Map depicting the way early modern humans (Homo sapiens) are thought to have spread across the globe. It also shows the geographical spread of Homo erectus and the Neanderthals. The dates are approximations (and not 100% guaranteed)
Researchers from Oxford University's Big Data Institute (BDI) have developed a technique to help construct the entire genetic relationship amongst humans to produce a single genealogy for all of us, showing how we have all evolved from a single founder population, and incorporating the genomes of archaic hominins such as Neanderthals and Denisovans
.
This has been made possible by the enormous technical advances in being able to extract and sequence DNA but the problem was in using this vast and growing database. However, the group has now developed a new method which allows researchers to easily and quickly combine data from multiple sources and scale to accommodate millions of genome sequences. Their method was published yesterday in Science.
The press release from BDI explains further:
The team's findings can be read in Science:Essentially, 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 then estimate when and where these ancestors lived. The power of our approach is that it makes very few assumptions about the underlying data and can also include both modern and ancient DNA samples.Since individual genomic regions are only inherited from one parent, either the mother or the father, the ancestry of each point on the genome can be thought of as a tree. The set of trees, known as a “tree sequence” or "ancestral recombination graph”, links genetic regions back through time to ancestors where the genetic variation first appeared.
While humans are the focus of this study, the method is valid for most living things, from orang-utans to bacteria. It could be particularly beneficial in medical genetics, in separating out true associations between genetic regions and diseases from spurious connections arising from our shared ancestral history.
Dr Anthony Wilder Wohns, first author
Broad Institute of MIT and Harvard, Cambridge, USA.
And Big Data Institute
Li Ka Shing Centre for Health Information and Discovery
University of Oxford, Oxford, UK.
[…]
This study is laying the groundwork for the next generation of DNA sequencing. As the quality of genome sequences from modern and ancient DNA samples improves, the tree will become even more accurate and we will eventually be able to generate a single, unified map that explains the descent of all the human genetic variation we see today.The study integrated data on modern and ancient human genomes from eight different databases, and included a total of 3,609 individual genome sequences from 215 populations. The ancient genomes included three Neanderthal genomes, a Denisovan* genome, and a family of four people who lived in Siberia around 4.6 thousand years ago. The algorithms predicted where common ancestors must be present in the evolutionary trees to explain the patterns of genetic variation. The resulting network contained almost 27 million ancestors.
Dr Yan Wong, co-author
Big Data Institute
Li Ka Shing Centre for Health Information and Discovery
University of Oxford, Oxford, UK.
After adding location data on these sample genomes, the authors used the network to estimate where the predicted common ancestors had lived. The results successfully recaptured key events in human evolutionary history, including the migration out of Africa.
[…]
Although the genealogical map is already an extremely rich resource, the research team plans to make it even more comprehensive by continuing to incorporate genetic data as it becomes available. Because tree sequences store data in a highly efficient way, the dataset could easily accommodate millions of additional genomes.
Visualizing inferred human ancestral lineages over time and space. Each line represents an ancestor-descendant relationship in our inferred genealogy of modern and ancient genomes. The width of a line corresponds to how many times the relationship is observed, and lines are colored on the basis of the estimated age of the ancestor.
Structured AbstractIt seems almost cruel to point out to Creationists how this research entirely vindicates the scientific understanding of how humans, and other species, evolve over time from common origins, and why they can be arranged in these tree structures and cladograms, and entirely refutes any notion that humans were created as is, just a few thousand years ago.
INTRODUCTION
The characterization of modern and ancient human genome sequences has revealed previously unknown features of our evolutionary past. As genome data generation continues to accelerate—through the sequencing of population-scale biobanks and ancient samples from around the world—so does the potential to generate an increasingly detailed understanding of how populations have evolved.
However, such genomic datasets are highly heterogeneous. Samples from diverse times, geographic locations, and populations are processed, sequenced, and analyzed using a variety of techniques. The resulting datasets contain genuine variation but also complex patterns of missingness and error. This makes combining data challenging and hinders efforts to generate the most complete picture of human genomic variation.
RATIONALE
To address these challenges, we use the foundational notion that the ancestral relationships of all humans who have ever lived can be described by a single genealogy or tree sequence, so named because it encodes the sequence of trees that link individuals to one another at every point in the genome. This tree sequence of humanity is immensely complex, but estimates of the structure are a powerful means of integrating diverse datasets and gaining greater insights into human genetic diversity. In this work, we introduce statistical and computational methods to infer such a unified genealogy of modern and ancient samples, validate the methods through a mixture of computer simulation and analysis of empirical data, and apply the methods to reveal features of human diversity and evolution.
RESULTS
We present a unified tree sequence of 3601 modern and eight high-coverage ancient human genome sequences compiled from eight datasets. This structure is a lossless and compact representation of 27 million ancestral haplotype fragments and 231 million ancestral lineages linking genomes from these datasets back in time. The tree sequence also benefits from the use of an additional 3589 ancient samples compiled from more than 100 publications to constrain and date relationships. Using simulations and empirical analyses, we demonstrate the ability to recover relationships between individuals and populations as well as to identify descendants of ancient samples. We calculate the distribution of the time to most recent common ancestry between the 215 populations of the constituent datasets, revealing patterns consistent with substantial variation in historical population size and evidence of archaic admixture in modern humans.
The tree sequence also offers insight into patterns of recurrent mutation and sequencing error in commonly used genetic datasets. We find pervasive signals of sequencing error as well as a small subset of variant sites that appear to be erroneous.
Finally, we introduce an estimator of ancestor geographic location that recapitulates key features of human history. We observe signals of very deep ancestral lineages in Africa, the out-of-Africa event, and archaic introgression in Oceania. The method motivates improved spatiotemporal inference methods that will better elucidate the paths and timings of historic migrations.
CONCLUSION
The profusion of genetic sequencing data creates challenges for integrating diverse data sources. Our results demonstrate that whole-genome genealogies provide a powerful platform for synthesizing genetic data and investigating human history and evolution.
Abstract
A unified genealogy of modern and ancient genomes: Supplementary Video 1 from Wilder Wohns on Vimeo.
The sequencing of modern and ancient genomes from around the world has revolutionized our understanding of human history and evolution. However, the problem of how best to characterize ancestral relationships from the totality of human genomic variation remains unsolved. Here, we address this challenge with nonparametric methods that enable us to infer a unified genealogy of modern and ancient humans. This compact representation of multiple datasets explores the challenges of missing and erroneous data and uses ancient samples to constrain and date relationships. We demonstrate the power of the method to recover relationships between individuals and populations as well as to identify descendants of ancient samples. Finally, we introduce a simple nonparametric estimator of the geographical location of ancestors that recapitulates key events in human history.
Wohns Anthony Wilder; Wong Yan; Jeffery Ben; Akbari Ali; Mallick Swapan; Pinhasi Ron; Patterson Nick; Reich David; Kelleher Jerome; McVean Gil
A unified genealogy of modern and ancient genomes
Science (2022) 375(6583); DOI: 10.1126/science.abi8264
Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science.
Reprinted by kind permission under licence #5256381350208
Once again, a piece of scientific research has refuted Creationism without even trying. It also dashes any increasingly forlorn hope Creationists might still have that the scientific theory of evolution is a theory in crisis and is about to be overthrown. It is not about to be replaced by the childish Bronze Age notion of intelligent [sic] design, to become the first established scientific theory to be replaced by superstition and mythology, and incorporating magic and unproven and inexplicable entities.
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