Virtual 3D faces can now be produced from DNA code. The application,
developed by Mark Shriver of Pennsylvania State University, produces a
virtual mug shot of potential criminals. Pictured here is a work flow
diagram showing how facial features were processed for the application. (Photo : PLOS ONE)
Models of a criminal's face may so be generated from any trace of DNA
left at the scene of a crime. Computer-generated 3D maps will show
exactly how the suspect would have looked from an angle.
Mark Shriver of Pennsylvania State University and his team developed
the application, which produces a virtual mug shot of potential
criminals.
Shriver and his team took 3D images of almost 600 volunteers, coming
from a wide range of racial and ethnic groups. They superimposed more
than 7,000 digital points of reference on the facial features and
recorded the exact position of each of those markers. These grids were
used to measure how the facial features of a subject differ from the
norm. For instance, they would quantify the distance between the eyes of
a subject, and record how much more narrow or wide they were than
average.
A computer model was created to see how facial features were affected
by sex, genes and race. Each of the study participants were tested for
76 genetic variants that cause facial mutations. Once corrected for
race and sex, 20 genes with 24 variants appeared to reliably predict
facial shape.
"Results on a set of 20 genes showing significant effects on facial
features provide support for this approach as a novel means to identify
genes affecting normal-range facial features and for approximating the
appearance of a face from genetic markers," the researchers wrote in the article announcing the results.
As part of data collection, the team asked participants to rate faces based on perceived ethnicity, as well as gender.
Digital facial reconstructions from DNA have proven to be notoriously
unreliable. Even seemingly simple information like height can be
difficult to determine through genetic analysis. Other aspects of human
physiology, such as eye color, are easier to predict using genetic
analysis.
"One thing we're certain of [is] there's no single gene that suddenly
makes your nose big or small," Kun Tang, from the Shanghai Institutes
for Biological Sciences in China, said.
In order to further refine the system, Shriver has already started
sampling more people. Adding further diversity to the database should
allow the application to make even more accurate recreations of a
person's face. In the next round of testing, 30,000 different points
will be used instead of 7,000. Merging this development with 3D
printers would make it possible to print out 3D models of a person, just based on a piece of DNA.
Such models - digital or physical - are not likely to be used in
courts anytime soon. A more likely scenario is use as modern day version
of police sketches, assisting police in finding suspects. Only after an
arrest would the DNA of a suspect be compared to that collected at the
scene of a crime.
Creating 3D facial models from genetic evidence was detailed in Nature.
Newly discovered mechanism could help researchers understand ageing process and lead to ways of slowing it down
Horvath looked at the
DNA of nearly 8,000 samples of 51 different healthy and cancerous cells
and tissues. Photograph: Zoonar GmbH/Alamy
A US scientist has discovered an internal body clock based on DNA that measures the biological age of our tissues and organs.
The
clock shows that while many healthy tissues age at the same rate as the
body as a whole, some of them age much faster or slower. The age of
diseased organs varied hugely, with some many tens of years "older" than
healthy tissue in the same person, according to the clock.
Researchers say that unravelling the mechanisms behind the clock will help them understand the ageing process and hopefully lead to drugs and other interventions that slow it down.
Therapies
that counteract natural ageing are attracting huge interest from
scientists because they target the single most important risk factor for
scores of incurable diseases that strike in old age.
"Ultimately, it would be very exciting to develop therapy interventions to reset the clock and hopefully keep us young," said Steve Horvath, professor of genetics and biostatistics at the University of California in Los Angeles.
Horvath
looked at the DNA of nearly 8,000 samples of 51 different healthy and
cancerous cells and tissues. Specifically, he looked at how methylation,
a natural process that chemically modifies DNA, varied with age.
Horvath
found that the methylation of 353 DNA markers varied consistently with
age and could be used as a biological clock. The clock ticked fastest in
the years up to around age 20, then slowed down to a steadier rate.
Whether the DNA changes cause ageing or are caused by ageing is an
unknown that scientists are now keen to work out.
"Does this
relate to something that keeps track of age, or is a consequence of age?
I really don't know," Horvath told the Guardian. "The development of
grey hair is a marker of ageing, but nobody would say it causes ageing,"
he said.
The clock has already revealed some intriguing results.
Tests on healthy heart tissue showed that its biological age – how worn
out it appears to be – was around nine years younger than expected.
Female breast tissue aged faster than the rest of the body, on average
appearing two years older.
Diseased tissues also aged at different rates, with cancers speeding up the clock by an average of 36 years. Some brain cancer tissues taken from children had a biological age of more than 80 years.
"Female
breast tissue, even healthy tissue, seems to be older than other
tissues of the human body. That's interesting in the light that breast
cancer is the most common cancer in women. Also, age is one of the
primary risk factors of cancer, so these types of results could explain
why cancer of the breast is so common," Horvath said.
Healthy
tissue surrounding a breast tumour was on average 12 years older than
the rest of the woman's body, the scientist's tests revealed.
Writing in the journal Genome Biology,
Horvath showed that the biological clock was reset to zero when cells
plucked from an adult were reprogrammed back to a stem-cell-like state.
The process for converting adult cells into stem cells, which can grow
into any tissue in the body, won the Nobel prize in 2012 for Sir John Gurdon at Cambridge University and Shinya Yamanaka at Kyoto University.
"It
provides a proof of concept that one can reset the clock," said
Horvath. The scientist now wants to run tests to see how
neurodegenerative and infectious diseases affect, or are affected by,
the biological clock.
"These data could prove valuable in
furthering our knowledge of the biological changes that are linked to
the ageing process," said Veryan Codd, who works on the effects of
biological ageing in cardiovascular disease at Leicester University. "It
will be important to determine whether the accelerated ageing, as
described here, is associated with other age-related diseases and if it
is a causal factor in, or a consequence of, disease development.
"As
more data becomes available, it will also be interesting to see whether
a similar approach could identify tissue-specific ageing signatures,
which could also prove important in disease mechanisms," she added.
An example of a chemical program. Here, A, B and C are different chemical species.
Similar to using Python or Java to write code for a computer,
chemists soon could be able to use a structured set of instructions to
“program” how DNA molecules interact in a test tube or cell.
A team led by the University of Washington has developed a
programming language for chemistry that it hopes will streamline efforts
to design a network that can guide the behavior of chemical-reaction
mixtures in the same way that embedded electronic controllers guide
cars, robots and other devices. In medicine, such networks could serve
as “smart” drug deliverers or disease detectors at the cellular level.
Chemists and educators teach and use chemical reaction networks, a
century-old language of equations that describes how mixtures of
chemicals behave. The UW engineers take this language a step further and
use it to write programs that direct the movement of tailor-made
molecules.
“We start from an abstract, mathematical description of a chemical
system, and then use DNA to build the molecules that realize the desired
dynamics,” said corresponding author Georg Seelig,
a UW assistant professor of electrical engineering and of computer
science and engineering. “The vision is that eventually, you can use
this technology to build general-purpose tools.”
Currently, when a biologist or chemist makes a certain type of
molecular network, the engineering process is complex, cumbersome and
hard to repurpose for building other systems. The UW engineers wanted to
create a framework that gives scientists more flexibility. Seelig
likens this new approach to programming languages that tell a computer
what to do.
“I think this is appealing because it allows you to solve more than
one problem,” Seelig said. “If you want a computer to do something else,
you just reprogram it. This project is very similar in that we can tell
chemistry what to do.”
Humans and other organisms already have complex networks of
nano-sized molecules that help to regulate cells and keep the body in
check. Scientists now are finding ways to design synthetic systems that
behave like biological ones with the hope that synthetic molecules could
support the body’s natural functions. To that end, a system is needed
to create synthetic DNA molecules that vary according to their specific
functions.
The new approach isn’t ready to be applied in the medical field, but
future uses could include using this framework to make molecules that
self-assemble within cells and serve as “smart” sensors. These could be
embedded in a cell, then programmed to detect abnormalities and respond
as needed, perhaps by delivering drugs directly to those cells.
Seelig and colleague Eric Klavins, a UW associate professor of electrical engineering, recently received $2 million
from the National Science Foundation as part of a national initiative
to boost research in molecular programming. The new language will be
used to support that larger initiative, Seelig said.
Co-authors of the paper are Yuan-Jyue Chen, a UW doctoral student in
electrical engineering; David Soloveichik of the University of
California, San Francisco; Niranjan Srinivas at the California Institute
of Technology; and Neil Dalchau, Andrew Phillips and Luca Cardelli of
Microsoft Research.
The research was funded by the National Science Foundation, the
Burroughs Wellcome Fund and the National Centers for Systems Biology.
NEC is working on a suitcase-sized DNA analyzer, which it says will
be able to process samples at the scene of a crime or disaster in as
little as 25 minutes.
The company said it aims to launch the device globally in 2014, and
sell it for around 10 million yen, or US$120,000. It will output samples
that can be quickly matched via the growing number of DNA databases
worldwide.
“At first we will target investigative organizations, like police,”
said spokeswoman Marita Takahashi. “We will also push its use on victims
of natural disasters, to quickly match samples from siblings and
parents.”
NEC hopes to use research and software from its mature fingerprint
and facial matching technology, which have been deployed in everyday
devices such as smartphones and ATMs.
NEC
is working on a suitcase-sized DNA sampler that it says will weigh 35
kilograms and be able to process samples in about 25 minutes.
The company said that the need for cheaper and faster DNA testing
became clear in the aftermath of the Tohoku earthquake and tsunami that
devasted much of Japan’s northeast coastline last year, when authorities
performed nearly 20,000 samples.
NEC pointed to growing databases such as CODIS (Combined DNA Index System) in the U.S. and a Japanese database of DNA samples.
The company said it is aiming to make the device usable for those
with minimal training, requiring only a cotton swab or small blood
sample. NEC aims to make a device that weighs around 35 kilograms,
measuring 850 millimeters by 552mm by 240mm, about the size of a large
suitcase. The unit will run on a 12V power source.
NEC said it will be able to complete three-stage analysis process
using a “lab on a chip” process, a term for for technology that
recreates lab processes on chip-sized components. The basic steps for
analysis include extracting DNA from samples, amplifying the DNA for
analysis, and then separating out the different DNA strands.
The current version of the analyzer takes about an hour for all three tasks, and NEC said it aims to lower that to 25 minutes.
NEC it is carrying out the development of the analyzer together with
partners including Promega, a U.S. biotechnology firm, and is testing it
with a police science research institute in Japan.
Inter-individual variation in facial shape is one of the most noticeable
phenotypes in humans, and it is clearly under genetic regulation;
however, almost nothing is known about the genetic basis of normal human
facial morphology. We therefore conducted a genome-wide association
study for facial shape phenotypes in multiple discovery and replication
cohorts, considering almost ten thousand individuals of European descent
from several countries. Phenotyping of facial shape features was based
on landmark data obtained from three-dimensional head magnetic resonance
images (MRIs) and two-dimensional portrait images. We identified five
independent genetic loci associated with different facial phenotypes,
suggesting the involvement of five candidate genes—PRDM16, PAX3, TP63, C5orf50, and COL17A1—in
the determination of the human face. Three of them have been implicated
previously in vertebrate craniofacial development and disease, and the
remaining two genes potentially represent novel players in the molecular
networks governing facial development. Our finding at PAX3
influencing the position of the nasion replicates a recent GWAS of
facial features. In addition to the reported GWA findings, we
established links between common DNA variants previously associated with
NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape
variations based on a candidate gene approach. Overall our study implies
that DNA variants in genes essential for craniofacial development
contribute with relatively small effect size to the spectrum of normal
variation in human facial morphology. This observation has important
consequences for future studies aiming to identify more genes involved
in the human facial morphology, as well as for potential applications of
DNA prediction of facial shape such as in future forensic applications.
Introduction
The morphogenesis and
patterning of the face is one of the most complex events in mammalian
embryogenesis. Signaling cascades initiated from both facial and
neighboring tissues mediate transcriptional networks that act to direct
fundamental cellular processes such as migration, proliferation,
differentiation and controlled cell death. The complexity of human
facial development is reflected in the high incidence of congenital
craniofacial anomalies, and almost certainly underlies the vast spectrum
of subtle variation that characterizes facial appearance in the human
population.
Facial appearance has
a strong genetic component; monozygotic (MZ) twins look more similar
than dizygotic (DZ) twins or unrelated individuals. The heritability of
craniofacial morphology is as high as 0.8 in twins and families [1], [2], [3]. Some craniofacial traits, such as facial height and position of the lower jaw, appear to be more heritable than others [1], [2], [3].
The general morphology of craniofacial bones is largely genetically
determined and partly attributable to environmental factors [4]–[11]. Although genes have been mapped for various rare craniofacial syndromes largely inherited in Mendelian form [12],
the genetic basis of normal variation in human facial shape is still
poorly understood. An appreciation of the genetic basis of facial shape
variation has far reaching implications for understanding the etiology
of facial pathologies, the origin of major sensory organ systems, and
even the evolution of vertebrates [13], [14].
In addition, it is feasible to speculate that once the majority of
genetic determinants of facial morphology are understood, predicting
facial appearance from DNA found at a crime scene will become useful as
investigative tool in forensic case work [15]. Some externally visible human characteristics, such as eye color [16]–[18] and hair color [19], can already be inferred from a DNA sample with practically useful accuracies.
In a recent candidate
gene study carried out in two independent European population samples,
we investigated a potential association between risk alleles for
non-syndromic cleft lip with or without cleft palate (NSCL/P) and nose
width and facial width in the normal population [20].
Two NSCL/P associated single nucleotide polymorphisms (SNPs) showed
association with different facial phenotypes in different populations.
However, facial landmarks derived from 3-Dimensional (3D) magnetic
resonance images (MRI) in one population and 2-Dimensional (2D) portrait
images in the other population were not completely comparable, posing a
challenge for combining phenotype data. In the present study, we focus
on the MRI-based approach for capturing facial morphology since previous
facial imaging studies by some of us have demonstrated that MRI-derived
soft tissue landmarks represent a reliable data source [21], [22].
In geometric
morphometrics, there are different ways to deal with the confounders of
position and orientation of the landmark configurations, such as (1)
superimposition [23], [24] that places the landmarks into a consensus reference frame; (2) deformation [25]–[27], where shape differences are described in terms of deformation fields of one object onto another; and (3) linear distances [28], [29],
where Euclidean distances between landmarks instead of their
coordinates are measured. Rationality and efficacy of these approaches
have been reviewed and compared elsewhere [30]–[32].
We briefly compared these methods in the context of our genome-wide
association study (GWAS) (see Methods section) and applied them when
appropriate.
We extracted facial
landmarks from 3D head MRI in 5,388 individuals of European origin from
Netherlands, Australia, and Germany, and used partial Procrustes
superimposition (PS) [24], [30], [33]
to superimpose different sets of facial landmarks onto a consensus 3D
Euclidean space. We derived 48 facial shape features from the
superimposed landmarks and estimated their heritability in 79 MZ and 90
DZ Australian twin pairs. Subsequently, we conducted a series of GWAS
separately for these facial shape dimensions, and attempted to replicate
the identified associations in 568 Canadians of European (French)
ancestry with similar 3D head MRI phenotypes and additionally sought
supporting evidence in further 1,530 individuals from the UK and 2,337
from Australia for whom facial phenotypes were derived from 2D portrait
images.
It may look like an ordinary USB memory stick, but a
little gadget that can sequence DNA while plugged into your laptop could
have far-reaching effects on medicine and genetic research.
The UK firm Oxford Nanopore built the
device, called MinION, and claims it can sequence simple genomes – like
those of some viruses and bacteria – in a matter of seconds. More
complex genomes would take longer, but MinION could also be useful for
obtaining quick results in sequencing DNA from cells in a biopsy to look
for cancer, for example, or to determine the genetic identity of bone
fragments at an archaeological dig.
The company demonstrated today at the
Advances in Genome Biology and Technology (AGBT) conference in Marco
Island, Florida, that MinION has sequenced a simple virus called Phi X,
which contains 5000 genetic base pairs.
Proof of principle
This is merely a proof of principle –
"Phi X was the first DNA genome to be sequenced ever," says Nick Loman, a
bioinformatician at the Pallen research group at the University of
Birmingham, UK, and author of the blog Pathogens: Genes and Genomes. But
it shows for the first time that this technology works, he says. "If
you can sequence this genome you should be able to sequence larger
genomes."
Oxford Nanopore is also building a
larger device, GridION, for lab use. Both GridION and MinION operate
using the same technology: DNA is added to a solution containing enzymes
that bind to the end of each strand. When a current is applied across
the solution these enzymes and DNA are drawn to hundreds of wells in a
membrane at the bottom of the solution, each just 10 micrometres in
diameter.
Within each well is a modified version
of the protein alpha hemolysin (AHL), which has a hollow tube just 10
nanometres wide at its core. As the DNA is drawn to the pore the enzyme
attaches itself to the AHL and begins to unzip the DNA, threading one
strand of the double helix through the pore. The unique electrical
characteristics of each base disrupt the current flowing through each
pore, enough to determine which of the four bases is passing through it.
Each disruption is read by the device, like a tickertape reader.
Long strands, and simple
This approach has two key advantages
over other sequencing techniques: first, the DNA does not need to be
amplified - a time-consuming process that replicates the DNA in a sample
to make it abundant enough to make a reliable measurement.
Second, the devices can sequence DNA
strands as long as 10,000 bases continuously, whereas most other
techniques require the DNA to be sheared into smaller fragments of at
most a few hundred bases. This means that once they have been read they
have to be painstakingly reassembled by software like pieces of a
jigsaw. "We just read the entire thing in one go," as with Phi X, says
Clive Brown, Oxford Nanopore's chief technology officer.
But Oxford Nanopore will face stiff
competition. Jonathan Rothberg, a scientist and entrepreneur who founded
rival firm 454 Life Sciences, also announced at the AGBT conference
that his start-up company, Ion Torrent, will be launching a desktop
sequencing machine. Dubbed the Ion Proton, it identifies bases by using
transistors to detect hydrogen ions as they are given off during the
polymerisation of DNA.
This device will be capable of
sequencing a human genome in 2 hours for around $1000, Rothberg claims.
Nanopores are an "elegant" technology, he says, but Ion Torrent already
has a foot in the door. "As we saw last summer with the E. coli outbreak in Germany, people are already now using it," he says.
Pocketful of DNA
By contrast, the MinION would take
about 6 hours to complete a human genome, Brown claims, though the
company plans to market the device for use in shorter sequencing tasks
like identifying pathogens, or screening for genetic mutations that can
increase risk of certain diseases. Each unit is expected to cost $900
when it goes on sale later this year.
"The biggest strength of nanopore
sequencing is that it generates very long reads, which has been a
limitation for most other technologies," says Loman. If the costs,
quality, ease of use and throughput can be brought in line with other
instruments, it will be a "killer technology" for sequencing, he says.
As for clinical applications, David
Rasko at the Institute for Genome Sciences at the University of Maryland
in Baltimore, says the MinION could have huge benefits. "It may have
serious implications for public health and it could really change the
way we do medicine," he says. "You can see every physician walking
around the hospital with a pocketful of these things." And it will
likely increase the number of scientists generating sequencing data by
making the technology cheaper and more accessible, he says.
The first human genome cost $3 billion to complete; now we can sequence the entire population of Chicago for the same price
The mythical "$1,000 genome" is almost upon us, said Jonathan Rothberg, CEO of sequencing technology company Ion Torrent, at MIT's Emerging Technology conference. If his prediction comes true, it will represent an astonishing triumph in rapid technological development. The rate at which genome sequencing has become more affordable isfaster than Moore's law. (You can read a Q&ATRdid with Rothberg earlier this yearhere, and a profile of his companyhere).
"By this time next year sequencing human genomes as fast and cheap as bacterial genome," said Rothberg. (Earlier, he'd commented that his company can now do an entire bacterial genome in about two hours.)
I was in the room on October 19 when he said it, and I would have thought it pure hubris were it not for Rothberg's incredible track record in this area, from founding successful previous-generation sequencing company 454 Life Sciences to recent breakthroughs made with the same technology he proposes will get us to the $1,000 genome.
The Personal Genome Maker is already showing up in clinical labs, even doctors' offices
The key to this breakthrough, says Rothberg, is that the PGM does not rely on conventional wet chemistry to sequence DNA. Instead, it works almost entirely throughconventional microchip technology, which means Ion Torrent is leveraging decades of investment in conventional transistors and chips.
So what's the age of the $1,000 genome look like? Until we know what more of those genes actually correlate with, for most of us it won't be so different from the present.
"Right now don't have very many correlations between those 3 billion base pairs [of the human genome] and outcomes or medicines," says Rothberg. He predicts it will take at least 10 years of clinical experiments with full genome sequencing to get us to the point where we can begin to unlock its value.
"And it will be 20 years before we understand cancer at same level as HIV and can come up with combinations of medicine [tailored] for each individual," says Rothberg.
Even as some scientists and engineers develop improved versions of current computing technology, others are looking into drastically different approaches. DNA computing offers the potential of massively parallel calculations with low power consumption and at small sizes. Research in this area has been limited to relatively small systems, but a group from Caltech recently constructedDNA logic gatesusing over 130 different molecules and used the system to calculate the square roots of numbers. Now, the same group published a paper in Naturethat shows an artificial neural network, consisting of four neurons, created using the same DNA circuits.
The artificial neural network approach taken here is based on the perceptron model, also known as a linear threshold gate. This models the neuron as having many inputs, each with its own weight (or significance). The neuron is fired (or the gate is turned on) when the sum of each input times its weight exceeds a set threshold. These gates can be used to construct compact Boolean logical circuits, and other circuits can be constructed to store memory.
As we described in thelast articleon this approach to DNA computing, the authors represent their implementation with an abstraction called "seesaw" gates. This allows them to design circuits where each element is composed of two base-paired DNA strands, and the interactions between circuit elements occurs as new combinations of DNA strands pair up. The ability of strands to displace each other at a gate (based on things like concentration) creates the seesaw effect that gives the system its name.
In order to construct a linear threshold gate, three basic seesaw gates are needed to perform different operations. Multiplying gates combine a signal and a set weight in a seesaw reaction that uses up fuel molecules as it converts the input signal into output signal. Integrating gates combine multiple inputs into a single summed output, while thresholding gates (which also require fuel) send an output signal only if the input exceeds a designated threshold value. Results are read using reporter gates that fluoresce when given a certain input signal.
To test their designs with a simple configuration, the authors first constructed a single linear threshold circuit with three inputs and four outputs—it compared the value of a three-bit binary number to four numbers. The circuit output the correct answer in each case.
For the primary demonstration on their setup, the authors had their linear threshold circuit play a computer game that tests memory. They used their approach to construct a four-neuronHopfield network, where all the neurons are connected to the others and, after training (tuning the weights and thresholds) patterns can be stored or remembered. The memory game consists of three steps: 1) the human chooses a scientist from four options (in this case, Rosalind Franklin, Alan Turing, Claude Shannon, and Santiago Ramon y Cajal); 2) the human “tells” the memory network the answers to one or more of four yes/no (binary) questions used to identify the scientist (such as, “Did the scientist study neural networks?” or "Was the scientist British?"); and 3) after eight hours of thinking, the DNA memory guesses the answer and reports it through fluorescent signals.
They played this game 27 total times, for a total of 81 possible question/answer combinations (34). You may be wondering why there are three options to a yes/no question—the state of the answers is actually stored using two bits, so that the neuron can be unsure about answers (those that the human hasn't provided, for example) using a third state. Out of the 27 experimental cases, the neural network was able to correctly guess all but six, and these were all cases where two or more answers were not given.
In the best cases, the neural network was able to correctly guess with only one answer and, in general, it was successful when two or more answers were given. Like the human brain, this network was able to recall memory using incomplete information (and, as with humans, that may have been a lucky guess). The network was also able to determine when inconsistent answers were given (i.e. answers that don’t match any of the scientists).
These results are exciting—simulating the brain using biological computing. Unlike traditional electronics, DNA computing components can easily interact and cooperate with our bodies or other cells—who doesn’t dream of being able to download information into your brain (or anywhere in your body, in this case)? Even the authors admit that it’s difficult to predict how this approach might scale up, but I would expect to see a larger demonstration from this group or another in the near future.
The inventor Jonathan Rothberg with a semiconductor chip used in the Ion Torrent machine.
The inventor of a new machine that decodes DNA with semiconductors has
used it to sequence the genome of Gordon Moore, co-founder of Intel, a
leading chip maker.
The inventor, Jonathan Rothberg of Ion Torrent Systems in Guilford,
Conn., is one of several pursuing the goal of a $1,000 human genome,
which he said he could reach by 2013 because his machine is rapidly
being improved.
“Gordon Moore worked out all the tricks that gave us modern
semiconductors, so he should be the first person to be sequenced on a
semiconductor,” Dr. Rothberg said.
At $49,000, the new DNA decoding device is cheaper than its several
rivals. Its promise rests on the potential of its novel technology to be
improved faster than those of machines based on existing techniques.
Manufacturers are racing to bring DNA sequencing costs down to the point
where a human genome can be decoded for $1,000, the sum at which
enthusiasts say genome sequencing could become a routine part of medical
practice.
But the sequencing of Dr. Moore’s genome also emphasizes how far
technology has run ahead of the ability to interpret the information it
generates.
Dr. Moore’s genome has a genetic variant that denotes a “56 percent
chance of brown eyes,” one that indicates a “typical amount of
freckling” and another that confers “moderately higher odds of smelling
asparagus in one’s urine,” Dr. Rothberg and his colleagues reported Wednesday in the journal Nature. There are also two genetic variants in Dr. Moore’s genome said to be associated with “increased risk of mental retardation” — a risk evidently never realized. The clinical value of this genomic information would seem to be close to nil.
Dr. Rothberg said he agreed that few genes right now yield useful
genetic information and that it will be a 10- to 15-year quest to really
understand the human genome. For the moment his machine is specialized
for analyzing much smaller amounts of information, like the handful of
genes highly active in cancer.
The Ion Torrent machine requires only two hours to sequence DNA,
although sample preparation takes longer. The first two genomes of the
deadly E. coli bacteria that swept Europe in the spring were decoded on
the company’s machines.
The earliest DNA sequencing method depended on radioactivity to mark the
four different units that make up genetic material, but as the system
was mechanized, engineers switched to fluorescent chemicals.The
new device is the first commercial system to decode DNA directly on a
semiconductor chip and to work by detecting a voltage change, rather
than light.
About 1.2 million miniature wells are etched into the surface of the
chip and filled with beads holding the DNA strands to be sequenced. A
detector in the floor of the well senses the acidity of the solution in
each well, which rises each time a new unit is added to the DNA strands
on the bead. The cycle is repeated every few seconds until each unit in
the DNA strand has been identified.
Several years ago, Dr. Rothberg invented another DNA sequencing machine,
called the 454, which was used to sequence the genome of James Watson,
the co-discoverer of the structure of DNA. Dr. Rothberg said he was
describing how the machine had “read” Dr. Watson’s DNA to his young son
Noah, who asked why he did not invent a machine to read minds.
Dr. Rothberg said he began his research with the idea of making a
semiconductor chip that could detect an electrical signal moving across a
slice of neural tissue. He then realized the device he had developed
was more suited to sequencing DNA.
George Church, a genome technologist at the Harvard Medical School, said
he estimated the cost to sequence Dr. Moore’s genome at $2 million.
This is an improvement on the $5.7 million it cost in 2008 to sequence
Dr. Watson’s genome on the 454 machine, but not nearly as good as the
$3,700 spent by Complete Genomics to sequence Dr. Church’s genome and
others in 2009.
Dr. Rothberg said he had already reduced the price of his chips to $99
from $250, and today could sequence Dr. Moore’s genome for around
$200,000. Because of Moore’s Law — that the number of transistors
placeable on a chip doubles about every two years — further reductions
in the cost of the DNA sequencing chip are inevitable, Dr. Rothberg
said.
Stephan Schuster, a genome biologist at Penn State, said his two Ion
Torrent machines were “outstanding,” and enabled a project that would
usually have taken two months to be completed in five days.
There is now “a race to the death as to who can sequence faster and
cheaper, always with the goal of human resequencing in mind,” Dr.
Schuster said.
