'Mitochondrial Eve': Mother of All Humans Lived 200,000
ScienceDaily (Aug. 17, 2010) - The most robust
statistical examination to date of our species' genetic
links to "mitochondrial Eve" -- the maternal ancestor
of all living humans -- confirms that she lived about
200,000 years ago. The Rice University study was based
on a side-by-side comparison of 10 human genetic models
that each aim to determine when Eve lived using a very
different set of assumptions about the way humans
migrated, expanded and spread across Earth.
The research is available online in the journal
Theoretical Population Biology.
"Our findings underscore the importance of taking into
account the random nature of population processes like
growth and extinction," said study co-author Marek
Kimmel, professor of statistics at Rice. "Classical,
deterministic models, including several that have
previously been applied to the dating of mitochondrial
Eve, do not fully account for these random processes."
The quest to date mitochondrial Eve (mtEve) is an
example of the way scientists probe the genetic past to
learn more about mutation, selection and other genetic
processes that play key roles in disease.
"This is why we are interested in patterns of genetic
variability in general," Kimmel said. "They are very
important for medicine."
For example, the way scientists attempt to date mtEve
relies on modern genetic techniques. Genetic profiles
of random blood donors are compared, and based upon the
likenesses and differences between particular genes,
scientists can assign a number that describes the
degree to which any two donors are related to one
Using mitochondrial genomes to gauge relatedness is a
way for geneticists to simplify the task of finding
common ancestors that lived long ago. That is because
the entire human genome contains more than 20,000
genes, and comparing the differences among so many
genes for distant relatives is problematic, even with
today's largest and fastest supercomputers.
But mitochondria -- the tiny organelles that serve as
energy factories inside all human cells -- have their
own genome. Besides containing 37 genes that rarely
change, they contain a "hypervariable" region, which
changes fast enough to provide a molecular clock
calibrated to times comparable to the age of modern
humanity. Because each person's mitochondrial genome is
inherited from his or her mother, all mitochondrial
lineages are maternal.
To infer mtEve's age, scientists must convert the
measures of relatedness between random blood donors
into a measure of time.
"You have to translate the differences between gene
sequences into how they evolved in time," said co-
author Krzysztof Cyran, vice head of the Institute of
Informatics at Silesian University of Technology in
Gliwice, Poland. "And how they evolved in time depends
upon the model of evolution that you use. So, for
instance, what is the rate of genetic mutation, and is
that rate of change uniform in time? And what about the
process of random loss of genetic variants, which we
call genetic drift?"
Within each model, the answers to these questions take
the form of coefficients -- numeric constants that are
plugged into the equation that returns the answer for
when mtEve lived.
Each model has its own assumptions, and each assumption
has mathematical implications. To further complicate
matters, some of the assumptions are not valid for
human populations. For example, some models assume that
population size never changes. That is not true for
humans, whose population has grown exponentially for at
least several thousand generations. Other models assume
perfect mixing of genes, meaning that any two humans
anywhere in the world have an equal chance of producing
Cyran said human genetic models have become more
complex over the past couple of decades as theorists
have tried to correct for invalid assumptions. But some
of the corrections -- like adding branching processes
that attempt to capture the dynamics of population
growth in early human migrations -- are extremely
complex. Which raises the question of whether less
complex models might do equally well in capturing
"We wanted to see how sensitive the estimates were to
the assumptions of the models," Kimmel said. "We found
that all of the models that accounted for random
population size -- such as different branching
processes -- gave similar estimates. This is
reassuring, because it shows that refining the
assumptions of the model, beyond a certain point, may
not be that important in the big picture."
The research was supported by grants from the Polish
Ministry of Science and Higher Education and the Cancer
Prevention and Research Institute of Texas. It has
resulted from a standing collaboration between Rice
University and Silesian University of Technology.
Portside aims to provide material of interest
to people on the left that will help them to
interpret the world and to change it.
Submit via email: [log in to unmask]
Submit via the Web: portside.org/submit
Frequently asked questions: portside.org/faq
Account assistance: portside.org/contact
Search the archives: portside.org/archive