Tagged: Genomics Toggle Comment Threads | Keyboard Shortcuts

  • richardmitnick 11:02 am on July 23, 2015 Permalink | Reply
    Tags: , Genomics,   

    From UCSC: “Keck Foundation awards UC Santa Cruz $2 million for human genome variation project” 

    UC Santa Cruz

    UC Santa Cruz

    July 22, 2015
    Tim Stephens

    The UC Santa Cruz Genomics Institute has received a $2 million grant from the W. M. Keck Foundation for ongoing research to develop a comprehensive map of human genetic variation. The Human Genome Variation Map will be a valuable new resource for medical researchers, as well as for basic research on human evolution and diversity.

    2
    Human Genome Variation Map

    The Keck grant provides funding over two years for UC Santa Cruz researchers to create a full-scale map, building on the results of a one-year pilot project funded by the Simons Foundation.

    “We’ve been experimenting with pilot regions of the genome and evaluating a variety of methods. The next steps will be to take it from a prototype to a full-scale genome reference that we can release to the community,” said Benedict Paten, a research scientist at the Genomics Institute and co-principal investigator of the project.

    1
    Benedict Paten (Photo by Summer Stiegman)

    The Human Genome Variation Map is needed to overcome the limitations of using a single reference sequence for the human genome. Currently, new data from sequencing human genomes is analyzed by mapping the new sequences to one reference set of 24 human chromosomes to identify variants. But this approach leads to biases and mapping ambiguities, and some variants simply cannot be described with respect to the reference genome, according to David Haussler, distinguished professor of biomolecular engineering and scientific director of the Genomics Institute at UC Santa Cruz.

    Global Alliance

    Haussler and Paten are coordinating their work on the new map with the Global Alliance for Genomics and Health (GA4GH), which involves more than 300 collaborating institutions that have agreed to work together to enable secure sharing of genomic and clinical data. The overall vision of the global alliance includes a genomics platform based on something akin to the planned Human Genome Variation Map, along with open-source software tools to enable researchers to mine the data for new scientific and medical breakthroughs. In the long run, the map will be used to identify genomic variants encountered in precision medical care as well, Haussler said.

    The UCSC team has been collaborating with leading genomics researchers at other institutions to develop the map, which Paten began working on in 2014 as co-chair of the GA4GH Reference Variation Task Team. The new Human Genome Variation Map will replace the current assortment of isolated, incompatible databases of human genetic variation with a single, fundamental representation formalized as a very large mathematical graph. The clean mathematical formulation is a major strength of this new approach, Paten said.

    The primary reference genome is a linear sequence of DNA bases (represented by the letters A, C, T, and G). To build the Human Genome Variation Map, each new genome will be merged into the reference genome at the points where it matches the primary sequence, with variations appearing as additional alternate paths in the map.

    Mathematical structure

    This mathematical graph-based structure will augment the existing human reference genome with all common human variations, providing a means to name, identify, and analyze variations precisely and reproducibly. “The original human reference genome project gave us a detailed picture of one human genome. This map will give us a detailed picture of the world’s variety of human genomes,” Paten said.

    In the spirit of the original human genome project, the Human Genome Variation Map will be publicly and freely available to all. Haussler’s team at UC Santa Cruz made the first human genome sequence publicly available on the Internet 15 years ago. This new project has many parallels with that earlier work, in which UCSC genomics researchers assembled and posted the first human genome sequence and went on to create the widely used UCSC Genome Browser.

    “This is an infrastructure project for genomics that everyone agrees is important,” Paten said. “It is ambitious, and it requires a fundamental shift from thinking of the reference as one sequence to thinking of it as this structure that incorporates all variation. But now is the time to do it. We need to build a model that works, and make it easy enough to use to get community acceptance.”

    The UC Santa Cruz Genomics Institute is a fundraising priority of the $300-million Campaign for UC Santa Cruz.

    W. M. Keck Foundation

    Based in Los Angeles, the W. M. Keck Foundation was established in 1954 by the late W. M. Keck, founder of the Superior Oil Company. The Foundation’s grant making is focused primarily on pioneering efforts in the areas of medical, science and engineering research. The Foundation also maintains an undergraduate education program that promotes distinctive learning and research experiences for students in the sciences and in the liberal arts, and a Southern California Grant Program that provides support for the Los Angeles community, with a special emphasis on children and youth from low-income families, special needs populations and safety-net services. For more information, please visit www. wmkeck.org.

    See the full article here.

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition
    The University of California, Santa Cruz, opened in 1965 and grew, one college at a time, to its current (2008-09) enrollment of more than 16,000 students. Undergraduates pursue more than 60 majors supervised by divisional deans of humanities, physical & biological sciences, social sciences, and arts. Graduate students work toward graduate certificates, master’s degrees, or doctoral degrees in more than 30 academic fields under the supervision of the divisional and graduate deans. The dean of the Jack Baskin School of Engineering oversees the campus’s undergraduate and graduate engineering programs.

     
  • richardmitnick 7:50 am on May 2, 2015 Permalink | Reply
    Tags: , Genomics,   

    From Princeton: “Digging for Meaning in the Big Data of Human Biology” 

    Princeton University
    Princeton University

    April 28, 2015
    No Writer Credit

    1

    Since the Human Genome Project drafted the human body’s genetic blueprint more than a decade ago, researchers around the world have generated a deluge of information related to genes and the role they play in diseases like hypertension, diabetes, and various cancers.

    Although thousands of studies have made discoveries that promise a healthier future, crucial questions remain. An especially vexing challenge has been to identify the function of genes in specific cells, tissues, and organs. Because tissues cannot be studied by direct experimentation (in living people), and many disease-relevant cell types cannot be isolated for analysis, the data have emerged in bits and pieces through studies that produced mountains of disparate signals.

    A multi-year effort by researchers from Princeton and other universities and medical schools has taken a big step toward extracting knowledge from these big data collections and opening the door to new understanding of human illnesses. Their paper, published online by the prestigious biology journal Nature Genetics, demonstrates how computer science and statistical methods can comb broad expanses of diverse data to identify how genetic circuits function and change in different tissues relevant to disease.

    Led by Olga Troyanskaya, professor in the Department of Computer Science and the Lewis-Sigler Institute of Integrative Genomics and deputy director for genomics at the Simons Center for Data Analysis in New York, the team used integrative computational analysis to dig out interconnections and relationships buried in the data pile. The study collected and integrated about 38,000 genome-wide experiments from an estimated 14,000 publications. Their findings produced molecular-level functional maps for 144 different human tissues and cell types, including many that are difficult or impossible to uncover experimentally.

    “A key challenge in human biology is that genetic circuits in human tissues and cell types are very difficult to study experimentally,” Troyanskaya said. “For example, the podocyte cells in the kidneys, which are the cells that perform the filtering that the kidneys are responsible for, cannot be isolated and studied experimentally. Yet we must understand how proteins interact in these cells if we want to understand and treat chronic kidney disease. Our approach mines big data collections to build a map of how genetic circuits function in the podocyte cells, as well as in many other disease-relevant tissues and cell types.”

    These networks allow biomedical researchers to understand the function and interactions of genes in specific cellular contexts and can illuminate the molecular basis of many complex human diseases. The researchers developed an algorithm, which they call a network-guided association study, or NetWAS, that combines these tissue-specific functional maps with standard genome-wide association studies (GWAS) in order to identify genes that are causal drivers of human disease. Because the technique is completely data-driven, NetWAS avoids biases toward well-studied genes and diseases — enabling discovery of completely new disease-associated genes, processes, and pathways.

    To put NetWAS and the tissue-specific networks in the hands of biomedical researchers around the world, the team created an interactive server called GIANT (for Genome-scale Integrated Analysis of Networks in Tissues). GIANT allows users to explore these networks, compare how genetic circuits change across tissues, and analyze data from genetic studies to find genes that cause disease.

    Aaron K. Wong, a data scientist at the Simons Center for Data Analysis and formerly a graduate student in the computer science department at Princeton, played the lead role in creating GIANT. “Our goal was to develop a resource that was accessible to biomedical researchers,” he said. “For example, with GIANT, researchers studying Parkinson’s disease can search the substantia nigra network, which represents the brain region affected by Parkinson’s, to identify new genes and pathways involved in the disease.” Wong is one of three co-first authors of the paper.

    The paper’s other two co-first authors are Arjun Krishnan, a postdoctoral fellow at the Lewis-Sigler Institute; and Casey Greene, an assistant professor of genetics at Dartmouth College, who was a postdoctoral fellow at Lewis-Sigler from 2009 to 2012. The team also included Ran Zhang, a graduate student in Princeton’s Department of Molecular Biology, and Kara Dolinski, assistant director of the Lewis-Sigler Institute.

    Looking to the future, Troyanskaya sees practical therapeutic uses for the group’s findings about the interrelatedness of genetic actions. “Biomedical researchers can use these networks and the pathways that they uncover to understand drug action and side effects, and to repurpose drugs,” she said. “They can also be useful for understanding how various therapies work and how to develop new ones.”

    Other contributors to the study were Emanuela Ricciotti, Garret A. FitzGerald, and Tilo Grosser of the Department of Pharmacology and the Institute for Translational Medicine and Therapeutics at the Perelman School of Medicine, University of Pennsylvania; Rene A. Zelaya, of Dartmouth; Daniel S. Himmelstein, of the University of California, San Francisco; Boris M. Hartmann, Elena Zaslavsky, and Stuart C. Sealfon, of the Department of Neurology at the Icahn School of Medicine at Mount Sinai, in New York; and Daniel I. Chasman, of Brigham and Women’s Hospital and Harvard Medical School in Boston.

    The Simons Center for Data Analysis was formed in 2013 by the Simons Foundation, a private organization dedicated to advancing research in mathematics and the basic sciences.

    See the full article here.

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition
    Princeton University Campus

    About Princeton: Overview

    Princeton University is a vibrant community of scholarship and learning that stands in the nation’s service and in the service of all nations. Chartered in 1746, Princeton is the fourth-oldest college in the United States. Princeton is an independent, coeducational, nondenominational institution that provides undergraduate and graduate instruction in the humanities, social sciences, natural sciences and engineering.

    As a world-renowned research university, Princeton seeks to achieve the highest levels of distinction in the discovery and transmission of knowledge and understanding. At the same time, Princeton is distinctive among research universities in its commitment to undergraduate teaching.

    Today, more than 1,100 faculty members instruct approximately 5,200 undergraduate students and 2,600 graduate students. The University’s generous financial aid program ensures that talented students from all economic backgrounds can afford a Princeton education.

    Princeton Shield

     
  • richardmitnick 4:04 pm on April 16, 2015 Permalink | Reply
    Tags: , , , Genomics,   

    From Quanta: “How Structure Arose in the Primordial Soup” 

    Quanta Magazine
    Quanta Magazine

    Life’s first epoch saw incredible advances — cells, metabolism and DNA, to name a few. Researchers are resurrecting ancient proteins to illuminate the biological dark ages.

    April 16, 2015
    Emily Singer

    1
    Olena Shmahalo/Quanta Magazine

    About 4 billion years ago, molecules began to make copies of themselves, an event that marked the beginning of life on Earth. A few hundred million years later, primitive organisms began to split into the different branches that make up the tree of life. In between those two seminal events, some of the greatest innovations in existence emerged: the cell, the genetic code and an energy system to fuel it all. All three of these are essential to life as we know it, yet scientists know disappointingly little about how any of these remarkable biological innovations came about.

    “It’s very hard to infer even the relative ordering of evolutionary events before the last common ancestor,” said Greg Fournier, a geobiologist at the Massachusetts Institute of Technology. Cells may have appeared before energy metabolism, or perhaps it was the other way around. Without fossils or DNA preserved from organisms living during this period, scientists have had little data to work from.

    Fournier is leading an attempt to reconstruct the history of life in those evolutionary dark ages — the hundreds of millions of years between the time when life first emerged and when it split into what would become the endless tangle of existence.

    He is using genomic data from living organisms to infer the DNA sequence of ancient genes as part of a growing field known as paleogenomics. In research published online in March in the Journal of Molecular Evolution, Fournier showed that the last chemical letter added to the code was a molecule called tryptophan — an amino acid most famous for its presence in turkey dinners. The work supports the idea that the genetic code evolved gradually.

    Using similar methods, he hopes to decipher the temporal order of more of the code — determining when each letter was added to the genetic alphabet — and to date key events in the origins of life, such as the emergence of cells.

    Dark Origins

    Life emerged so long ago that even the rock formations covering the planet at that time have been destroyed — and with them, most chemical and geological clues to early evolution. “There’s a huge chasm between the origins of life and the last common ancestor,” said Eric Gaucher, a biologist at the Georgia Institute of Technology in Atlanta.

    2
    The stretch of time between the origins of life and the last universal common ancestor saw a series of remarkable innovations — the origins of cells, metabolism and the genetic code. But scientists know little about when they happened or the order in which they occurred. Olena Shmahalo/Quanta Magazine

    Scientists do know that at some point in that time span, living creatures began using a genetic code, a blueprint for making complex proteins. It is those proteins that carry out the vital functions of the cell. (The structure of DNA and RNA also enables genetic information to be replicated and passed on from generation to generation, but that’s a separate process from the creation of proteins.) The components of the code and the molecular machinery that assembles them “are some of the oldest and most universal aspects of cells, and biologists are very interested in understanding the mechanisms by which they evolved,” said Paul Higgs, a biophysicist at McMaster University in Hamilton, Ontario.

    How the code came into being presents a chicken-and-egg problem. The key players in the code — DNA, RNA, amino acids, and proteins — are chemically complicated structures that work together to make proteins. But in modern cells, proteins are used to make the components of the code. So how did a highly structured code emerge?

    Most researchers believe that the code began simply with basic proteins made from a limited alphabet of amino acids. It then grew in complexity over time, as these proteins learned to make more sophisticated molecules. Eventually, it developed into a code capable of creating all the diversity we see today. “It’s long been hypothesized that life’s ‘standard alphabet’ of 20 amino acids evolved from a simpler, earlier alphabet, much as the English alphabet has accumulated extra letters over its history,” said Stephen Freeland, a biologist at the University of Maryland, Baltimore County.

    The earliest amino acid letters in the code were likely the simplest in structure, those that can be made from purely chemical means, without the assistance of a protein helper. (For example, the amino acids glycine, alanine and glutamic acid have been found on meteorites, suggesting they can form spontaneously in a variety of environments.) These are like the letters A, E and S — primordial units that served as the foundation for what came later.

    Tryptophan, in comparison, has a complex structure and is comparatively rare in the protein code, like a Y or Z, leading scientists to theorize that it was one of the latest additions to the code.

    That chemical evidence is compelling, but circumstantial. Enter Fournier. He suspected that by extending his work on paleogenomics, he would be able to prove tryptophan’s status as the last letter added to the code.

    The Last Letter

    Scientists have been reconstructing ancient proteins for more than a decade, primarily to figure out how ancient proteins differed from modern ones — what they looked like and how they functioned. But these efforts have focused on the period of evolution after the last universal common ancestor (or LUCA, as researchers call it). Fournier’s work delves further back than any other previous efforts. To do so, he had to move beyond the standard application of comparative genomics, which analyzes the differences between branches on the tree of life. “By definition, anything pre-LUCA lies beyond the deepest split in the tree,” he said.

    Fournier started with two related proteins, TrpRS (tryptophanyl tRNA synthetase) and TyrRS (tyrosyl tRNA synthetase), which help decode RNA letters into the amino acids tryptophan and tyrosine. TrpRS and TyrRS are more closely related to each other than to any other protein, indicating that they evolved from the same ancestor protein. Sometime before LUCA, that parent protein mutated slightly to produce these two new proteins with distinct functions. Fournier used computational techniques to decipher what that ancestral protein must look like.

    4
    Greg Fournier, a geobiologist at MIT, is searching for the origins of the genetic code. Helen Hill

    He found that the ancestral protein has all the amino acids but tryptophan, suggesting that its addition was the finishing touch to the genetic code. “It shows convincingly that tryptophan was the last amino acid added, as has been speculated before but not really nailed as has been done here,” said Nigel Goldenfeld, a physicist at the University of Illinois, Urbana-Champaign, who was not involved in the study.

    Fournier now plans to use tryptophan as a marker to date other major pre-LUCA events such as the evolution of metabolism, cells and cell division, and the mechanisms of inheritance. These three processes form a sort of biological triumvirate that laid the foundation for life as we know it today. But we know little about how they came into existence. “If we understand the order of those basic steps, it creates an arrow pointing to possible scenarios for the origins of life,” Fournier said.

    For example, if the ancestral proteins involved in metabolism lack tryptophan, some form of metabolism probably evolved early. If proteins that direct cell division are studded with tryptophan, it suggests those proteins evolved comparatively late.

    Different models for the origins of life make different predictions for which of these three processes came first. Fournier hopes his approach will provide a way to rule out some of these models. However, he cautions that it won’t definitively sort out the timing of these events.

    Fournier plans to use the same techniques to figure out the order in which other amino acids were added to the code. “It really reinforces the idea that evolution of the code itself was a progressive process,” said Paul Schimmel, a professor of molecular and cell biology at the Scripps Research Institute, who was not involved in the study. “It speaks to the refinement and subtlety that nature was using to perfect these proteins and the diversity it needed to form this vast tree of life.”

    See the full article here.

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition

    Formerly known as Simons Science News, Quanta Magazine is an editorially independent online publication launched by the Simons Foundation to enhance public understanding of science. Why Quanta? Albert Einstein called photons “quanta of light.” Our goal is to “illuminate science.” At Quanta Magazine, scientific accuracy is every bit as important as telling a good story. All of our articles are meticulously researched, reported, edited, copy-edited and fact-checked.

     
  • richardmitnick 11:42 am on March 8, 2015 Permalink | Reply
    Tags: , , , Genomics,   

    From NYT: “Is Most of Our DNA Garbage?” 

    New York Times

    The New York Times

    MARCH 5, 2015
    CARL ZIMMER

    T. Ryan Gregory’s lab at the University of Guelph in Ontario is a sort of genomic menagerie, stocked with creatures, living and dead, waiting to have their DNA laid bare. Scorpions lurk in their terrariums. Tarantulas doze under bowls. Flash-frozen spiders and crustaceans — collected by Gregory, an evolutionary biologist, and his students on expeditions to the Arctic — lie piled in beige metal tanks of liquid nitrogen. A bank of standing freezers holds samples of mollusks, moths and beetles. The cabinets are crammed with slides splashed with the fuchsia-stained genomes of fruit bats, Siamese fighting fish and ostriches.

    1
    Moths in the lab of T. Ryan Gregory at the University of Guelph. Credit Jamie Campbell for The New York Times

    Gregory’s investigations into all these genomes has taught him a big lesson about life: At its most fundamental level, it’s a mess. His favorite way to demonstrate this is through what he calls the “onion test,” which involves comparing the size of an onion’s genome to that of a human. To run the test, Gregory’s graduate student Nick Jeffery brought a young onion plant to the lab from the university greenhouse. He handed me a single-edged safety razor, and then the two of us chopped up onion stems in petri dishes. An emerald ooze, weirdly luminous, filled my dish. I was so distracted by the color that I slashed my ring finger with the razor blade, but that saved me the trouble of poking myself with a syringe — I was to supply the human genome. Jeffery raised a vial, and I wiped my bleeding finger across its rim. We poured the onion juice into the vial as well and watched as the green and red combined to produce a fluid with both the tint and viscosity of maple syrup.

    3
    T. Ryan Gregory in his lab at University of Guelph. Credit Jamie Campbell for The New York Times

    After adding a fluorescent dye that attaches to DNA, Jeffrey loaded the vial into a boxy device called a flow cytometer, which sprayed the onion juice and blood through a laser beam. Each time a cell was hit, its DNA gave off a bluish glow; bigger genomes glowed more brightly. On a monitor, we watched the data accumulate on a graph. The cells produced two distinct glows, one dim, one bright, which registered on the graph as a pair of peaks.

    One peak represented my genome, or the entirety of my DNA. Genomes are like biological books, written in genetic letters known as bases; the human genome contains about 3.2 billion bases. Print them out as letters on a page, and they would fill a book a thousand times longer than “War and Peace.” Gregory leaned toward the screen. At 39, with a chestnut-colored goatee and an intense gaze, he somewhat resembles a pre-Heisenberg Walter White. He pointed out the onion’s peak. It showed that the onion’s genome was five times bigger than mine.

    “The onion wins,” Gregory said. The onion always does.

    But why? Why does an onion carry around so much more genetic material than a human? Or why, for that matter, do the broad-footed salamander (65.5 billion bases), the African lungfish (132 billion) and the Paris japonica flower (149 billion)? These organisms don’t appear to be more complex than we are, so Gregory rejects the idea that they’re accomplishing more with all their extra DNA. Instead, he champions an idea first developed in the 1970s but still startling today: that the size of an animal’s or plant’s genome has essentially no relationship to its complexity, because a vast majority of its DNA is — to put it bluntly — junk.

    The human genome contains around 20,000 genes, that is, the stretches of DNA that encode proteins. But these genes account for only about 1.2 percent of the total genome. The other 98.8 percent is known as noncoding DNA. Gregory believes that while some noncoding DNA is essential, most probably does nothing for us at all, and until recently, most biologists agreed with him. Surveying the genome with the best tools at their disposal, they believed that only a small portion of noncoding DNA showed any evidence of having any function.

    But in the past few years, the tide has shifted within the field. Recent studies have revealed a wealth of new pieces of noncoding DNA that do seem to be as important to our survival as our more familiar genes. Many of them may encode molecules that help guide our development from a fertilized egg to a healthy adult, for example. If these pieces of noncoding DNA become damaged, we may suffer devastating consequences like brain damage or cancer, depending on what pieces are affected. Large-scale surveys of the genome have led a number of researchers to expect that the human genome will turn out to be even more full of activity than previously thought.

    In January, Francis Collins, the director of the National Institutes of Health, made a comment that revealed just how far the consensus has moved. At a health care conference in San Francisco, an audience member asked him about junk DNA. “We don’t use that term anymore,” Collins replied. “It was pretty much a case of hubris to imagine that we could dispense with any part of the genome — as if we knew enough to say it wasn’t functional.” Most of the DNA that scientists once thought was just taking up space in the genome, Collins said, “turns out to be doing stuff.”

    For Gregory and a group of like-minded biologists, this idea is not just preposterous but also perilous, something that could yield bad science. The turn against the notion of junk DNA, they argue, is based on overinterpretations of wispy evidence and a willful ignorance of years of solid research on the genome. They’ve challenged their opponents face to face at scientific meetings. They’ve written detailed critiques in biology journals. They’ve commented on social media. When the N.I.H.’s official Twitter account relayed Collins’s claim about not using the term “junk DNA” anymore, Michael Eisen, a professor at the University of California, Berkeley, tweeted back with a profanity.

    The junk DNA wars are being waged at the frontiers of biology, but they’re really just the latest skirmish in an intellectual struggle that has played out over the past 200 years. Before Charles Darwin articulated his theory of evolution, most naturalists saw phenomena in nature, from an orchid’s petal to the hook of a vulture’s beak, as things literally designed by God. After Darwin, they began to see them as designs produced, instead, by natural selection. But some of our greatest biologists pushed back against the idea that everything we discover in an organism had to be an exquisite adaptation. To these biologists, a fully efficient genome would be inconsistent with the arbitrariness of our genesis, with the fact that every species emerged through pure happenstance, over eons of false starts. Where some look at all those billions of bases and see a finely tuned machine, others, like Gregory, see a disorganized, glorious mess.

    In 1953, Francis Crick and James Watson published a short paper in the journal Nature setting out the double-helix structure of DNA. That brief note sent biologists into a frenzy of discovery, leading eventually to multiple Nobel Prizes and to an unprecedented depth of understanding about how living things grow and reproduce. To make a protein from DNA, they learned, a cell makes a single-stranded copy of the relevant gene, using a molecule called RNA. It then builds a corresponding protein using the RNA as a guide.

    This research led scientists to assume that the genome was mostly made up of protein-coding DNA. But eventually scientists found this assumption hard to square with reality. In 1964, the German biologist Friedrich Vogel did a rough calculation of how many genes a typical human must carry. Scientists had already discovered how big the human genome was by staining the DNA in cells, looking at the cells through microscopes and measuring its size. If the human genome was made of nothing but genes, Vogel found, it would need to have an awful lot of them — 6.7 million genes by his estimate, a number that, when he published it in Nature, he admitted was “disturbingly high.” There was no evidence that our cells made 6.7 million proteins or anything close to that figure.

    Vogel speculated that a lot of the genome was made up of essential noncoding DNA — possibly operating as something like switches, for example, to turn genes on and off. But other scientists recognized that even this idea couldn’t make sense mathematically. On average, each baby is born with roughly 100 new mutations. If every piece of the genome were essential, then many of those mutations would lead to significant birth defects, with the defects only multiplying over the course of generations; in less than a century, the species would become extinct.

    4
    Cells are gathered from spiders for DNA studies at the lab of T. Ryan Gregory at the University of Guelph. Credit Jamie Campbell for The New York Times

    Faced with this paradox, Crick and other scientists developed a new vision of the genome during the 1970s. Instead of being overwhelmingly packed with coding DNA, the genome was made up mostly of noncoding DNA. And, what’s more, most of that noncoding DNA was junk — that is, pieces of DNA that do nothing for us. These biologists argued that some pieces of junk started out as genes, but were later disabled by mutations. Other pieces, called transposable elements, were like parasites, simply making new copies of themselves that were usually inserted harmlessly back in the genome.

    Junk DNA’s recognition was part of a bigger trend in biology at the time. A number of scientists were questioning the assumption that biological systems are invariably “well designed” by evolution. In a 1979 paper in The Proceedings of the Royal Society of London, Stephen Jay Gould and Richard Lewontin, both of Harvard, groused that too many scientists indulged in breezy storytelling to explain every trait, from antlers to jealousy, as an adaptation honed by natural selection for some essential function. Gould and Lewontin refer to this habit as the Panglossian paradigm, a reference to Voltaire’s “Candide,” in which the foolish Professor Pangloss keeps insisting, in the face of death and disaster, that we live in “the best of all possible worlds.” Gould and Lewontin did not deny that natural selection was a powerful force, but they stressed that it was not the only explanation for why species are the way they are. Male nipples are not adaptations, for example; they’re just along for the ride.

    Gould and Lewontin called instead for a broader vision of evolution, with room for other forces, for flukes and historical contingencies, for processes unfolding at different levels of life — what Gould often called “pluralism.” At the time, geneticists were getting their first glimpses of the molecular secrets of the human genome, and Gould and Lewontin saw more evidence for pluralism and against the Panglosses. Any two people may have millions of differences in their genomes. Most of those differences aren’t a result of natural selection’s guiding force; they just arise through random mutations, without any effect for good or ill.

    When Crick and others began to argue for junk DNA, they were guided by a similar vision of nature as slipshod. Just as male nipples are a useless vestige of evolution, so, in their theory, is a majority of our genome. Far from the height of machine-like perfection, the genome is largely a palimpsest of worthless instructions, a den of harmless parasites. Crick and his colleagues argued that transposable elements were common in our genome not because they did something essential for us, but because they could exploit us for their own replication. Gould delighted at this good intellectual company, arguing that transposable elements behaved like miniature organisms, evolving to become better at adding new copies to their host genomes. Our genomes were their ocean, their savanna. “They are merely playing Darwin’s game, but at the ‘wrong level,’ ” Gould wrote in 1981.

    Soon after Gould wrote those words, scientists set out to decipher the precise sequence of the entire human genome. It wasn’t until 2001, shortly before Gould’s death, that they published their first draft. They identified thousands of segments that had the hallmarks of dead genes. They found transposable elements by the millions. The Human Genome Project team declared that our DNA consisted of isolated oases of protein-coding genes surrounded by “vast expanses of unpopulated desert where only noncoding ‘junk’ DNA can be found.” Junk DNA had started out as a theoretical argument, but now the messiness of our evolution was laid bare for all to see.

    If you want to see the genome in a fundamentally different way, the best place to go is the third floor of Harvard’s Department of Stem Cell and Regenerative Biology, in a maze of cluttered benches, sequencing machines and microscopes. This is the lab of John Rinn, a 38-year-old former competitive snowboarder who likes to ponder biological questions on top of a skateboard, which he rides from one wall of his office to the other and back. Rinn is overseeing more than a dozen research projects looking for pieces of noncoding DNA that might once have been classified as junk but actually are essential for life.

    5
    John Rinn in his lab at Harvard. Credit Jamie Campbell for The New York Times

    Rinn studies RNA, but not the RNA that our cells use as a template for making proteins. Scientists have long known that the human genome contains some genes for other types of RNA: strands of bases that carry out other jobs in the cell, like helping to weld together the building blocks of proteins. In the early 2000s, Rinn and other scientists discovered that human cells were reading thousands of segments of their DNA, not just the coding parts, and producing RNA molecules in the process. They wondered whether these RNA molecules could be serving some vital function.
    Continue reading the main story

    As a postdoctoral fellow at Stanford University, Rinn decided he would try to show that one of these new RNA molecules had some important role. After a couple years of searching, he and a professor there, Howard Chang, settled on an RNA molecule that, somewhat bizarrely, was produced widely by skin cells below the waist but not above. Rinn and Chang were well aware that this pattern might be meaningless, but they set out to investigate it nevertheless. They had to give their enigmatic molecule a name, so they picked one that was a joke at their own expense: hotair. (“If it ends up being hot air, at least we tried,” Rinn said.)

    Rinn ran a series of experiments on skin cells to figure out what, if anything, hotair was doing. He carefully pulled hotair molecules out of the cells and examined them to see if they had attached to any other molecules. They had, in fact: they were stuck to a protein called Polycomb.

    Polycomb belongs to a group of proteins that are essential to the development of animals from a fertilized egg. They turn genes on and off in different patterns, so that a uniform clump of cells can give rise to bone, muscle and brain. Polycomb latches onto a number of genes and muzzles them, preventing them from making proteins. Rinn’s research revealed that hotair acts as a kind of guide for Polycomb, attaching to it and escorting it through the jungle of the cell to the precise spots on our DNA where it needs to silence genes.

    When Rinn announced this result in 2007, other geneticists were stunned. Cell, the journal that released it, hailed it as a breakthrough, calling Rinn’s paper one of the most important they had ever published. In the years since, Chang and other researchers have continued to examine hotair, using even more sophisticated tools. They bred engineered mice that lack the hotair gene, for example, and found that the mice developed a constellation of deformities, like stunted wrists and jumbled vertebrae. It appears very likely that hotair performs important jobs throughout the body, not just in the skin but in the skeleton and in other tissues too.

    In 2008, having been lured to Harvard, Rinn set up his new lab entirely in hopes of finding more hotair-like molecules. The first day I visited, a research associate named Diana Sanchez was dissecting mouse embryos the size of pinto beans. In a bowl of ice next to her were tubes for the parts she delicately removed — liver, leg, kidney, lung — that would be searched for cells making RNA molecules. After Rinn and I left Sanchez to her dissections, we ran into Martin Sauvageau, a blue-eyed Quebecer carrying a case of slides, each affixed with a slice of a mouse’s brain, with stains revealing cells making different RNA molecules. I tagged along with Sauvageau as he headed to a darkened microscope room to look at the slides with a pink-haired grad student named Abbie Groff. On one slide, a mouse’s brain looked as if it wore a cerulean mustache. To Groff, every pattern comes as a surprise. She once discovered an RNA molecule that created thousands of tiny rings on a mouse’s body, each encircling a hair follicle. “You come in in the morning, and it’s like Christmas,” she said.

    In December 2013, Rinn and his colleagues published the first results of their search: three potential new genes for RNA that appear to be essential for a mouse’s survival. To investigate each potential gene, the scientists removed one of the two copies in mice. When the mice mated, some of their embryos ended up with two copies of the gene, some with one and some with none. If these mice lacked any of these three pieces of DNA, they died in utero or shortly after birth. “You take away a piece of junk DNA, and the mouse dies,” Rinn said. “If you can come up with a criticism of that, go ahead. But I’m pretty satisfied. I’ve found a new piece of the genome that’s required for life.”

    As the scientists find new RNA molecules that look to be important, they are picking out a few to examine in close molecular detail. “I’m totally in love with this one,” Rinn said, standing at a whiteboard wall and drawing a looping line to illustrate yet another RNA molecule, one that he calls “firre.” The experiments that Rinn’s team has run on firre suggest that it performs a spectacular lasso act, grabbing onto three different chromosomes at once and drawing them together. Rinn suspects that there are thousands of RNA molecules encoded in our genomes that perform similar feats: bending DNA, unspooling it, bringing it in contact with certain proteins and otherwise endowing it with a versatility it would lack on its own.

    “It’s genomic origami,” Rinn said about this theory. “In every cell, you have the same piece of paper. Stem cell, brain cell, liver cell, it’s all made from the same piece of paper. How you fold that paper determines if you get a paper airplane or a duck. It’s the shape that you fold it into that matters. This has to be the 3-D code of biology.”

    To some biologists, discoveries like Rinn’s hint at a hidden treasure house in our genome. Because a few of these RNA molecules have turned out to be so crucial, they think, the rest of the noncoding genome must be crammed with riches. But to Gregory and others, that is a blinkered optimism worthy of Dr. Pangloss. They, by contrast, are deeply pessimistic about where this research will lead. Most of the RNA molecules that our cells make will probably not turn out to perform the sort of essential functions that hotair and firre do. Instead, they are nothing more than what happens when RNA-making proteins bump into junk DNA from time to time.

    “You say, ‘I found it — America!’ ” says Alex Palazzo, a biochemist at the University of Toronto who co-wrote a spirited defense of junk DNA with Gregory last year in the journal PLOS Genetics. “But probably what you found is a little bit of noise.”

    Palazzo and his colleagues also roll their eyes at the triumphant declarations being made about recent large-scale surveys of the human genome. One news release from an N.I.H. project declared, “Much of what has been called ‘junk DNA’ in the human genome is actually a massive control panel with millions of switches regulating the activity of our genes.” Researchers like Gregory consider this sort of rhetoric to be leaping far beyond the actual evidence. Gregory likens the search for useful pieces of noncoding DNA to using a metal detector to find gold buried at the beach. “The idea of combing the beach is a great idea,” he says. But you have to make sure your metal detector doesn’t go off when it responds to any metal. “You’re going to find bottle caps and nails,” Gregory says.

    He expects that as we examine the genome more closely, we’ll find many bottle caps and nails. It’s a prediction based, he and others argue, on the deep evolutionary history of our genome. Over millions of years, essential genes haven’t changed very much, while junk DNA has picked up many harmless mutations. Scientists at the University of Oxford have measured evolutionary change over the past 100 million years at every spot in the human genome. “I can today say, hand on my heart, that 8 percent, plus or minus 1 percent, is what I would consider functional,” Chris Ponting, an author of the study, says. And the other 92 percent? “It doesn’t seem to matter that much,” he says.

    It’s no coincidence, researchers like Gregory argue, that bona fide creationists have used recent changes in the thinking about junk DNA to try to turn back the clock to the days before Darwin. (The recent studies on noncoding DNA “clearly demonstrate we are ‘fearfully and wonderfully made’ by our Creator God,” declared the Institute for Creation Research.) In a sense, this debate stretches back to Darwin himself, whose 1859 book, “On the Origin of Species,” set the course for our understanding natural selection as a natural “designer.” Later in his life, Darwin took pains to stress that there was more to evolution than natural selection. He was frustrated to see how many of his readers thought he was arguing that natural selection was the only force behind life’s diversity. “Great is the power of steady misrepresentation,” Darwin grumbled when he updated the book for its sixth edition in 1872. In fact, he wrote, he was quite open-minded about other forces that might drive evolution, like “variations that seem to us in our ignorance to arise spontaneously.”

    Darwin was certainly ignorant about genomes, as scientists would continue to be for decades after his death. But Gregory argues that genomes embody the very mix of adaptation and arbitrariness that Darwin had in mind. Over millions of years, the human genome has spontaneously gotten bigger, swelling with useless copies of genes and new transposable elements. Our ancestors tolerated all that extra baggage because it wasn’t actually all that heavy. It didn’t make them inordinately sick. Copying all that extra DNA didn’t require them to draw off energy required for other tasks. They couldn’t add an infinite amount of junk to the genome, but they could accept an awful lot. To subtract junk, meanwhile, would require swarms of proteins to chop out every single dead gene or transposable element — without chopping out an essential gene. A genome evolving away its junk would lose the race to sloppier genomes, which left more resources for fighting diseases or having children.

    The blood-drenched slides that pack Gregory’s lab with their giant genomes only make sense, he argues, if we give up thinking about life as always evolving to perfection. To him, junk DNA isn’t a sign of evolution’s failure. It is, instead, evidence of its slow and slovenly triumph.

    See the full article here.

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition

     
  • richardmitnick 3:24 pm on February 26, 2015 Permalink | Reply
    Tags: , Genomics,   

    From Uncovering Genome Mysteries at WCG: “Seven quadrillion comparisons later, Uncovering Genome Mysteries is just getting started” 

    New WCG Logo

    Uncovering Genome Mysteries Screensaver

    By: Wim Degrave, Ph.D.
    Laboratório de Genômica Funcional e Bioinformática Instituto Oswaldo Cruz – Fiocruz
    26 Feb 2015

    Summary
    The Uncovering Genome Mysteries research team has started analyzing results from their massive ongoing project, which is comparing proteins between diverse organisms from around the world. Better understanding of similarities between proteomes should help scientists develop sustainable technologies, renewable materials, productive crops, and new treatments for stubborn diseases.

    1
    Uncovering Genome Mysteries researchers, left-to-right: Wim Degrave – Senior Researcher, Marcos Catanho – Adjunct Researcher and Ana Carolina Guimarães – Adjunct Researcher at the Oswaldo Cruz Foundation

    The Uncovering Genome Mysteries (UGM) project started running on World Community Grid on October 16, 2014, with the daunting task of comparing all currently predicted protein sequences encoded in the genomes of a wide variety of living organisms, with special emphasis on microorganisms. The project expects to examine more than 200 million proteins, the majority of which were generated in environmental and ecological studies ranging from bacteria in marine ecosystems in Australia, to Amazon River samples from Brazil. Similarity data from these comparisons will lead to a better understanding of metabolic and structural functions of the predicted proteins in databases, and uncover many new features and cellular processes in microorganisms. Of the expected 20 quadrillion (20,000,000,000,000,000) comparisons in the project, about 36% have been completed thus far, equivalent to almost 8,000 CPU-years of computation.

    This project involves cooperation between World Community Grid; the laboratory of Dr. Torsten Thomas and his team in the School of Biotechnology and Biomolecular Sciences & Centre for Marine Bio-Innovation at the University of New South Wales, Sydney, Australia; and the laboratory for Functional Genomics and Bioinformatics of Dr. Wim Degrave and his team at the Oswaldo Cruz Foundation – Fiocruz, in Brazil.

    Volunteers participating in the UGM project process work units that contain sets of protein sequences predicted from a variety of organisms, and compare those against each other. Every time a significant similarity between two sequences is detected, a line of output is written that contains the coordinates and information on the statistical significance of the similarity. All of the output data together allow us to trace functional predictions of unknown sequences when they are similar to sequences with known functions, and indicate how organisms and their biochemistry, metabolic functions, and other cellular processes relate to one another.

    The data resulting from those calculations are starting to be processed at Fiocruz and the University of New South Wales, and will later be presented in a database that will allow researchers to study the relationships between the proteins of all living things, to help develop a much better understanding of organisms in their (biodiverse) environment. Many applications in health, environment, and agriculture can be attributed to making use of such data. For example, they enabled the development of new strategies to fight pathogens that threaten human and animal health, and development of diagnostics, treatments, and preventions through appropriate design of vaccines. But there are many other applications to be discovered, in agriculture, industry or the environment, through the study of the wide variety of proteins and enzymes. For example, these might function as insecticides, antibiotics or enzymes that can degrade and eliminate waste or industrial pollutants such as oil or organic chemicals. Enzymes can aid in the synthesis and production of “green chemicals” and biotransformation systems, but also in the production of renewable energy such as bio-alcohols, or in more sophisticated systems through synthetic biology, where the engineering of microorganisms can optimize the production of biopharmaceuticals, green plastics and biofuels. A thorough knowledge of biochemical pathways and their regulation is necessary and is being addressed in part through projects like UGM, where the wide variety of enzymatic and biological functions in nature will become more available to the scientific community.

    We deeply thank the World Community Grid volunteers who are contributing to this massive effort.

    See the full article here.

    Please help promote STEM in your local schools.
    STEM Icon

    Stem Education Coalition

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing.

    CAN ONE PERSON MAKE A DIFFERENCE? YOU BETCHA!!

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-
    Outsmart Ebola together

    Outsmart Ebola Together

    Mapping Cancer Markers
    mappingcancermarkers2

    Uncovering Genome Mysteries
    Uncovering Genome Mysteries

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding

    FightAIDS@Home

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
    ibm

    IBM – Smarter Planet
    sp

     
  • richardmitnick 3:31 am on February 18, 2015 Permalink | Reply
    Tags: , Genomics,   

    From UCSC: “DNA sequencer the size of a mobile phone” 

    UC Santa Cruz

    UC Santa Cruz

    February 17, 2015
    Branwyn Wagman, UC Santa Cruz Genomics Institute

    1

    Investigators at the UC Santa Cruz Genomics Institute have optimized performance of a mobile-phone-sized MinIONTM DNA sequencer, marketed by Oxford Nanopore. Their work was reported in Nature Methods on February 16, 2015.

    The MinION device reads individual DNA strands base-by-base as they pass through a nanoscale pore (nanopore) under control of an applied voltage. This process is facilitated by an enzyme bound to the DNA.

    Biomolecular engineering graduate student Miten Jain led the research with director of comparative genomics Benedict Paten and biomolecular engineering professor Mark Akeson, who along with biochemist David Deamer has helped develop the scientific foundation of the nanopore device for the past 18 years.

    To optimize the MinION’s performance, the researchers used standard reference genomes and an expectation-maximization algorithm to obtain robust maximum likelihood estimates for rates of read insertions, deletions, and substitution errors (4.9%, 7.8%, and 5.1% respectively).

    The MinION technology is constantly evolving, resulting in multiple updates to the platform in the past six months, Akeson explained. “Each of these updates has resulted in improved read quality,” he said.

    “In this study we saw performance significantly better than what has been seen with this device before,” Akeson said. “Over 99% of high-quality, two-dimensional MinION reads mapped to the reference genome at a mean identity of 85%.”

    The UC Santa Cruz investigators also presented a tool that can be used to detect single nucleotide variants from MinION data. It employs maximum-likelihood parameter estimates and marginalization over many possible read alignments.

    “In this study, we were able to detect single-nucleotide variations with precision and recall of up to 99%,” said Paten.

    By pairing a high-confidence alignment strategy with long MinION reads, the group resolved the copy number for a cancer/testis gene family (CT47) within an unresolved region of human chromosome Xq24, a feat possible only with long-read sequencing such as the MinION makes possible.

    “The MinION nanopore sequencer is changing how we think about DNA sequencing,” Jain said. He explained that while DNA base read lengths of 8-10 kilobases are now considered normal, the MinION device has achieved reads exceeding 48 kilobases.

    “With the combination of long-reads and portability, the MinION is primed to disrupt the way we do genomics,” Jain said.

    The paper’s co-authors also included biomolecular engineering graduate student Ian Fiddes, postdoctoral scholar Karen Miga, and staff scientist Hugh Olsen. All are from the UC Santa Cruz Genomics Institute.

    The study was supported by National Human Genome Research Institute (NHGRI) grant HG006321.

    Read the report in Nature Methods.

    See the full article here.

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition
    The University of California, Santa Cruz, opened in 1965 and grew, one college at a time, to its current (2008-09) enrollment of more than 16,000 students. Undergraduates pursue more than 60 majors supervised by divisional deans of humanities, physical & biological sciences, social sciences, and arts. Graduate students work toward graduate certificates, master’s degrees, or doctoral degrees in more than 30 academic fields under the supervision of the divisional and graduate deans. The dean of the Jack Baskin School of Engineering oversees the campus’s undergraduate and graduate engineering programs.

     
  • richardmitnick 5:55 pm on December 10, 2014 Permalink | Reply
    Tags: , , , Genomics,   

    From isgtw: “Supercomputer compares modern and ancient DNA” 


    international science grid this week

    December 10, 2014
    Jorge Salazar, Texas Advanced Computing Center
    tc

    What if you researched your family’s genealogy, and a mysterious stranger turned out to be an ancestor? A team of scientists who peered back into Europe’s murky prehistoric past thousands of years ago had the same surprise. With sophisticated genetic tools, supercomputing simulations and modeling, they traced the origins of modern Europeans to three distinct populations.The international research team’s results are published in the journal Nature.

    s
    The Stuttgart skull, from a 7,000-year-old skeleton found in Germany among artifacts from the first widespread farming culture of central Europe. Right: Blue eyes and dark skin – how the European hunter-gatherer appeared 7,000 years ago. Artist depiction based on La Braña 1, whose remains were recovered at La Braña-Arintero site in León, Spain. Images courtesy Consejo Superior de Investigaciones Cientificas.

    “Europeans seem to be a mixture of three different ancestral populations,” says study co-author Joshua Schraiber, a National Science Foundation postdoctoral fellow at the University of Washington, in Seattle, US. Schraiber says the results surprised him because the prevailing view among scientists held that only two distinct groups mixed between 7,000 and 8,000 years ago in Europe, as humans first started to adopt agriculture.

    Scientists have only a handful of ancient remains well preserved enough for genome sequencing. An 8,000-year-old skull discovered in Loschbour, Luxembourg provided DNA evidence for the study. The remains were found at the caves of Loschbour, La Braña, Stuttgart, a ritual site at Motala, and at Mal’ta.

    The third mystery group that emerged from the data is ancient northern Eurasians. “People from the Siberia area is how I conceptualize it,” says Schraiber. “We don’t know too much anthropologically about who these people are. But the genetic evidence is relatively strong because we do have ancient DNA from an individual that’s very closely related to that population, too.”

    The individual is a three-year-old boy whose remains were found near Lake Baikal in Siberia at the Mal’ta site. Scientists determined his arm bone to be 24,000 years old. They then sequence his genome, making it the second oldest modern human sequenced. Interestingly enough, in late 2013 scientists used the Mal’ta genome to find that about one-third of Native American ancestry originated through gene flow from these ancient North Eurasians.

    The researchers took the genomes from these ancient humans and compared them to those from 2,345 modern-day Europeans. “I used the POPRES data set, which had been used before to ask similar questions just looking at modern Europeans,” Schraiber says. “Then I used software called Beagle, which was written by Brian Browning and Sharon Browning at the University of Washington, which computationally detects these regions of identity by descent.”

    The National Science Foundation’s XSEDE (Extreme Science and Engineering Discovery Environment) and Stampede supercomputer at the Texas Advanced Computing Center provided computational resources used in the study. The research was funded in part by the National Cancer Institute of the National Institutes of Health.

    See the full article here.

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition

    iSGTW is an international weekly online publication that covers distributed computing and the research it enables.

    “We report on all aspects of distributed computing technology, such as grids and clouds. We also regularly feature articles on distributed computing-enabled research in a large variety of disciplines, including physics, biology, sociology, earth sciences, archaeology, medicine, disaster management, crime, and art. (Note that we do not cover stories that are purely about commercial technology.)

    In its current incarnation, iSGTW is also an online destination where you can host a profile and blog, and find and disseminate announcements and information about events, deadlines, and jobs. In the near future it will also be a place where you can network with colleagues.

    You can read iSGTW via our homepage, RSS, or email. For the complete iSGTW experience, sign up for an account or log in with OpenID and manage your email subscription from your account preferences. If you do not wish to access the website’s features, you can just subscribe to the weekly email.”

     
  • richardmitnick 4:28 pm on October 16, 2014 Permalink | Reply
    Tags: , Genomics,   

    From WCG: “Project Launch: Uncovering Genome Mysteries” 

    16 Oct 2014
    Summary
    To kick off World Community Grid’s 10th anniversary celebrations, we’re launching Uncovering Genome Mysteries to compare hundreds of millions of genes from many organisms that have never been studied before, helping scientists unearth some of the hidden superpowers of the natural world.

    From the realization that the Penicillium fungus kills germs, to the discovery of bacteria that eat oil spills and the identification of aspirin in the willow tree bark – a better understanding of the natural world has resulted in many improvements to human health, welfare, agriculture and industry.

    diver
    Diver collecting microbial samples from Australian seaweeds for Uncovering Genome Mysteries

    Our understanding of life on earth has grown enormously since the advent of genetic research. But the vast majority of life on this planet remains unstudied or unknown, because it’s microscopic, easy to overlook, and hard to study. Nevertheless, we know that tiny, diverse organisms are continually evolving in order to survive and thrive in the most extreme conditions. The study of these organisms can provide valuable insights on how to deal with some of the most pressing problems that human society faces, such as drug-resistant pathogens, pollution, and energy shortages.

    Inexpensive, rapid DNA sequencing technologies have enabled scientists to decode the genes of many organisms that previously received little attention, or were entirely unknown to science. However, making sense of all that genomic information is an enormous task. The first step is to compare unstudied genes to others that are already better understood. Similarities between genes point to similarities in function, and by making a large number of these comparisons, scientists can begin to sort out what each organism is and what it can do.

    In Uncovering Genome Mysteries, World Community Grid volunteers will run approximately 20 quadrillion comparisons to identify similarities between genes in a wide variety of organisms, including microorganisms found on seaweeds from Australian coastlines and in the Amazon River. This database of similarities will help researchers understand the diversity and capabilities that are hidden in the world all around us. For more on the project’s aims and methods, see here.

    Once published, these results should help scientists with the following goals:

    Discovering new protein functions and augmenting knowledge about biochemical processes in general
    Identifying how organisms interact with each other and the environment
    Documenting the current baseline microbial diversity, allowing a better understanding of how microorganisms change under environmental stresses, such as climate change
    Understanding and modeling complex microbial systems

    In addition, a better understanding of these organisms will likely be useful in developing new medicines, harnessing new sources of renewable energy, improving nutrition, cleaning the environment, creating green industrial processes and many other advances.

    The timing of this project launch is a perfect way to kick off celebrations of another important achievement – World Community Grid’s 10th anniversary. There’s much to celebrate and reflect upon from the past decade’s work, but it’s equally important to continue pushing forward and making new scientific discoveries. With your help – and the help of your colleagues and friends – we can continue to expand our global network of volunteers and achieve another 10 years of success. Here’s to another decade of discovery!

    To contribute to Uncovering Genome Mysteries, go to your My Projects page and make sure the box for this new project is checked.

    Please visit the following pages to learn more:

    Uncovering Genome Mysteries project overview
    Frequently Asked Questions

    See the full article here.

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing.

    CAN ONE PERSON MAKE A DIFFERENCE? YOU BETCHA!!

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding

    FightAIDS@Home

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
    ibm

    IBM – Smarter Planet
    sp

    ScienceSprings relies on technology from

    MAINGEAR computers

    Lenovo
    Lenovo

    Dell
    Dell

     
  • richardmitnick 8:06 pm on August 27, 2014 Permalink | Reply
    Tags: , , , Genomics   

    From Berkeley Lab: “Encyclopedia of How Genomes Function Gets Much Bigger” 

    Berkeley Logo

    Berkeley Lab

    August 27, 2014
    Dan Krotz 510-486-4019

    A big step in understanding the mysteries of the human genome was unveiled today in the form of three analyses that provide the most detailed comparison yet of how the genomes of the fruit fly, roundworm, and human function.

    The research, appearing August 28 in in the journal Nature, compares how the information encoded in the three species’ genomes is “read out,” and how their DNA and proteins are organized into chromosomes.

    The results add billions of entries to a publicly available archive of functional genomic data. Scientists can use this resource to discover common features that apply to all organisms. These fundamental principles will likely offer insights into how the information in the human genome regulates development, and how it is responsible for diseases.

    mod
    Berkeley Lab scientists contributed to an NHGRI effort that provides the most detailed comparison yet of how the genomes of the fruit fly, roundworm, and human function. (Credit: Darryl Leja, NHGRI)

    The analyses were conducted by two consortia of scientists that include researchers from the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab). Both efforts were funded by the National Institutes of Health’s National Human Genome Research Institute.

    One of the consortiums, the “model organism Encyclopedia of DNA Elements” (modENCODE) project, catalogued the functional genomic elements in the fruit fly and roundworm. Susan Celniker and Gary Karpen of Berkeley Lab’s Life Sciences Division led two fruit fly research groups in this consortium. Ben Brown, also with the Life Sciences Division, participated in another consortium, ENCODE, to identify the functional elements in the human genome.

    The consortia are addressing one of the big questions in biology today: now that the human genome and many other genomes have been sequenced, how does the information encoded in an organism’s genome make an organism what it is? To find out, scientists have for the past several years studied the genomes of model organisms such as the fruit fly and roundworm, which are smaller than our genome, yet have many genes and biological pathways in common with humans. This research has led to a better understanding of human gene function, development, and disease.

    Comparing Transcriptomes

    In all organisms, the information encoded in genomes is transcribed into RNA molecules that are either translated into proteins, or utilized to perform functions in the cell. The collection of RNA molecules expressed in a cell is known as its transcriptome, which can be thought of as the “read out” of the genome.

    In the research announced today, dozens of scientists from several institutions looked for similarities and differences in the transcriptomes of human, roundworm, and fruit fly. They used deep sequencing technology and bioinformatics to generate large amounts of matched RNA-sequencing data for the three species. This involved 575 experiments that produced more than 67 billion sequence reads.

    A team led by Celniker, with help from Brown and scientists from several other labs, conducted the fruit fly portion of this research. They mapped the organism’s transcriptome at 30 time points of its development. They also explored how environmental perturbations such as heavy metals, herbicides, caffeine, alcohol and temperature affect the fly’s transcriptome. The result is the finest time-resolution analysis of the fly genome’s “read out” to date—and a mountain of new data.

    “We went from two billion reads in research we published in 2011, to 20 billion reads today,” says Celniker. “As a result, we found that the transcriptome is much more extensive and complex than previously thought. It has more long non-coding RNAs and more promoters.”

    When the scientists compared transcriptome data from all three species, they discovered 16 gene-expression modules corresponding to processes such as transcription and cell division that are conserved in the three animals. They also found a similar pattern of gene expression at an early stage of embryonic development in all three organisms.

    This work is described in a Nature article entitled “Comparative analysis of the transcriptome across distant species.”

    Comparing chromatin

    Another group, also consisting of dozens of scientists from several institutions, analyzed chromatin, which is the combination of DNA and proteins that organize an organism’s genome into chromosomes. Chromatin influences nearly every aspect of genome function.

    Karpen led the fruit fly portion of this work, with Harvard Medical School’s Peter Park contributing on the bioinformatics side, and scientists from several other labs also participating. The team mapped the distribution of chromatin proteins in the fruit fly genome. They also learned how chemical modifications to chromatin proteins impact genome functions.

    Their results were compared with results from human and roundworm chromatin research. In all, the group generated 800 new chromatin datasets from different cell lines and developmental stages of the three species, bringing the total number of datasets to more than 1400. These datasets are presented in a Nature article entitled “Comparative analysis of metazoan chromatin organization.”

    Here again, the scientists found many conserved chromatin features among the three organisms. They also found significant differences, such as in the composition and locations of repressive chromatin.

    But perhaps the biggest scientific dividend is the data itself.

    “We found many insights that need follow-up,” says Karpen. “And we’ve also greatly increased the amount of data that others can access. These datasets and analyses will provide a rich resource for comparative and species-specific investigations of how genomes, including the human genome, function.”

    See the full article here.

    A U.S. Department of Energy National Laboratory Operated by the University of California

    University of California Seal

    DOE Seal

    ScienceSprings relies on technology from

    MAINGEAR computers

    Lenovo
    Lenovo

    Dell
    Dell

     
  • richardmitnick 8:01 am on August 19, 2014 Permalink | Reply
    Tags: , , Genomics   

    From M.I.T.: “The History Inside Us” 


    MIT News

    August 19, 2014
    Christine Kenneally

    Improvements in DNA analysis are helping us rewrite the past and better grasp what it means to be human.

    book

    Every day our DNA breaks a little. Special enzymes keep our genome intact while we’re alive, but after death, once the oxygen runs out, there is no more repair. Chemical damage accumulates, and decomposition brings its own kind of collapse: membranes dissolve, enzymes leak, and bacteria multiply. How long until DNA disappears altogether? Since the delicate molecule was discovered, most scientists had assumed that the DNA of the dead was rapidly and irretrievably lost. When Svante Pääbo, now the director of the Max Planck Institute for Evolutionary Anthropology in Germany, first considered the question more than three decades ago, he dared to wonder if it might last beyond a few days or weeks. But Pääbo and other scientists have now shown that if only a few of the trillions of cells in a body escape destruction, a genome may survive for tens of thousands of years.

    dna
    An example of the results of automated chain-termination DNA sequencing.

    In his first book, Neanderthal Man: In Search of Lost Genomes, Pääbo logs the genesis of one of the most groundbreaking scientific projects in the history of the human race: sequencing the genome of a Neanderthal, a human-like creature who lived until about 40,000 years ago. Pääbo’s tale is part hero’s journey and part guidebook to shattering scientific paradigms. He began dreaming about the ancients on a childhood trip to Egypt from his native Sweden. When he grew up, he attended medical school and studied molecular biology, but the romance of the past never faded. As a young researcher, he tried to mummify a calf liver in a lab oven and then extract DNA from it. Most of Pääbo’s advisors saw ancient DNA as a “quaint hobby,” but he persisted through years of disappointing results, patiently awaiting technological innovation that would make the work fruitful. All the while, Pääbo became adept at recruiting researchers, luring funding, generating publicity, and finding ancient bones.

    Eventually, his determination paid off: in 1996, he led the effort to sequence part of the Neanderthal mitochondrial genome. (Mitochondria, which serve as cells’ energy packs, appear to be remnants of an ancient single-celled organism, and they have their own DNA, which children inherit from their mothers. This DNA is simpler to read than the full human genome.) Finally, in 2010, Pääbo and his colleagues published the full Neanderthal genome.

    That may have been one of the greatest feats of modern biology, yet it is also part of a much bigger story about the extraordinary utility of DNA. For a long time, we have seen the genome as a tool for predicting the future. Do we have the mutation for Huntington’s? Are we predisposed to diabetes? But it may have even more to tell us about the past: about distant events and about the network of lives, loves, and decisions that connects them.

    Empires

    Long before research on ancient DNA took off, Luigi Cavalli-Sforza made the first attempt to rebuild the history of the world by comparing the distribution of traits in different living populations. He started with blood types; much later, his popular 2001 book Genes, Peoples, and Languages explored demographic history via languages and genes. Big historical arcs can also be inferred from the DNA of living people, such as the fact that all non-Africans descend from a small band of humans that left Africa 60,000 years ago. The current distribution across Eurasia of a certain Y chromosome—which fathers pass to their sons—rather neatly traces the outline of the Mongolian Empire, leading researchers to propose that it comes from Genghis Khan, who pillaged and raped his way across the continent in the 13th century.

    But in the last few years, geneticists have found ways to explore not just big events but also the dynamics of populations through time. A 2014 study used the DNA of ancient farmers and hunter-gatherers from Europe to investigate an old question: Did farming sweep across Europe and become adopted by the resident hunter-gatherers, or did farmers sweep across the continent and replace the hunter-gatherers? The researchers sampled ancient individuals who were identified as either farmers or hunters, depending on how they were buried and what goods were buried with them. A significant difference between the DNA of the two groups was found, suggesting that even though there may have been some flow of hunter-­gatherer DNA into the farmers’ gene pool, for the most part the farmers replaced the hunter-gatherers.

    Looking at more recent history, Peter Ralph and Graham Coop compared small segments of the genome across Europe and found that any two modern Europeans who lived in neighboring populations, such as Belgium and Germany, shared between two and 12 ancestors over the previous 1,500 years. They identified tantalizing variations as well. Most of the common ancestors of Italians seem to have lived around 2,500 years ago, dating to the time of the Roman Republic, which preceded the Roman Empire. Though modern Italians share ancestors within the last 2,500 years, they share far fewer of them than other Europeans share with their own countrymen. In fact, Italians from different regions of Italy today have about the same number of ancestors in common with one another as they have with people from other countries. The genome reflects the fact that until the 19th century Italy was a group of small states, not the larger country we know today.

    In a very short amount of time, the genomes of ancient people have ­facilitated a new kind of population genetics. It reveals phenomena that we have no other way of knowing about.

    Significant events in British history suggest that the genetics of Wales and some remote parts of Scotland should be different from genetics in the rest of Britain, and indeed, a standard population analysis on British people separates these groups out. But this year scientists led by Peter Donnelly at Oxford uncovered a more fine-grained relationship between genetics and history. By tracking subtle patterns across the genomes of modern Britons whose ancestors lived in particular rural areas, they found at least 17 distinct clusters that probably reflect different groups in the historic population of Britain. This work could help explain what happened during the Dark Ages, when no written records were made—for example, how much ancient British DNA was swamped by the invading Saxons of the fifth century.

    The distribution of certain genes in modern populations tells us about cultural events and choices, too: after some groups decided to drink the milk of other mammals, they evolved the ability to tolerate lactose. The descendants of groups that didn’t make this choice don’t tolerate lactose well even today.

    Mysteries

    Analyzing the DNA of the living is much easier than analyzing ancient DNA, which is always vulnerable to contamination. The first analyses of Neanderthal mitochondrial DNA were performed in an isolated lab that was irradiated with UV light each night to destroy DNA carried in on dust. Researchers wore face shields, sterile gloves, and other gear, and if they entered another lab, Pääbo would not allow them back that day. Still, controlling contamination only took Pääbo’s team to the starting line. The real revolution in analysis of ancient DNA came in the late 1990s, with ­second-generation DNA sequencing techniques. Pääbo replaced Sanger sequencing, invented in the 1970s, with a technique called pyrosequencing, which meant that instead of sequencing 96 fragments of ancient DNA at a time, he could sequence hundreds of thousands.

    Such breakthroughs made it possible to answer one of the longest-running questions about Neanderthals: did they mate with humans? There was scant evidence that they had, and Pääbo himself believed such a union was unlikely because he had found no trace of Neanderthal genetics in human mitochondrial DNA. He suspected that humans and Neanderthals were biologically incompatible. But now that the full Neanderthal genome has been sequenced, we can see that 1 to 3 percent of the genome of non-Africans living today contains variations, known as alleles, that apparently originated with Neanderthals. That indicates that humans and Neanderthals mated and had children, and that those children’s children eventually led to many of us. The fact that sub-Saharan Africans do not carry the same Neanderthal DNA suggests that Neanderthal-human hybrids were born just as humans were expanding out of Africa 60,000 years ago and before they colonized the rest of the world. In addition, the way Neanderthal alleles are distributed in the human genome tells us about the forces that shaped lives long ago, perhaps helping the earliest non-Africans adapt to colder, darker regions. Some parts of the genome with a high frequency of Neanderthal variants affect hair and skin color, and the variants probably made the first Eurasians lighter-skinned than their African ancestors.

    Ancient DNA will almost certainly complicate other hypotheses, like the ­African-origin story, with its single migratory human band. Ancient DNA also reveals phenomena that we have no other way of knowing about. When Pääbo and colleagues extracted DNA from a few tiny bones and a couple of teeth found in a cave in the Altai Mountains in Siberia, they discovered an entirely new sister group, the Denisovans. Indigenous Australians, Melanesians, and some groups in Asia may have up to 5 percent Denisovan DNA, in addition to their Neanderthal DNA.

    In a very short amount of time, a number of ancients have been sequenced by teams all over the world, and the growing library of their genomes has facilitated a new kind of population genetics. What is it that DNA won’t be able to tell us about the past? It may all come down to what happened in the first moments or days after someone’s death. If, for some reason, cells dry out quickly—if you die in a desert or a dry cave, if you are frozen or mummified—post-mortem damage to DNA can be halted, but it may never be possible to sequence DNA from remains found in wet, tropical climates. Still, even working with only the scattered remains that we have found so far, we keep gaining insights into ancient history. One of the remaining mysteries, Pääbo observes, is why modern humans, unlike their archaic cousins, spread all over the globe and dramatically reshaped the environment. What made us different? The answer, he believes, lies waiting in the ancient genomes we have already sequenced.

    There is some irony in the fact that Pääbo’s answer will have to wait until we get more skillful at reading our own genome. We are at the very beginning stages of understanding how the human genome works, and it is only once we know ourselves better that we will be able to see what we had in common with Neanderthals and what is truly different.

    See the full article here.

    ScienceSprings relies on technology from

    MAINGEAR computers

    Lenovo
    Lenovo

    Dell
    Dell

     
c
Compose new post
j
Next post/Next comment
k
Previous post/Previous comment
r
Reply
e
Edit
o
Show/Hide comments
t
Go to top
l
Go to login
h
Show/Hide help
shift + esc
Cancel
Follow

Get every new post delivered to your Inbox.

Join 455 other followers

%d bloggers like this: