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  • 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.

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    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.

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    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.

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    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.

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    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.

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  • 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” 

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    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.

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    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.

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    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-
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  • 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

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    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.

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    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
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    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.

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  • 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-

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  • 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

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  • 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.

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  • richardmitnick 6:45 pm on March 24, 2014 Permalink | Reply
    Tags: , , , Genomics   

    From Berkeley Lab: “New Technique for Identifying Gene-Enhancers” 


    Berkeley Lab

    Berkeley Lab-Led Research Team Unveils Powerful New Tool for Studying DNA Elements that Regulate Genes

    March 24, 2014
    Lynn Yarris (510) 486-5375 lcyarris@lbl.gov

    An international team led by researchers with the Lawrence Berkeley National Laboratory (Berkeley Lab) has developed a new technique for identifying gene enhancers – sequences of DNA that act to amplify the expression of a specific gene – in the genomes of humans and other mammals. Called SIF-seq, for site-specific integration fluorescence-activated cell sorting followed by sequencing, this new technique complements existing genomic tools, such as ChIP-seq (chromatin immunoprecipitation followed by sequencing), and offers some additional benefits.

    “While ChIP-seq is very powerful in that it can query an entire genome for characteristics associated with enhancer activity in a single experiment, it can fail to identify some enhancers and identify some sites as being enhancers when they really aren’t,” says Diane Dickel, a geneticist with Berkeley Lab’s Genomics Division and member of the SIF-seq development team. “SIF-seq is currently capable of testing only hundreds to a few thousand sites for enhancer activity in a single experiment, but can determine enhancer activity more accurately than ChIP-seq and is therefore a very good validation assay for assessing ChIP-seq results.”

    Dickel is the lead author of a paper in Nature Methods describing this new technique. The paper is titled Function-based identification of mammalian enhancers using site-specific integration. The corresponding authors are Axel Visel and Len Pennacchio, also geneticists with Berkeley Lab’s Genomics Division. (See below for a complete list of authors.)

    With the increasing awareness of the important role that gene enhancers play in normal cell development as well as in disease, there is strong scientific interest in identifying and characterizing these enhancers. This is a challenging task because an enhancer does not have to be located directly adjacent to the gene whose expression it regulates, but can instead be located hundreds of thousands of DNA base pairs away. The challenge is made even more difficult because the activity of many enhancers is restricted to specific tissues or cell types.

    dd
    Diane Dickel is the lead author of Nature Methods paper describing a new technique for identifying gene enhancers in the genomes of humans and other mammals. (Photo by Roy Kaltschmidt)

    “For example, brain enhancers will not typically work in heart cells, which means that you must test your enhancer sequence in the correct cell type,” Dickel says.

    Currently, enhancers can be identified through chromatin-based assays, such as ChIP-seq, which predict enhancer elements indirectly based on the enhancer’s association with specific epigenomic marks, such as transcription factors or molecular tags on DNA-associated histone proteins. Visel, Pennacchio, Dickel and their colleagues developed SIF-seq in response to the need for a higher-throughput functional enhancer assay that can be used in a wide variety of cell types and developmental contexts.

    “We’ve shown that SIF-seq can be used to identify enhancers active in cardiomyocytes, neural progenitor cells, and embryonic stem cells, and we think that it has the potential to be expanded for use in a much wider variety of cell types,” Dickel says. “This means that many more types of enhancers could potentially be tested in vitro in cell culture.”

    In SIF-seq, hundreds or thousands of DNA fragments to be tested for enhancer activity are coupled to a reporter gene and targeted into a single, reproducible site in embryonic cell genomes. Every embryonic cell will have exactly one potential enhancer-reporter. Fluorescence-activated sorting is then used to identify and retrieve from this mix only those cells that display strong reporter gene expression, which represent the cells with the most active enhancers.

    “Unlike previous enhancer assays for mammals, SIF-seq includes the integration of putative enhancers into a single genomic locus,” says Visel. “Therefore, the activity of enhancers is assessed in a reproducible chromosomal context rather than from a transiently expressed plasmid. Furthermore, by making use of embryonic stem cells and in vitro differentiation, SIF-seq can be used to assess enhancer activity in a wide variety of disease-relevant cell types.”

    two
    Berkeley Lab’s Len Pennacchio (left) and Axel Visel led the development of a new technique for identifying gene enhancers called SIF-seq, for site-specific integration fluorescence-activated cell sorting followed by sequencing. (Photo by Roy Kaltschmidt)

    Adds Pennacchio, “The range of biologically or disease-relevant enhancers that SIF-seq can be used to identify is limited only by currently available stem cell differentiation methods. Although we did not explicitly test the activity of species-specific enhancers, such as those derived from certain classes of repetitive elements, our results strongly suggest that SIF-seq can be used to identify enhancers from other mammalian genomes where desired cell types are difficult or impossible to obtain.”

    The ability of SIF-seq to use reporter assays in mouse embryonic stem cells to identify human embryonic stem cell enhancers that are not present in the mouse genome opens the door to intriguing research possibilities as Dickel explains.

    “Human and chimpanzee genes differ very little, so one hypothesis in evolutionary genomics holds that humans and chimpanzees are so phenotypically different because of differences in the way they regulate gene expression. It is very difficult to carry out enhancer identification through ChIP-seq that would be useful in studying this hypothesis,” she says. “However, because SIF-seq only requires DNA sequence from a mammal and can be used in a variety of cell types, it should be possible to compare the neuronal enhancers present in a large genomic region from human to the neuronal enhancers present in the orthologous chimpanzee region. This could potentially tell us interesting things about the genetic differences that differentiate human brain development from that of other primates.”

    In addition to Dickel, Pennacchio and Visel, other co-authors of the Nature Methods paper were Yiwen Zhu, Alex Nord, John Wylie, Jennifer Akiyama, Veena Afzal, Ingrid Plajzer-Frick, Aileen Kirkpatrick, Berthold Göttgens and Benoit Bruneau.

    This research was primarily supported by the National Institutes of Health.

    See the full article here.

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

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  • richardmitnick 1:58 pm on March 17, 2014 Permalink | Reply
    Tags: , , Genomics,   

    From Berkeley Lab: “Vast Gene-Expression Map Yields Neurological and Environmental Stress Insights” 


    Berkeley Lab

    March 16, 2014
    Dan Krotz 510-486-4019 dakrotz@lbl.gov

    A consortium led by scientists from the U.S. Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) has conducted the largest survey yet of how information encoded in an animal genome is processed in different organs, stages of development, and environmental conditions. Their findings paint a new picture of how genes function in the nervous system and in response to environmental stress.

    They report their research this week in the Advance Online Publication of the journal Nature.

    The scientists studied the fruit fly, an important model organism in genetics research. Seventy percent of known human disease genes have closely related genes in the fly, yet the fly genome is one-thirtieth the size of ours. Previous fruit fly research has provided insights on cancer, birth defects, addictive behavior, and neurological diseases. It has also advanced our understanding of processes common to all animals such as body patterning and synaptic transmission.

    fly
    The remarkable complexity of the fruit fly transcriptome comes to life in this fruit fly embryo. Blue dye indicates the presence of RNA molecules in the brain from a previously uncharacterized gene (CG42748) that encodes hundreds of different proteins. No image credit.

    In the latest scientific fruit from the fruit fly, the consortium, led by Susan Celniker of Berkeley Lab’s Life Sciences Division, generated the most comprehensive map of gene expression in any animal to date. Scientists from the University of California at Berkeley, Indiana University at Bloomington, the University of Connecticut Health Center, and several other institutions contributed to the research.

    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.

    While the genome is essentially the same in every cell in our bodies, the transcriptome is different in each cell type and constantly changing. Cells in cardiac tissue are radically different from those in the gut or the brain, for example.

    The transcriptome also changes rapidly in response to environmental challenges. These dynamics in gene expression allow our bodies to adapt to changes such as temperature or exposure to chemicals.

    graph
    The broad range of genes that respond to environmental stress is evident in this genome-wide map of genes that are up or down-regulated when fruit flies are exposed to the heavy metal cadmium. Labeled genes are those that showed a 20-fold change in response. No image credit.

    To map the transcriptome, the scientists used deep sequencing technology to generate 1.2 trillion bases of RNA sequence data. They analyzed RNA in 29 fruit fly tissue types, 25 cell lines, and “environmental challenge” scenarios including heat, cold, heavy metal poisoning, and acute exposure to pesticides.

    The combination of extremely deep sequencing and a diverse array of tissues and conditions resulted in a full-body map of RNA activity, which revealed new genes and rare RNAs that are expressed in only one tissue type. Among the discoveries are the unexpected complexity and diversity of the RNAs present in tissues of the nervous system, and previously unknown genes implicated in stress response.

    In samples of the fly’s nervous system, the scientists found about 100 genes that can encode hundreds or even thousands of different types of proteins. Many of these proteins are made in the developing embryo during the early formation of the nervous system. This hints at a previously unknown source of the complexity of the brain, given that most genes express five or fewer types of transcripts, and half encode just one protein.

    “Our study indicates that the total information output of an animal transcriptome is heavily weighted by the needs of the developing nervous system,” says Ben Brown, a Berkeley Lab staff scientist in the Life Sciences Division who led the data analysis team.

    The scientists also discovered a much broader response to stress than previously recognized. Exposure to heavy metals like cadmium resulted in the activation of known stress-response pathways that prevent damage to DNA and proteins. It also revealed several new genes of completely unknown function.

    “To better understand how cells fight stress, we have to figure out what these mysterious genes do,” says Celniker.

    The research was funded by the National Human Genome Research Institute modENCODE Project.

    Other institutions involved in this research include the Sloan-Kettering Institute, Japan’s RIKEN Yokohama Institute, Cold Spring Harbor Laboratory, and Harvard Medical School.

    See the full article here.

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

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  • richardmitnick 6:19 pm on February 6, 2014 Permalink | Reply
    Tags: , , , , Genomics, , ,   

    From Berkeley Lab: “New Insight into an Emerging Genome-Editing Tool” 


    Berkeley Lab

    Berkeley Researchers Show Expanded Role for Guide RNA in Cas9 Interactions with DNA

    February 06, 2014
    Lynn Yarris (510) 486-5375 lcyarris@lbl.gov

    The potential is there for bacteria and other microbes to be genetically engineered to perform a cornucopia of valuable goods and services, from the production of safer, more effective medicines and clean, green, sustainable fuels, to the clean-up and restoration of our air, water and land. Cells from eukaryotic organisms can also be modified for research or to fight disease. To achieve these and other worthy goals, the ability to precisely edit the instructions contained within a target’s genome is a must. A powerful new tool for genome editing and gene regulation has emerged in the form of a family of enzymes known as Cas9, which plays a critical role in the bacterial immune system. Cas9 should become an even more valuable tool with the creation of the first detailed picture of its three-dimensional shape by researchers with the Lawrence Berkeley National Laboratory (Berkeley Lab) and the University of California (UC) Berkeley.

    dna
    The crystal structure of SpyCas9 features a nuclease domain lobe (red) and an alpha-helical lobe (gray) each with a nucleic acid binding cleft that becomes functionalized when Cas9 binds to guide RNA.

    binding
    Upon binding with guide RNA, the two structural lobes of Cas9 reorient so that the two nucleic acid binding clefts face each other, forming a central channel that interfaces with target DNA.

    Biochemist Jennifer Doudna and biophysicist Eva Nogales, both of whom hold appointments with Berkeley Lab, UC Berkeley, and the Howard Hughes Medical Institute (HHMI), led an international collaboration that used x-ray crystallography to produce 2.6 and 2.2 angstrom (Å) resolution crystal structure images of two major types of Cas9 enzymes. The collaboration then used single-particle electron microscopy to reveal how Cas9 partners with its guide RNA to interact with target DNA. The results point the way to the rational design of new and improved versions of Cas9 enzymes for basic research and genetic engineering.

    “The combination of x-ray protein crystallography and electron microscopy single-particle analysis showed us something that was not anticipated,” says Nogales. “The Cas9 protein, on its own, exists in an inactive state, but upon binding to the guide RNA, the Cas9 protein undergoes a radical change in its three-dimensional structure that enables it to engage with the target DNA.”

    “Because we now have high-resolution structures of the two major types of Cas9 proteins, we can start to see how this family of bacterial enzymes has evolved,” Doudna says. “We see that the two structures are quite different from each other outside of their catalytic domains, suggesting an interesting structural plasticity that could explain how Cas9 is able to use different kinds of guide RNAs. Also, the differences in the two structures suggest that it may be possible to engineer smaller Cas9 variants and still retain function, an important goal for some genome engineering applications.”

    two
    Eva Nogales (left) and Jennifer Doudna led a study that produced the first detailed look at the 3D structure of the Cas9 enzyme and how it partners with guide RNA. (Photo by Roy Kaltschmidt)

    Doudna and Nogales are the corresponding authors, along with Martin Jinek of the University of Zurich, of a paper in Science that describes this research. The paper is titled Structures of Cas9 endonucleases reveal RNA-mediated conformational activation. Co-authors are Fuguo Jiang, David Taylor, Samuel Sternberg, Emine Kaya, Enbo Ma, Carolin Anders, Michael Hauer, Kaihong Zhou, Steven Lin, Mattias Kaplan, Anthony Iavarone and Emmanuelle Charpentier.

    See the full article here.

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

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