Every protein you look up on a screen started as an organism somewhere. The data travelled. The question of who benefits didn’t.
Digital sequence information is the genetic code of living things stored in databases. If you have looked up a protein on UniProt or the AlphaFold Database, you have used it.
Digital sequence information, or DSI, covers DNA and RNA sequences, and in many readings the protein sequences they encode, plus some of the data attached to them.
The term comes from the Convention on Biological Diversity, the UN treaty on nature. Governments first took it up in 2016. They still haven’t agreed a single definition, and that gap matters, because what counts as DSI decides who might be asked to pay.
For decades the rule was simple. If a company took a plant, fungus or microbe from a country and made money from it, it should share the benefit with that country. The Nagoya Protocol (2010) set this out, and it works on physical samples.
Then sequencing got cheap. Today most of what matters about an organism sits in free online databases. Anyone can download a sequence and use it without touching the organism or visiting the place it came from. The rules on sharing benefits didn’t follow the data online.
Many database entries don’t even record where the organism came from. Once a sequence is in a database, the link back to a place is often lost.
In 2024, at the UN biodiversity summit in Cali, Colombia, governments agreed a shared fund, the Cali Fund. Companies that profit from DSI are asked to pay in 1% of their profits or 0.1% of their revenue. Universities, public research and public databases aren’t expected to pay. At least half of the money is meant for Indigenous peoples and local communities.
Paying is voluntary, and very little has come in. In October 2026, at COP17 in Yerevan, governments kept the fund going and sent the hard questions on to COP18 in 2028.
If you open UniProt, look up a shape in the AlphaFold Database, or paste a sequence into a design tool, you’re working with DSI.
AlphaFold learned from shapes in the Protein Data Bank, which people measured and shared over 50 years. It predicts new shapes from sequences in UniProt. Every one of those sequences came from an organism, collected somewhere, by someone.
Most of the time the database tells you the species, and sometimes the strain. It rarely tells you the place, who collected it, or who knew the organism first.
You don’t need to settle the policy fight to work with care. A few habits help:
Read the entry for where it came from. Look for the organism, the strain, and any country of origin. Note when it isn’t there.
Tag what you know. Is the shape measured, predicted, or unknown?
Name who and what a change touches. That includes the organism, the place it came from, and the people who knew it first. This is the care part of being an AI-native biodesigner.
Look for biocultural labels. Some Indigenous communities attach their own guidance on how genetic data and biological collections should be used, through Local Contexts Biocultural Labels. Respect them where you find them.
This page isn’t legal advice. If you’re building a product on sequence data, ask a lawyer about the rules where you work.
Convention on Biological Diversity. Digital sequence information on genetic resources. cbd.int
Convention on Biological Diversity and UNEP (2026, June). Guide to the Cali Fund. cbd.int
Third World Network (2024, 5 November). Outcome of COP16 on digital sequence information. twn.my
Eco-Business (2026). COP17: Can countries break deadlock on sharing benefits from nature’s digital data? eco-business.com
Local Contexts. Biocultural Labels. localcontexts.org