The genetic causes, ethnic origins and history of red hair

 

What causes red hair ? Red hair is a recessive genetic trait caused by a series of mutations in the melanocortin 1 receptor (MC1R), a gene located on chromosome 16. As a recessive trait it must be inherited from both parents to cause the hair to become red. Consequently there are far more people carrying the mutation for red hair than people actually having red hair. In Scotland, approximately 13% of the population are redheads, although 40% carry at least one mutation. There are many kinds of red hair, some fairer, or mixed with blond ('strawberry blond'), some darker, like auburn hair, which is brown hair with a reddish tint. This is because some people only carry one or a few of the several possible MC1R mutations. The lightness of the hair ultimately depends on other mutations regulating the general pigmentation of both the skin and hair. Red Hair Facts Skin and hair pigmentation is caused by two different kinds of melanin: eumelanin and pheomelanin. The most common is eumelanin, a brown-black polymer responsible for dark hair and skin, and the tanning of light skin. Pheomelanin has a pink to red hue and is present in lips, nipples, and genitals. The mutations in the MC1R gene imparts the hair and skin more pheomelanin than eumelanin, causing both red hair and freckles. Redheads have very fair skin, almost always lighter than non-redheads. This is an advantage in northern latitudes and very rainy countries, where sunlight is sparse, as lighter skin improves the absorption of sunlight, which is vital for the production of vitamin D by the body. The drawback is that it confers redheads a higher risk for both sunburns and skin cancer. Studies have demonstrated that people with red hair are more sensitive to thermal pain and also require greater amounts of anesthetic than people with other hair colours. The reason is that redheads have a mutation in a hormone receptor that can apparently respond to at least two different hormones: the melanocyte-stimulating hormone (for pigmentation) and endorphins (the pain relieving hormone). Folk wisdom has long described redheads as hot-tempered and short-tempered. If you did an autosomal DNA test (e.g. with 23andMe), you can check if you carry some of the MC1R mutations.   Red hair, a Celto-Germanic trait ? Red hair has long been associated with Celtic people. Both the ancient Greeks and Romans described the Celts as redheads. The Romans extended the description to Germanic people, at least those they most frequently encountered in southern and western Germany. It still holds true today. Although red hair is an almost exclusively northern and central European phenomenon, isolated cases have also been found in the Middle East, Central Asia (notably among the Tajiks), as well as in some of the Tarim mummies from Xinjiang, in north-western China. The Udmurts, an Uralic tribe living in the northern Volga basin of Russia, between Kazan and Perm, are the only non-Western Europeans to have a high incidence of red hair (over 10%). So what do all these people have in common ? Surely the Udmurts and Tajiks aren't Celts, nor Germans. Yet, as we will see, all these people share a common ancestry that can be traced back to a single Y-chromosomal haplogroup: R1b.   Where is red hair more common ? It is hard to calculate the exact percentage of the population having red hair as it depends on how wide a definition one adopts. For example, should men with just partial red beards, but no red hair on the top of their heads be included or not ? Should strawberry blond be counted as red, blond, or both ? Regardless of the definition, the frequency of red hair is highest in Ireland (10 to 30%) and Scotland (10 to 25%), followed by Wales (10 to 15%), Cornwall and western England, Brittany, the Franco-Belgian border, then western Switzerland, Jutland and southwest Norway. The southern and eastern boundaries, beyond which red hair only occurs in less than 1% of the population, are northern Spain, central Italy, Austria, western Bohemia, western Poland, Baltic countries and Finland. Overall, the distribution of red hair matches remarkably well the ancient Celtic and Germanic worlds. It is undeniable too that the highest frequencies are always observed in Celtic areas, especially in those that remained Celtic-speaking to this day or until recently. The question that inevitably comes to many people's minds is: did red hair originate with the Celtic or the Germanic people ? Southwest Norway may well be the clue to the origin of red hair. It has been discovered recently, thanks to genetic genealogy, that the higher incidence of both dark hair and red hair (as opposed to blond) in southwest Norway coincided with a higher percentage of the paternal lineage known as haplogroup R1b-L21, including its subclade R1b-M222, typical of northwestern Ireland and Scotland (the so-called lineage of Niall of the Nine Hostages). It is now almost certain that native Irish and Scottish Celts were taken (probably as slaves) to southwest Norway by the Vikings, and that they increased the frequency of red hair there. Map of red hair frequency in Europe Map of Y-haplogroup R1b in Europe The 45th parallel, a natural boundary for red hair ? What is immediately apparent to genetic genealogists is that the map of red hair correlates with the frequency of haplogroup R1b in northern and western Europe. It doesn't really correlate with the percentage of R1b in southern Europe, for the simple reason that red hair is more visible among people carrying various other genes involved in light skin and hair pigmentation. Mediterranean people have considerably darker pigmentations (higher eumelanin), especially as far as hair is considered, giving the red hair alleles little opportunity to express themselves. The reddish tinge is always concealed by black hair, and rarely visible in dark brown hair. Rufosity being recessive, it can easily stay hidden if the alleles are too dispersed in the gene pool, and that the chances of both parents carrying an allele becomes too low. Furthermore, natural selection also progressively pruned red hair from the Mediterranean populations, because the higher amount of sunlight and strong UV rays in the region was more likely to cause potentially fatal melanoma in fair-skinned redheads. At equal latitude, the frequency of red hair correlates amazingly well with the percentage of R1b lineages. The 45th parallel north, running through central France, northern Italy and Croatia, appears to be a major natural boundary for red hair frequencies. Under the 45th parallel, the UV rays become so strong that it is no longer an advantage to have red hair and very fair skin. Under the 41th parallel, redheads become extremely rare, even in high R1b areas. The 45th parallel is also the traditional boundary between northern European cultures, where cuisine is butter-based, and southern European cultures, preferring olive oil for cooking. In France, the 45th parallel is the also limit between the northern Oïl dialects of French and the southern Occitan language. In northern Italy, it is the 46th parallel that separates German speakers (in South Tyrol) from Italian speakers. The natural boundary probably has a lot to do with the sun and climate in general, since the 45th parallel is exactly halfway between the Equator and the North Pole. Even as far back as Neolithic times, the 45th parallel roughly divided the Mediterranean Cardium Pottery culture from the Central European Linear Pottery culture. It is entirely possible, and even likely, that the European north-south divide, not just for culture and agriculture, but also for phenotypes and skin pigmentation, go back to Neolithic times, when the southern expansion of agriculture was carried out mostly by the migration of farmers from the Near East to Iberia, following the Mediterranean coastlines, while the northern Danubian diffusion of farming was achieved by native Mesolithic Europeans who acquired Neolithic techniques by contact with farmers from Thessaly and Albania (Sesklo culture), and only blending to a small extent. Slavic, Baltic and Finnish people are predominantly descended from haplogroup R1a, N1c1 and I1. Their limited R1b ancestry means that the MC1R mutation is much rarer in these populations. This is why, despite their light skin and hair pigmentation and living at the same latitude as Northwest Europeans, almost none of them have red hair, apart from a few Poles or Czechs with partial German ancestry.   Where did red hair first arise ? It has been suggested that red hair could have originated in Paleolithic Europe, especially since Neanderthal also had red hair. The only Neanderthal specimen tested so far (from Croatia) did not carry the same MC1R mutation responsible for red hair in modern humans (the mutation in question in known as Arg307Gly). But since Neanderthals evolved alongside Homo Sapiens for 600,000 years, and had numerous subspecies across all Europe, the Middle East and Central Asia, it cannot be ruled out that one particular subspecies of Neanderthal passed on the MC1R mutation to Homo Sapiens. It is however unlikely that this happened in Europe, because red hair is conspicuously absent from, or very low in parts of Europe with the highest percentages of haplogroup I (e.g. Finland, Bosnia, Sardinia) and R1a (Eastern Europe), the only two lineage associated with Mesolithic and Paleolithic Europeans. We must therefore look for the source of red hair, elsewhere. unsurpisingly, the answer lies with the R1b people - thought to have recolonised Central and Western Europe during the Bronze Age. The origins of haplogroup R1b are complex, and shrouded in controversy to this day. The present author favours the theory of a Middle Eastern origin (a point upon which very few population geneticists disagree) followed by a migration to the North Caucasus and Pontic Steppe, serving as a starting point for a Bronze-age invasion of the Balkans, then Central and Western Europe. This theory also happens to be the only one that explains the presence of red hair among the Udmurts, Central Asians and Tarim mummies.   A possible Neanderthal link ? Haplogroup R1b probably split from R1a during the Upper Paleolithic, roughly 25,000 years ago. The most likely location was Central Asia, around what is now the Caspian Sea, which only became a sea after the last Ice Age ended and the ice caps over western Russia melted. After the formation of the Caspian Sea, these nomadic hunter-gatherers, ended up on the greener and richer Caucaso-Anatolian side of the Caspian, where they may have domesticated local animals, such as cows, pigs, goats and sheep. If the mutation for red hair was inherited from Neanderthal, it would have been from a Central Asian Neanderthal, perhaps from modern Uzbekistan, or an East Anatolian/Mesopotamian one. The mutation probably passed on to some other (extinct ?) lineages for a few millennia, before being inherited by the R1b tribe. Otherwise, it could also have arisen independently among R1b people as late as the Neolithic period (but no later).   Red hair and the Indo-European migrations Developing pottery, or more probably acquiring the skills from Middle Eastern neighbours (notably haplogroup G2a), part of the R1b tribe (and a small minority of G2a3b1) migrated across the Caucasus to take advantage of the vast expanses of grassland for their herds. This is where the Proto-Indo-European culture would have emerged, and spread to the native R1a tribes of the Eurasian steppe, with whom the R1b people blendeded to a moderate level (the reason why there is always a minority of R1b and G2a among predominantly R1a populations today, anywhere from Eastern Europe to Siberia and India). The domestication of the horse in the Volga-Ural region circa 4000-3500 BCE, combined with the emergence of Bronze Age technology in the North Caucasus around 3300 BCE, would lead to the spectacular expansion of R1b and R1a lineages, an adventure that would lead these Proto-Indo-European speakers to the Atlantic fringe of Europe to the west, to Siberia and North America to the east, and all the way from Egypt to India to the south. From 3500 BCE, the vast majority of the R1b migrated westward along the Black Sea coast, to the metal-rich Balkans, where they mixed with the local inhabitants of Chalcolithic "Old Europe". A small number of R1b accompanied R1a to Siberia and Central Asia, which is why red hair very occasionally turns up in R1a-dominant populations of those areas (who usually still have a minority of R1b among their lineages, although some tribes may have lost them due to the founder effect). The archeological record indicates that this sustained series of invasions was extremely violent and led to the complete destruction of the until then flourishing civilizations of the Balkans and Carpathians (whose descendants survive as the I2a1b and E1b1b1a lineages). The R1b invaders took local women as wives and concubines, creating a new mixed ethnicity. The language evolved in consequence, adopting loanwords from the languages of Old Europe. This new ethnic and linguistic entity could be referred to as the Proto-Italo-Celto-Germanic people. After nearly a millennium in the Danubian basin (as far west as Bavaria), they would continue their westward expansion (from 2500 BCE) to Western Europe. In fact, the westward expansion was most likely carried out exclusively by the westernmost faction of R1b, who had settled north of the Alps, around Austria and Bavaria, and developed the Unetice culture. Many R1b lineages stayed behind in the Balkans, where they progressively blended with the natives, then with later immigrants to the region (notably J2, under the Greek, Roman, Byzantine and Ottoman rules) over the next millennia - mostly losing their red hair due to the high incidence of very dark hair in the region today. According to ancient Greek writers, red hair was common among the Thracians, who lived around modern Bulgaria, an region where rufosity has almost completely disappeared today. Red hair alleles may have survived in the local gene pool though, but cannot be expressed due to the lack of other genes for light hair pigmentation. The red-haired Proto-Italic, Proto-Celtic and Proto-Germanic split in three branches during the progressive expansion of the successive Bronze-age Unetice, Tumulus and Urnfield cultures from Central Europe. The Proto-Germanic branch, originating as the R1b-U106 subclade, is thought to have migrated from present-day Austria to the Low Countries and north-western Germany. They would continue their expansion (probably from 1200 BCE) to Denmark, southern Sweden and southern Norway, where, after blending with the local I1 and R1a people, the ancient Germanic culture emerged. Nowadays, the frequency of red hair among Germanic people is highest in the Netherlands, Belgium, north-western Germany and Jutland, i.e. where the percentage of R1b is the highest, and presumably the first region to be settled by R1b, before blending with the blond-haired R1a and I1 people from Scandinavia and re-expanding south to Germany during the Iron Age, with a considerably lower percentage of R1b and red-hair alleles. Red-haired is therefore most associated with the continental West Germanic peoples, and least with Scandinavians and Germanic tribes that originated in Sweden, like the Goths and the Vandals. This also explains why the Anglo-Saxon settlements on southern England have a higher frequency of redheads than the Scandinavian settlements of northeast England. The Italic branch crossed the Alps around 1300 BCE and settled across most of the peninsula, but especially in Central Italy (Umbrians, Latins, Oscans). They probably belonged predominantly to the R1b-U152 subclade. It is likely that the original Italics had just as much red hair as the Celts and Germans, but lost them progressively as they intermarried with their dark-haired neighbours, like the Etruscans. The subsequent Gaulish Celtic settlements in northern Italy increased the rufosity in areas that had priorly been non-Indo-European (Ligurian, Etruscan, Rhaetic) and therefore dark-haired. Nowadays red hair is about as common in northern and in central Italy. The Celtic branch is the largest and most complex. The area that was Celtic-speaking in Classical times encompassed regions belonging to several distinct subclades of R1b-S116 (the Proto-Italo-Celtic haplogroup). The earliest migration of R1b to Western Europe must have happened with the diffusion of the Bronze Age to France, Belgium, Britain and Ireland around 2100 BCE - a migration best associated with the R1b-L21 subclade. A second migration took place around 1800 BCE to Southwest France and Iberia, and is associated with R1b-Z196. These two branches are usually considered as Celtic, but was probably more distinct than the later continental Celtic were from Italic languages, due to its earlier split. The Northwest Celtic branch could have been ancestral to Goidelic languages (Gaelic), and the south-western one to Celtiberian. Both belong to the Q-Celtic group, as opposed to the P-Celtic group, to which Gaulish and Brythonic belong and which is associated with the expansion of the Hallstatt and La Tène cultures and R1b-U152 (the same subclade as the Italic branch). Nowadays, red hair is found in all three Celtic branches, although it is most common in the R1b-L21 branch. The reason is simply that it is the northernmost branch (red hair being more useful at higher latitudes) and that the Celtic populations of Britain and Ireland have retained the purest Proto-Celtic ancestry (extremely high percentage of R1b). Red hair was also found among the tartan-wearing Chärchän man, one of the Tarim mummies dating from 1000 BCE, who according to the author were an offshoot of Central European Celts responsible for the presence of R1b among modern Uyghurs. The earlier, non-tartan-wearing Tarim mummies from 2000 BCE, which were DNA tested and identified as members of haplogroup R1a, did not have red hair, just like modern R1a-dominant populations. http://www.eupedia.com/genetics/origins_of_red_hair.shtml

Longstanding problem put to rest

 

Thu, 06/11/2015 - 9:51am Larry Hardesty, MIT News Office Image: iStock (edited by MIT News) Comparing the genomes of different species—or different members of the same species—is the basis of a great deal of modern biology. DNA sequences that are conserved across species are likely to be functionally important, while variations between members of the same species can indicate different susceptibilities to disease. The basic algorithm for determining how much two sequences of symbols have in common—the “edit distance” between them—is now more than 40 years old. And for more than 40 years, computer science researchers have been trying to improve upon it, without much success. At the ACM Symposium on Theory of Computing (STOC), Massachusetts Institute of Technology (MIT) researchers will report that, in all likelihood, that’s because the algorithm is as good as it gets. If a widely held assumption about computational complexity is correct, then the problem of measuring the difference between two genomes—or texts, or speech samples, or anything else that can be represented as a string of symbols—can’t be solved more efficiently. In a sense, that’s disappointing, since a computer running the existing algorithm would take 1,000 years to exhaustively compare two human genomes. But it also means that computer scientists can stop agonizing about whether they can do better. “This edit distance is something that I’ve been trying to get better algorithms for since I was a graduate student, in the mid-’90s,” says Piotr Indyk, a professor of computer science and engineering at MIT and a co-author of the STOC paper. “I certainly spent lots of late nights on that—without any progress whatsoever. So at least now there’s a feeling of closure. The problem can be put to sleep.” Moreover, Indyk says, even though the paper hasn’t officially been presented yet, it’s already spawned two follow-up papers, which apply its approach to related problems. “There is a technical aspect of this paper, a certain gadget construction, that turns out to be very useful for other purposes as well,” Indyk says. Squaring off Edit distance is the minimum number of edits—deletions, insertions and substitutions—required to turn one string into another. The standard algorithm for determining edit distance, known as the Wagner-Fischer algorithm, assigns each symbol of one string to a column in a giant grid and each symbol of the other string to a row. Then, starting in the upper left-hand corner and flooding diagonally across the grid, it fills in each square with the number of edits required to turn the string ending with the corresponding column into the string ending with the corresponding row. Computer scientists measure algorithmic efficiency as computation time relative to the number of elements the algorithm manipulates. Since the Wagner-Fischer algorithm has to fill in every square of its grid, its running time is proportional to the product of the lengths of the two strings it’s considering. Double the lengths of the strings, and the running time quadruples. In computer parlance, the algorithm runs in quadratic time. That may not sound terribly efficient, but quadratic time is much better than exponential time, which means that running time is proportional to 2N, where N is the number of elements the algorithm manipulates. If on some machine a quadratic-time algorithm took, say, a hundredth of a second to process 100 elements, an exponential-time algorithm would take about 100 quintillion years. Theoretical computer science is particularly concerned with a class of problems known as NP-complete. Most researchers believe that NP-complete problems take exponential time to solve, but no one’s been able to prove it. In their STOC paper, Indyk and his student Artūrs Bačkurs demonstrate that if it’s possible to solve the edit-distance problem in less-than-quadratic time, then it’s possible to solve an NP-complete problem in less-than-exponential time. Most researchers in the computational-complexity community will take that as strong evidence that no subquadratic solution to the edit-distance problem exists. Can’t get no satisfaction The core NP-complete problem is known as the “satisfiability problem”: Given a host of logical constraints, is it possible to satisfy them all? For instance, say you’re throwing a dinner party, and you’re trying to decide whom to invite. You may face a number of constraints: Either Alice or Bob will have to stay home with the kids, so they can’t both come; if you invite Cindy and Dave, you’ll have to invite the rest of the book club, or they’ll know they were excluded; Ellen will bring either her husband, Fred, or her lover, George, but not both; and so on. Is there an invitation list that meets all those constraints? In Indyk and Bačkurs’ proof, they propose that, faced with a satisfiability problem, you split the variables into two groups of roughly equivalent size: Alice, Bob and Cindy go into one, but Walt, Yvonne and Zack go into the other. Then, for each group, you solve for all the pertinent constraints. This could be a massively complex calculation, but not nearly as complex as solving for the group as a whole. If, for instance, Alice has a restraining order out on Zack, it doesn’t matter, because they fall in separate subgroups: It’s a constraint that doesn’t have to be met. At this point, the problem of reconciling the solutions for the two subgroups—factoring in constraints like Alice’s restraining order—becomes a version of the edit-distance problem. And if it were possible to solve the edit-distance problem in subquadratic time, it would be possible to solve the satisfiability problem in subexponential time. Source: Massachusetts Institute of Technology

World's first genetic modification of human embryos reported: Experts consider ethics

 

The team injected 86 embryos and 71 survived, of which 54 were genetically tested. This revealed that just 28 were successfully spliced, and that only a fraction of those contained the replacement genetic material. Analysis also revealed a number of 'off-target' mutations assumed to be caused by the technique acting in other areas of the genome. The results reveal serious obstacles to using the method in medical applications. The scientists have tried to head off ethical concerns by using 'non-viable' embryos, which cannot result in a live birth, that were obtained from local fertility clinics. However, the work is very controversial, with some warning it could be the start of a slippery slope towards designer babies. Below, some experts weigh-in with ethical questions and considerations. Prof Robin Lovell Badge, Crick Institute, on the science: "The experiments reported by Junjiu Huang and colleagues (Liang et al) in the journal Protein Cell on gene editing in abnormally fertilised human embryos are, I expect, the first of several that we will see this year. There has been much excitement among scientists about the power of these new gene editing methods, and particularly about the CRISPR/Cas9 system, which is relatively simple to use and generally very efficient. The possibility of using such methods to genetically modify human embryos, and therefore humans, has been on the cards since these methods were first described, and recently these prospects have been brought to the attention of the public through several commentaries made by senior scientists and commentators, some of whom have called for a moratorium to halt any attempts." Dr Yalda Jamshidi, Senior Lecturer in Human Genetics, St George's University Hospital Foundation Trust, said: "Inherited genetic conditions often result because the function of a gene is disrupted. In theory replacing the defective gene with a healthy one would be the ideal solution. This type of treatment is what we call gene therapy and researchers have been working on developing techniques to accomplish this for many years. "Techniques to correct defective genes in 'non-reproductive' cells are already at various stages of clinical development and promise to be a powerful approach for many human diseases which don't yet have an effective treatment. However, altering genes in human embryos can have unpredictable effects on future generations. Furthermore the study by Huang et al showed that the although the CRISPR/Cas9 technique they used can work in the embryo, it can miss the target in the gene and is too inefficient. "Future research on the technique may improve the accuracy and efficiency, however scientists still don't fully understand the role of the DNA, and all of its genes. Therefore it is impossible to assess the risks from mis-targeted changes in the DNA sequence, which would affect both the treated embryo and any future generations." Prof Shirley Hodgson, Professor of Cancer Genetics, St George's University of London, said: "I think that this is a significant departure from currently accepted research practice. This is because any manipulation of the germline of human embryos is potentially heritable. Can we be certain that the embryos that the researchers were working on were indeed non-viable? In the past all the gene therapy research that has been approved by regulatory bodies has been somatic, not germline, because of the potentially unpredictable and heritable effects of germline research. The fact that these researchers found that there were a number of "off target" mutations resulting from the technique they used is clearly a worry in this context. Any proposal to do germline genetic manipulation should be very carefully considered by international regulatory bodies before it should be considered as a serious research prospect. This is because of the obvious concerns about the heritability of the genetic alterations induced, and the way in which such research could spread from work on "non-viable" embryos, to work on viable ones once this type of research had been accepted in principle by international regulatory bodies." Prof Darren Griffin, Professor of Genetics, University of Kent, said: "Given the widespread use of the CRISPR/Cas9 system, such announcement was inevitable, sooner rather than later. We clearly have a lot of thinking to do. Germline manipulation is currently illegal in the UK but the question is bound to be asked whether this should change, especially if the safety concerns are allayed." Associate Professor Peter Illingworth is Medical Director at IVFAustralia: "This is a fascinating piece of experimental science. Using abnormally-fertilised human embryos (I.e. With three sets of DNA instead of two), they have studied whether the a human gene can be modified. They have demonstrated that, in some embryos, but not all, they can change the abnormal human gene. They also find that other genes are affected which may be a serious concern. What they have shown is that it is technically possible, not that it is practically feasible or safe." Further information: http://www.sciencemediacentre.org/expert-reaction-to-the-application-of-genome-editing-techniques-to-human-embryos/ http://www.smc.org.au/expert-reaction-worlds-first-genetic-modification-of-human-embryos-reported-protein-cell/

Supercomputing reveals genetic code of cancer

 

"This charting may help tailor the treatment to each patient," says Associate Professor Rolf Skotheim, who is affiliated with the Centre for Cancer Biomedicine and the Research Group for Biomedical Informatics at the University of Oslo in Norway, as well as the Department of Molecular Oncology at Radiumhospitalet, Oslo University Hospital. His research group is working to identify the genes that cause bowel and prostate cancer, which are both common diseases. There are 4,000 new cases of bowel cancer in Norway every year. Only six out of ten patients survive the first five years. Prostate cancer affects 5,000 Norwegians every year. Nine out of ten survive. Comparisons between healthy and diseased cells In order to identify the genes that lead to cancer, Skotheim and his research group are comparing the genetic material in tumours with the genetic material in healthy cells. In order to understand this process, a fast introduction to our genetic material is needed. Our genetic material consists of just over 20,000 genes. Each gene consists of thousands of base pairs, represented by a specific sequence of the four building blocks adenine, thymine, guanine, and cytosine, popularly abbreviated to A, T, G, and C. The sequence of these building blocks is the very recipe for the gene. Our whole DNA consists of some six billion base pairs. The DNA strand carries the molecular instructions for activity in the cells. In other words, DNA contains the recipe for proteins, which perform the tasks in the cells. DNA, nevertheless, does not actually produce proteins. First a copy of DNA is made. This transcript is called RNA, and it is this molecule that is read when proteins are produced. RNA is only a small component of DNA, and is made up of its active constituents. Most of DNA is inactive. Only 1-2 % of the DNA strand is active. In cancer cells, something goes wrong with the RNA-transcription. There is either too much RNA, which means that far too many proteins of a specific type are formed, or the composition of base pairs in RNA is wrong. The latter is precisely the area being studied by the UiO researchers. Wrong combinatorics All genes can be divided into active and inactive parts. A single gene may consist of tens of active stretches of nucleotides (exons). "RNA is a copy of a specific combination of the exons from a specific gene in DNA." There are many possible combinations, and it is precisely this search for all of the possible combinations that is new in cancer research. Different cells can combine the nucleotides in a single gene in different ways. A cancer cell can create a combination that should not exist in healthy cells. And as if that didn't make things complicated enough, sometimes RNA can be made up of stretches of nucleotides from different genes in DNA. These special, complex genes are called fusion genes. In other words, researchers must look for errors both inside genes and between the different genes. "Fusion genes are usually found in cancer cells, but some of them are also found in healthy cells." In patients with prostate cancer, researchers have found some fusion genes that are only created in diseased cells. These fusion genes may then be used as a starting-point in the detection of and fight against cancer. The researchers have also found fusion genes in bowel cells, but they were not cancer-specific. "For some reason, these fusion genes can also be found in healthy cells. This discovery was a let-down." Can improve treatment There are different RNA errors in the various cancer diseases. The researchers must therefore analyse the RNA errors of each disease. Among other things, the researchers are comparing RNA in diseased and healthy tissue from 550 patients with prostate cancer. The patients that make up the study do not receive any direct benefits from the results themselves. However, the research is important in order to be able to help future patients. "We want to find the typical defects associated with prostate cancer. This will make it easier to understand what goes wrong with healthy cells, and to understand the mechanisms that develop cancer. Once we have found the cancer-specific molecules, they can be used as biomarkers. In some cases, the biomarkers can be used to find cancer, determine the level of severity of the cancer, the risk of spreading, and whether the patient should be given a more aggressive treatment. Even though the researchers find deviations in the RNA, there is no guarantee that there is appropriate, targeted medicine available. "The point of our research is to figure out more of the big picture. If we identify a fusion gene that is only found in cancer cells, the discovery will be so important in itself that other research groups around the world will want to begin working on this straight away. If a cure is found that counteracts the fusion genes, this may have enormous consequences for the cancer treatment." Laborious work Recreating RNA is laborious work. The set of RNA molecules consists of about 100 million bases, divided into a few thousand bases from each gene. The laboratory machine reads millions of small nucleotides. Each one is only one hundred base pairs long. In order for the researchers to be able to place them in the right location, they must run large statistical analyses. The RNA analysis of a single patient can take a few days. All of the nucleotides must be matched with the DNA strand. Unfortunately the researchers do not have the DNA strands of each patient. In order to learn where the base pairs come from in the DNA strand, they must therefore use the reference genome of the human species. "This is not ideal, because there are individual differences." The future potentially lies in fully sequencing the DNA of each patient when conducting medical experiments. Supercomputing There is no way the research can be carried out using pen and paper. "We need powerful computers to crunch the enormous amounts of raw data. Even if you spent your whole life on this task, you would not be able to find the location of a single nucleotide. This is a matter of millions of nucleotides that must be mapped correctly in the system of coordinates of the genetic material. Once we have managed to find the RNA versions that are only found in cancer cells, we will have made significant progress. However, the work to get that far requires advanced statistical analyses and supercomputing," says Rolf Skotheim to the reserach magazine Apollon. The analyses are so demanding that the researchers must use the University's supercomputer, which was ranked as one of the world's fastest computers a few years ago. It is 10,000 times faster than a regular computer. "With the ability to run heavy analyses on such large amounts of data, we have an enormous advantage not available to other cancer researchers. Many medical researchers would definitely benefit from this possibility. This is why they should spend more time with biostatisticians and informaticians. RNA samples are taken from the patients only once. The types of analyses that can be run are only limited by the imagination." "We need to be smart in order to analyse the raw data. There are enormous amounts of data here that can be interpreted in many different ways. We have just got started. There is lots of useful information that we have not seen yet. Asking the right questions is the key. Most cancer researchers are not used to working with enormous amounts of data, and how to best analyse vast data sets. Once researchers have found a possible answer, they must determine whether the answer is chance or if it is a real finding. The solution is to find out whether they get the same answers from independent data sets from other parts of the world."

First major analysis of Human Protein Atlas is published

 

3D render of DNA structure (stock image). The approximately 20,000 protein coding genes in humans have been analysed and classified using a combination of genomics, transcriptomics, proteomics, and antibody-based profiling, says the article's lead author, Mathias Uhlén A research article published in Science presents the first major analysis based on the Human Protein Atlas, including a detailed picture of the proteins that are linked to cancer, the number of proteins present in the bloodstream, and the targets for all approved drugs on the market. The Human Protein Atlas, a major multinational research project supported by the Knut and Alice Wallenberg Foundation, recently launched (November 6, 2014) an open source tissue-based interactive map of the human protein. Based on 13 million annotated images, the database maps the distribution of proteins in all major tissues and organs in the human body, showing both proteins restricted to certain tissues, such as the brain, heart, or liver, and those present in all. As an open access resource, it is expected to help drive the development of new diagnostics and drugs, but also to provide basic insights in normal human biology. In the Science article, "Tissue-based Atlas of the Human Proteome," the approximately 20,000 protein coding genes in humans have been analysed and classified using a combination of genomics, transcriptomics, proteomics, and antibody-based profiling, says the article's lead author, Mathias Uhlén, Professor of Microbiology at Stockholm's KTH Royal Institute of Technology and the director of the Human Protein Atlas program. The analysis shows that almost half of the protein-coding genes are expressed in a ubiquitous manner and thus found in all analysed tissues. Approximately 15% of the genes show an enriched expression in one or several tissues or organs, including well-known tissue-specific proteins, such as insulin and troponin. The testes, or testicles, have the most tissue-enriched proteins followed by the brain and the liver. The analysis suggests that approximately 3,000 proteins are secreted from the cells and an additional 5,500 proteins are located to the membrane systems of the cells. "This is important information for the pharmaceutical industry. We show that 70% of the current targets for approved pharmaceutical drugs are either secreted or membrane-bound proteins," Uhlén says. "Interestingly, 30% of these protein targets are found in all analysed tissues and organs. This could help explain some side effects of drugs and thus might have consequences for future drug development." The analysis also contains a study of the metabolic reactions occurring in different parts of the human body. The most specialised organ is the liver with a large number of chemical reactions not found in other parts of the human body. Story Source: The above story is based on materials provided by KTH, Royal Institute of Technology. Note: Materials may be edited for content and length. Journal Reference: M. Uhlen, L. Fagerberg, B. M. Hallstrom, C. Lindskog, P. Oksvold, A. Mardinoglu, A. Sivertsson, C. Kampf, E. Sjostedt, A. Asplund, I. Olsson, K. Edlund, E. Lundberg, S. Navani, C. A.-K. Szigyarto, J. Odeberg, D. Djureinovic, J. O. Takanen, S. Hober, T. Alm, P.-H. Edqvist, H. Berling, H. Tegel, J. Mulder, J. Rockberg, P. Nilsson, J. M. Schwenk, M. Hamsten, K. von Feilitzen, M. Forsberg, L. Persson, F. Johansson, M. Zwahlen, G. von Heijne, J. Nielsen, F. Ponten. Tissue-based map of the human proteome. Science, 2015; 347 (6220): 1260419 DOI: 10.1126/science.1260419

Living longer, but not healthier?

 

January 20, 2015 University of Massachusetts Medical School A study of long-lived mutant C. elegans shows that the genetically altered worms spend a greater portion of their life in a frail state and exhibit less activity as they age then typical nematodes. These findings suggest that genes that increase longevity may not significantly increase healthy lifespan and point to the need to measure health as part of aging studies going forward. A study of long-lived mutant C. elegans by scientists at the University of Massachusetts Medical School shows that the genetically altered worms spend a greater portion of their life in a frail state and exhibit less activity as they age then typical nematodes. These findings, published in the Proceedings of the National Academy of Sciences, suggest that genes that increase longevity may not significantly increase healthy lifespan and point to the need to measure health as part of aging studies going forward. "Our study reveals that if we want to find the genes that help us remain physically active as we age, the genes that will allow us to play tennis when we're 70 similar to when we were 40, we have to look beyond longevity as the sole criteria. We have to start looking at new genes that might play a part in 'healthspan.'" said Heidi A. Tissenbaum, PhD, professor of molecular, cellular & cancer biology and the program in molecular medicine at UMass Medical School, and principal investigator of the study. Genomic and technological advances have allowed scientists to identify several groups of genes that control longevity in C. elegans, a nematode used as a model system for genetic studies in the lab, as well as in yeast and flies. These genes, when examined, have analogs in mammals. The underlying assumption by scientists has always been that extending lifespan would also increase the time spent by the organism in a healthy state. However, for various reasons, most studies only closely examine these model animals while they're still relatively young and neglect to closely examine the latter portion of the animals' lives. Challenging the assumption that longevity and health are intrinsically connected, Dr. Tissenbaum and colleagues sought to investigate how healthy long-lived C. elegans mutants were as they aged. "The term healthspan is poorly defined in the lab, and in C. elegans few parameters have been identified for measuring health," said Tissenbaum. "So we set out to create a definition of healthspan by identifying traits that could be easily verified and measured as the worms aged." Identifying both frailty and movement as measureable physical attributes that declined in the nematode with age and that could be tested, Ankita Bansal, PhD, now a postdoctoral scientist at the University of Pennsylvania, took four different C. elegans mutant specimen (daf-2, eat-2, ife-2 and clk-1) known to live longer than typical nematodes and measured their resistance to heat stress, oxidative stress and activity levels on solids and in liquids as they aged. When Tissenbaum and her colleagues, Dr. Bansal; Kelvin Yen, PhD, now assistant research professor at the University of Southern California; and Lihua Julie Zhu, PhD, research associate professor of molecular, cellular & cancer biology at UMMS, compared these results with wild-type nematodes they found that all the animals--wild-type and mutants--declined physically as they aged. And depending on the mutant specimen and trait being measured, each declined at different rates. Overall they found that the mutant worms, despite having longer lifespans, spent a greater percentage of their lives at less than 50 percent of measured maximum function when compared to wild-type nematodes. The increased lifespan experienced by the mutants was spent, instead, in a frail and debilitated state. "What this means, is that the mutant nematodes were living longer, but most of that extra time wasn't healthy time for the worm," said Tissenbaum. "While we saw some extension in health as the mutants aged for certain traits, invariably the trade off was an extended period of frailty and inactivity for the animal. In fact, as a percentage of total lifespan, the wild-type worms spent more time in a healthy state than the long-lived mutants." The implication for scientists, according to Tissenbaum, is that the set of genes that influence longevity may be distinct from the genes that control healthspan. "This study suggests that there is a separate and unexplored group of genes that allow us to perform at a higher level physically as we age. When we study aging we can no longer look at lifespan as the only parameter; we also have to consider health as a distinct factor of its own." Story Source: The above story is based on materials provided by University of Massachusetts Medical School. Note: Materials may be edited for content and length. Journal Reference: Ankita Bansal, Lihua J. Zhu, Kelvin Yen, Heidi A. Tissenbaum. Uncoupling lifespan and healthspan inCaenorhabditis eleganslongevity mutants. Proceedings of the National Academy of Sciences, 2015; 112 (3): E277 DOI: 10.1073/pnas.1412192112

Twelve new genetic causes of developmental disorders

 

Deciphering Developmental Disorders (DDD), the world's largest, nationwide and genome-wide diagnostic sequencing programme, has discovered 12 new genetic causes of developmental disorders. The project will ultimately analyse data from 12,000 families. This paper describes results from the first 1133 samples, which have increased the proportion of patients that can be diagnosed by 10 per cent. DDD is paving the way for translating advances in genomics into patient care in the NHS by demonstrating the feasibility and affordability of large-scale sequencing and analysis. These capabilities are critical to the Government's Genomics England programme, which aims to sequence 100,000 genomes by 2017. The first results to emerge from a nationwide project to study the genetic causes of rare developmental disorders have revealed 12 causative genes that have never been identified before. The Deciphering Developmental Disorders (DDD) project, the world's largest, nationwide genome-wide diagnostic sequencing programme, sequenced DNA and compared the clinical characteristics of over a thousand children to find the genes responsible for conditions that include intellectual disabilities and congenital heart defects, among others. DDD, which is a collaboration between the NHS and the Wellcome Trust Sanger Institute and is funded by the Department of Health and Wellcome Trust through the Health Innovation Challenge Fund, worked with 180 clinicians from 24 regional genetics services across the UK and the Republic of Ireland to analyse all ~20,000 genes in each of 1133 children with severe disorders so rare and poorly characterised that they cannot be easily diagnosed using standard clinical tests. The benefits of diagnosis include improving clinical management, helping parents obtain support, informing reproductive choice and providing a molecular basis for the disorder, which is the starting point in the search for new treatments. The DDD project works by collecting together clinical information in a database along with the genetic variants from each patient's genome. If patients who share similar symptoms also have variants in common, it helps to narrow down the search for causative mutations across the genome. However, this can be challenging, since the chance of having a particular type of mutation can be as low as one in fifty million. DDD's nationwide secure data-sharing network has made it possible to find and compare these incredibly rare disorders; in fact, for four of the 12 newly identified genes, identical mutations were found in two or more unrelated children living hundreds of miles apart. "Working at enormous scale, both nationwide and genome-wide, is critical in our mission to find diagnoses for these families," explains Dr Helen Firth, an author from the Department of Clinical Genetics at Addenbrooke's Hospital and Clinical Lead for the DDD study. "This project would not have been possible without the nationwide reach of the UK National Health Service, which has enabled us to unite a number of families who live hundreds of miles apart but whose children share equivalent mutations and very similar symptoms." In one example, two unrelated children, both with identical mutations in the gene PCGF2, which is involved in regulating genes important in embryo development, were found to have strikingly similar symptoms and facial features. This constitutes the discovery of a new, distinct dysmorphic syndrome. All of the newly discovered developmental disorders were caused by new, 'de novo', mutations, which are present in the child but are not in their parents' genomes. The DDD project has shown that it is critical to use, where possible, genetic data from parents, most of whom do not have a developmental disorder, to help filter out benign inherited variants and find the cause of their child's condition. "The DDD study has shown how combining genetic sequencing with more traditional strategies for studying patients with very similar symptoms can enable large-scale gene discovery," says Professor Sir John Burn, Professor of Clinical Genetics at Newcastle University. "This data-set becomes more effective with each diagnosis and each newly identified gene." Originally, the DDD project focused on applying array technology to screen genes for deletions or duplications that cause the patient's disorder. However, this strategy enabled researchers to find a diagnosis for only 5 per cent of patients. Improvements in sequencing technology have allowed DDD to use genome-wide 'exome' sequencing that searches through all protein-coding genes for all classes of genetic variants. This approach produces 100 times more data but delivers a diagnosis for 30 per cent of patients. "The success of DDD has provided a valuable test bed for Genomics England," says Professor Mark Caulfield, Chief Scientist for Genomics England. "This research has shown that the Government's commitment to sequencing 100,000 genomes can produce powerful data that will make a real difference to genetic research as well as to clinical diagnostics and treatment." The DDD project, which started in 2010, will ultimately analyse data from 12,000 families. So far 10 per cent of the 12,000 families that will participate in the study have been analysed in detail, but already the discovery of 12 novel genetic causes of developmental disorders has increased the proportion of patients that can be diagnosed by 10 per cent. Nonetheless, some DDD children will not be able to be diagnosed by looking at data from UK patients in isolation, and so to identify similar patients from around the world DDD is sharing limited anonymised genetic and clinical data on these undiagnosed DDD children through the DECIPHER database. Researchers hope that the project will inspire more clinical and research programmes around the world to deposit data in the DECIPHER database to pinpoint more genetic causes of developmental disorders and improve diagnostic rates internationally. "There is a clear moral imperative for both clinical testing laboratories and research studies to share this information globally," says Dr Matt Hurles, senior author and principal investigator on the DDD project. "DDD and DECIPHER have demonstrated that large-scale data sharing can give families the diagnoses they so urgently need; diagnoses that simply cannot be made by looking at the data in isolation." Story Source: The above story is based on materials provided by Wellcome Trust Sanger Institute. Note: Materials may be edited for content and length. Journal Reference: T. W. Fitzgerald, S. S. Gerety, W. D. Jones, M. van Kogelenberg, D. A. King, J. McRae, K. I. Morley, V. Parthiban, S. Al-Turki, K. Ambridge, D. M. Barrett, T. Bayzetinova, S. Clayton, E. L. Coomber, S. Gribble, P. Jones, N. Krishnappa, L. E. Mason, A. Middleton, R. Miller, E. Prigmore, D. Rajan, A. Sifrim, A. R. Tivey, M. Ahmed, N. Akawi, R. Andrews, U. Anjum, H. Archer, R. Armstrong, M. Balasubramanian, R. Banerjee, D. Baralle, P. Batstone, D. Baty, C. Bennett, J. Berg, B. Bernhard, A. P. Bevan, E. Blair, M. Blyth, D. Bohanna, L. Bourdon, D. Bourn, A. Brady, E. Bragin, C. Brewer, L. Brueton, K. Brunstrom, S. J. Bumpstead, D. J. Bunyan, J. Burn, J. Burton, N. Canham, B. Castle, K. Chandler, S. Clasper, J. Clayton-Smith, T. Cole, A. Collins, M. N. Collinson, F. Connell, N. Cooper, H. Cox, L. Cresswell, G. Cross, Y. Crow, M. D’Alessandro, T. Dabir, R. Davidson, S. Davies, J. Dean, C. Deshpande, G. Devlin, A. Dixit, A. Dominiczak, C. Donnelly, D. Donnelly, A. Douglas, A. Duncan, J. Eason, S. Edkins, S. Ellard, P. Ellis, F. Elmslie, K. Evans, S. Everest, T. Fendick, R. Fisher, F. Flinter, N. Foulds, A. Fryer, B. Fu, C. Gardiner, L. Gaunt, N. Ghali, R. Gibbons, S. L. Gomes Pereira, J. Goodship, D. Goudie, E. Gray, P. Greene, L. Greenhalgh, L. Harrison, R. Hawkins, S. Hellens, A. Henderson, E. Hobson, S. Holden, S. Holder, G. Hollingsworth, T. Homfray, M. Humphreys, J. Hurst, S. Ingram, M. Irving, J. Jarvis, L. Jenkins, D. Johnson, D. Jones, E. Jones, D. Josifova, S. Joss, B. Kaemba, S. Kazembe, B. Kerr, U. Kini, E. Kinning, G. Kirby, C. Kirk, E. Kivuva, A. Kraus, D. Kumar, K. Lachlan, W. Lam, A. Lampe, C. Langman, M. Lees, D. Lim, G. Lowther, S. A. Lynch, A. Magee, E. Maher, S. Mansour, K. Marks, K. Martin, U. Maye, E. McCann, V. McConnell, M. McEntagart, R. McGowan, K. McKay, S. McKee, D. J. McMullan, S. McNerlan, S. Mehta, K. Metcalfe, E. Miles, S. Mohammed, T. Montgomery, D. Moore, S. Morgan, A. Morris, J. Morton, H. Mugalaasi, V. Murday, L. Nevitt, R. Newbury-Ecob, A. Norman, R. O’Shea, C. Ogilvie, S. Park, M. J. Parker, C. Patel, J. Paterson, S. Payne, J. Phipps, D. T. Pilz, D. Porteous, N. Pratt, K. Prescott, S. Price, A. Pridham, A. Procter, H. Purnell, N. Ragge, J. Rankin, L. Raymond, D. Rice, L. Robert, E. Roberts, G. Roberts, J. Roberts, P. Roberts, A. Ross, E. Rosser, A. Saggar, S. Samant, R. Sandford, A. Sarkar, S. Schweiger, C. Scott, R. Scott, A. Selby, A. Seller, C. Sequeira, N. Shannon, S. Sharif, C. Shaw-Smith, E. Shearing, D. Shears, I. Simonic, D. Simpkin, R. Singzon, Z. Skitt, A. Smith, B. Smith, K. Smith, S. Smithson, L. Sneddon, M. Splitt, M. Squires, F. Stewart, H. Stewart, M. Suri, V. Sutton, G. J. Swaminathan, E. Sweeney, K. Tatton-Brown, C. Taylor, R. Taylor, M. Tein, I. K. Temple, J. Thomson, J. Tolmie, A. Torokwa, B. Treacy, C. Turner, P. Turnpenny, C. Tysoe, A. Vandersteen, P. Vasudevan, J. Vogt, E. Wakeling, D. Walker, J. Waters, A. Weber, D. Wellesley, M. Whiteford, S. Widaa, S. Wilcox, D. Williams, N. Williams, G. Woods, C. Wragg, M. Wright, F. Yang, M. Yau, N. P. Carter, M. Parker, H. V. Firth, D. R. FitzPatrick, C. F. Wright, J. C. Barrett, M. E. Hurles. Large-scale discovery of novel genetic causes of developmental disorders. Nature, 2014; DOI: 10.1038/nature14135

Gene critical for proper brain development discovered

 

Scientists at A*STAR's Institute of Medical Biology (IMB) and Institute of Molecular and Cellular Biology (IMCB) have identified a genetic pathway that accounts for the extraordinary size of the human brain. The team led by Dr Bruno Reversade[1] from A*STAR in Singapore, together with collaborators from Harvard Medical School, have identified a gene, KATNB1, as an essential component in a genetic pathway responsible for central nervous system development in humans and other animals. By sequencing the genome of individuals of normal height but with a very small head size, the international team revealed that these individuals had mutations in the KATNB1 gene, indicating that this gene is important for proper human brain development. Microcephaly (literally meaning "small head" in Latin) is a condition often associated with neurodevelopmental disorders. Measured at birth by calculating the baby's head circumference, a diagnosis of microcephaly is given if it is smaller than average. Microcephaly may stem from a variety of conditions that cause abnormal growth of the brain during gestation or degenerative processes after birth, all resulting in a small head circumference. In general, individuals with microcephaly have a reduced life expectancy due to reduced brain function which is often associated with mental retardation. The team also carried out further experiments to determine the function of KATNB1, whose exact mode of action was previously unknown in humans. Using organisms specifically designed to lack this gene, they realised that KATNB1 is crucial for the brain to reach its correct size. Zebrafish and mice embryos without this gene could not live past a certain stage and showed dramatic reduction in brain and head size, similar to the human patients. Their results were published in the 17 December 2014 online issue of Neuron. Sequencing and screening for this particular gene before birth or at birth might also help to detect future neurocognitive problems in the general population. Dr Reversade said, "We will continue to search for other genes important for brain development as they may unlock some of the secrets explaining how we, humans, have evolved such cognitive abilities." Prof Birgit Lane, Executive Director of IMB, said, "This is one of a small number of genes that scientists have found to be vital for brain development. The work is therefore an important advance in understanding the human brain. The team's findings provide a new platform from which to look further into whether -- and how -- this gene can be used for targeted therapeutic applications." Prof Hong Wanjin, Executive Director of IMCB, said, "This coordinated effort shows the increasingly collaborative nature of science. As the complexity and interdisciplinary nature of research evolves, so do the networks of collaborations between research institutes at A*STAR and across continents." Story Source: The above story is based on materials provided by A*Star Agency for Science, Technology and Research. Note: Materials may be edited for content and length. Journal Reference: Ketu Mishra-Gorur, Ahmet Okay Çağlayan, Ashleigh E. Schaffer, Chiswili Chabu, Octavian Henegariu, Fernando Vonhoff, Gözde Tuğce Akgümüş, Sayoko Nishimura, Wenqi Han, Shu Tu, Burçin Baran, Hakan Gümüş, Cengiz Dilber, Maha S. Zaki, Heba A.A. Hossni, Jean-Baptiste Rivière, Hülya Kayserili, Emily G. Spencer, Rasim Ö. Rosti, Jana Schroth, Hüseyin Per, Caner Çağlar, Çağri Çağlar, Duygu Dölen, Jacob F. Baranoski, Sefer Kumandaş, Frank J. Minja, E. Zeynep Erson-Omay, Shrikant M. Mane, Richard P. Lifton, Tian Xu, Haig Keshishian, William B. Dobyns, Neil C. Chi, Nenad Šestan, Angeliki Louvi, Kaya Bilgüvar, Katsuhito Yasuno, Joseph G. Gleeson, Murat Günel. Mutations in KATNB1 Cause Complex Cerebral Malformations by Disrupting Asymmetrically Dividing Neural Progenitors. Neuron, 2014; 84 (6): 1226 DOI: 10.1016/j.neuron.2014.12.014