That's one study at one lab. It's not surprising that a single lab would be able to generate a single tree, and particularly not when they are studying such a closed set. I guess we'll have to wait and see if that study is reproduced elsewhere.
Here's an alternative study that illustrates the problems by drawing two contradictory trees for mankind:
http://cogweb.ucla.edu/Abstracts/Bower_99.html
A bit more on the problems of genetic evidence...Practitioners of what has been dubbed anthropological genetics now operate with a sense of caution and a hunger for better explanations of how evolutionary forces produce genetic diversity among individuals and groups.
"A lot of us have been too eager to assume that a strict out-of-Africa model is correct because it's compatible with the genetic data, without considering that the data also fit with the multiregional theory," says anthropologist John H. Relethford of the State University of New York at Oneonta. "It's time to go back to the drawing board on this issue."
A fundamental conflict between the two current theories - each of which has several proposed variations on its theme - lies in their differing assumptions about the evolutionary significance of genetic differences among individuals and populations, Relethford asserts. DNA analyses appear unable to determine which perspective proves superior, he says.
According to the more common assumption, which supports recent African origins for humanity, DNA disparities between modern populations arose as prehistoric populations split into distinct regional groups, which then rarely interbred. Computer programs retrace this tree-like evolutionary pattern back to a common genetic ancestor, based on estimates of the presumed rate at which particular DNA regions undergo change.
Such reconstructions of an evolutionary tree branching from a single ancestor have hinged on evidence that sub-Saharan Africans have accumulated more variations in their genetic makeup than any other geographic group. According to the theory, they therefore have existed as a relatively separate population for a longer time. Moreover, African DNA diverges in particularly pronounced ways from the genetic material of people living elsewhere in the world, the presumed result of a longer period of African evolution.
Beginning with the first reported branching analysis in 1987, directed by Rebecca L. Cann of the University of Hawaii at Manoa in Honolulu, evolutionary trees portray all modern H. sapiens populations as descendants of a single African population living 100,000 to 200,000 years ago. At some more recent time, part of the original African group departed its homeland and trekked into Asia. Further splits, migration, and occasional interbreeding between some human groups yielded distinctive human populations now found throughout the world.
Only about 10,000 breeding adults comprised the founding block of H. sapiens, according to these investigations. That number could not have supported the network of interbreeding populations proposed in the multiregional model.
The alternative perspective on these same genetic data, however, favors the multiregional picture of human evolution. It holds that genetic variation within and among groups arises from low but consistent levels of interbreeding combined with the buildup in regional groups of random changes in the makeup of DNA.
Proponents of this view argue that Africa's greater genetic diversity arose because more people inhabited Africa than any other continent during the rise of H. sapiens, not because the African population is older. DNA determinations of ancient population sizes represent conservative estimates that may turn out to be unreliable, these scientists argue.
The standoff between contrasting genetic perspectives shows no signs of resolution, Relethford contends. Attempts to confirm presumed splits of prehistoric human populations face particular difficulty, he says. However our species originated, it's likely that interbreeding has occurred among dispersed human populations during the past 100,000 years. The resulting jumbling of DNA traits and patterns has diminished the reliability of reconstructed evolutionary trees and estimates of their ages, in Relethford's view.
http://www-biology.ucsd.edu/faculty/huelsenbeck.html
http://www.creationism.org/caesar/genesevolution.htm:The Phylogeny Problem. Evolutionary biology is founded on the concept that
organisms share a common origin and have subsequently diverged through
time. Phylogenies represent our attempts to reconstruct those evolutionary
histories, and there is probably more interest in phylogenetic reconstruction
today than at any time in the past. Phylogenies are central to virtually
all comparisons among species, and they have found practical uses in
tracing routes of infectious disease transmission (e.g., dental transmission
of AIDS/HIV) and in identifying new pathogens such as the New Mexico hantavirus.
The phylogeny problem--the estimation of the genealogy of organisms from DNA
sequences--is not a standard statistical one. Hence one cannot simply consult
statistical texts for a solution. Our research concentrates on how phylogeny
can be estimated and how phylogenies can be used to address questions in
evolutionary biology. In general, we have taken a Bayesian approach to the
inference of phylogeny. Bayesian inference is a widely used method for
making statistical inferences but has found only limited use in evolutionary
biology. The technology I use to perform Bayesian analysis of DNA sequences
is Markov chain Monte Carlo (MCMC). MCMC takes valid, albeit dependent,
samples from the probability distribution of interest and has made Bayesian
inference practical for many scientific problems. Here we outline a few of
the phylogenetic questions that we are interested in.
Estimating large phylogenies. There are only three possible trees that could
represent the phylogenetic history of three species: (A,(B,C)); (B,(A,C));
and (C,(A,B)). Even a method that picks one of the trees at random, then,
has a reasonable chance of correctly inferring phylogenetic history. However,
for a "small" phylogenetic problem involving 10 species, there are 34,459,425
possible trees, and for a problem of only 22 species, there is over a mole of
trees. Today, most phylogenetic problems involve over 80 species and there are
some data sets that have over 500 species. (For 500 species, there are
approximately 1.0085 X 101280 possible trees, only one of which can be
correct.) The analysis of phylogenetic problems involving hundreds of sequences
poses enormous compuational problems.
Most of the methods for tackling such large problems have serious deficiencies.
The optimality criteria used by these methods often have dubious statistical
justifications. Also many of the methods are simply step-wise addition algorithms
and make no effort to explore the space of trees. However, the methods having the
best statistical justification, such as maximum likelihood and Bayesian inference,
are also the most difficult to implement for large problems. We are using Bayesian
inference using MCMC to infer large phylogenies. There are several advantages of
such an approach. For one, the optimality criterion uses all the information
present in the data and the method provides the posterior probability of trees.
Also, some variants of MCMC can allow better exploration of the space of trees.
Comparative analysis. The comparative method in evolutionary biology involves
comparing one or more features across species. The comparative method has
provided much of the evidence for natural selection and is probably the most
widely used statistical method in evolutionary biology. Since the mid 1980's
it has been realized that phylogeny must be accommodated in comparative analyses;
failure to take account of the similarity in features across species that is
caused by a common history can seriously bias comparative analyses, rendering
them meaningless. Hence, the gold standard for a comparative analysis today
includes the phylogenetic history of the species. These methods all, however,
suffer one serious problem: They all assume that the phylogeny is known without
error. Yet, almost all phylogenies have a large degree of uncertainty. How can
comparative analyses be performed that accommodate phylogenetic history but do
not depend upon any single phylogeny being correct?
Jonathan Losos, professor of biology at Washington University and director of that school's Tyson Research Center, writes:
"By comparing DNA sequences for the same gene or genes in different species, biologists can draw INFERENCES about how species are related evolutionarily. Although controversy exists about the best method of deducing phylogenetic relationships from DNA comparisons, researchers agree that species that have more similar DNA are, in most cases, more closely related to each other than to another species whose DNA is less similar" (2001: 66 [emphasis added]).
Zimmer himself, despite his previous statement, has also shown that genetic mapping only provides inference for, not proof of, evolution. Instead of showing a clear map of how a given species evolved from a lower life-form, the genetic record shows a gigantic amount of genetic mutations that neither harm nor improve the species (called "neutral evolution"). Zimmer reports: "The irony [of this discovery] was inescapable: scientists finally had a chance to tune in to evolution on its most basic level, but the signal of natural selection seemed to be swamped by the static of neutral evolution" (2001b: 16).
Worse, the signs of evolution by natural selection, supposedly visible in the genetic record, are simply not there, so inferences have to be made, as Zimmer admits:
"…[R]esearchers can't go back millions of years to read a gene's ancestral sequence, nor can they know the precise history of mutations that led up to its current form. But biologists can make some INFERENCES by comparing the genes of closely related animals….But the evidence from real genes is rarely so clean, and thus some uncertainty inevitably creeps in" (Ibid. 18 [emphasis added]).
