October 3, 2024

Roslin: DNA encoding method aids data-driven genetics research

A new method of encoding and understanding the ancestry of a set of related DNA sequences could support storage and analysis of large genetic datasets, the Roslin Institute said.

The development has widespread applications, from understanding the evolution of viruses such as SARS-CoV-2, and mapping areas of DNA linked to disease, to leveraging these insights to benefit agricultural populations of plants and animals.

A team of researchers involving a Roslin scientist developed a simple, efficient method of capturing the history and relatedness of DNA sequences from sampled individuals. Their method keeps track of which sections of DNA were inherited from which ancestors, and how these various sections are related.

This can be applied to large sets of DNA sequences from different individuals, creating a network of inheritance paths between sampled DNA sequences and their ancestors, also known as a genetic genealogy or an ancestral recombination graph (ARG). These can be used to shed light on the history of DNA sequences of sampled individuals and to compress this DNA data and speed genetic analyses.

The novel approach allows scientists to store and analyse large amounts of genetic data, and it can be applied to any species of life on Earth.

The study, led by the Big Data Institute and involving the Roslin Institute, is published in Genetics.

"This work highlights a way forward in working with ever-increasing genomic datasets both in number of individuals and number of DNA markers," said Professor Gregor Gorjanc of the Roslin Institute. "We expect that analyses based on this DNA data encoding will also enable richer analyses and their applications across several areas of genetics."

Dr. Yan Wong of the Big Data Institute at the University of Oxford, said: "We hope that this formal standard for how to represent genetic genealogies can help to unify the field of genetic history and make it easier for scientists to analyse, share, and compare results."

- Roslin