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Rabu, 12 Juni 2013

Mobile elements across human populations

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8 May 201311 Jun 2013021743365086710831300

Explanation of terms and methodology

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Program in Medical and Population Genetics

The Broad's Program in Medical and Population Genetics brings together a scientific community focused on understanding how genomic variation contributes to susceptibility to human disease and to an individual's response to therapy. Experts in population genetics, statistics, molecular biology, genomics, and bioinformatics collaborate to characterize common genetic variants and establish their role in disease.
Scientists in the Program in Medical and Population Genetics share ideas and launch collaborative projects to tackle key challenges. The program also works closely with scientists in the Genetic Analysis Platform. In addition, it collaborates with many other labs in the Harvard-MIT community and elsewhere.
Major areas of focus include:
Human genetic variation
Understanding the pattern of common genetic variation in the human population is a major focus of the program. First, this involves generating a systematic catalog of the common single-nucleotide polymorphisms (SNPs) in the human population. Second, it involves characterizing the correlations among nearby SNPs (known as haplotypes), making it possible to design genetic studies that are more efficient and powerful. With such information, it becomes possible to undertake systematic studies of the genetic factors underlying inherited susceptibility to common diseases.
Population genetics
Patterns of genetic variation shed light on recombination, demography, admixture, and evolutionary selection in the human population. In turn, knowledge about human population history helps inform studies in medical genetics.
Metabolic disease
The genetic basis of diseases associated with hormonal imbalance is being investigated. These include diabetes, obesity, and cardiovascular traits, in collaboration with colleagues in Sweden and in the Framingham Heart Study.
Cancer susceptibility
Cancer risk is a combination of genetic and environmental factors. Genetic risk factors in hormone-dependent cancers are being studied, in collaboration with the USC-based Multi-Ethnic Cohort Study.
Inflammatory disease
Studies are focused on the genetic basis of autoimmune diseases such as Crohn's disease, ulcerative colitis, systemic lupus erythematosus, rheumatoid arthritis, and multiple sclerosis.
Medical and Population Genetics scientists are at the heart of genetic analysis projects across Broad, collaborating in the design and interpretation of genetic and genomic research efforts by developing computational methods that enable scientists to recognize and understand gene variation patterns and their influence on disease and drug response.

STRUCTURE: is STRUCTURE suitable for human population genetic analyses?

STRUCTURE is a commonly used program to detect population structure among humans using mutilocu genotype data.  The program was originally developed to control for population structure for association studies, but this program and other structure-like programs are widely used for genetic studies of human to understand human prehistory and population subdivision patterns. 
STRUCTURE is a model based program, which means that the results obtained are only an approximation under the assumptions that model is build on.  Therefore, the applicability of the program has to be considered carefully by examining its assumptions. 
This method assumes that Hardy-Weingberg equilibrium and linkage equilibrium.  There should be no evolutionary force acting on the populations being analyzed (no mutation, no natural selection, no genetic drift, random mating, and population size should be large), except for gene flow which are included in the model to estimate admixture proportion of individuals. The genetic markers chosen have to be unlinked, non-gene coding markers.
However, the human populations violate these assumptions.  Mating among human are not random and non-gene coding markers could be linked to allele are naturally selected.  The populations size of hunter-gatherers is usually very small, so genetic drift have affected their genetic variations.  The genetic markers used for analysis have to be selected carefully, because the long linkage disequilibrium is observed in small populations and recently admixed populations. 
I do not think Pritchard et al (2000) address some other possibly important issues.  How the changes in population size affect the program?  What if ancestral populations did not evolve independently?  What happen, if one of the ancestral populations was genetically diverse and other did not have much diversity?
Maybe, is newer version of STRUCTURE more suitable for human population genetic studies?

CAN CULTURAL ANTHROPOLOGY SCROGG POPULATION GENETICS?



James Mullooly invented the word Scrogg, meaning something along the line of “anthropologist who catch geneticists playing fast and loose with the data.” In my experience, Scrogging is fairly easy to do on open-source turf of the Biological Sciences journals where there are often places for comments. These comments are typically reviewed by editors, and while not strictly “peer-reviewed,” would in my mind contribute to the academic record of aspiring academics. The editors I have had contact here andhere were fair and open to critiques of articles which were well-done technically, but missed out on a more social scientific perspective, as do many articles about human population genetics. The editors were quick to respond to me—it seems the biological sciences are much quicker than the social scientific journals at making editorial decisions.



I got away with two Scroggings because population geneticists wrote about a group that I knew just a little about, the Mlabri of Thailand. But I knew enough to know that lab-based geneticists who missed key points, and did not cite standard ethnographies. I am sure that there are many sociologists, anthropologists, and others who have similar experiences with geneticists writing about groups with which they are familiar. What I would encourage you to do is to go into Google Scholar, and PubMed and search for genetic studies of ethnic groups you are familiar with as a result of your field and library work. Then evaluate carefully how the data (typically blood samples) was handled on its way to the lab. Does the “sample” reflect social relations on the ground? Is it consistent with historical, geographical, and anthropological data with which you are familiar? If not, the article deserves a carefully written Scrogg highlighting how conclusions might have been different if anthropological data were also considered.

Scrogging by cultural anthropologists should result in a number of well-reasoned postings. More to the point, it is hoped that geneticists will be more careful about how they handle data, and editors more consistently solicit ethnographers and cultural anthropologists as peer reviewers. While scrogging, of course, be as narrow, precise, and gracious as possible given the circumstances. The point is not to embarrass, but to highlight the importance of cultural anthropology and qualitative data in evaluating populations.

From the Rhine to the Rift Valley: Human population genetics in Genome Biology

Has hypoxia adaptation in the Ethiopian highlands mirrored that seen in Tibet and the Andes? Is there a genetic definition for an Ashkenazi Jew? These are two questions on human diversity that can now be answered, thanks to new research articles published in this month's Genome Biology.
In the first article, the University of Pennsylvania's Tishkoff lab, in collaboration with Addis Ababa University, sought to identify genetic adaptations to high altitude present in the Amhara peopleof the Ethiopian Highlands. Two other high altitude populations – in Tibet and the Andes – have previously been studied in this way; obtaining Ethiopian samples, however, proved to be a challenging feat.
http://en.wikipedia.org/wiki/File:Ethiopian_Highlands_01.jpgA set of strong candidate genes for high altitude selection were identified in the Amhara, whose samples were used both for genotyping and for physiological measurements. As with Tibetan and Andean populations, adaptations targeted the HIF-1 pathway, demonstrating the selective pressure brought about by the risk of hypoxia in high altitude environments. While the three populations share an adaptive pathway in common, the individual genetic changes underlying the hypoxia-resistant phenotype were different in the Ethiopian cohort to those seen in Tibetans or Andeans. This example of convergent evolution suggests that the HIF-1 pathway is an inevitable adaptation in any population under selection pressure for hypoxia.
The definition of what constitutes a Jew is an age-old question without a simple answer. TheAshkenazim are a subpopulation of the Jewish people descended from a small founder population based in Western Europe approximately 1,000 years ago; using the largest Ashkenazi genotyping cohort to date, Todd Lencz (The Feinstein Institute for Medical Research) and colleagues were able to determine a distinct genetic signature that can identify Ashkenazi Jews.
Consistent with previous reports, the article concludes that the founding Ashkenazi population likely included both Levantine Jewish and European Caucasian individuals. However, the results presented by Lencz and colleagues powerfully show that, since the founding event, the level of admixture with "host" European populations (and with other Jewish populations) has been extremely low.
The genetic signature also harbors an enrichment of genes associated with disease pathways known to be overrepresented in the Ashkenazi population, and so will therefore help to unravel the genetic bases by which these conditions (including cystic fibrosis and Usher syndrome) have become prevalent among Ashkenazim.

Let us now praise human population genetics


By Harry Ostrer

Exactly who are we anyway? Over the last generation, population genetics has emerged as a science that has made the discovery of human origins, relatedness, and diversity knowable in a way that is simple not possible from studying texts, genealogies, or archeological remains. Viewed as the successor to a race science that promoted the superiority of some human groups over others and that provided a basis for prejudice, forced sterilization, and even extermination, population genetics is framed as a discipline that is based on discovery using the amazing content of fully-sequenced human genomes and novel computational methods. None of the recent discoveries would have been possible in the past. And what have we learned?

Humans descended from chimpanzees approximately 5 million years ago and that descent was not strictly linear. Other human-like species (“hominins’) emerged along the way, some fairly recently. Neanderthals emerged in Europe 300,000 years ago and Denisovans emerged 40,000 years ago. The latter group was identified only a few years ago when the DNA from a tooth in a Siberian cave was found to be that of a unique hominin species. Neither group kept strictly to itself. Rather, both mixed with humans who left Africa 50-60,000 years ago and left imprints in the genomes of contemporary Middle Easterners (Neanderthals) and Southeast Asians and New Guineans (Denisovans).

Humans originated in Africa 200,000 years ago. Although a Molecular Adam and Mitochondrial Eve have been inferred to have lived in Africa, they were not the first and they were not contemporaneous with each other. Instead, they were the successful pair among a number of early humans who were able to transmit the male-determining Y chromosome (Adam) and egg-transmitted mitochondria (Eve) to future generations. Differentiation occurred along the way. The click-speaking Khoisan split from other Africans 125,000 years ago and maintained this differentiation despite living in proximity with other groups. In fact, because humans spent most of their history in Africa, far greater genetic diversity accumulated among people on that continent compared to those in the rest of the world combined. This explains why contemporary Africans and African Americans have greater difficulty with finding compatible organ transplantation donors — there is simply a far greater range to choose from. It also renders the racist statements of the distant and not-so-distant past meaningless. Unlike Dr. Watson, we should not be “inherently gloomy about the prospect of Africa,” because the genetic diversity may give Africans a leg up on meeting the challenges of diverse environments.

Much of the population genetics of the Old World is local. Not only can the major continental groups be readily distinguished from one another, but within each of those continents, the residents of countries, provinces, and villages can be distinguished from their neighbors. A genetic map of Europe tends to overlay almost perfectly with the physical map. The same is true for the genetic maps of China, India, the Middle East, and North Africa. Some interesting exceptions exist. Religious groups who kept to themselves over the past two millennia, such as Jews and Gypsies, tend to resemble themselves genetically more than they resemble their neighbors — despite covering large geographical distances. People who speak Bantu-Niger-Kordofanian languages across equatorial, eastern, and southern Africa also tend to share greater genetic similarity than they do with their foreign language-speaking neighbors.

Much of the population genetics of the New World is not local. Because of the contact among Native Americans, Africans and Europeans, most of the people of the New World have hybrid genomes. Thus genetic maps do not tend to mimic geographical maps. Variation among the contributing populations — Native American tribe, African tribe, and European, Jewish, or North African ancestry — can all be identified. But as the result of geographic isolation and selective mating procedures among religious groups or social castes, a local population genetics has also developed in the Americas. This has occurred among the Plain People (Amish, Mennonites) of Pennsylvania as well as among the residents of the Central Valley of Costa Rica and other isolated valleys in North and South America. Oftentimes, the degree of relatedness of any two random people within these populations is what one would observe for first cousins once removed.

The content of human genomes has been shaped by exposure to diets and infectious agents through the process of natural selection — exactly as Darwin predicted in Origin of Species. The ability to digest milk sugar as an adult was selected by different genetic mechanisms both in Eurasia and in East Africa. Resistance to malaria, Lassa fever, HIV, and other infectious agents gave certain groups a leg up to exposure. In the Americas, not only were these agents brought by colonizing Europeans and enslaved Africans, but so too were the mechanisms of resistance.

Rather than promoting prejudice, population genetics should peel it away. Along with the study of history and cultures, population genetics should become a required part of curricula for understanding human origins, similarity and diversity.

Harry Ostrer, MD is the author of Legacy: A Genetic History of the Jewish People. He is Professor of Pathology and Genetics at Albert Einstein College of Medicine and Director of Genetic and Genomic Laboratories at Montefiore Medical Center. In October 2010, he was named to the Forward 50 list of “people who have made an imprint in the past year on the ways in which American Jews view the world and relate to each other.”

Human population genetic structure

I was re-reading a classic paper [1] by Wilson et al. which first used the model-based software STRUCTURE program to cluster human populations. This approach was later used by Rosenberg et al. [2] with many more populations and markers. The following two tables from the paper are quite useful. The first table shows (right column) the probability of the number of clusters given the data.

Image Hosted by ImageShack.us

As you can see, this probability is ~1 for K=4. Contrary to often repeated claims, the number of subdivisions ("races") of a group of individuals is not arbitrary, but for a set of individuals some numbers (in this case 4) are much better than others. Of course with more markers or larger samples, some of these clusters may be further refined, but the basic structure would not change. An alternative clustering with say 2 or 3 clusters would not emerge.

The second table shows that human populations usually fall within the clusters that correspond to the classical anthropological racial categories.

Image Hosted by ImageShack.us

It is also interesting that the Ethiopians belong in the Caucasoid cluster A and also in the Negroid cluster C. The Ethiopians don't "fit well" in the 4-race scheme, but this is a fact that was also appreciated by traditional anthropology. In all likelihood, both ancient links between Proto-Eurasians and East Africans and recent migrations of Caucasoids into East Africa are responsible for Ethiopian intermediacy.

Admixture analysis using K clusters summarizes the genetic structure of populations and individuals with K numbers adding up to 1, i.e., with K-1 degrees of freedom. But, they cannot distinguish between similarity deriving from common descent, or from recent admixture.

For example, Kazakhs and South Asians both score highly for European and Asian ancestry in Ancestry By DNA type tests. But, in the case of the former, this is due to admixture between Caucasoids and Mongoloids in Central Asia, whereas in the latter it is due to admixture between Caucasoids and Proto-Asians, i.e., non-Mongoloid people sharing common descent with East Asians.

This is why autosomal markers are useful for determining overall (genomic) similarity, but we have to turn to haploid markers such as mtDNA and the Y chromosome to interpret this similarity. Such markers can be tied to regions and times of origin and can thus be used to determine the actual processes of expansion and admixture that have led to the observable genetic variation.
 

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