLD, the Barcode of Life Data Systems, also stores barcode records linked to specimens. Your job is to clean the data, line up the sequences, and see how local insect groups cluster across habitats, regions, or taxonomic groups.

Why This Is a Good Topic

This topic works well because every step makes a measurable choice. You can compare habitats, databases, or taxonomic groups and test whether the tree changes in a predictable way. The project also connects to real biodiversity monitoring, invasive species tracking, and conservation work. You will learn data cleaning, sequence alignment, tree building, and how to defend a result with evidence.

Research Questions

• How does habitat type affect the number of distinct insect barcode clusters recovered from local specimens?
• What is the effect of using BOLD versus GenBank references on species assignment confidence?
• Does filtering out short or low-quality sequences change the shape of the final phylogenetic tree?
• To what extent do insects from the same habitat cluster more closely than insects from different habitats?
• Which insect order gives the clearest barcode separation in a local sample set?
• How does specimen source, such as citizen-collected samples versus public voucher records, affect the number of usable taxa?

Basic Materials

• Computer with internet access.
• Spreadsheet software such as Google Sheets or LibreOffice Calc.
• Free access to BOLD Systems and NCBI GenBank.
• Sequence alignment and tree-building software.
• Local insect observation log or citizen science records.
• Smartphone or digital camera for specimen photos and labels.

Advanced Materials

• Ethanol-preserved insect vouchers with collection labels.
• Fine forceps, specimen vials, and waterproof labels.
• DNA extraction kit for small arthropods.
• PCR reagents and COI primers.
• Gel electrophoresis setup or capillary sequencing access.
• Access to a sequencer or university sequencing core.
• Bioinformatics workstation with tree-building software.

Software & Tools

• BOLD Systems: Finds barcode records and specimen metadata for insect identifications.
• NCBI GenBank: Downloads public DNA sequences for comparison and tree building.
• NCBI BLAST: Checks how closely each sequence matches known references.
• MEGA: Aligns sequences and builds starter phylogenetic trees.
• R (ape and ggtree): Cleans metadata, runs comparison tests, and plots trees.

Experiment Steps

1. Define the insect group, region, and habitat boundaries you will include.
2. Decide whether your dataset will come from public sequences, new specimens, or both, and set acceptance rules.
3. Build a clean reference table that tracks specimen ID, taxon name, location, and sequence source.
4. Choose one alignment method and one tree-building method, then keep them fixed across all samples.
5. Plan your comparison, such as habitat, database source, or sequence quality, and define the statistic that will answer it.
6. Set a rule for how you will judge confidence, such as bootstrap support or clustering agreement.

Common Pitfalls

• Mixing many unrelated insect groups in one tree, which can blur the barcode signal and hide real clusters.
• Trusting sequence records with weak metadata, which can merge mislabeled or duplicate entries into your sample.
• Comparing specimens collected under different ID standards, which makes the reference names inconsistent.
• Building a tree before checking sequence quality, which can let partial or contaminated records distort the result.
• Claiming a biodiversity pattern from too few sites or too few specimens, which makes one local snapshot look broader than it is.

What Makes This Competitive

A stronger version of this project does more than build a tree. It tests one careful question with clean controls, a clear comparison group, and a larger reference set than a typical school project. If you add sequence quality filters, compare more than one database, or measure how stable the tree stays under different analysis methods, your work starts to look much more serious. That kind of design shows real command of data and method, not just data collection.

Project Variations

• Compare insect biodiversity across urban, suburban, and natural sites using the same barcode workflow.
• Test whether citizen-collected specimens and public museum vouchers produce different species counts or tree patterns.
• Focus on one insect family, such as butterflies or beetles, to see how well barcode IDs match morphology.

Learn More

• BOLD Systems: Search barcode records, specimen pages, and taxonomic links on the Barcode of Life Data Systems site.
• NCBI GenBank: Find public DNA sequences and metadata through the NCBI nucleotide database.
• NCBI BLAST: Compare your sequences to known references using the BLAST search on NCBI.
• MEGA documentation: Read free tutorials for alignment, distance analysis, and tree building on the MEGA website.
• Smithsonian National Museum of Natural History, DNA barcoding resources: Read free background on specimen-based identification and barcoding on the museum site.