Dugs Papers

A collection of Douglas Racionzer's thinking on a variety of topics including assignments in ethics.

Monday, November 27, 2006

Dug's First published article

Over 21 years ago I got this small piece published in a student rag. What is astounding is that the basic message hasn't changed. Can you pick up what the them is?

Story: Writing on the wall
(Published in Imprint, University of Cape Town; March 1985)

The hyper-busy editorial office of ASCENT gets a tip-off that there is a “Big Story” in town. A story about Cape Town’s underworld.

The overworked, but intelligent Editors, know what to do. They send their star reporter to the scene, the Intrepid Joe Student.

Joe Student hits Cape Town bus terminus around eight on Friday night. She walks resolutely through the concourse of closed shops and tired guards.

Joe walks up the still escalators and past the nodding fat guard out into the half moon night.

The windmill lunch box lies ahead. The sign over the entrance is painted red and blue. The windmill lunch box is a sleazy tavern that opens after 8.00 and is renowned for its dark seats where prostitutes and merchants can sit and relax while dealing with clients.

A large gold emblazoned scrawl on the wall at the entrance to the windmill proclaims CTS.

Aha thinks Joe Student, the Cape Town Scorpions control this place Joe prides herself in her research work. She knows that the CTS are the main dope dealers in Cape Town, Big importers.

Out of the windmill struts a woman of unknown age. She wears a tight pair of black leather pants, and 6 inches of high heels.






Big XR6, mag wheels deluxe tyre stops and the woman leans into the passenger side window. After some talk, the woman gets into the
car and it drives of fast. Prostitute? Why not?

Yes, Joe sees things happen in inner-city Cape Town. Whores, merchants, pimps, roanees, taxi drivers, sailors, “Nite” clubs, bergies, drunks, alternative types and all the rest.

This is part of the real world thinks our Joe Student. How come our university life reflects so little of this hard world?

Joe Student returns to the hectic offices of ASCENT without a story. Sad though, cause Joe saw so much. But some how it all got loft in the translation.

I mean, how do you tell your average student that life is more than countless fish-braais at Hout Bay and Champagne Breakfasts at Hangklip. How does one translate the graffiti on the walls of the inner city – into newsprint for rich cotton wool wrapped babies who spend every vac at Plett?

The split’s too big. The writing’s on the wall.

Saturday, November 25, 2006

Poetry

My FriendMy friend the tree
May fling his arms
In any twisted
Way
But the leaves
Still chase the sun
(Previously unpublished; 1979)

HandsThe steady beat of blood and life
Course through strong square hands
These instruments of man can
Hold each other
In silent prayer or
Kill with plunging knife
They can mold the supple clay of the mind
And in turn the mind’s clay, now hardened
In times course
Transmits its experience back to the hands that
Holds the brush and mixes the paints
Of life’s experience
(First Printed in the Christian Bothers College Pretoria Annual,1978)


Seven
A part of me is still seven
Holding hands in a queue at the
Odeon on Saturday morning

A part of me is still seven
Sharing a Nougat bar with you when
the lights go down for the matinee

A part of me is still seven
Watching the usher shining
her torch and trying to quiet
the rowdy boys during the trailers

A part of me is still seven
Playing cowboys and crooks in
your garden corner house on the hill

A part of me is still seven
Getting beaten-up by Steven
because he liked you too

A part of me is still seven
Planting a tree with the
headmaster at the entrance to school

A part of me is still seven
Stealing a chaste kiss before
going home

Apart of me
Is
still
(unpublished; 2006)

Wednesday, November 15, 2006

Doing the math on DNA

Common ancestors of all humans (using mathematical models)
Main Sources:
Mathematical models:
Chang, Joseph T. (1999), Recent common ancestors of all present-day individuals, Advances in Applied Probability 31(4), 1002-26. Followed by discussion and author's reply, 1027-38. The discussion includes comments by:
Carsten Wiuf and Jotun Hein.
Montgomery Slatkin.
W.J. Ewens.
J.F.C. Kingman.

Neil O'Connell (formerly here)
Branching and Inference in Population Genetics (1994)
N. O'Connell. The genealogy of branching processes and the age of our most recent common ancestor. Advances in Applied Probability, 27:418-42, 1995.

Computer simulations:
Douglas L.T. Rohde
His paper:
Somewhat Less-Recent Common Ancestors of all present-day individuals (title is reference to Chang's paper), draft, 2002.
On the common ancestors of all living humans, updated version, 2003, submitted to American Journal of Physical Anthropology.

Modelling the recent common ancestry of all living humans, Douglas L. T. Rohde, Steve Olson and Joseph T. Chang, Nature 431 (7008), 562-6, (September 30, 2004), "Letters to Nature".
News and views
Supplementary Information
Nature news release
Yale news release

Sources yet to be consulted:
Mathematical models:
A.M. Zubkov. Limiting distributions for the distance to the closest mutual ancestor. Theory Probab. Appl., 20(3):602-12, 1975.
P. Jagers, O. Nerman, and Z. Taib. When did Joe's great ...grandfather live? Or on the timescale of evolution. In I.V. Basawa and R.L. Taylor, editors, Selected Proceedings of the Sheffield Symposioum on Applied Probability, volume 18 of IMS Lecture Notes-Monograph Series, 1991.

Branching Processes
V.A. Vatutin. Distance to the nearest common ancestor in Bellman-Harris branching processes. Math. Notes, 25:378-87, 1979.
Coalescent Theory
Martin Moehle


Summary
Mathematical models of populations are limited by the difficulty they have with modelling in a clean way the complex, non-random mating patterns caused by geography, population movement, religion and social status. It is easier to make an assumption like random mating.
To actually model the quirks of the history and geography of the world you really need a computer simulation.




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With random mating, the MRCA would be c.1200 AD
Many mathematical models are of 1-parent genealogies - which is basically like modelling the female-female or male-male CAs.
[Chang, 1999] builds a 2-parent rather than 1-parent model - in pursuit of the real MRCA, rather than just the female-female or male-male one. In his model, if we assume a constant population size, 2 parents per individual, and random mating, then we expect the MRCA to be (log2 of the population size) generations in the past. This is incredibly recent. e.g. Take population size as (a generous) 500 million to estimate the world population over recent history. Then the MRCA is 29 generations ago - say around 1200 AD!

[Ewens, 1999] notes this is basically the reverse analogue of the fact that you only need to go back log2(n) generations to need n separate ancestors.



Non-random mating would push the MRCA further back
Chang says this medieval MRCA is implausible (though as my Royal Descents page illustrates, it is not that implausible at all) and notes that one problem with applying the model to humans is random mating. In reality, mating is of course local. The model does allow for "unlucky" random mating which could push the MRCA back, but notes that it is very unlikely in a large population that you get unlucky enough mating to push it even twice as far back. Perhaps local mating is just unlucky random mating and makes little difference in the long run. But this needs to be proved (by constructing a local-mating mathematical model). It may be that the pattern of local mating is extremely distorted by earth's specific geography, so perhaps only a computer simulation (rather than a general mathematical model) can solve this issue.
An extreme example of earth's geography would be total isolation. Many human populations, especially in Australia, the Pacific, the Americas and the Arctic, seem to have been isolated from each other until modern times. If populations were truly isolated, then the probability of 2 individuals mating either side of the barrier may truly have been zero for thousands of years. In which case the MRCA for the world would be pushed back to thousands of years ago. Apparently [Nei and Roychoudhury, 1982] and [Goldstein et al, 1995] use DNA to estimate ages for the MRCA of 116,000 and 156,000 years ago. One wonders if they are aware that DNA cannot be used to estimate the MRCA.

In theory, cases of extreme religious isolation (or ethnic or linguistic or social isolation) could also push back the MRCA. But we know that extreme religious (or other ethnic or cultural) reproductive isolation simply does not last for hundreds of years. If people share the same territory, some of them will interbreed no matter what. A tiny minority perhaps, but that's all we need to rapidly get everyone descended from an MRCA. The only thing that will stop people interbreeding is total geographical isolation.

Whatever about the world as a whole, Chang's model does suggest that the MRCA for Europe, where populations constantly mixed, may be well within historical times. Quite likely (as is suggested by other independent evidence on my Royal Descents page) the entire population of the West descends from Charlemagne.

One wonders what Chang's model would predict for the most recent strict female-female or strict male-male ancestor. Comparing this with the DNA figures might give us a handle on how unrealistic random mating is as a model.




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In the past, ancestor of some means ancestor of all
Chang's second result is that when you go far enough back, every individual is either an ancestor of the whole world today, or else is an ancestor of no one alive today. In nature, it is obvious that this state must be reached as you go back, see [Dawkins, 1992] - just consider ancestral fish. If I am descended from a particular one, then so are all humans.
In Chang's mathematical model this state is reached very quickly, within about 1.77 times the number of generations of the MRCA, i.e. using our numbers above, perhaps c.700 AD. So it would look like this:

Before 700 AD, every single human is either ancestor of no one alive today, or ancestor of everyone alive today. [Rohde, 2002] refers to this as the "All Common Ancestors", or ACA, point. Obviously if someone in this period is a proven ancestor of someone alive today then they must be ancestor of everyone alive today. So, for example, Charlemagne, because he is a proven ancestor of some people alive today, is probably the ancestor of everyone alive today in the West.

Between 700 AD and 1200 AD, every single human is either ancestor of no one alive today, ancestor of everyone alive today, or ancestor of some people alive today.

After 1200 AD, every single human is either ancestor of no one alive today, or ancestor of some people alive today.
Accepting that it is wrong to draw the above conclusions with locally-mating humans - despite that, these figures are in fact quite plausible (if restricted to the Western world at least).



In the past, you are descended from most of the population
In fact, Chang's model predicts that around 80 percent of the population before the ACA point is an ancestor of everyone alive today (and 20 percent are ancestors of no one alive today). But there is no realistic model of mate choice. [Rohde, 2002] has a better model of mate choice, and comes up with a more convincing figure of around 60 percent of those who survive to adulthood and have children. This is discussed below.



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Computer simulations
[Rohde, 2002] has run the first ever serious computer simulation of the history of the world's genealogy.
He makes a serious attempt to model non-random mating. He sets up an abstract model of "continents", "countries" and "towns", which can be viewed not merely as geographic position but more abstractly as the pool from which one is more or less likely to choose a mate - whether that pool be geographic, religious or whatever.

He even simulates the historical growth of the world population - adjusting the birth and survival rate so that population growth matches the real numbers over the centuries from 1000 BC to 2000 AD. Interestingly, he found this made little difference to the MRCA date.

Given a reasonable choice of parameters, he estimates the MRCA for the world at c. 300 AD, with bounds of c. 150 BC to c. 800 AD.

The lowest rate of migration (and hence lowest rate of cross-breeding) he tried was: probability of leaving the "country" 0.05 percent and probability of leaving the "continent" 0.001 percent. Even with this extreme local-breeding model he still gets an MRCA for the whole world in historical times at c. 150 BC.




Growing Artificial Societies: Social Science from the Bottom Up by Joshua M. Epstein and Robert L. Axtell.

Before the ACA point, ancestor of some means ancestor of all
Very interestingly, Rohde empirically confirms Chang's model that not long (only a few centuries) before the MRCA, we reach the ACA point, where everyone is either a CA (ancestor of everyone) or else their line is extinct.


Before the ACA point, you are descended from most of the population that has children
Rohde does, however, correct Chang's figure of 80 percent of people being CAs before the ACA point. He uses non-random mating, a realistic birth rate, and a model of male-female mate choice, to get a more convincing figure of around 60 percent for the percentage of people whose lines do not go extinct. This is restricted to those who have lines in the first place, i.e. 60 percent of those who survive to adulthood and have children.
In other words, if you go back before the ACA point, which may be as recent as classical times, you are descended from around 60 percent of any ancient population that has children.

My DNA results

GENETIC ANCESTRY TESTING REPORT
Division of Human Genetics, National Health Laboratory Service, P O Box 1038, Johannesburg, 2000
Room 303 James Gear Building, Corner of Hospital and DeKorte Streets, Braamfontein
Tel: (011) 489-9237 (Laboratory) Prof Himla Soodyall: (011) 489-9208 FAX: (011) 489-9226
MRC/NHLS/WITS HUMAN GENOMIC
DIVERSITY AND DISEASE RESEARCH UNIT
(HGDDRU)

NAME: Douglas Racionzer
SEX: Male
MtDNA analysis
MtDNA HVRI variation: 16183A-C, 16189T-C, 16223C-T,16278C-T,
16294C-T, 16390G-A
MtDNA HVRII variation: 73A-G, 143G-A, 146T-C, 195T-C, 263A-G
MtDNA haplogroup: L2a
MtDNA matches: When we searched our sub-Saharan African
database we found no identical match; closest
match differed by two base positions to 2
Bantu-speakers from South Africa.
Haplogroup information

It is possible for us to reconstruct the evolutionary history of all mtDNA lineages
found in living peoples to a common ancestor, sometimes referred to in the
popular press as “Mitochondrial Eve”. This ancestor lived in Africa, about
150,000 years ago. She lies at the root of all the maternal ancestries of every
one of the six billion people in the world. We are all her direct maternal
descendants. The various “patterns” of mtDNA sequence variation found in living
people are referred to as “haplogroups” that are defined by the presence of
certain changes (mutations) when compared to a published sequence referred to
as the reference sequence. These mutations are random and not associated with
any disease. The global pattern of distribution of mtDNA haplogroups is shown in
Figure 2 in the information sheet given to you at the time of sampling.

Of the thirty-three haplogroups recognized worldwide, thirteen can be traced to
geographic origins in Africa. MtDNA types found in African populations share
certain common features and have been assigned to haplogroup L. Haplogroup L
can be further resolved into L1, L2 and L3 (Sykes 2001). Haplogroup L2 is
divided into 4 subclades L2a through to L2d.

L2a is the most frequent and widespread mtDNA cluster in Africa. It does appear
to have an origin in West Africa and to have undergone dramatic expansion
either in southeastern Africa or in a population ancestral to present day
southeastern Africans, its distribution does suggest a signature for the Bantu
expansion (see distribution in map below). Sequences associated with this
haplogroup have been evolving for about 33,000 years (Salas et al. 2002).

The following is an extract from and article published in the American Journal of Human Genetics:
The Making of the African mtDNA Landscape
Antonio Salas,1,2,3 Martin Richards,2 Tomás De la Fe,1 María-Victoria Lareu,1 Beatriz Sobrino,1 Paula Sánchez-Diz,1 Vincent Macaulay,3 and Ángel Carracedo1
Haplogroup L2
Haplogroup L2 (figs. 6 and 7) is commonly subdivided into four main subclades, L2a through L2d (Chen et al. 2000; Pereira et al. 2001; Torroni et al. 2001). L2c cannot be distinguished from L2* without HVS-II information (325 in HVS-II) or coding-region mutations, although some of its subclades have distinctive HVS-I motifs. Among the southeastern Africans typed for this study (table 1), we found no L2* mtDNAs (in agreement with Torroni et al. 2001). The great majority belong to L2a (fig. 6), the most frequent and widespread mtDNA cluster in Africa (nearly a quarter of all indigenous types), as well as in African Americans.
We have attempted partly to disentangle the structure of L2a, retaining as irreducible on present evidence three major squares close to the root of the cluster. These reticulations link eight main clusters by single-step mutations. We assume that the main reticulations of the network are due to the existence of rapid transitions at positions 16189 and 16192 (Howell et al. 2000), which approach saturation due to the high time depth of African lineages. We also assume that position 16309 is more stable than the two known fast sites and therefore is not responsible for the main reticulations. On these grounds, clusters α1-α2-α3, as well as β1-β2-β3, might be collapsed into two main clusters, one of them with the basal motif of L2a and the other harboring the transition at 16309 (L2a1). Several instances in which 16309 must nevertheless evolve in parallel can then be read off the network.
There are two L2a clusters well represented in southeastern Africans, L2a1a and L2a1b, both defined by transitions at quite stable HVS-I positions. Both of these appear to have an origin in West Africa (as indicated by the distribution of matching or neighboring types), and to have undergone dramatic expansion either in southeastern Africa or in a population ancestral to present-day southeastern Africans. L2a1b almost certainly includes the 16192T-derived subcluster, which is exclusively present in the southeast. The very recent starbursts in subclades L2a1a and L2a2 suggest a signature for the Bantu expansions, as also suggested by Pereira et al. (2001). The L2a1a founder candidate dates to 2,700 (SE 1,200) years ago. For L2a1b there is a rather older age estimate of 8,850 years, but this has an enormous standard error (SE 4,600 years) as a result of the early 16192 branch (Pereira et al. 2001). If we assume a starlike tree by suppressing the 16192 variant (effectively assuming that this is a third founder type), the age is 5,250 (SE 1,600) years. An average age estimate, under the assumption of two founders in L2a, is 6,600 (SE 3,000) years or, under the assumption of three founders, 3,750 (SE 900) years. Thus, it appears that the founder ages for L2a are significantly older than for L1a, consistent with the phylogeographical picture, with an earlier West African origin for the L2a lineages of southeastern Africa and a more recent East African origin for the L1a lineages. Indeed, the age of the L2a founders in southeastern Africa is consistent with an origin in the earliest Bantu dispersal from the Cameroon plateau, 3,500 years ago (Phillipson 1993).
It is difficult to trace the origin of L2a with any confidence. The deepest part of L2a, represented by clusters α1-α3, is most common in East Africa. However, the diversity and TMRCA are similar in East (61,250 [SE 13,500] years) and West (54,100 [SE 17,087] years) Africa. The diversity accumulated separately in East and West Africa, estimated from the main shared founder types (and disregarding the possibility of subsequent gene flow), is again similar in the two regions, at ∼14,000 years (14,100 years [SE 5,100], and 13,800 years [SE 4,700], respectively), suggesting a separation shortly after the Last Glacial Maximum. An easterly origin for L2a also faces the following difficulties: that the other subclades of L2 (L2b, L2c, and L2d) have a clear western distribution, and that L2d diverges earlier in the mtDNA phylogeny than L2a (Torroni et al. 2001). A possible solution would be an origin for L2a somewhere between east and west, followed by dispersals in both directions along the Sahel corridor.
Haplogroups L2b, L2c, and L2d appear to be largely confined to West and western Central Africa (and African Americans), with only minor occurrences of a few derived types in the southeast. L2b also shows isolated occurrences in the east and as far north as Iberia. Therefore, an origin for all three in West and western Central Africa seems likely. Complete sequence data indicate that L2d is the oldest of the four subclades of L2, diverging before L2a, and that L2b and L2c are sister clades that diverged more recently (Torroni et al. 2001). The estimated divergence times, ranging from ∼120,000 years, for L2d, through 55,000 years, for L2a, and ∼30,000 years, for L2b and L2c, with an estimated overall age for L2 of ∼70,000 years, are consistent with this pattern. In the light of this, it is scarcely surprising that tracing its place of origin is problematic. At such an age, it seems perhaps unlikely that L2d should have diverged in West Africa, but, given the period of potential drift and extinction, the data are certainly consistent with a Central African origin. A single type in the subclade L2d1, not seen in the southeastern Africans but present at high frequency in the Bubi of Bioko, may represent a trace of this.
L2 contributes 36% (95% CR .316–.408) to the southeastern Bantu population. If we sum this with the other major southeastern haplogroups of clear West African origin, L3b and L3d, the combined contribution of a putative West African source is ∼44% (95% CR .398–.493).
(Am J Hum Genet. November 2002; 71(5): 1082–1111)


Y chromosome analysis
Two kinds of Y chromosome data were used to resolve your Y chromosome
lineage. The first involved screening for certain mutations to elucidate the Y
chromosome haplogroup (groups of lineages that are identical by descent since
they share a common defining mutation). The second involved the use of faster
evolving DNA called short tandem repeats (STRs) that we use to further resolve
the haplogroup. By screening for several of these STR markers it is possible to
derive a haplotype, a combination of the patterns observed for each region on
the Y chromosome tested.

Y chromosome haplogroup: E-M35
Haplogroup information:
Haplogroup E-M35 was one of the Y haplogroups that was common among the
Neolithic farmers from the Middle East who first brought agriculture into Europe
about 9 000 years ago. It has been estimated that the date of the most recent
common ancestor of all E-M35's is 24 000 to 27 000 years ago and that the
probable place of origin was east Africa (Cruciani et al. 2004). It is seen most
frequently along the Mediterranean coast at frequencies of 20-24% in Greece,
10-27% in Italy, and 2-11% in Spain (Semino et al. 2004). It is present at low
frequencies in Britain at 6%, in Germany at 3%, and less than 0.5% in Norway
(Capelli et al. 2003). Haplogroup E-M35 is seen at a frequency of ~ 10% in the
South African White and Jewish population.

STR profile:
Marker DYS19 DYS389I DYS389II DYS390 DYS391 DYS392 DYS393
Profile 14 14 32 24 10 11 13
Range 10-19 9-17 24-35 12-29 6-15 6-18 7-17
Marker DYS385 DYS438 DYS439
Profile 16, 17 10 12
Range 7-25 8-12 8-15

STR Matches:
We compared your Y chromosome STR profile with about 41,000 Y chromosome
haplotypes from a STR database (www.ystr.org). When using all ten markers
(both tables above) we found no identical match. However, when using 7
markers (first table) we found 10 identical matches worldwide, i.e. 4 European, 3
Latin American, 1 North American and 2 matches found in an African population.
When we searched our local database, using the first seven markers we found
no identical match; closest matches differed by one STR repeat to 2 South
Africans, i.e. 1 Jewish and 1 Coloured

References
Capelli et al. 2003. Curr Biol. 13(11):979-84.
Cruciani et al. 2004. Am J Hum Genet. 74(5):1014-22.
Semino et al. 2004. Am J Hum Genet. 74(5):1023-34.
Salas et al. 2002. Am J Hum Genet 71: 1082-1111.