From Living Computers to Nano-Robots: How We’re Taking DNA Beyond Genetics

DNA is one of the most amazing molecules in nature, providing a way to carry the instructions needed to create almost any life form on Earth in a microscopic package. Now scientists are finding ways to push DNA even further, using it not just to store information but to create physical components in a range of biological machines.

Deoxyribonucleic acid or “DNA” carries the genetic information that we, and all living organisms, use to function. It typically comes in the form of the famous double-helix shape, made up of two single-stranded DNA molecules folded into a spiral. Each of these is made up of a series of four different types of molecular component: adenine (A), guanine (G), thymine (T), and cytosine (C).

Genes are made up from different sequences of these building block components, and the order in which they appear in a strand of DNA is what encodes genetic information. But by precisely designing different A, G, T and C sequences, scientists have recently been able to develop new ways of folding DNA into different origami shapes, beyond the conventional double helix.

This approach has opened up new possibilities of using DNA beyond its genetic and biological purpose, turning it into a Lego-like material for building objects that are just a few billionths of a meter in diameter (nanoscale). DNA-based materials are now being used for a variety of applications, ranging from templates for electronic nano-devices, to ways of precisely carrying drugs to diseased cells.

DNA-based nanothermometers

Designing electronic devices that are just nanometers in size opens up all sorts of possible applications but makes it harder to spot defects. As a way of dealing with this, researchers at the University of Montreal have used DNA to create ultrasensitive nanoscale thermometers that could help find minuscule hotspots in nanodevices (which would indicate a defect). They could also be used to monitor the temperature inside living cells.

The nanothermometers are made using loops of DNA that act as switches, folding or unfolding in response to temperature changes. This movement can be detected by attaching optical probes to the DNA. The researchers now want to build these nanothermometers into larger DNA devices that can work inside the human body.

Biological nanorobots

Researchers at Harvard Medical School have used DNA to design and build a nanosized robot that acts as a drug delivery vehicle to target specific cells. The nanorobot comes in the form of an open barrel made of DNA, whose two halves are connected by a hinge held shut by special DNA handles. These handles can recognize combinations of specific proteins present on the surface of cells, including ones associated with diseases.

When the robot comes into contact with the right cells, it opens the container and delivers its cargo. When applied to a mixture of healthy and cancerous human blood cells, these robots showed the ability to target and kill half of the cancer cells, while the healthy cells were left unharmed.

DNA barrel. Image credit: Campbell Strong, Shawn Douglas, and Gaël McGill.

Bio-computers in living animals

Because DNA structures can act as switches, moving from one position to another and back again, they can be used to perform the logical operations that make computer calculations possible. Researchers at Harvard and Bar-Ilan University in Israel have used this principle to build different nanoscale robots that can interact with each other, using their DNA switches to react to and produce different signals.

What’s more, the scientists implanted the robots into a living animal, in this instance a cockroach. This allowed them to develop a novel type of biological computer that can control the delivery of therapeutic molecules inside the cockroach by switching elements of their structure “on” or “off”. A trial of these DNA nanorobots is now scheduled to take place in humans.

Light-harvesting antennas

As well as creating minuscule machines, DNA can provide a way for us to copy natural processes at the nanoscale. For example, nature can capture energy from the sun using photosynthesis to convert light into chemical energy, which acts as fuel for plants and other organisms (and the animals that eat them). Researchers at Arizona State University and the University of British Columbia have now built a three-arm DNA structure that can capture and transfer light that mimics this process.

Photosynthesis occurs in living organisms thanks to tiny antennas made up of a large number of pigment molecules at specific orientations and distances from each other, which are able to absorb visible light. The artificial DNA-based structures act as similar antennas, controlling the position of specific dye molecules that absorb the light energy and channel it to a reaction centre where it is converted into chemical energy. This work could pave the way for devices capable of more efficiently using the most abundant source of energy we have at our disposal: sunlight.

So what’s next for DNA nanotechnology? It is hard to know but, with DNA, nature has given us a very versatile tool. It is now up to us to make the best use of it.

ORIGINAL: Singularity Hub

By MATTEO PALMA

ON JUN 07, 2016

Research on largest network of cortical neurons to date published in Nature

Robust network of connections between neurons performing similar tasks shows fundamentals of how brain circuits are wired

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Even the simplest networks of neurons in the brain are composed of millions of connections, and examining these vast networks is critical to understanding how the brain works. An international team of researchers, led by R. Clay Reid, Wei Chung Allen Lee and Vincent Bonin from the Allen Institute for Brain Science, Harvard Medical School and Neuro-Electronics Research Flanders (NERF), respectively, has published the largest network to date of connections between neurons in the cortex, where high-level processing occurs, and have revealed several crucial elements of how networks in the brain are organized. The results are published this week in the journal Nature.

A network of cortical neurons whose connections were traced from a multi-terabyte 3D data set. The data were created by an electron microscope designed and built at Harvard Medical School to collect millions of images in nanoscopic detail, so that every one of the “wires” could be seen, along with the connections between them. Some of the neurons are color-coded according to their activity patterns in the living brain. This is the newest example of functional connectomics, which combines high-throughput functional imaging, at single-cell resolution, with terascale anatomy of the very same neurons. Image credit: Clay Reid, Allen Institute; Wei-Chung Lee, Harvard Medical School; Sam Ingersoll, graphic artist

“This is a culmination of a research program that began almost ten years ago. Brain networks are too large and complex to understand piecemeal, so we used high-throughput techniques to collect huge data sets of brain activity and brain wiring,” says R. Clay Reid, M.D., Ph.D., Senior Investigator at the Allen Institute for Brain Science. “But we are finding that the effort is absolutely worthwhile and that we are learning a tremendous amount about the structure of networks in the brain, and ultimately how the brain’s structure is linked to its function.”

“Although this study is a landmark moment in a substantial chapter of work, it is just the beginning,” says Wei-Chung Lee, Ph.D., Instructor in Neurobiology at Harvard Medicine School and lead author on the paper. “We now have the tools to embark on reverse engineering the brain by discovering relationships between circuit wiring and neuronal and network computations.” 

“For decades, researchers have studied brain activity and wiring in isolation, unable to link the two,” says Vincent Bonin, Principal Investigator at Neuro-Electronics Research Flanders. “What we have achieved is to bridge these two realms with unprecedented detail, linking electrical activity in neurons with the nanoscale synaptic connections they make with one another.”

“We have found some of the first anatomical evidence for modular architecture in a cortical network as well as the structural basis for functionally specific connectivity between neurons,” Lee adds. “The approaches we used allowed us to define the organizational principles of neural circuits. We are now poised to discover cortical connectivity motifs, which may act as building blocks for cerebral network function.”

Lee and Bonin began by identifying neurons in the mouse visual cortex that responded to particular visual stimuli, such as vertical or horizontal bars on a screen. Lee then made ultra-thin slices of brain and captured millions of detailed images of those targeted cells and synapses, which were then reconstructed in three dimensions. Teams of annotators on both coasts of the United States simultaneously traced individual neurons through the 3D stacks of images and located connections between individual neurons.

Analyzing this wealth of data yielded several results, including the first direct structural evidence to support the idea that neurons that do similar tasks are more likely to be connected to each other than neurons that carry out different tasks. Furthermore, those connections are larger, despite the fact that they are tangled with many other neurons that perform entirely different functions.

“Part of what makes this study unique is the combination of functional imaging and detailed microscopy,” says Reid. “The microscopic data is of unprecedented scale and detail. We gain some very powerful knowledge by first learning what function a particular neuron performs, and then seeing how it connects with neurons that do similar or dissimilar things.

“It’s like a symphony orchestra with players sitting in random seats,” Reid adds. “If you listen to only a few nearby musicians, it won’t make sense. By listening to everyone, you will understand the music; it actually becomes simpler. If you then ask who each musician is listening to, you might even figure out how they make the music. There’s no conductor, so the orchestra needs to communicate.”

This combination of methods will also be employed in an IARPA contracted project with the Allen Institute for Brain Science, Baylor College of Medicine, and Princeton University, which seeks to scale these methods to a larger segment of brain tissue. The data of the present study is being made available online for other researchers to investigate.

This work was supported by the National Institutes of Health (R01 EY10115, R01 NS075436 and R21 NS085320); through resources provided by the National Resource for Biomedical Supercomputing at the Pittsburgh Supercomputing Center (P41 RR06009) and the National Center for Multiscale Modeling of Biological Systems (P41 GM103712); the Harvard Medical School Vision Core Grant (P30 EY12196); the Bertarelli Foundation; the Edward R. and Anne G. Lefler Center; the Stanley and Theodora Feldberg Fund; Neuro-Electronics Research Flanders (NERF); and the Allen Institute for Brain Science.

About the Allen Institute for Brain Science

The Allen Institute for Brain Science, a division of the Allen Institute (alleninstitute.org), is an independent, 501(c)(3) nonprofit medical research organization dedicated to accelerating the understanding of how the human brain works in health and disease. Using a big science approach, the Allen Institute generates useful public resources used by researchers and organizations around the globe, drives technological and analytical advances, and discovers fundamental brain properties through integration of experiments, modeling and theory. Launched in 2003 with a seed contribution from founder and philanthropist Paul G. Allen, the Allen Institute is supported by a diversity of government, foundation and private funds to enable its projects. Given the Institute’s achievements, Mr. Allen committed an additional $300 million in 2012 for the first four years of a ten-year plan to further propel and expand the Institute’s scientific programs, bringing his total commitment to date to $500 million. The Allen Institute’s data and tools are publicly available online at brain-map.org.

About Harvard Medical School

HMS has more than 7,500 full-time faculty working in 10 academic departments located at the School’s Boston campus or in hospital-based clinical departments at 15 Harvard-affiliated teaching hospitals and research institutes: Beth Israel Deaconess Medical Center, Boston Children’s Hospital, Brigham and Women’s Hospital, Cambridge Health Alliance, Dana-Farber Cancer Institute, Harvard Pilgrim Health Care Institute, Hebrew SeniorLife, Joslin Diabetes Center, Judge Baker Children’s Center, Massachusetts Eye and Ear/Schepens Eye Research Institute, Massachusetts General Hospital, McLean Hospital, Mount Auburn Hospital, Spaulding Rehabilitation Hospital and VA Boston Healthcare System.

About NERF

Neuro-Electronics Research Flanders (NERF; www.nerf.be) is a neurotechnology research initiative is headquartered in Leuven, Belgium initiated by imec, KU Leuven and VIB to unravel how electrical activity in the brain gives rise to mental function and behaviour. Imec performs world-leading research in nanoelectronics and has offices in Belgium, the Netherlands, Taiwan, USA, China, India and Japan. Its staff of about 2,200 people includes almost 700 industrial residents and guest researchers. In 2014, imec's revenue (P&L) totaled 363 million euro. VIB is a life sciences research institute in Flanders, Belgium. With more than 1470 scientists from over 60 countries, VIB performs basic research into the molecular foundations of life. KU Leuven is one of the oldest and largest research universities in Europe with over 10,000 employees and 55,000 students.

ORIGINAL: Allen Institute

March 28th, 2016

Master monkey's brain controls sedated 'avatar'

The brain of one monkey has been used to control the movements of another, "avatar", monkey, US scientists report.

Brain scans read the master monkey's mind and were used to electrically stimulate the avatar's spinal cord, resulting in controlled movement.

The team hope the method can be refined to allow paralysed people to regain control of their own body.

The findings, published in Nature Communications, have been described as "a key step forward".

Figure 1: Schematic illustration of the dual-primate set-up.

The master is displayed on top and the avatar is displayed on the bottom. Note that on decoding-based sessions, the master had a joystick during training that was then disconnected during the real-time neural prosthetic trials.

Damage to the spinal cord can stop the flow of information from the brain to the body, leaving people unable to walk or feed themselves.

The researchers are aiming to bridge the damage with machinery. Match electrical activity

The scientists at Harvard Medical School said they could not justify paralysing a monkey. Instead, two were used - a master monkey and a sedated avatar.

The master had a brain chip implanted that could monitor the activity of up to 100 neurons.

During training, the physical actions of the monkey were matched up with the patterns of electrical activity in the neurons.

The avatar had 36 electrodes implanted in the spinal cord and tests were performed to see how stimulating different combinations of electrodes affected movement.

The two monkeys were then hooked up so that the brain scans in one controlled movements in real time in the other.

The sedated avatar held a joystick, while the master had to think about moving a cursor up or down.

In 98% of tests, the master could correctly control the avatar's arm.

One of the researchers, Dr Ziv Williams, told the BBC: "The goal is to take people with brain stem or spinal cord paralysis and bypass the injury.

"The hope is ultimately to get completely natural movement, I think it's theoretically possible, but it will require an exponential additional effort to get to that point."

He said that giving paralysed people even a small amount of movement could dramatically alter their quality of life. Reality or science fiction?

The idea of one brain controlling an avatar body is the stuff of blockbuster Hollywood movies.

However, Prof Christopher James, of the University of Warwick, dismissed a future of controlling other people's bodies by thought.

He said: "Some people may be concerned this might mean someone taking over control of someone else's body, but the risk of this is a no-brainer.

"Whilst the control of limbs is sophisticated, it is still rather crude overall, plus of course in an able-bodied person their own control over their limbs remains anyway, so no-one is going to control anyone else's body against their wishes any time soon."

Instead, he said this was "very important research" with "profound" implications "especially for controlling limbs in spinal cord injury, or controlling prosthetic limbs with limb amputees".

Realising that goal will face additional challenges. Moving a cursor up and down is a long way from the dextrous movement needed to drink from a cup.

There are also differences in the muscles of people after paralysis; they tend to become more rigid. And fluctuating blood pressure may make restoring control more challenging.

Prof Bernard Conway, head of biomedical engineering at the University of Strathclyde, said: "The work is a key step forward that demonstrates the potential of brain machine interfaces to be used in restoring purposeful movement to people affected by paralysis. 

"However, significant work still remains to be done before this technology will be able to be offered to the people who need it."


ORIGINAL: BBC Mundo

By James Gallagher Health and science reporter, BBC News 

18 February 2014

The genetic contribution Neanderthal man made to modern humanity is clearer

Kissing cousins

HOW Neanderthal are you? That question sounds vaguely insulting. But unless you are African, or of recent African ancestry, the answer is likely to be 1-3%.

Though Homo sapiens is the only type of human around at the moment, that was not true until recently. Sixty thousand years ago, when modern humans first left Africa, they encountered other species of humanity, such as Neanderthals (imagined above, in an artist’s interpretation), in Europe and Asia. In some cases, they interbred with them. The genetic traces of those encounters remain in modern human genomes. And two studies, one just published in Nature, and one in Science, have now looked in detail at this miscegenation, and tried to understand its consequences.


The Nature study, conducted by Sriram Sankararaman of Harvard Medical School and his colleagues, looked at the genomes of 1,004 living people of European and Asian descent and compared them with Neanderthal DNA from a 50,000-year-old toe bone found in a Siberian cave, and also with the genomes of 176 west Africans. This latter group, Dr Sankararaman assumed, could have little Neanderthal DNA in them because Neanderthals, as far as can be determined from the fossil record, lived only in Europe and western Asia.

Dr Sankararaman and his colleagues certainly did find plenty of DNA which seems to have come from Neanderthals in their Eurasians. Tellingly, it was not sprinkled evenly throughout the modern human genome. That let them make educated guesses about the effects it is having on those who carry it. For instance, genes affecting the production of keratin—an important component of hair and skin—showed more Neanderthal influence than most. Neanderthals, whose homeland was much colder then than it is now because of the ice age, were hairier (and thus better insulated) than Homo sapiens. Retaining Neanderthal traits of this sort, in an African species that was trying to make good in sub-Arctic conditions, would thus be encouraged by natural selection.

More surprisingly, Dr Sankararaman also found Neanderthal DNA in genes associated with diabetes, Crohn’s disease, lupus and even the propensity to smoke. This does not necessarily mean such DNA was bad for those who inherited it. A gene which increases the risk of diabetes in modern circumstances of abundant food might, for example, have had benefits in a more austere environment.

Indeed, truly deleterious DNA would be expected to be noticeable by its absence, because natural selection would have worked to eliminate it in the 30,000 years since Neanderthals died out. And Dr Sankararaman found evidence for exactly that, as well.

There is, for example, little Neanderthal DNA on the X chromosome (which, along with the Y chromosome, determines an individual’s sex). Nor is there much in genes that are expressed in the testicles. Studies from other hybrid animals, which are frequently sterile, suggest genes which reduce male fertility are often found on the X chromosome. Since few things are a bigger evolutionary no-no than being unable to produce children, tremendous selective pressure would have existed to remove the offending DNA from the hybrid descendants of Neanderthals and Homo sapiens.

The study published in Science, by Benjamin Vernot and Joshua Akey of the University of Washington, in Seattle, reaches similar conclusions to Dr Sankararaman’s. Dr Vernot and Dr Akey hunted down Neanderthal DNA in the genomes of 665 Europeans and East Asians. They, too, found evidence of its having inserted itself into genes associated with the skin, and that not all of the newly arrived genetic material is helpful to its current bearers.

They made other discoveries, too. With the help of computer models, they concluded that there were probably several pulses of interbreeding over the millennia, rather than a steady stream of it. Both they and Dr Sankararaman also found that, on average, East Asians have more Neanderthal DNA than Europeans do—which is odd, because Neanderthals are not known to have lived in East Asia.

The ghost in the machine
Dr Vernot and Dr Akey also used their data to try to improve understanding of the Neanderthal genome itself, by combining the bits and bobs scattered among modern humans. Though both their study and Dr Sankararaman’s depended on being able to identify what was Neanderthal by comparing modern human genomes with fossil DNA, the fossil material available is imperfect. Looking at the exact sequence of DNA “letters” (the chemical bases which carry the genetic message) in areas identified as Neanderthal in modern genomes can therefore improve understanding of the Neanderthal original.

Crucially, though the amount of Neanderthal DNA in any individual is small, the exact bits vary a lot from person to person. Look at enough people, then, and it becomes possible to rebuild quite large swathes of the Neanderthal genome. Dr Vernot and Dr Akey reckon that from their sample of 665 they have recovered around 20% of it.

This is an impressive figure for an extinct species. It shows just how much the concept of a “species” is a construct of human thinking rather than a truly natural category. Technically, Neanderthals may be gone. But their DNA ghosts linger on.

From the print edition: Science and technology


ORIGINAL: The Economist

Feb 1st 2014

Genome-scale engineering for systems and synthetic biology

ORIGINAL: Nature

Kevin M Esvelt1 & Harris H Wang1,2,a

This paper is part of the series on Systems Biology Technologies. See more papers from this series.

Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA

Department of Systems Biology, Harvard Medical School, Boston, MA, USA

Correspondence to: Kevin M Esvelt1Harris H Wang1,2,a Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, MA 02115, USA. Tel.: +1 617 955 9575; Fax: +1 617 432 7828; Email: hw2429@columbia.edu or Tel.: +1 857 919 3375; Fax: +1 617 432 7828; Email: kevin.esvelt@wyss.harvard.edu

Received 21 September 2012; Accepted 16 December 2012; Published online 22 January 2013

aPresent address: Department of Systems Biology, Columbia University Medical Center, 701 West 168th Street, Room 1308-B, New York, NY 10032, USA

Abstract

Genome-modification technologies enable the rational engineering and perturbation of biological systems. Historically, these methods have been limited to gene insertions or mutations at random or at a few pre-defined locations across the genome. The handful of methods capable of targeted gene editing suffered from low efficiencies, significant labor costs, or both. Recent advances have dramatically expanded our ability to engineer cells in a directed and combinatorial manner. Here, we 

• review current technologies and methodologies for genome-scale engineering, 
• discuss the prospects for extending efficient genome modification to new hosts, and 
• explore the implications of continued advances toward the development of 
  • flexibly programmable chasses, 
  • novel biochemistries, and s
  • afer organismal and ecological engineering.

The phrase ‘genome-scale engineering’ invokes a future in which organisms are custom designed to serve humanity. Yet humans have sculpted the genomes of domesticated plants and animals for generations. Darwin’s contemporary William Youatt described selective breeding as ‘that which enables the agriculturalist, not only to modify the character of his flock, but to change it altogether. It is the magician's wand, by means of which he may summon into life whatever form and mold he pleases’ (Youatt, 1837). Selective breeding has transformed aurochs into Holsteins, wolves into Chihuahuas and Great Danes, and teosinte into maize. All of these examples involved genomic changes at a scale dwarfing any attempted through rational design. Understanding why genomes have been more readily shaped by evolutionary principles than conventional design-based approaches is important for current and future genome engineering endeavors.

Engineering is a human enterprise consisting of iterative cycles of design, construction, and testing. Optimizing this iterative process involves balancing the relative time, costs, and expected benefits gained at each phase. However, rationally designing and building a genome to produce the desired phenotype has proven exceedingly difficult. Designing organisms to specification requires accurately predicting phenotype from genotype, a complex problem that is worsened by our incomplete knowledge of biomolecule production, degradation, and interaction rates. Moreover, the computational resources required to run bottom-up molecular-level simulations are daunting even for simpler systems (Karr et al, 2012; Koch, 2012). Nevertheless, models have been useful for generating new hypotheses and targeting promising areas for engineering. Yet, even with the best in silico predictions, we are still limited by our ability to construct the designed genome. More than any other factor, the absence of molecular tools for manipulating genomic sequences has forced us to rely on selective breeding and evolutionary optimization (Conrad et al, 2011) rather than rational genome design.

Recent breakthroughs in genomics and genome editing have promised a greater role for rational design in biological engineering (Figure 1), offering new opportunities for systems and synthetic biologists aiming to reverse-engineer naturally evolved systems and to build new systems. In particular, advances in high-throughput DNA sequencing and large-scale biomolecular modeling of metabolic and signaling networks represent two important new frontiers that aid genome-scale engineering. Over the last few years, thousands of bacterial genomes have been sequenced from a wide variety of natural species and numerous laboratory-generated strains (Pagani et al, 2012). These efforts have illuminated many essential features of the core genome (Lukjancenko et al, 2010), the extent and importance of genetic heterogeneity across populations (Avery, 2006), the ubiquity of horizontal gene transfer (Smillie et al, 2011), and the evolution and selection of functional genetic elements (David and Alm, 2011). At the same time, new computational tools have used the flood of data to model metabolic processes and signaling networks across the entire cell, generating many new testable hypotheses (Lewis et al, 2012). Most importantly, emerging advances in de novosynthesis and in vivo gene targeting allow empirical validation of these model-driven hypotheses. By building and testing synthetic variants of biological systems, we have a unique opportunity to decipher the constraints imposed by the complexity of evolved systems and develop strategies for engineering living systems more conducive to quantitative modeling and rational design.

Figure 1. A historical timeline of selected advances leading to genome-scale engineering.

Here we review recent technologies that empower design-based genome engineering approaches, identify potential bottlenecks, discuss strengths and limitations of strategies employing rational design versus evolution, and consider future applications of genome-scale engineering. We advocate a synergistic engineering strategy that adopts the best aspects of rational genome design and evolutionary optimization.

What is genome-scale engineering?

Genome engineering is the art of constructing a genotype that gives rise to a desired phenotype, a challenge whose difficulty is influenced by the scale of genomic alteration required. One measure of scale is the number of changes that must be made to an existing genome to produce the desired phenotype. In some cases, this may require editing only one gene, a task that is clearly not genome scale. The same is true for a library of single-gene variants and even a complete collection of single-gene knockouts (Giaever et al, 2002; Baba et al, 2006), as each genome has only a single change. We define genome-scale engineering to be any endeavor involving sequence modifications to at least two distinct regions of a genome. In what follows, we will mainly focus on technologies potentially capable of modifying large fractions of a single genome.

Genome-scale engineering allows us to experimentally probe deep biological questions such as essentiality (Koonin, 2000), epistasis (Chou et al, 2011; Khan et al, 2011), encoding (Itzkovitz and Alon, 2007), evolvability (Tokuriki and Tawfik, 2009; Wagner and Zhang, 2011;Hill and Zhang, 2012), and robustness (Bershtein et al, 2006). At the same time, we aim to rationally build useful organisms that cannot be easily generated by harnessing evolution alone. Such endeavors require foundational tools in design, modeling, construction, and testing that extend from individual cells to populations of organisms (Figure 2). Iterations of design, model, build, and test phases are likely to be more important as the scale of the endeavor increases because biological complexity can grow exponentially. Below, we describe key features of these phases in genome-scale engineering, outline current capabilities, and suggest opportunities for improvement.

Figure 2. Foundational genome engineering tools and approaches are needed to extend single site genetic perturbations of a single genome to multiple changes across many genomes.

Genome designs and models

Design is a set of specifications intended to achieve a dedicated objective under various constraints. Biological designs are those that describe the underlying blueprint of living organisms, built upon the information encoded in genes across the genome. As the focus of biological engineering shifts from individual genes to entire genomes, there is a growing need for more sophisticated genome design tools to assist such large-scale engineering endeavors. Recordkeeping software is essential for tracking numerous modifications designed and generated across libraries of genomes. Traditional gene editors such as Vector NTI and SeqBuilder are largely inadequate for such purposes. However, new design tools and software suites such as J5 (Hillson et al, 2012), Clotho (Xia et al, 2011), and Genome Compiler (http://www.genomecompiler.com/) provide better data management and user interfaces for the design of large operons and whole genomes.

Most Mutations Come from Dad: New Insights Into Age, Height and Sex Reshape Views of Human Evolution

ORIGINAL: Science Daily

Humans inherit more than three times as many mutations from their fathers as from their mothers, and mutation rates increase with the father's age but not the mother's, researchers have found in the largest study of human genetic mutations to date. (Credit: © yanlev / Fotolia)

ScienceDaily (Aug. 23, 2012) — Humans inherit more than three times as many mutations from their fathers as from their mothers, and mutation rates increase with the father's age but not the mother's, researchers have found in the largest study of human genetic mutations to date.

The study, based on the DNA of around 85,000 Icelanders, also calculates the rate of human mutation at high resolution, providing estimates of when human ancestors diverged from nonhuman primates. It is one of two papers published this week by the journal Nature Genetics as well as one published at Nature that shed dramatic new light on human evolution.

"Most mutations come from dad," said David Reich, professor of genetics at Harvard Medical School and a co-leader of the study. In addition to finding 3.3 paternal germ line mutations for each maternal mutation, the study also found that the mutation rate in fathers doubles from age 20 to 58 but that there is no association with age in mothers -- a finding that may shed light on conditions, such as autism, that correlate with the father's age.

The study's first author is James Sun, a graduate student in Reich's lab who worked with researchers from deCODE Genetics, a biopharma company based in Reykjavik, Iceland, to analyze about 2,500 short sequences of DNA taken from 85,289 Icelanders in 24,832 father-mother-child trios. The sequences, called microsatellites, vary in the number of times that they repeat, and are known to mutate at a higher rate than average places in the genome.

Reich's team identified 2,058 mutational changes, yielding a rate of mutation that suggests human and chimpanzee ancestral populations diverged between 3.7 million and 6.6 million years ago.

A second team, also based at deCODE Genetics (but not involving HMS researchers), published a paper this week in Nature on a large-scale direct estimate of the rate of single nucleotide substitutions in human genomes (a different type of mutation process), and came to largely consistent findings.

The finding complicates theories drawn from the fossil evidence. The upper bound, 6.6 million years, is less than the published date of Sahelanthropus tchadensis, a fossil that has been interpreted to be a human ancestor since the separation of chimpanzees, but is dated to around 7 million years old. The new study suggests that this fossil may be incorrectly interpreted.

Great Heights

A second study led by HMS researchers, also published in Nature Genetics this week, adds to the picture of human evolution, describing a newly observable form of recent genetic adaptation.

The team led by Joel Hirschhorn, Concordia Professor of Pediatrics and professor of genetics at Boston Children's Hospital and HMS, first asked why closely-related populations can have noticeably different average heights. David Reich also contributed to this study.

They examined genome-wide association data and found that average differences in height across Europe are partly due to genetic factors. They then showed that these genetic differences are the result of an evolutionary process that acts on variation in many genes at once. This type of evolution had been proposed to exist but had not previously been detected in humans.

Although recent human evolution is difficult to observe directly, some of its impact can be inferred by studying the human genome. In recent years, genetic studies have uncovered many examples where recent evolution has left a distinctive signature on the human genome. The clearest "footprints" of evolution have been seen in regions of DNA surrounding mutations that occurred fairly recently (typically in the last several thousand years) and confer an advantageous trait, such as resistance to malaria. Hirschhorn's team observed, for the first time in humans, a different signature of recent evolution: widespread small but consistent changes at many different places in the genome, all affecting the same trait, adult height.

"This paper offers the first proof and clear example of a new kind of human evolution for a specific trait," said Hirschhorn, who is also a senior associate member of the Broad Institute. "We provide a demonstration of how humans have been able to adapt rapidly without needing to wait for new mutations to happen, by drawing instead on the existing genetic diversity within the human population."

Average heights can differ between populations, even populations that are genetically very similar, which suggests that human height might have been evolving differently across these populations. Hirschhorn's team studied variants in the genome that are known to have small but consistent effects on height: people inheriting the "tall" version of these variants are known to be slightly taller on average than people inheriting the "short" versions of the same variants.

The researchers discovered that, in northern Europe, the "tall" versions of these variants are consistently a little more common than they are in southern Europe. The combined effects of the "tall" versions being more common can partly explain why northern Europeans are on average taller than southern Europeans. The researchers then showed that these slight differences have arisen as a result of evolution acting at many variants, and acting differently in northern than in southern Europe.

"This paper explains -- at least in part -- why some European populations, such as people from Sweden, are taller on average than others, such as people from Italy," Hirschhorn said.

The researchers were only able to detect this signature of evolution by using the results of recent genome-wide association studies by the GIANT consortium, which identified hundreds of different genetic variants that influence height.