April 25, 2013: A commemorative all-day symposium, in Kirschstein Auditorium, Natcher Conference Center, featured a group of speakers. The event, The Genomics Landscape a Decade after the Human Genome Project,looked at the accomplishments of the decade with an eye to what is on the horizon. The date of the symposium was significant, occurring in the month that the HGP was announced 10 years ago, and coinciding with the date 60 years ago when James Watson and Francis Crick's article describing DNA's double-helical structure was published. The symposium is timed with both historic achievements in mind.
The complete list of talks is available here (with slides).
In this article, I (the author) followed multiple sources in referring to 'Photo 51' as the work of Rosalind Franklin. However, medical geneticist Jim Lupski raised a query about the accuracy of the attribution, having received correspondence from Jim Watson which mentioned in passing that Ray Gosling had taken the photo.Note that Gosling was originally Wilkins' graduate student. The two were taking X-ray photographs of DNA before Franklin ever became involved. Additional background:
I put the query to Gosling, who confirms that he was indeed 'Photo 51' photographer:
'It was part of the program that Rosalind and I were carrying out to check the effect of the humidity on the crystallization of DNA. This was the 51st of that program, and I was the one who took that particular diffraction pattern.'
Thanks to Jim Lupski for bringing the inaccuracy to my attention, to Ray Gosling for providing further information, and to Jim Watson for confirming that this was his understanding of events.
Wilkins began using optical spectroscopy to study DNA in the late 1940s. In 1950 he and Gosling obtained the first clearly crystalline X-ray diffraction patterns from DNA fibres, and Alec Stokes suggested that the patterns indicated that DNA was helical (spiral) in structure. [source]
Franklin's fellowship proposal called for her to work on x-ray diffraction studies of proteins in solution. However, there was a shift in research priorities after Maurice Wilkins, the assistant director of Randall's lab, began working with an unusually pure sample of DNA obtained from Rudolf Signer. Excited about the possibilities, Wilkins suggested to Randall that Franklin's expertise might be better applied to this promising DNA research. Randall agreed; he wrote to Franklin in November 1950, explaining the change of plan, and stated that she and graduate student Raymond Gosling would be the only staff doing crystallographic studies of DNA. Randall did not mention Wilkins' serious interest in DNA, nor did he tell Wilkins the details of the letter. These omissions soon generated misunderstandings between Wilkins and Franklin--Franklin assumed that the x-ray diffraction studies of DNA would be her project alone; Wilkins assumed that she was joining the loosely organized research team ("Randall's Circus") at the biophysics lab, as the expert on crystallography. When Wilkins continued working on DNA and suggested that he and Franklin collaborate, she resented what she regarded as interference. [source]
Rosalind Franklin has become such a symbolic figure that it is now hard to separate facts from myths. However, in the rush to see Franklin as wronged, it needs to be recalled that Wilkins was a senior independent scientist, had laid a lot of groundwork for the DNA work, and had obtained the actual DNA samples Franklin went on to take x-ray pictures of. All this was then essentially taken off him by the unit head (Randall) and given to Franklin. So it could be argued with a good deal of justification that the DNA project at King's was very much Wilkins' baby, and would not have existed for Franklin to take forward without years of Wilkins' groundwork. [source]
“To think that Rosy had all the 3D data for 9 months & wouldn’t fit a helix to it and there was I taking her word for it that the data was anti-helical. Christ,” Dr. Wilkins wrote, musing on how close he might have come to making the discovery himself. [source]
Genome 562 - Population Genetics - Joe Felsenstein
Theoretical Evolutionary Genetics - a draft text - Joe Felsenstein
Population Genetics notes - Graham Coop
Population genetics teaching resources - Graham Coop
Lecture notes in population genetics - Kent Holsinger
The Progress of Genetics From the 1930s to Today - James Crow (2010)
Introduction to Population Genetics - Lynn Jorde (2012)
From the detailed genomes of both Neandertals and Denisovans, Pääbo and Montgomery Slatkin of the University of California, Berkeley, estimated that 17% of the Denisovan DNA was from the local Neandertals. And the comparison revealed another surprise: Four percent of the Denisovan genome comes from yet another, more ancient, human—"something unknown," Pääbo reported. "Getting better coverage and more genomes, you can start to see the networks of interactions in a world long ago," says David Kingsley, an evolutionary biologist at Stanford University in Palo Alto, California.John Hawks: New Denisova and Neandertal DNA results reported
With all the interbreeding, "it's more a network than a tree," points out Carles Lalueza-Fox, a paleogeneticist from the Institute of Evolutionary Biology in Barcelona, Spain. Pääbo hesitates to call Denisovans a distinct species, and the picture is getting more complicated with each new genome.
Now, we may be learning that the Denisovan genome itself represents different ancestral groups -- not only a more ancient "something unknown" population, but substantially the local Neandertals. That kind of mixture is not the population history described by papers on the Denisova genome so far. And a third Denisovan mtDNA from one of the third molars at the site is substantially different from the other two, pointing to greater mtDNA diversity within the Denisovan population than now known from either Neandertals or living people.Related posts:
What does it mean? I don't think there's a contradiction here in the data. What this shows is that the methods applied to the data have been too simplistic. The methods will come to a result, but that result may not fit the data as well as a population model with more complexity. Looking only at one kind of comparison -- as the Li and Durbin model applied to the Denisova genome by Meyer and colleagues last year  -- will probably not give a result that describes the true population history. We need to keep our minds open to more complex population histories that may be more consistent with other sources of data, including archaeological and fossil information.
The first three are currently in progress, but I believe you can still sign up and watch the lectures.
Genes and the Human Condition (From Behavior to Biotechnology)
Tammatha O'Brien, Raymond J. St. Leger
Introduction to Biology - The Secret of Life
Archaeology's Dirty Little Secrets
Human Evolution: Past and Future
The ethnic breakdown I come up with for the March 2013 update of Forbes' "The World's Billionaires" list:
|Asian or Pacific Islander||313||21.95|
|Middle Eastern or Central Asian||120||8.42|
|(New World) Hispanic or Brazilian||74||5.19|
Particularly for Eastern Europe, individual classifications may be less accurate than my classifications of US billionaires, but the overall breakdown should be reasonably close to reality. I may have incorrectly included a few people in the Jewish list, but if anything probably incorrectly left off a larger number -- my Jewish category should be more accurate/comprehensive than Forbes Israel's "Richest Jews" list in any case. Note that I've arbitrarily chosen to include Tatars in the Middle Eastern category, along with Armenians, Azerbaijanis, etc. Mongoloid-appearing Kazakhs were included in the Asian category. I generally put Latin Americans with Northern European or Italian names (who were not obviously mestizo) in the appropriate European category.
You're free to post any corrections.
- 2012 Forbes 400 by ethnic origins
- The world's richest Jews (an incomplete list)
- Ethnic origins of US attendees of 2013 World Economic Forum in Davos
Full list below.
But, from the Middle Neolithic onwards, DNA patterns more closely resembled those of people living in the area today, pointing to a major - and previously unrecognised - population upheaval around 4,000 BC.Neolithic mitochondrial haplogroup H genomes and the genetic origins of Europeans
Co-author Prof Alan Cooper, from the University of Adelaide in Australia, said: "What is intriguing is that the genetic markers of this first pan-European culture, which was clearly very successful, were then suddenly replaced around 4,500 years ago, and we don't know why.
"Something major happened, and the hunt is now on to find out what that was." [. . .]
A significant contribution appears to have been made in the Late Neolithic, by populations linked to the so-called Bell Beaker archaeological culture. Sub-types of haplogroup H that are common today first appear with the Beaker people and the overall percentage of individuals belonging to the H clan jumps sharply at this time.
The origins of the "Beaker folk" are the subject of much debate. Despite having been excavated from the Mittelelbe Saale region of Germany, the Beaker individuals in this study showed close genetic similarities with people from modern Spain and Portugal.
Other remains belonging to the Late Neolithic Unetice culture attest to links with populations further east.
"We have established that the genetic foundations for modern Europe were only established in the Mid-Neolithic, after this major genetic transition around 4000 years ago," said co-author Dr Wolfgang Haak.
"This genetic diversity was then modified further by a series of incoming and expanding cultures from Iberia and Eastern Europe through the Late Neolithic."
Haplogroup H dominates present-day Western European mitochondrial DNA variability (>40%), yet was less common (~19%) among Early Neolithic farmers (~5450 BC) and virtually absent in Mesolithic hunter-gatherers. Here we investigate this major component of the maternal population history of modern Europeans and sequence 39 complete haplogroup H mitochondrial genomes from ancient human remains. We then compare this ‘real-time’ genetic data with cultural changes taking place between the Early Neolithic (~5450 BC) and Bronze Age (~2200 BC) in Central Europe. Our results reveal that the current diversity and distribution of haplogroup H were largely established by the Mid Neolithic (~4000 BC), but with substantial genetic contributions from subsequent pan-European cultures such as the Bell Beakers expanding out of Iberia in the Late Neolithic (~2800 BC). Dated haplogroup H genomes allow us to reconstruct the recent evolutionary history of haplogroup H and reveal a mutation rate 45% higher than current estimates for human mitochondria.
The (sold out!) 2013 Genomes, Environments and Traits (GET) Conference is taking place this Thursday and Friday in Boston. We are celebrating the 60th anniversary of the DNA double helix with an amazing line-up of speakers and Labs.
You may watch the live webcast for free via our new channel at Fora.TV: get2013.fora.tv.
Summary: No dramatic departures from 2009/2010.
|1987 (%)||2009 (%)||2010 (%)||2012 (%)|
[Update: see Ethnic origins of Forbes world billionaires (2013) for a more comprehensive list of Jewish billionaires.]
Steve Sailer alerted me to Forbes Israel's list of Jewish billionaires (http://www.forbes.co.il/rating/list.aspx?en6v0tVq=FK), pointing out the number of American Jews appears to be much lower than might be expected based on assessments of the ethnic makeup of the Forbes 400 in 2009 and 2010. As translated by Google:
The world's richest JewsHaving now looked at the 2012 Forbes 400, I see an ethnic breakdown similar to 2009/2010. The Forbes Israel "richest Jews" list was published about a week ago and appears to be put together based on the Forbes World's Billionaires list, which was updated in March 2013. The most recent Forbes 400 was finalized in September 2012, so, while minor differences are possible, for the US the lists should mostly overlap. The Forbes 400 threshold is about $1.1 billion (rather than $1 billion), so we'd tend to expect more US names on the Forbes Israel list than Jews in the Forbes 400 -- if the compilers were thorough. They don't appear to have been.
Jewish billionaires comprise 11% of global billionaires list, and common wealth reaches -812 billion. Who is the top, and in some places deteriorated Mark Zuckerberg?
We investigate the relationship between intelligence and bribing behavior in a simple one-shot game of corruption. We find a robust relationship between intelligence and the probability of bribing in which a higher intelligence quotient (IQ) leads to a lower probability of bribing in the game. This result holds after controlling for other determinants such as gender, attitude toward corruption, and perceptions of corruption. By revealing the gender of the matched player, we also show that gender perceptions of corruption are strong determinants of bribery.Intelligence and corruption
This study finds that countries with high-IQ populations enjoy less corruption. I propose that this is because intelligent people have longer time horizons.(Via UDADISI.)
The current study, based on the nationally representative NLSY data, follows incarceration over a 24-year period. This represents the longest prospective examination of the NLSY crime data to date, since previous analyses have been shorter and is not prospective (Herrnstein & Murray, 1994). With the aim of providing greater confidence in the results, unlike prior analyses the current study uses three major criminological outcomes (onset, incidence and frequency of incarceration), and not one (incidence of incarceration). Based on theoretically reformulated associations between the study variables, the results show that low IQ, low parental SES and their interaction modestly predict the incidence of, frequency of and time to incarceration.Related posts:
Theoretically, a low IQ may make coping and decision-making difficult and increase the likelihood of crime. Taken in isolation the association between low IQ and increased risk of crime in the current results may be taken as evidence that is consistent with the Bell Curve (Herrnstein & Murray, 1994). Concurrently, however, the present results also indicate that a low parental SES increases the risk of crime, potentially through an inadequate familial environment (Bradley & Corwyn, 2002). These family characteristics may include little emphasis on social attainment. Thus, the current findings indicate that the family environment may provide a route to influence the association between IQ and crime. This possibility is not considered in the Bell Curve view on crime that emphasizes neighborhood SES (Herrnstein & Murray, 1994), and is consistent with opponents to the Bell Curve (Fischer et al., 1996).
Collectively, however, the effects of IQ and parental SES on crime are modestly amplified, as captured by the interaction reflecting unfavorable conditions (i.e., particularly if both IQ and parental SES are low). A possible explanation of this interaction is that a disadvantaged home environment does not encourage social attainment and a low IQ makes coping and decision-making difficult. Taken together this increases the likelihood of crime. Thus these findings support an interactional perspective of crime. Their interpretation is consistent with the usually competing theoretical notions that contrast low SES (Fischer et al., 1996) or low IQ (Herrnstein & Murray, 1994) as factors that increase the likelihood of crime. [. . .]
This study does not separate genetic–environmental influences, unlike past research (e.g., Koenen, Caspi, Moffitt, Rijsdijk, & Taylor, 2006). SES may not purely be an environmental factor that is unrelated to IQ. Parents may give children both genes for IQ and SES (i.e., passive gene–environment associations), and a parent’s SES is partly based on their IQ as a result of life-long active gene–environment interactions. Accordingly, IQ and SES may be moderately correlated due to common genetic influences. Also, as the participants in this study mature, they become increasingly free to create their own environments, partly due to both IQ and SES. The current study, however, affords no assessment of genetics, or upward or downward social mobility, thereby highlighting key directions for future research.
Racial/ethnic differences in serum sex steroid hormone concentrations in US adolescent males. Cancer Causes & Control. April 2013, Volume 24, Issue 4, pp 817-826
OBJECTIVE: Contrary to the hypothesis that the racial/ethnic disparity in prostate cancer has a hormonal basis, we did not observe a difference in serum testosterone concentration between non-Hispanic black and white men in the Third National Health and Nutrition Examination Survey (NHANES III), although non-Hispanic black men had a higher estradiol level. Unexpectedly, Mexican–American men had the highest testosterone level. Next, we evaluated whether the same patterns are observed during adolescence, the time of prostate maturation.This sample is not large, and some of the statistical adjustments may be questionable. But others have also failed to find black-white differences in testosterone among adolescents in unadjusted NHANES data; nor were they seen in a larger study of adolescents,
METHODS: We measured serum testosterone, estradiol, and sex hormone-binding globulin (SHBG) by immunoassay in 134 males aged 12–19 in NHANES III. Mean concentrations were compared by race/ethnicity adjusting for age, Tanner stage, percent body fat, waist, physical activity, tobacco smoke, and the other hormones.
RESULTS: After multivariable adjustment, in the 12–15-year-old males, testosterone concentration was lower in non-Hispanic blacks than whites (p = 0.043), SHBG concentration did not significantly differ between the two groups. Mexican–Americans had the highest testosterone (versus non-Hispanic black: p = 0.002) and lowest SHBG (versus non-Hispanic white: p = 0.010; versus non-Hispanic black: p = 0.047) concentrations. Estradiol concentration was lower in non-Hispanic blacks (p = 0.11) and Mexican–Americans (p = 0.033) compared with non-Hispanic whites. After multivariable adjustment, in the 16–19-year-old males, testosterone, estradiol, and SHBG concentrations did not differ between non-Hispanic blacks and whites. Mexican–Americans had the highest testosterone concentration (versus non-Hispanic white: p = 0.08), but did not differ from the other groups on estradiol and SHBG concentrations. In both age groups, these patterns were generally present, but less pronounced after adjusting for age and Tanner stage only.
CONCLUSION: In adolescent males, non-Hispanic blacks did not have a higher testosterone concentration than non-Hispanic whites, and Mexican–Americans had the highest testosterone concentration, patterns similar to adult males.
A large biracial cross-section of 1038 healthy children aged 6-18 yr with 519 blacks, 519 whites, 678 males, and 360 females was evaluated for Tanner stage and serum levels of androstenedione, dehydroepiandrosterone- sulfate, estradiol, progesterone, and testosterone. The anthropometric values of the blacks and whites were very similar at each Tanner stage with only minor differences in age, height, and weight related to an earlier onset of puberty in blacks. The hormones dehydroepiandrosterone- sulfate, progesterone, and testosterone did not exhibit any racial differences. Estradiol showed a significantly higher level among black males compared to white males (P 5 0.05) whereas androstenedione was significantly higher in both white males (P = 0.0001) and females (P I 0.01) compared with blacks.
The human lineage two million years ago was a population with ape-sized brains limited to sub-Saharan Africa. The human lineage expanded into Eurasia around 1.85 million years ago, and our brain size increased throughout the Pleistocene. Anatomically modern humans first appeared in Africa about 200,000 years ago, with anatomically modern forms appearing outside of Africa at more recent dates. [. . .]
One powerful way of extracting this information about past evolution is through multilocus nested clade analysis (MLNCA). This method converts the evolutionary history of a DNA region with little to no recombination into a series of nested branches (clades), which captures time (the deeper the branch in a nested series, the older the time), and then overlays the spatial distribution of the currently observed genetic variation upon the nested series. In this manner, we can estimate the evolutionary history of current variation through both space and time. [. . .]
MLNCA does not require a prespecified model of evolution; rather, the model emerges naturally out of the cross-validated statistically significant inferences. Thus, there is no inherent bias toward any a priori model of human evolution. The cross-validated MLNCA inferences produced a model of human evolution that had some features of previous models, but unique features as well (Figure).
How far can media undermine democratic institutions and how persuasive can it be in assuring public support for dictator policies? We study this question in the context of Germany between 1929 and 1939. Using quasi-random geographical variation in radio availability, we show that radio had a significant negative effect on the Nazi vote share between 1930 and 1933, when political news had an anti-Nazi slant. This negative effect was fully undone in just one month after Nazis got control over the radio in 1933 and initiated heavy radio propaganda.Steve Sailer: "Gay Marriage" in Ngram: Media Muscle in action
Here's a Google Ngram graph of usage in books of the terms "gay marriage" in red and "homosexual marriage" in blue from 1800 to 2008. The terms were essentially nonexistent until the early 1970s, after which there were a tiny, relatively stable number of references to "homosexual marriage" for two decades. Then there was an inflection point around 1994 and another one around 2003. (Methodology notes: The graph above reflects Ngram's default three-year moving average smoothing. If you turn off smoothing, the inflection points appear a little later than when smoothing is on. Of course, books perhaps lag behind other media because of their longer production cycles.)Nate Silver: Gay Marriage Opponents Now in Minority
I'm fascinated by the mechanics of media muscle reflected in the two inflection points. Here's a topic that had interested almost nobody, straight or gay, for, roughly, ever, yet then in two stages becomes a cultural obsession.
This is the fourth credible poll in the past eight months to show an outright majority of Americans in favor of gay marriage. That represents quite a lot of progress for supporters of same-sex marriage. Prior to last year, there had been just one survey — a Washington Post poll conducted in April 2009 — to show support for gay marriage as the plurality position, and none had shown it with a majority.
As we noted last August, support for gay marriage seems to have been increasing at an accelerated pace over the past couple of years. Below is an update to the graph from last year’s article, which charts the trend from all available public polls on same-sex marriage going back to 1988.
Audacious Epigone: Skin tone and IQ, and volunteering, too
Human Varieties: Is Psychometric g a Myth?
Bruce Charlton: Harvard is a second rate research university
IQ-height correlation partly attributable to pleiotropic genetic factors (not just cross-assortative mating)2 comments Posted by n/a at 4/05/2013 12:25:00 AM
In this study, we modeled the covariation between monozygotic and dizygotic twins, their siblings, and their parents (total N = 7,905) to elucidate the nature of the correlation between two potentially sexually selected traits in humans: height and IQ. Unlike previous designs used to investigate the nature of the height–IQ correlation, the present design accounts for the effects of assortative mating and provides much less biased estimates of additive genetic, non-additive genetic, and shared environmental influences. Both traits were highly heritable, although there was greater evidence for non-additive genetic effects in males. After accounting for assortative mating, the correlation between height and IQ was found to be almost entirely genetic in nature. Model fits indicate that both pleiotropy and assortative mating contribute significantly and about equally to this genetic correlation. [. . .]Related posts:
Taller people tend to be smarter. Although the relationship is modest, height and IQ are consistently correlated at ~.10–.20 , , . [. . .]
The importance of genetic pleiotropy on the association between IQ and height is notable. On the surface, it might seem that height and IQ involve very different functional systems with different developmental origins. Genetic pleiotropy between IQ and height (indeed, between any two complex fitness traits) is consistent with the idea that variation in these traits partly reflects genome-wide mutational loads, and that these traits are components of attractiveness because of this—i.e., they are honest signals or cues of ‘good genes’ , , . The additional and substantial increase in additive genetic covariance as a function of assortative mating is consistent with both traits being attractive to the opposite sex.
A New Model of Social Class? Findings from the BBC’s Great British Class Survey Experiment (pdf):
We analyse the largest survey of social class ever conducted in the UK, the BBC’s 2011 Great British Class Survey, with 161,400 web respondents, as well as a nationally representative sample survey, which includes unusually detailed questions asked on social, cultural and economic capital. Using latent class analysis on these variables, we derive seven classes. We demonstrate the existence of an ‘elite’, whose wealth separates them from an established middle class, as well as a class of technical experts and a class of ‘new affluent’ workers. We also show that at the lower levels of the class structure, alongside an ageing traditional working class, there is a ‘precariat’ characterised by very low levels of capital, and a group of emergent service workers. We think that this new seven class model recognises both social polarisation in British society and class fragmentation in its middle layers, and will attract enormous interest from a wide social scientific community in offering an up-to-date multi-dimensional model of social class.
The controversy surrounding the $400-million Encode project’s dubious public relations claims surrounding the function of ‘junk DNA’ and the Battelle Institute’s defense of the $3-billion Human Genome Project (HGP) as economically beneficial (as cited in the recent State of the Union address) make this a good time to examine President Obama’s attempts to bring more of American science under centralized direction and control. [. . .]
The burden of proof for proposed mega-projects should be high, because for every research team working on a billion-dollar, centrally planned National Institutes of Health program, there are hundreds of independent scientists who will go begging. This is a tragedy, as the bulk of our scientific progress—especially in the life sciences—comes not from sclerotic bureaucracies following 10-year plans, but from the genius of independent scientists challenging the status quo.
Starting in January, 2014, I will be offering a massive open online course titled, "Human Evolution: Past and Future".
This course and all its materials will be open and free for anyone, anywhere in the world. As of this moment, more than 6500 people have already signed up for the course. The course is still more than nine months away, and I'll be developing materials across the entire time up through January. [. . .]
With a worldwide group of thousands of students, we'll be giving people the opportunity to participate in some real research. Some will be as simple as massive measurements of body proportions. Others will be more involved, leading us to...
Looking to the future. The course title is "Human Evolution: Past and Future." To me, the path of our evolution in the past is closely tied to where our species may be going. To that end, the course will be looking at the next hundred, thousand and ten thousand years of our evolution. I'll be interviewing people who are thinking about the impact of technology on our future evolution, and students will come up with their own scenarios based on a strong understanding of the forces that shaped human evolution in the past.