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Scooped by Dr. Stefan Gruenwald!

Genomics for the masses: AstraZeneca launches project to sequence 2 million genomes

Genomics for the masses: AstraZeneca launches project to sequence 2 million genomes | Amazing Science |
Drug company aims to pool genomic and medical data in hunt for rare genetic sequences associated with disease.


One of the world’s largest pharmaceutical companies has launched a massive effort to compile genome sequences and health records from two million people over the next decade. In doing so, AstraZeneca and its collaborators hope to unearth rare genetic sequences that are associated with disease and with responses to treatment.


It’s an unprecedented number of participants for this type of study, says Ruth March, vice-president and head of personalized health care and biomarkers at AstraZeneca, which is headquartered in London. “That’s necessary because we’re going to be looking for very rare differences among individuals.”


To achieve that ambitious goal, AstraZeneca will partner with research institutions including the Wellcome Trust Sanger Institute in Hinxton, UK, and Human Longevity, a biotechnology company founded in San Diego, California, by genomics pioneer Craig Venter. AstraZeneca also expects to draw on data from 500,000 participants in its own clinical trials, and medical samples that it has accrued over the past 15 years.


In doing so, AstraZeneca will be following a burgeoning trend in genetics research. For years, geneticists pursued common variations in human DNA sequences that are linked to complex diseases such as diabetes and heart disease. The approach yielded some important insights, but these common variations often accounted for only a small percentage of the genetic contribution to individual diseases.


Researchers are now increasingly focusing on the contribution of unusual genetic variants to disease. Combinations of these variants can hold the key to an individual's traits, says Venter.


The hunt for important rare variants has led AstraZeneca to partner with the Institute for Molecular Medicine Finland, says Aarno Palotie, who heads the Human Genomics Program there. Finland’s population was geographically isolated until recently, he notes, which makes for a unique genetic make-up. As a result, some variations that are very rare in other populations may be more common in Finland, making them easier to detect and study.

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We're finally cracking the secrets of what makes us sick

We're finally cracking the secrets of what makes us sick | Amazing Science |

For the data in our genome to be useful, we need to process not just the 3 billion base pairs of DNA that make up each person's genome but also the genomes of many people. The Precision Medicine Initiative is starting with the genomes of at least one million people. That's a mind-boggling amount of data already, and we'll eventually end up needing even more: "many millions" of genomes, saysDr. Eric Schadt, founding director of the Icahn Institute for Genomics and Multiscale Biology at Mount Sinai.

We're still figuring out how to decode it all.


At Mount Sinai, scientists are trying to "collect as much information on as many patients as we can, integrate it, build predictive models from it, and then derive from those models more refined diagnoses, risk assessments, and plans for treatment than has been possible before," Schadt told Nature Biotechnology in 2012.


The team at Icahn is collecting genetic information from patients and trying to incorporate that data with everything from their clinical history to the bacteria on and around them in order to develop predictive models that will calculate how a disease will affect a person.


"The technology advances [that make that possible] have been astounding," says Schadt. "The ability to generate sequencing data has moved at a super-Moore's law rate," faster than even computing technology, he says. The supercomputers we have now can process genetic information in ways that would have been "just impossible 10 years ago." Scientists all over the country are pushing for new ways to understand genomic data.


Deep Genomics, a startup run by Brendan Frey, is leveraging artificial intelligence to help decode the meaning of the genome.

Specifically, the company is using deep learning: the process by which a computer takes in data and then, based on its extensive knowledge drawn from analyzing other data, interprets that information.

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HPV Genomes Show Greater Diversity Than Expected Among Cervical Cancer Patients

HPV Genomes Show Greater Diversity Than Expected Among Cervical Cancer Patients | Amazing Science |
Human papillomaviruses are associated with invasive cervical cancer as well as more benign disorders such as skin warts. Although more than 180 HPV genomes have been sequenced, there has been little research on the diversity of HPV genomes within the same patient, primarily because the virus is thought to have a low mutation rate.

Of the 13 HPV genotypes thought to be carcinogenic, HPV16 is responsible for about half of all invasive cervical cancer cases worldwide. In the study, the researchers sequenced HPV16 genomes from 10 patients with cervical cancer and one with non-malignant genital warts.

To date, most genomic studies of papillomaviruses have used Sanger sequencing to look at the "most prevalent, consensus sequence" during chronic infection, but Sanger sequencing may "not be appropriate to capture the dynamics of slowly evolving viruses, such as PVs," the authors wrote.

So, they decided to turn to next-generation sequencing. The authors extracted DNA from 10 clinical samples of invasive cervical cancer and one case of genital warts caused by HPV16. They used long PCR to generate 8-kb long amplicons — the size of the HPV genome — and sequenced them using Thermo Fisher's Ion Torrent PGM.

The authors generated both a consensus genome and also de novo assembled each sample using CLC software.

Comparing the clinical samples to the reference sequence, the researchers observed 190 changes, with the E2 gene containing the largest number of changes. Two samples had duplication events in the L1 gene and L2 gene, respectively.

The team also performed a phylogenetic analysis using consensus sequences from the PGM data as well as 20 HPV16 genomes from GenBank. From the eleven clinical samples, the researchers identified three types of HPV: HPV16_A1, HPV16_A2, and HPV16_D. In addition, these types correlated with specific tumor types, with squamous cell carcinomas associated with the A type and adenocarcinomas associated with the D types.

To analyze intra-host variation, the researchers performed de novo assembly. They were able to generate one contiguous sequence for four samples, with the remaining seven samples in three to eight contigs.

The researchers identified between three and 125 polymorphic sites per genome. In the most diverse sample, 31 of the 125 polymorphic sites represented more than 10 percent of the reads in that position. In the least diverse sample, only one polymorphic site represented more than 5 percent of the reads at that position.

Next, the team calculated a "diversity index" for each sample, defined as the "probability of a randomly chosen genome to be identical to the consensus genome." The median value for the samples was just 40 percent.

The authors suggest a number of factors could contribute to the diversity observed, including both innate and adaptive immune responses. For instance, the APOBEC3G family of proteins have been shown to target papillomavirus DNA, " which may partially account for the broad diversity of human PVs." In addition, "polymorphisms observed in the E6 gene could be a result of an immune selective pressure," the authors wrote.

In the future, more research will need to be done on HPV infection to monitor viral diversity in asymptomatic, productive, benign, premalignant and malignant infections. "The possible role of oncovirus intralesion diversity generated during chronic infections should be explored as a differential factor for increased oncogenic potential," they wrote.
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Scientists uncover the key role of a single gene on how groups of animals diverge

Scientists uncover the key role of a single gene on how groups of animals diverge | Amazing Science |

A study by researchers at the Wellcome Trust Centre for Human Genetics at Oxford University has uncovered the key role played by a single gene in how groups of animals diverge to form new species. The study, published today in the journal Nature, restored fertility to the normally-infertile offspring of two subspecies of mice, by replacing part of the Prdm9 gene with the equivalent human version. Despite the nearly 150 million years of evolution separating mice and humans, these 'humanized' mice were completely fertile.

New animal species form when groups of animals become isolated and as a result, begin to separate through evolution (a process known as speciation). When these isolated populations meet later, they might be able to breed with each other, but the male offspring are often infertile. Horses and donkeys are an example of such speciation: they can interbreed, but their offspring, mules, are infertile.

'Our work studied similar infertility in hybrid house mice, whose two parents come from different subspecies found in Western and Eastern Europe', says Dr Ben Davies from the Nuffield Department of Medicine, the first author on the study. These two sub-species are therefore on the verge of splitting into two entirely different species, since like mules, their offspring are infertile.

Dr Davies and his colleagues studied the Prdm9  gene: this gene is already known to have a role in infertility in mice from different species, and  is in fact the only known speciation gene in mammals. However, how speciation might link up to infertility was unknown.

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NIST simulates fast, accurate DNA sequencing through graphene nanopore

NIST simulates fast, accurate DNA sequencing through graphene nanopore | Amazing Science |

Researchers at the National Institute of Standards and Technology (NIST) have simulated a new concept for rapid, accurate gene sequencing by pulling a DNA molecule through a tiny chemically activated hole in graphene—an ultrathin sheet of carbon atoms—and detecting changes in electrical current.

The NIST simulation study suggests the method could identify about 66 million bases per second with 90 percent accuracy and no false positives. If demonstrated experimentally, the NIST method might ultimately be faster and cheaper than conventional DNA sequencing, meeting a critical need for applications such as forensics.

Conventional sequencing, developed in the 1970s, involves separating, copying, labeling and reassembling pieces of DNA to read the genetic information. The new NIST proposal is a twist on the more recent “nanopore sequencing” idea of pulling DNA through a hole in specific materials, originally a protein (see “First full genome of a living organism sequenced and assembled using smartphone-size device“).

This concept—pioneered 20 years ago at NIST—is based on the passage of electrically charged particles (ions) through the pore. The idea remains popular but poses challenges such as unwanted electrical noise, or interference, and inadequate selectivity.

By contrast, NIST’s new proposal is to create temporary chemical bonds and rely on graphene’s capability to convert the mechanical strains (rather than charged particles) from breaking those bonds into measurable blips in electrical current.

“This is essentially a tiny strain sensor,” says NIST theorist Alex Smolyanitsky, who came up with the idea and led the project. “We did not invent a complete technology. We outlined a new physical principle that can potentially be far superior to anything else out there.”

Graphene is popular in nanopore-sequencing proposals due to its electrical properties and miniaturized thin-film structure. In the new NIST method, a graphene nanoribbon (4.5 by 15.5 nanometers) has several copies of a base attached to the nanopore (2.5 nm wide). DNA’s genetic code is built from four kinds of bases, which bond in pairs as cytosine–guanine and thymine–adenine.

In simulations of how the sensor would perform at room temperature in water, cytosine is attached to the nanopore to detect guanine. A single-strand (unzipped) DNA molecule is pulled through the pore. When guanine passes by, hydrogen bonds form with the cytosine. As the DNA continues moving, the graphene is yanked and then slips back into position as the bonds break.

The NIST study focused on how this strain affects graphene’s electronic properties and found that temporary changes in electrical current indeed indicate that a target base has just passed by. To detect all four bases, four graphene ribbons, each with a different base inserted in the pore, could be stacked vertically to create an integrated DNA sensor.

The researchers combined simulated data with theory to estimate levels of measurable signal variations. Signal strength was in the milliampere range, stronger than in the earlier ion-current nanopore methods.

Based on the performance of 90 percent accuracy without any false positives (i.e., errors were due to missed bases rather than wrong ones), the researchers suggest that four independent measurements of the same DNA strand would produce 99.99 percent accuracy, as required for sequencing the human genome.

The study authors concluded that the proposed method shows “significant promise for realistic DNA sensing devices” without the need for advanced data processing, microscopes, or highly restricted operating conditions. Other than attaching bases to the nanopore, all sensor components have been demonstrated experimentally by other research groups. Theoretical analysis suggests that basic electronic filtering methods could isolate the useful electrical signals. The proposed method could also be used with other strain-sensitive membranes, such as molybdenum disulfide.

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The Next Next Thing in NGS Sequencing

The Next Next Thing in NGS Sequencing | Amazing Science |

Though it may seem to be navigating by perceptibly unfixed stars, next-generation sequencing (NGS) is journeying ever more adventurously into the obscure, the rare, and the confoundingly heterogeneous domains within life’s molecular codescapes. 

NGS is already capable of producing billions of short reads, and it can do so quickly and economically. And NGS is reaching well beyond genomics. For example, it is revolutionizing transcriptomics through advances in RNA sequencing (RNA-Seq). Yet, despite this dazzling progress, a number of significant challenges remain.

These challenges were discussed at a recent Oxford Global event, the “Seventh Annual Next Generation Sequencing Congress”. The event provided a window through which attendees could browse the NGS field’s most daunting obstacles. It also displayed technologies that could allow these obstacles to be circumvented.

New capabilities and applications include the removal of toxic, unwanted transcripts from RNA-Seq libraries as well as the mapping of under-explored alternative splicing spaces. NGS is also making progress toward sequencing mitochondrial DNA. Mitochondria are increasingly recognized in disease development, yet sequencing the DNA from these organelles is complicated because mitochondria harbor considerable genetic complexity and heterogeneity.

Another area bedeviled by heterogeneity is tumor analysis. Fortunately, it appears that heterogeneous tumor samples could be subjected to sorting procedures that could isolate pure populations of cells. These populations would be more amenable to sequencing.

Finally, NGS is enhancing its single-molecule capabilities. One emerging approach involves coupling nanopore technology and mass spectrometry (MS).

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Humans may harbor more than 100 genes from other organisms

Humans may harbor more than 100 genes from other organisms | Amazing Science |

You’re not completely human, at least when it comes to the genetic material inside your cells. You—and everyone else—may harbor as many as 145 genes that have jumped from bacteria, other single-celled organisms, and viruses and made themselves at home in the human genome. That’s the conclusion of a new study, which provides some of the broadest evidence yet that, throughout evolutionary history, genes from other branches of life have become part of animal cells.

“This means that the tree of life isn’t the stereotypical tree with perfectly branching lineages,” says biologist Alastair Crisp of the University of Cambridge in the United Kingdom, an author of the new paper. “In reality, it’s more like one of those Amazonian strangler figs where the roots are all tangled and crossing back across each other.”

Scientists knew that horizontal gene transfer—the movement of genetic information between organisms other than parent-to-offspring inheritance—is commonplace in bacteria and simple eukaryotes. The process lets the organisms quickly share an antibiotic-resistance set of genes to adapt to an antibiotic, for instance. But whether genes have been horizontally transferred into higher organisms—like primates—has been disputed. Like in bacteria, it’s been proposed that animal cells could integrate foreign genetic material that’s introduced as small fragments of DNA or carried into cells by viruses. But proving that a bit of DNA in the human genome originally came from another organism is tricky.

Crisp and his colleagues analyzed the genome sequences of 40 different animal species, ranging from fruit flies and roundworms to zebrafish, gorillas, and humans. For each gene in the genomes, the scientists searched existing databases to find close matches—both among other animals and among nonanimals, including plants, fungi, bacteria, and viruses. When an animal’s gene more closely matched a gene from a nonanimal than any other animals, the researchers took a closer look, using computational methods to determine whether the initial database search had missed something.

In all, the researchers pinpointed hundreds of genes that appeared to have been transferred from bacteria, archaea, fungi, other microorganisms, and plants to animals, they report online today in Genome Biology. In the case of humans, they found 145 genes that seemed to have jumped from simpler organisms, including 17 that had been reported in the past as possible horizontal gene transfers.

“I think what this shows it that horizontal gene transfer is not just confined to microorganisms but has played a role in the evolution of many animals,” Crisp says, “perhaps even all animals.

The paper doesn’t give any hints as to how the genes—which now play established roles in metabolism, immune responses, and basic biochemistry—may have been transferred or the exact timeline of the jumps, he says. That will take more work.

Samuel Viana's curator insight, December 11, 2015 6:11 AM

Cientistas encontraram no nosso próprio genoma  genes que aparentam provir de origens completamente díspares: desde vírus ou fungos.


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Bacteria from the sea join the fight against cancer and infections

Bacteria from the sea join the fight against cancer and infections | Amazing Science |

For decades, bacteria have served society by producing antibiotics – the chemical compounds that can cure infectious diseases. However, it is possible that many natural microorganisms carry the recipes for the medicines of the future hidden in their genetic material, without this part of their genetic code being activated or “switched on”.

But now, biotechnologists from SINTEF and NTNU are developing technology that will make it easier to find – and exploit – these hidden and unutilized medicine factories in bacteria that exist in the natural environment. The hunt will concentrate on marine bacteria, and is one of the projects run by the new Norwegian Centre for Digital Life.

“Our aim is to identify novel compounds that are capable, for example, of killing cancer cells or antibiotic-resistant bacteria. The technology that we are developing will reduce the time taken to search for these and to make the production process more efficient,” says Alexander Wentzel, a senior scientist at SINTEF.

As a strategy, scientists will clip out genetic material from a large number of microorganisms before they transfer their DNA to cultivable bacteria; organisms whose characteristics have already been studied and will be optimized by the researchers in the INBioPharm project. The alterations will enable these organisms to switch on production of new substances that cannot be produced in the microorganism from which the DNA has been extracted.

With the aid of systems biology and synthetic biology (see fact-box), the project will develop the microorganisms in a way which, when they are cultivated, will produce small test quantities of all the possible products, and later, enable mass-production of the most promising substances.

Via Mariaschnee
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Genetics: Big hopes for big data

Genetics: Big hopes for big data | Amazing Science |

Technology is allowing researchers to generate vast amounts of information about tumors. The next step is to use this genomic data to transform patient care.

Adrian Lee has dedicated his career to studying breast cancer, which is to say he is actually tackling many different diseases at once. “No two breast cancers are the same,” says Lee, a pharmacologist and chemical biologist at the University of Pittsburgh in Pennsylvania. “Cancer is way more complex than we know.”

Lee is using genomic technology to fully describe cancers of the breast and apply that knowledge to guide treatment decisions for individual patients. “We can now analyse multiple variables from a single specimen, such as changes in DNA, changes in RNA and changes in methylation,” he says. “Genome-wide scans allow for better systems biology and allow us to learn what's gone wrong in a particular tumor.”

Sequencing tumors is faster, cheaper and easier than ever. With many researchers collecting sequence data and uploading these to public databases such as the The Cancer Genome Atlas (TCGA), opportunities to describe the many different cancers that arise in breast tissue are upon us. “The challenge used to be generating the data,” says Nicholas Navin, a geneticist at The University of Texas MD Anderson Cancer Center in Houston. “Those issues have been resolved. Now the challenge is data processing and data analysing — interpreting the mutations and communicating those to oncologists.”

At the University of Pittsburgh, researchers are working to link the molecular signatures of people with breast cancer to a host of clinical data, including demographic information associated with risk such as age, ethnicity and body weight. They are mining electronic health records for clinical correlates, treatment interactions and outcomes. “We've got a big haystack and we're trying to find the needle,” says Lee. “But we're also trying to incriminate the needle, by linking it to lots of things.” Collecting all that data from patients' electronic records adds up, Lee says. It takes infrastructure — Pittsburgh has already accumulated 5 petabytes, or 5 million gigabytes, which is enough data to overload around 40,000 new iPhone 6 devices.

Making the connection between the reams of data coming out of sequencing laboratories and the individual women fighting breast cancer takes big-time computing power. Big data needs researchers who are comfortable with statistical noise and those who are old hands at the iterative process required to create flexible computer programs.

Big-data researchers take a large data set and look for patterns. The idea is to identify mutations that can be targeted with drug treatment. It is the essence of personalized medicine: screen a patient's tumour for a set of biomarkers to choose the best treatment to fight the cancer. Big-data researchers believe that analysing the data of the thousands of tumours that have come before will reveal patterns that can improve screening and diagnosis, and inform treatment.

Lee and his colleagues have illustrated how big-data science led to a rethink of breast cancer1. They used two public databases — TCGA and METABRIC (Molecular Taxonomy of Breast Cancer International Consortium), which contain data on the entire set of genes, RNA transcripts and proteins of thousands of breast-cancer tumours — to parse out potential differences in the molecular signatures of breast tumours in younger compared with older women. Women who are diagnosed before the age of 40 tend to have worse disease: they are more likely to have later-stage cancers, poorer prognoses and worse survival outcomes than older women.

Via Integrated DNA Technologies
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Genome sequencing shows that myxozoan parasite is actually a 'micro' jellyfish

Genome sequencing shows that myxozoan parasite is actually a 'micro' jellyfish | Amazing Science |
It's a shocking discovery that may redefine how scientists interpret what it means to be an animal.

This week in the Proceedings of the National Academy of Sciences (PNAS), researchers at the University of Kansas reveal how a jellyfish—those commonplace sea pests with stinging tentacles—has evolved over time into a "really weird" microscopic organism, made of only a few cells, that lives inside other animals.

Genome sequencing confirms that myxozoans, a diverse group of microscopic parasites that infect invertebrate and vertebrate hosts, are actually are "highly reduced" cnidarians—the phylum that includes jellyfish, corals and sea anemones.

"This is a remarkable case of extreme degeneration of an animal body plan," said Paulyn Cartwright, associate professor of ecology and evolutionary biology at KU and principal investigator on the research project. "First, we confirmed they're cnidarians. Now we need to investigate how they got to be that way."

Not only has the parasitic micro jellyfish evolved a stripped-down body plan of just a few cells, but via data generated at the KU Medical Center's Genome Sequencing Facility researchers also found the myxozoan genome was drastically simplified.

"These were 20 to 40 times smaller than average jellyfish genomes," Cartwright said. "It's one of the smallest animal genomes ever reported. It only has about 20 million base pairs, whereas the average Cnidarian has over 300 million. These are tiny little genomes by comparison."

Despite its radical reduction of the modern jellyfish's body structure and genome over millions of years, Myxozoa has retained the essential characteristic of the jellyfish—its stinger, or "nematocyst"—along with the genes needed to make it. "Because they're so weird, it's difficult to imagine they were jellyfish," she said. "They don't have a mouth or a gut. They have just a few cells. But then they have this complex structure that looks just like stinging cell of cnidarian. Jellyfish tentacles are loaded with them—little firing weapons."

The findings are the stuff of scientific fascination but also could have a commercial effect. Myxozoa commonly plague commercial fish stock such as trout and salmon. "They're a very diverse group of parasites, and some have been well-studied because they infect fish and can wreak havoc in aquaculture of economic importance," Cartwright said. "They cause whirling disease in salmon. The fish start swimming in circles—it's a neurological problem caused by a myxozoan."

Cartwright said the confirmation that myxozoans are cnidarians would necessitate the re-classification of Myxozoa into the phylum Cnidaria. Moreover, these micro jellyfish could expand understanding of what makes up an animal. "Their biology was well-known, but not their evolutionary origins," she said. "They're microscopic, only a few cells measuring 10 to 20 microns. Some people originally thought they were single-celled organisms. But when their DNA was sequenced, researchers started to surmise they were animals—just really weird ones."

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Next-generation genetic sequencing found right diagnosis for Australian 'Mystery Boy'

Next-generation genetic sequencing found right diagnosis for Australian 'Mystery Boy' | Amazing Science |
Mystery Boy Brandon Keesing was incorrectly diagnosed with a degenerative muscular disease until revolutionary genetic sequencing gave him life-changing news.

Originally thought that Keesing has a mitochondrial disease, doctors had been wrong all along. Revolutionary advances in genetic sequencing proved he did not have mitochondrial disease at all. "In recent years the capacity to read the genetic code of every single gene — all 20,000 of them in the human body — has reached a point where it is now efficient, accurate, cost-effective to be able to do this," he says.

The new technique is called "next generation sequencing" — and where previously it took weeks or months to analyse the code of a single gene, today laboratory computers can decode all 20,000 genes in one go.

Almost immediately Westmead Children's Hospital researchers could pinpoint which one of Brandon's genes had a mutation. Professor Christodoulou illustrates how the technique works on a chart. "So here in the unaffected individual we have an 'A'. Here in the affected individual we have a 'G'. And that's precisely where the mistake is," he says.

Doctors using next generation sequencing discovered in fact that Brandon had congenital myasthenia — a different genetic disease which also affects the muscles. But although incurable, it is not usually fatal and can be treated with medication.

"The name of the gene that we found the mistakes in is called COLQ, and it has a completely different role," Professor Christodoulou says. "It has nothing to do with mitochondrial energy production. "What it is involved in is co-ordinating the communication of nerve cells with the muscle, so that the muscle, when it receives an impulse from a nerve cell, it contracts and relaxes appropriately.

"So the problem with the COLQ mistakes is that this process couldn't be co-ordinated properly. And that's what actually led to his progressive problems."

Finding that one gene in 20,000 has transformed Brandon's life. A simple drug quickly restored some of his muscle strength. As quickly as he had deteriorated as a toddler, he suddenly began making huge strides.

"We noticed it straight away. By the end of that week he got up off that bed and he walked," she says, wiping away tears. "That was unreal. I'll never forget that day. I was so happy for him and ... I just knew from that he was going to grow, he was going to enjoy his life that much more than what he had before. And he has."

Professor Christodoulou says it was a very gratifying outcome for doctors.

Samuel Viana's curator insight, October 30, 2015 7:38 AM

Quem diria, com a redução de preço das novas tecnologias de sequenciação foi possível diagnosticar correctamente a doença desta rapaz ?

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Genome Sequencing Is Becoming Less Ambiguous and More Clinically Relevant

Genome Sequencing Is Becoming Less Ambiguous and More Clinically Relevant | Amazing Science |

When people talk about the $1,000 genome, they are not speaking about the whole genome, but the exons, the so-called coding regions of the genome. “Six years ago, I was spending $15,000 per exome sequence,” says Gholson Lyon, M.D., Ph.D., a genomic scientist working for the Cold Spring Harbor Laboratory. “Now that costs about $700.”

Whole genome sequencing is more expensive. “We are still not at the $1,000 genome in my opinion,” Dr. Lyon continues. “Almost everyone I’ve talked to is charging $1,500–2,000, and we pay $3,000 because that gets us 60× coverage of the genome, which we have shown is very important to recover small insertions and deletions in the genome ranging in size from 5 to 50 base pairs.”

Dr. Lyon, who studies rare but heritable medical diseases such as Ogden syndrome and TAF1 syndrome, believes that advances in next-generation sequencing technology—better software algorithms, improved methodologies, and lower costs—accelerate his work and the work of others conducting clinical research.

The standard advocated by Illumina, the industry giant, and other sequencing companies is a 30× genome, which means sequencing the genome enough to generate on average 30 reads aligned at each base pair. But according to Dr. Lyon, the 30× genome does not capture all the insertions and deletions.

Illumina technology works by providing high-throughput short-read sequencing. This approach is optimized for detecting single-nucleotide polymorphisms commonly referred to as single nucleotide polymorphisms.

“Illumina has focused on the throughput,” says Jonas Korlach, Ph.D., CSO of PacBio. He contends that this focus “came at a price of having short read lengths, bias with respect to GC content, and sequence complexity that no longer allows you to sequence all of the DNA that is part of your genome.” Therefore, Dr. Korlach continues, “we wanted to build something that gives you the best performance in all four areas that are relevant to the performance of sequencing.”

Pacific Biosciences’ SMRT DNA sequencing is performed on SMRT Cells, nanofabricated consumable substrates that come in an “8Pac” format. Each SMRT Cell is patterned with 150,000 zero-mode waveguide (ZMW) light-detection volumes. Single polymerases are immobilized in the ZMWs, which are open at the top to diffusing phospholinked nucleotides, and exposed at the bottom to excitation illumination. The nucleotides held by the polymerase prior to incorporation emit an extended signal that identifies the base being incorporated, and so the ZMWs provide the windows to observe DNA sequencing in real-time.

Optimizing clinical diagnostics is important for the widespread adoption of next-generation sequencing. Organizations such as the Genome in a Bottle Consortium are focused on providing resources to clinical laboratory clients to reduce ambiguity in sequence analysis.

“A clinical laboratory will often need to establish the accuracy of their sequencing and analysis methods,” says Justin Zook, Ph.D., a founding member of the Genome in a Bottle Consortium and a researcher at the National Institute of Standards and Technology (NIST).
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Genomic Data Growing Much Faster Than Twitter and YouTube

Genomic Data Growing Much Faster Than Twitter and YouTube | Amazing Science |

In the age of Big Data, it turns out that the largest, fastest growing data source lies within your cells. Quantitative biologists at the University of Illinois Urbana-Champaign and Cold Spring Harbor Laboratory, in New York, found that genomics reigns as champion over three of the biggest data domains around: astronomy, Twitter, and YouTube.

The scientists determined which would expand the fastest by evaluating acquisition, storage, distribution, and analysis of each set of data. Genomes are quantified by their chemical constructs, or base pairs. Genomics trumps other data generators because the genome sequencing rate doubles every seven months. If it maintains this rate, by 2020 more than one billion billion bases will be sequenced and stored per year, or 1 exabase. By 2025, researchers estimate the rate will be almost one zettabase, one trillion billion bases, per sequence per year.

90 percent of the genome data analyzed in the study was human. The scientists estimate that 100 million to 2 billion human genomes will be sequenced by 2025. That’s a four to five order of magnitude of growth in ten years, which far exceeds the other three data generators they studied.

“For human genomics, which is the biggest driver of the whole field, the hope is that by sequencing many, many individuals, that knowledge will be obtained to help predict and cure a variety of diseases,” says University of Illinois Urbana-Champaign co-author, Gene Robinson. Before it can be useful for medicine, genomes must be coupled with other genomic data sets, including tissue information.

One reason the rate is doubling so quickly is because scientists have begun sequencing individual cells. Single-cell genome sequencing technology for cancer research can reveal mutated sequences and aid in diagnosis. Patients may have multiple single cells sequenced, and there could end up being more than 7 billion genomes sequenced. That “is more than the population of the Earth,” says Michael Schatz, associate professor at Cold Spring Harbor Laboratory, in New York. “What does it mean to have more genomes than people on the planet?”

What it means is a mountain of information must be collected, filed, and analyzed. “Other disciplines have been really successful at these scales, like YouTube,” says Schatz. Today, YouTube users upload 300 hours of video every minute, and the researchers expect that rate to grow up to 1,700 hours per minute, or 2 exabytes of video data per year, by 2025. Google set up a seamless data-flowing infrastructure for YouTube. They provided really fast Internet, huge hard drive space, algorithms that optimized results, and a team of experienced researchers.

“We need that investment in genomics in order to understand your diseases, what kinds of treatments to apply, or answer questions about ancestry,” Schatz says. “By sequencing hundreds of millions of people, we can look through the pattern. We can get a sense of global community, and how incredibly connected we really are.”

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Meraculous: Full Genome Alignment With Supercomputers in Mere Minutes

Meraculous: Full Genome Alignment With Supercomputers in Mere Minutes | Amazing Science |
A team of scientists from Berkeley Lab, JGI and UC Berkeley, simplified and sped up genome assembly, reducing a months-long process to mere minutes. This was primarily achieved by “parallelizing” the code to harness the processing power of supercomputers, such as NERSC’s Edison system.


Genomes are like the biological owner’s manual for all living things. Cells read DNA instantaneously, getting instructions necessary for an organism to grow, function and reproduce. But for humans, deciphering this “book of life” is significantly more difficult.


Nowadays, researchers typically rely on next-generation sequencers to translate the unique sequences of DNA bases (there are only four) into letters: A, G, C and T. While DNA strands can be billions of bases long, these machines produce very short reads, about 50 to 300 characters at a time. To extract meaning from these letters, scientists need to reconstruct portions of the genome—a process akin to rebuilding the sentences and paragraphs of a book from snippets of text.

But this process can quickly become complicated and time-consuming, especially because some genomes are enormous. For example, while the human genome contains about 3 billion bases, the wheat genome contains nearly 17 billion bases and the pine genome contains about 23 billion bases. Sometimes the sequencers will also introduce errors into the dataset, which need to be filtered out. And most of the time, the genomes need to be assembled de novo, or from scratch. Think of it like putting together a ten billion-piece jigsaw puzzle without a complete picture to reference.


By applying some novel algorithms, computational techniques and the innovative programming language Unified Parallel C (UPC) to the cutting-edge de novo genome assembly tool Meraculous, a team of scientists from the Lawrence Berkeley National Laboratory (Berkeley Lab)’s Computational Research Division (CRD), Joint Genome Institute (JGI) and UC Berkeley, simplified and sped up genome assembly, reducing a months-long process to mere minutes. This was primarily achieved by “parallelizing” the code to harness the processing power of supercomputers, such as the National Energy Research Scientific Computing Center’s (NERSC’s) Edison system. Put simply, parallelizing code means splitting up tasks once executed one-by-one and modifying or rewriting the code to run on the many nodes (processor clusters) of a supercomputer all at once.


“Using the parallelized version of Meraculous, we can now assemble the entire human genome in about eight minutes using 15,360 computer processor cores. With this tool, we estimate that the output from the world’s biomedical sequencing capacity could be assembled using just a portion of NERSC’s Edison supercomputer,” says Evangelos Georganas, a UC Berkeley graduate student who led the effort to parallelize Meraculous. He is also the lead author of a paper published and presented at the SC Conference in November 2014.  


“This work has dramatically improved the speed of genome assembly,” says Leonid Oliker computer scientist in CRD. “The new parallel algorithms enable assembly calculations to be performed rapidly, with near linear scaling over thousands of cores. Now genomics researchers can assemble large genomes like wheat and pine in minutes instead of months using several hundred nodes on NERSC’s Edison.”

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A global network of millions of genomes could be medicine’s next great advance

A global network of millions of genomes could be medicine’s next great advance | Amazing Science |

Noah is a six-year-old child suffering from a disease without a name. This year, his physicians will begin sending his genetic information across the Internet to see if there’s anyone, anywhere, in the world like him. A match could make a difference. Noah is developmentally delayed, uses a walker, speaks only a few words. And he’s getting sicker. MRIs show that his cerebellum is shrinking. His DNA was analyzed by medical geneticists at the Children’s Hospital of Eastern Ontario. Somewhere in the billions of DNA letters is a misspelling, and maybe the clue to a treatment. But unless they find a second child with the same symptoms, and a similar DNA error, his doctors can’t zero in on which mistake in Noah’s genes is the crucial one.


Programmers in Toronto recently began testing a system for trading genetic information with other hospitals. These facilities, in locations including Miami, Baltimore, and Cambridge, U.K., also treat children with so-called ­Mendelian disorders, which are caused by a rare mutation in a single gene. The system, called MatchMaker Exchange, represents something new: a way to automate the comparison of DNA from sick people around the world. One of the people behind this project is David Haussler, a bioinformatics expert based at the University of California, Santa Cruz. The problem Haussler is grappling with now is that genome sequencing is largely detached from our greatest tool for sharing information: the Internet. That’s unfortunate because more than 200,000 people have already had their genomes sequenced, a number certain to rise into the millions in years ahead. The next era of medicine depends on large-scale comparisons of these genomes, a task for which he thinks scientists are poorly prepared. “I can use my credit card anywhere in the world, but biomedical data just isn’t on the Internet,” he says. “It’s all incomplete and locked down.” Genomes often get moved around in hard drives and delivered by FedEx trucks.


Haussler is a founder and one of the technical leaders of the Global Alliance for Genomics and Health, a nonprofit organization formed in 2013 that compares itself to the W3C, the standards organization devoted to making sure the Web functions correctly. Also known by its unwieldy acronym, GA4GH, it’s gained a large membership, including major technology companies like Google. Its products so far include protocols, application programming interfaces (APIs), and improved file formats for moving DNA around the Web. But the real problems it is solving are mostly not technical. Instead, they are sociological: scientists are reluctant to share genetic data, and because of privacy rules, it’s considered legally risky to put people’s genomes on the Internet.


But pressure is building to use technology to study many, many genomes at once and begin to compare that genetic information with medical records. That is because scientists think they’ll need to sort through a million genomes or more to solve cases—like Noah’s—that could involve a single rogue DNA letter, or to make discoveries about the genetics of common diseases that involve a complex combination of genes. No single academic center currently has access to information that extensive, or the financial means to assemble it.


Haussler and others at the alliance are betting that part of the solution is a peer-to-peer computer network that can unite widely dispersed data. Their standards, for instance, would permit a researcher to send queries to other hospitals, which could choose what level of information they were willing to share and with whom. This control could ease privacy concerns. Adding a new level of complexity, the APIs could also call on databases to perform calculations—say, to reanalyze the genomes they store—and return answers.


The largest labs can now sequence human genomes to a high polish at the pace of two per hour. The first genome took about 13 years just 2 decades ago. Back-of-the-envelope calculations suggest that fast machines for DNA sequencing will be capable of producing 85 petabytes of data this year worldwide, twice that much in 2019, and so on. For comparison, all the master copies of movies held by Netflix take up 2.6 petabytes of storage.


“This is a technical question,” says Adam Berrey, CEO of Curoverse, a Boston startup that is using the alliance’s standards in developing open-source software for hospitals. “You have what will be exabytes of data around the world that nobody wants to move. So how do you query it all together, at once? The answer is instead of moving the data around, you move the questions around. No industry does that. It’s an insanely hard problem, but it has the potential to be transformative to human life.”


Last summer Haussler’s alliance launched a basic search engine for DNA, which it calls Beacon. Currently, Beacon searches through about 20 databases of human genomes that were previously made public and have implemented the alliance’s protocols. Beacon offers only yes-or-no answers to a single type of question. You can ask, for instance, “Do any of your genomes have a T at position 1,520,301 on chromosome 1?” “It’s really just the most basic question there is: have you ever seen this variant?” says Haussler. “Because if you did see something new, you might want to know, is this the first patient in the world that has this?” Beacon is already able to access the DNA of thousands of people, including hundreds of genomes put online by Google.

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Web resource: 1000 Fungal Genomes Project (2016)

Web resource: 1000 Fungal Genomes Project (2016) | Amazing Science |

Sequencing unsampled fungal diversity.  Efforts to sequence 1000+ fungal genomes. Also see the Google+ site for more discussion opportunities.


This project is in collaboration with the work of the JGI and you can find links on this site to the nomination page for submitting candidate species to the project.

Via Kamoun Lab @ TSL, Arjen ten Have
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Tick genome reveals secrets of a successful bloodsucker

Tick genome reveals secrets of a successful bloodsucker | Amazing Science |

With tenacity befitting their subject, an international team of nearly 100 researchers toiled for a decade and overcame tough technical challenges to decipher the genome of the blacklegged tick (Ixodes scapularis)The National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health, contributed primary support to the research, which appears in the online, open-access journal Nature Communications.

“Ticks spread more different kinds of infectious microbes to people and animals than any other arthropod group,” said NIAID Director Anthony S. Fauci, M.D. “The spiral-shaped bacterium that causes Lyme disease is perhaps the best known microbe transmitted by ticks; however, ticks also transmit infectious agents that cause human babesiosis, anaplasmosis, tick-borne encephalitis and other diseases. The newly assembled genome provides insight into what makes ticks such effective disease vectors and may generate new ways to lessen their impact on human and animal health.”

Catherine A. Hill, Ph.D., of Purdue University, headed the team of investigators. Aside from the logistical challenges of coordinating activities of dozens of workers across many time zones, the researchers’ focus was a creature that is extremely difficult to maintain and that lives a long time — up to two years in the wild and nine months in the lab, Dr. Hill noted. Ixodes ticks have three blood-feeding life stages, and during each one, they feed on a different vertebrate animal. During feeding, ticks ingest blood for hours or days at a time. After mating, adult female ticks rapidly imbibe a large blood meal during which they expand hugely. “Because genes may switch on or off depending on the life stage of the tick, we needed to culture and collect ticks at each stage for analysis. This was not easy to do,” said Dr. Hill.

Another challenge was the sheer size of the tick genome — some 2.1 billion DNA base pairs — and expansive regions where sequences are repeated. “The degree of DNA repetition — approximately 70 percent of the total — made assembling the full genome in the correct order very difficult,” Dr. Hill said. In the end, the team determined the order and sequence of about two-thirds of the total genome. “We determined the sequence for 20,486 protein-coding genes,” she said, “of which 20 percent may be unique to ticks. Those tick-specific genes are like guideposts that say ‘start here’ as we look for new ways to counter infectious ticks.”

Although the latest research represents just a first look at the tick genome, the scientists have already identified genes and protein families that shed light on why Ixodes ticks succeed so well as parasites and hint at the reasons they excel at spreading pathogens, Dr. Hill noted. For example, compared with other blood-feeders, ticks have many more proteins devoted to consuming, concentrating and detoxifying their iron-containing food. Although mosquitoes — which quickly siphon up relatively small amounts of blood through a tube-like mouthpiece — have several proteins dedicated to blood digestion, ticks have many more proteins involved in this process. Other genes code for proteins that help ticks concentrate the blood and rapidly excrete excess water that accompanies large blood meals. Still other genes allow ticks to quickly expand their stiff outer coats to accommodate a 100-fold increase in total body size during blood feeding.

Other peculiarities of the tick’s lifestyle reflected in the genome include genes associated with the multifaceted sensory systems that the parasite uses when “questing” for a host during each of its separate blood-feeding stages. Compared with mosquitoes, ticks appear to have fewer genes used to detect hosts, and, unlike a mosquito’s “smell” receptors, ticks may use “taste” receptors to locate their food sources. Each of the newly identified proteins is a potential target for new, tick-specific interventions, explained Dr. Hill. “The genome gives us a code book to the inner workings of ticks. With it, we can now begin to hack their system and write a counter-script against them.”

In an effort to explain variations in Lyme disease prevalence across the United States, the team also examined genetic diversity within and among I. scapularis populations gathered from five states in the Northeast and Midwest and three in the South. Some have speculated that ticks in the Northeast and Midwest spread the bacteria that cause Lyme disease more easily than those in the South, or that the two populations perhaps comprise separate species. The genetic analysis showed that there is only one species of I. scapularis, said Dr. Hill, but subtle genetic differences were detected, and these may help explain some of the variance in the ability of populations to transmit disease and, therefore, affect disease prevalence.

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Illumina will launch a new company, Grail, to develop blood tests to revolutionize cancer detection

Illumina will launch a new company, Grail, to develop blood tests to revolutionize cancer detection | Amazing Science |

The world’s largest DNA sequencing company says it will form a new company to develop blood tests that cost $1,000 or less and can detect many types of cancer before symptoms arise.

Illumina, based in San Diego, said its blood tests should reach the market by 2019, and would be offered through doctors’ offices or possibly a network of testing centers.

The spin-off’s name, Grail, reflects surging expectations around new types of DNA tests that might do more to defeat cancer than the more than $90 billion spent each year by doctors and hospitals on cancer drugs. Illumina CEO Jay Flatley says he hopes the tests could be a “turning point in the war on cancer.”

The startup will be based in San Francisco and has raised more than $100 million from Illumina as well as Bill Gates, Jeff Bezos’s venture fund, Bezos Expeditions, and Arch Venture Partners. Illumina will retain majority control.

The testing concept being pursued by Illumina, sometimes called a “liquid biopsy,” is to use high-speed DNA sequencing machines to scour a person’s blood for fragments of DNA released by cancer cells. If DNA with cancer-causing mutations is present, it often indicates a tumor is already forming, even if it’s too small to cause symptoms or be seen on an imaging machine.

Illumina didn’t invent the idea for the tests, which were first developed by academic centers including at Johns Hopkins University (see “Spotting Cancer in a Vial of Blood”) and in Hong Kong (see “Liquid Biopsy”). But Flatley says only recently has gene-sequencing become inexpensive enough to try to make the cancer screening tests affordable.

Illumina has established spin-offs in Silicon Valley to address consumer markets for DNA data. A DNA test able to pick up many kinds of cancer could be revolutionary because tumors caught early can often be cured with surgery or radiation. Since the 1970s, the largest declines in cancer deaths rates are due to either behavioral changes, like declining tobacco use, or because of effective screening tests, principally colonoscopies and pap smear. New drugs have helped, too, though their impact on survival has generally been modest.

Expectations that cancer blood tests will quickly turn into a multibillion-dollar industry has attracted growing interest from investors. For instance, last week, a startup called Guardant, run by former Illumina executives, also said it had raised $100 million.

Guardant’s test isn’t an early detection test, but is instead used to measure tumor DNA in patients already battling cancer and can be prescribed in place of an invasive tissue biopsy (see “The Great Cancer Test Experiment”). Other companies bidding for a share of the testing market include Personal Genome Diagnostics, a spin-off of Johns Hopkins University, as well as Trovagene, Boreal Genomics, and Natera.

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Broad Institute: Genome misfolding unearthed as a new path to cancer 

Broad Institute: Genome misfolding unearthed as a new path to cancer  | Amazing Science |

In a landmark study, researchers from the Broad Institute and Massachusetts General Hospital reveal a completely new biological mechanism that underlies cancer. By studying brain tumors that carry mutations in the isocitrate dehydrogenase (IDH) genes, the team uncovered some unusual changes in the instructions for how the genome folds up on itself. Those changes target key parts of the genome, called insulators, which physically prevent genes in one region from interacting with the control switches and genes that lie in neighboring regions. When these insulators run amok in IDH-mutant tumors, they allow a potent growth factor gene to fall under the control of an always-on gene switch, forming a powerful, cancer-promoting combination.

The findings, which point to a general process that likely also drives other forms of cancer, appear in the December 23rd advance online issue of the journal Nature“This is a totally new mechanism for causing cancer, and we think it will hold true not just in brain tumors, but in other forms of cancer,” said senior author Bradley Bernstein, an institute member at the Broad Institute and a professor of pathology at Massachusetts General Hospital. “It is well established that cancer-causing genes can be abnormally activated by changes in their DNA sequence. But in this case, we find that a cancer-causing gene is switched on by a change in how the genome folds.”

When extended from end to end, the human genome measures some six and a half feet. Although it is composed of smaller, distinct pieces (the chromosomes), it is now recognized that the pieces of the genome fold intricately together in three dimensions, allowing them to fit compactly within the microscopic confines of the cell. More than mere packaging, these genome folds consist of a series of physical loops, like those of a tied shoelace, that bring distant genes and gene control switches into close proximity.

By creating these loops — roughly 10,000 of them in total — the genome harnesses form to regulate function. “It has become increasingly clear that the functional unit of the genome is not a chromosome or even a gene, but rather these loop domains, which are physically separated — and thereby insulated — from neighboring loop domains,” said Bernstein.

But Bernstein’s group did not set out to study this higher-order packing of the genome. Instead, they sought a deeper molecular understanding of glioma, a form of brain cancer, including the highly aggressive form, glioblastoma. Relatively little progress has been made in the last two decades in treating these often incurable malignancies. In order to unlock these tumors’ biology, Bernstein and his colleagues combed through vast amounts of data from recent cancer genome projects, including the Cancer Genome Atlas (TCGA). They detected an unusual trend in IDH-mutant tumors: When a growth factor gene, called PDGFRA, was switched on, so was a faraway gene, called FIP1L1. When PDGFRA was turned off, so, too, was FIP1L1.

Via Integrated DNA Technologies
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Spacefaring tardigrade (water bear) has largest contribution of foreign DNA in its genome

Spacefaring tardigrade (water bear) has largest contribution of foreign DNA in its genome | Amazing Science |

Sequencing reveals that the genome of the Tardigrade has been published, revealing approximately 6,000 genes of foreign origin.

The tardigrade, also known as the water bear, is renowned for many reasons. The nearly indestructible micro-organism is known to have the capacity to survive extreme temperatures (-272C to 151C), and is the only animal able to survive in the vacuum of space.

Today, with the publication of its genome in PNAS, the humble water bear can add another item to its exhaustive list of superlatives. Sequencing of the genome, performed by a team of researchers at the University of North Carolina at Chapel Hill, has revealed that a massive portion of the tiny organism’s genome is of foreign origin. Indeed, nearly 17.5% of the water bear’s genome is comprised of foreign DNA, translating to a genetic complement of approximately 6,000 genes. These genes are primarily of bacterial origin, though genes from fungi and plants have also been identified.

Horizontal gene transfer, defined as the shifting of genetic material materially (thus horizontally) between organisms is widespread in the microscopic world. In humans, however, the process does occur, but in a limited fashion, and via transposons and viruses. Other microscopic animals are also known to have large complements of foreign genes.

The authors of the newly published work have proposed a method by which this extremely extensive gene transfer may have occurred. Tardigrades have long been known to undergo, and survive, the process of desiccation (extreme drying out). The authors therefore postulated that during this drying out process and the subsequent rehydration, the tardigrade’s genome may have undergone significant sheering and breakage, resulting in a general loss of integrity and leakiness experienced by the water bear’s nucleus. In turn, this compromised nuclear integrity may have enabled foreign genetic material to readily integrate the genome, in much the same way as scientists perform gene transfer through the process of electroporation.

For now, the tardigrade has a dual claim to fame, being the only known animal to survive the vacuum of space, and being the animal with the largest genetic complement. Only with the study of other micro-organisms will we be able to validate if the humble tardigrade maintains its two, current, great claims to fame.

"Animals that can survive extreme stresses may be particularly prone to acquiring foreign genes—and bacterial genes might be better able to withstand stresses than animal ones," said Boothby, a postdoctoral fellow in Goldstein's lab. After all, bacteria have survived the Earth's most extreme environments for billions of years.

The team speculates that the DNA is getting into the genome randomly but what is being kept is what allows tardigrades to survive the harshest of environments, e.g. stick a tardigrade in a - 80 celsius freezer for a year or 10 and it starts running around in 20 minutes after thawing.

This is what the team thinks happens: when tardigrades are under conditions of extreme stress such as desiccation - or a state of extreme dryness—Boothby and Goldstein believe that the tardigrade's DNA breaks into tiny pieces. When the cell rehydrates, the cell's membrane and nucleus, where the DNA resides, becomes temporarily leaky and DNA and other large molecules can pass through easily. Tardigrades not only can repair their own damaged DNA as the cell rehydrates but also stitch in the foreign DNA in the process, creating a mosaic of genes that come from different species.

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Cheap DNA sequencing is here, writing DNA inexpensively is next

Cheap DNA sequencing is here, writing DNA inexpensively is next | Amazing Science |

Twist Bioscience dramatically scaled down the equipment for synthesizing DNA in a lab, making the process cheaper and faster. The stamp-sized wafers contain 100 microwells. Each of these contains 100 nanowells in which DNA can be synthesized.

AT TWIST BIOSCIENCE’S office in San Francisco, CEO Emily Leproust pulled out of her tote bag two things she carries around everywhere: a standard 96-well plastic plate ubiquitous in biology labs and her company’s invention, a silicon wafer studded with a similar number of nanowells.

Twist’s pitch is that it has dramatically scaled down the equipment for synthesizing DNA in a lab, making the process cheaper and faster. As Leproust gave her spiel, I looked from the jankety plastic plate, the size of two decks of cards side by side, to the sleek stamp-sized silicon wafer and politely nodded along. Then she handed me a magnifying lens to look down the wafer’s nanowells. Inside each nanowell was another 100 microscope holes.

That’s when I actually got it. The 96-well plate was not equivalent to the wafer, the entire plate was equivalent toone nanowell on the wafer. To put a number on it, traditional DNA synthesis machines can make one gene per 96-well plate; Twist’s machine can make 10,000 genes on a silicon wafer set the same size as the plate.

But who wants to order 10,000 genes? Until recently, that question might have been met with silence. “It was a lonely time,” says Leproust of her early fundraising efforts for Twist. Fast forward a couple years, though, and Twist has just signed a deal to sell at least 100 million letters of DNA—equivalent to tens of thousands of genes—to Ginkgo Bioworks, a synthetic biology outfit that inserts genes into yeast to make scents like rose oil or flavors like vanillin. Ginkgo is at the forefront of a wave of synthetic biology companies, bolstered by new gene-editing technologies like Crispr and investor interest.

“We’re Intel and Ginkgo is Microsoft,” says Leproust, which sounds exactly the kind of rhetoric you hear all the time in startupland. But her words reveal Twist’s specific ambition to be the driver behind synthetic biology innovations. Synthesizing genes in a lab allows biologists to design—down to the letter—the ones they want to test. Companies out there are already tinkering with DNA in various cells to create spider silk, cancer treatments, biodegradable plastic, diesel fuel—and Twist’s founders thinks the company can become the driving technology behind that new world.

Via Marko Dolinar
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Genomics and Precision Agriculture: The Future of Farming

Genomics and Precision Agriculture: The Future of Farming | Amazing Science |

For nearly 400 years, Thanksgiving has been a time in North America when families come together to celebrate food and agriculture. As we reflect on yet another year, agricultural scientists at USDA continue to keep a wary eye on the future. At the end of what may be the hottest year on record, a period of drought has threatened the heart of one of the most important agricultural production zones in the United States. Water demands are increasing, and disease and pest pressures are continually evolving. This challenges our farmers’ ability to raise livestock and crops.  How are science and technology going to address the problems facing our food supply? 

To find answers, agricultural scientists turn to data—big data.  Genomics, the field of science responsible for cataloging billions of DNA base pairs that encode thousands of genes in an organism, is fundamentally changing our understanding of plants and animals.  USDA has already helped to fund and collect genomes for 25 crop plant species, important livestock and fish species, and numerous bacteria, fungi, and insect species related to agricultural production. Other USDA-supported research projects expanding these efforts are currently underway, including genome sequencing of 1,000 breeds of bulls and 5,000 insect species in the i5K initiative. But classifying and understanding DNA is only part of the story.

Even if neighboring farmers were to raise identical varieties of tomato, small variations in the environment can reduce crop performance and/or increase pests and disease. So, scientists and farmers are increasingly using technology like satellites, drones, sensors, and laser-guided tractors to collect thousands of data points about the environmental conditions in a field, such as temperature, humidity, soil composition, or slope of the land. Using these “precision agriculture” techniques, farmers could reduce their environmental footprint by matching land management practices to the unique environments on their farm.

In the long term, USDA researchers are hoping to combine precision agriculture and genomics in a remarkable way—to develop crops with combinations of genes that lead to the best performance in specific environments. To support this goal, USDA continues to lead the way in collecting and maintaining open access to these types of agriculture data.  As a result, your local farmer’s market or grocery store may one day have even more varieties of produce to choose from on Thanksgiving, with each optimized for the farm or field on which it was grown.

Via Integrated DNA Technologies
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Uneven growth of identical monozygotic twins may begin shortly after conception

Uneven growth of identical monozygotic twins may begin shortly after conception | Amazing Science |

Unequal growth between genetically identical monozygotic (MZ) twins in the womb may be triggered in the earliest stages of human embryo development, according to a new study led by King’s College London.

Around 80% of MZ twins originate from monochorionic/diamniotic pregnancies, where they share the same placenta in the womb. MZ twins are recognized to be at greater risk of congenital anomalies. One of the most common complications is severe discordant growth, in which there is a 25% or greater difference in fetal or birth weight between the twins in the absence of twin-to-twin transfusion syndrome. Such severe discordant growth has been reported in 7% to 14% of all monochorionic/diamniotic pregnancies. Unequal placental sharing can explain about half of these pregnancies; the cause of the other half is largely unknown.

The case presented in the latest paper, published in the journal Stem Cell Reports, suggests that uneven growth of identical twins could start during the early stages of preimplantation development. An embryo donated for research revealed two inner cell masses (ICMs, internal cluster of cells at the embryonic pole of the blastocyst which develops into the body of the embryo), which is a sign of monochorionic/diamniotic pregnancy that will give rise to MZ twins. In this case, the two ICMs were not equal and high-resolution RNA sequencing indicated that they were at different stages of development; the smaller one was in the earliest stages of cell lineage commitment, while the bigger one had already differentiated to some extent. The differences in development would become negligible; however, the difference in size would be likely to continue throughout the pregnancy.

Laila Noli, first author and PhD student from King's College London said: 'Having two distinct ICMs within a single embryo of which one was bigger and more developmentally advanced than the other was an unexpected finding. Prevailing opinion would expect them to be absolutely identical at that stage, and that the cause of uneven growth of MZ twins would be due to their position in the womb or other unknown environmental circumstances at later stages of pregnancy.'

Dr Dusko Ilic, lead author from the Division of Women’s Health, King's College London, says: ‘Until now, the earliest report of uneven growth of MZ twins was at 12 weeks of pregnancy. We found that it can start virtually in the first few days after conception. The prevalence of such early stage uneven growth is not known and further case reports and studies are needed. We do not know whether the two ICMs within the same embryo may have originated from uneven splitting of a single “parental” ICM or whether the two ICMs formed independently. Either way, our case report suggests that cellular and molecular events may play a role in uneven growth of MZ twins from monochorionic/diamniotic pregnancies.’

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How to Catch a Virus: Targeted Capture for Viral Sequencing

How to Catch a Virus: Targeted Capture for Viral Sequencing | Amazing Science |

Metagenomic profiling, also called metagenomic shotgun sequencing (MSS) represents a powerful application made possible by the digital nature of next-generation sequencing technologies. In it, one basically sequences a sample isolate obtained from somewhere — a shovelful of dirt, a scoop of plankton, or anything else that contains living organisms. MSS has proven particularly useful to studies of the human microbiome, or in layman’s terms, all of the bacteria/viruses/fungi that live in our bodies.

Many such microbiota are beneficial or simply commensal (not doing harm) with us. Others, like methicillin-resistant Staphylococcus aureus (MRSA), can cause severe disease. Most efforts to chart the human microbiome have focused on bacteria, whose relatively stable genomes make them amenable to assay development. Viruses, in contrast, are somewhat under-studied. Part of that is due to the small size and highly variable nature of viral genomes.

A new study in Genome Research showcases a capture-based enrichment strategy to improve virome sequencing. The ViroCap panel was developed by Todd and Kristine Wylie, who happen to be colleagues of mine at the McDonnell Genome Institute. The panel enriches for nucleic acids from 34 families of DNA or RNA viruses that infect vertebrate hosts, beautifully illustrated in a figure from the paper (see above).

At the time of the ViroCap design, NCBI GenBank contained the sequenced genomes of around 440 viral species, for a total of about 1 Gbp (billion base pairs) of sequence. After considerable bioinformatics efforts, the authors produced a ~200 Mbp sequence target and worked with Nimblegen to have it designed.

Wylie TN, Wylie KM, Herter BN, & Storch GA (2015). Enhanced virome sequencing through solution-based capture enrichment. Genome research PMID: 26395152

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Scientists hope to attract millions of people to 'DNA.LAND'

Scientists hope to attract millions of people to 'DNA.LAND' | Amazing Science |

Geneticists have launched a project to test whether they can study millions of genomes — without collecting a drop of blood or tube of spit themselves. The project, DNA.LAND, aims to entice people who have already had their genomes analysed by consumer genetics companies to share that data, allowing DNA.LAND geneticists to study the information. Although some consumer genetic-testing companies share data with researchers, they provide only aggregate information about their customers, not individual genomes. Because the data are not always accompanied by detailed information on patients' health, they are of limited use for drawing links between genes and disease.

“Millions of people have access to their genomes, and many more millions will join them in the near future,” sayscomputational geneticist Yaniv Erlich. He is launching DNA.LAND with fellow geneticist Joseph Pickrell at the New York Genome Center and Columbia University in New York. “Can you get to the point that instead of paying for each study from scratch, we can use the crowd to collect and repurpose this data?” Erlich asks.

Erlich will present the project on 10 October at the annual meeting of the American Society of Human Genetics (ASHG) in Baltimore, Maryland. This is not the first time that he has sought to engage the public to assemble data for large research studies. For instance, Erlich has previously combined data from genealogy websites into the world’s largest family tree, with information on 13 million people.

DNA.Land is an example of the 'participatory turn' in human subjects research, says Michelle Meyer, a bioethicist and legal scholar at the Icahn School of Medicine at Mount Sinai in New York.This is a smart research model, since it keeps sequencing and data-storage costs low and doesn't run into the patchwork of federal and state laws governing genetic testing itself.

Erlich hopes to tap the genomes of up to three million customers of companies such as 23andMe, and Family Tree DNA. The companies allow people to download a file containing the readout of their genetic results.

By combining these data with other information about the participants, such as that on their health, Erlich hopes to assemble a very large data set. A recent analysis, for instance, suggested that as many as 2 billion genomes could be sequenced by 2025.

“The sky is the limit,” he says. Erlich has studied the potential for unmasking the identities of anonymous donors of genetic data, and the study's consent document warns participants that “we cannot guarantee that your identity and/or data will never become known, which could have significant implications in some scenarios. We estimate that the risk for such a confidentiality breach is low but not zero.” Erlich and Pickrell have adopted what they call a “skin in the game” philosophy by making their own genomes publicly available.

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