The delivery of a rough draft of the human genome was achieved by two rival groups of researchers.
A complete map of our chromosomes was the beginning of what would become a vast trove of individualized sequences from all corners of the globe.
There is a story of our shared humanity in that ocean of decoded DNA.
It's difficult to read it because of the sheer amount of data, subtle differences in samples, diverse formats, and analysis techniques all present obstacles to a unified interpretation.
Researchers from the Big Data Institute at the University of Oxford in the UK have made a significant start by merging a forest of more than 3,600 individual sequence from 215 populations into a single tree.
231 million ancestral lineages are contained in the tree's branches. A spread of roots is represented by eight ancient, highly detailed human genome sequences, with thousands of smaller snippets used to confirm their place deep in our past.
Three Neanderthal genomes, one Denisovan genome, and a small family who lived in Siberia more than four thousand years ago are among them.
We are reconstructing the genomes of our ancestors and using them to form a series of linked evolutionary trees that we call a tree sequence.
We can estimate when and where these ancestors lived.
Their tree sequence method uses a computing concept that aims to represent data in an optimal amount of space that also limits the amount of time needed to probe it all with questions.
We might apply the same thinking when we save files on our computer, finding a compromise between saving them on the desktop and squeezing them into long lists of folders.
A tree sequence can be used to find correlations between branches of a tree to make it easier to study.
By turning the data into graphs with nodes representing various lineages and mapping mutations along the edges, massive genetic databases can not only be squeezed into a relatively small space, but can be accessed more easily by algorithms designed to search for interesting statistics.
The power of our approach is that it makes very few assumptions about the underlying data and can include both modern and ancient DNA samples, according to Wohns, who explains their work in the video below.
The team was able to estimate where common ancestors might have once lived and how they moved about with the use of labels on the geographical locations of the sequence.
We already know how human populations migrated from Africa, and this shows us changes in population densities within ancestral groups, such as the Denisovans.
As more genetic data becomes available in the future, the tree has plenty of room to grow.
Adding millions more genomes will only make the results more accurate, as they will be able to identify exactly where a novel sequence fits in a genealogy that spans around the world.
"This genealogy allows us to see how every person's genetic sequence relates to every other, along all the points of the genome," says a geneticist.
There is no reason that the same approach could not be applied to other species, possibly one day contributing to a global tapestry of life on Earth.
While humans are the focus of the study, the method is valid for most living things.
It could be particularly beneficial in medical genetics, in distinguishing true associations between genetic regions and diseases from spurious connections arising from our shared ancestral history.
Science published this research.
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