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New Technology Opens Evolutionary Window into Brain Development

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DNA runs across the top and bottom. Skulls show the evolution of man from left to right

One of the great mysteries in biology is how we humans ended up with such large, complex brains. In search of clues, researchers have spent years studying the protein-coding genes activated during neurodevelopment. But some answers may also be hiding in non-coding regions of the human genome, where sequences called regulatory elements increase or decrease the activity of genes.


A fascinating example involves a type of regulatory element called a human accelerated region (HAR). Although “human” is part of this element’s name, it turns out that the genomes of all vertebrates—not just humans—contain the DNA segments now designated as HARs.

In most organisms, HARs show a relatively low rate of mutation, which means these regulatory elements have been highly conserved across species throughout evolutionary time [1]. The big exception is Homo sapiens, in which HARs have exhibited a much higher rate of mutations.

The accelerated rate of HARs mutations observed in humans suggest that, over the course of very long periods of time, these genomic changes might have provided our species with some sort of evolutionary advantage. What might that be? Many have speculated the advantage might involve the brain because HARs are often associated with genes involved in neurodevelopment. Now, in a paper published in the journal Neuron, an NIH-supported team confirms that’s indeed the case [2].

In the new work, researchers found that about half of the HARs in the human genome influence the activity, or expression, of protein-coding genes in neural cells and tissues during the brain’s development [3]. The researchers say their study—the most comprehensive to date of the 3,171 HARs in the human genome—firmly establishes that this type of regulatory element helps to drive patterns of neurodevelopmental gene activity specific to humans.

Yet to be determined is precisely how HARs affect the development of the human brain. The quest to uncover these details will no doubt shed new light on fundamental questions about the brain, its billions of neurons, and their trillions of interconnections. For example, why does human neural development span decades, longer than the life spans of most primates and other mammals? Answering such questions could also reveal new clues into a range of cognitive and behavioral disorders. In fact, early research has already made tentative links between HARs and neurodevelopmental conditions such as autism spectrum disorder and schizophrenia [3].

The latest work was led by Kelly Girskis, Andrew Stergachis, and Ellen DeGennaro, all of whom were in the lab of Christopher Walsh while working on the project. An NIH grantee, Walsh is director of the Allen Discovery Center for Brain Evolution at Boston Children’s Hospital and Harvard Medical School, which is supported by the Paul G. Allen Foundation Frontiers Group, and is an Investigator of the Howard Hughes Medical Institute.

Though HARs have been studied since 2006, one of the big challenges in systematically assessing them has been technological. The average length of a HAR is about 269 bases of DNA, but current technologies for assessing function can only easily analyze DNA molecules that span 150 bases or less.

Ryan Doan, who was then in the Walsh Lab, and his colleagues solved the problem by creating a new machine called CaptureMPRA. (MPRA is short for “massively parallel reporter assays.”) This technological advance cleverly barcodes HARs and, more importantly, makes it possible to analyze HARs up to about 500 bases in length.

Using CaptureMPRA technology in tandem with cell culture studies, researchers rolled up their sleeves and conducted comprehensive, full-sequence analyses of more than 3,000 HARs. In their initial studies, primarily in neural cells, they found nearly half of human HARs are active to drive gene expression in cell culture. Of those, 42 percent proved to have increased ability to enhance gene expression compared to their orthologues, or counterparts, in chimpanzees.

Next, the team integrated these data with an existing epigenetic dataset derived from developing human brain cells, as well as additional datasets generated from sorted brain cell types. They found that many HARs appeared to have the ability to increase the activity of protein-coding genes, while a smaller—but very significant—subset of the HARs appeared to be enhancing gene expression specifically in neural progenitor cells, which are responsible for making various neural cell types.

The data suggest that as the human HAR sequences mutated and diverged from other mammals, they increased their ability to enhance or sometimes suppress the activity of certain genes in neural cells. To illustrate this point, the researchers focused on two HARs that appear to interact specifically with a gene referred to as R17. This gene can have highly variable gene expression patterns not only in different human cell types, but also in cells from other vertebrates and non-vertebrates.

In the human cerebral cortex, the outermost part of the brain that’s responsible for complex behaviors, R17 is expressed only in neural progenitor cells and only at specific time points. The researchers found that R17 slows the progression of neural progenitor cells through the cell cycle. That might seem strange, given the billions of neurons that need to be made in the cortex. But it’s consistent with the biology. In the human, it takes more than 130 days for the cortex to complete development, compared to about seven days in the mouse.

Clearly, to learn more about how the human brain evolved, researchers will need to look for clues in many parts of the genome at once, including its non-coding regions. To help researchers navigate this challenging terrain, the Walsh team has created an online resource displaying their comprehensive HAR data. It will appear soon, under the name HAR Hub, on the University of California Santa Cruz Genome Browser.

References:

[1] An RNA gene expressed during cortical development evolved rapidly in humans. Pollard KS, Salama SR, Lambert N, Lambot MA, Coppens S, Pedersen JS, Katzman S, King B, Onodera C, Siepel A, Kern AD, Dehay C, Igel H, Ares M Jr, Vanderhaeghen P, Haussler D. Nature. 2006 Sep 14;443(7108):167-72.

[2] Rewiring of human neurodevelopmental gene regulatory programs by human accelerated regions. Girskis KM, Stergachis AB, DeGennaro EM, Doan RN, Qian X, Johnson MB, Wang PP, Sejourne GM, Nagy MA, Pollina EA, Sousa AMM, Shin T, Kenny CJ, Scotellaro JL, Debo BM, Gonzalez DM, Rento LM, Yeh RC, Song JHT, Beaudin M, Fan J, Kharchenko PV, Sestan N, Greenberg ME, Walsh CA. Neuron. 2021 Aug 25:S0896-6273(21)00580-8.

[3] Mutations in human accelerated regions disrupt cognition and social behavior. Doan RN, Bae BI, Cubelos B, Chang C, Hossain AA, Al-Saad S, Mukaddes NM, Oner O, Al-Saffar M, Balkhy S, Gascon GG; Homozygosity Mapping Consortium for Autism, Nieto M, Walsh CA. Cell. 2016 Oct 6;167(2):341-354.

Links:

Christopher Walsh Laboratory (Boston Children’s Hospital and Harvard Medical School)

The Paul G. Allen Foundation Frontiers Group (Seattle)

NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute of General Medical Sciences; National Cancer Institute


The Amazing Brain: Tracking Molecular Events with Calling Cards

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In days mostly gone by, it was fashionable in some circles for people to hand out calling cards to mark their arrival at special social events. This genteel human tradition is now being adapted to the lab to allow certain benign viruses to issue their own high-tech calling cards and mark their arrival at precise locations in the genome. These special locations show where there’s activity involving transcription factors, specialized proteins that switch genes on and off and help determine cell fate.

The idea is that myriad, well-placed calling cards can track brain development over time in mice and detect changes in transcription factor activity associated with certain neuropsychiatric disorders. This colorful image, which won first place in this year’s Show Us Your BRAINs! Photo and Video contest, provides a striking display of these calling cards in action in living brain tissue.

The image comes from Allen Yen, a PhD candidate in the lab of Joseph Dougherty, collaborating with the nearby lab of Rob Mitra. Both labs are located in the Washington University School of Medicine, St. Louis.

Yen and colleagues zoomed in on this section of mouse brain tissue under a microscope to capture dozens of detailed images that they then stitched together to create this high-resolution overview. The image shows neural cells (red) and cell nuclei (blue). But focus in on the neural cells (green) concentrated in the brain’s outer cortex (top) and hippocampus (two lobes in the upper center). They’ve been labelled with calling cards that were dropped off by adeno-associated virus [1].

Once dropped off, a calling card doesn’t bear a pretentious name or title. Rather, the calling card, is a small mobile snippet of DNA called a transposon. It gets dropped off with the other essential component of the technology: a specialized enzyme called a transposase, which the researchers fuse to one of many specific transcription factors of interest.

Each time one of these transcription factors of interest binds DNA to help turn a gene on or off, the attached transposase “grabs” a transposon calling card and inserts it into the genome. As a result, it leaves behind a permanent record of the interaction.

What’s also nice is the calling cards are programmed to give away their general locations. That’s because they encode a fluorescent marker (in this image, it’s a green fluorescent protein). In fact, Yen and colleagues could look under a microscope and tell from all the green that their calling card technology was in place and working as intended.
The final step, though, was to find out precisely where in the genome those calling cards had been left. For this, the researchers used next-generation sequencing to produce a cumulative history and map of each and every calling card dropped off in the genome.

These comprehensive maps allow them to identify important DNA-protein binding events well after the fact. This innovative technology also enables scientists to attribute past molecular interactions with observable developmental outcomes in a way that isn’t otherwise possible.

While the Mitra and Dougherty labs continue to improve upon this technology, it’s already readily adaptable to answer many important questions about the brain and brain disorders. In fact, Yen is now applying the technology to study neurodevelopment in mouse models of neuropsychiatric disorders, specifically autism spectrum disorder (ASD) [2]. This calling card technology also is available for any lab to deploy for studying a transcription factor of interest.

This research is supported by the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. One of the major goals of BRAIN Initiative is to accelerate the development and application of innovative technologies to gain new understanding of the brain. This award-winning image is certainly a prime example of striving to meet this goal. I’ll look forward to what these calling cards will tell us in the future about ASD and other important neurodevelopmental conditions affecting the brain.

References:

[1] A viral toolkit for recording transcription factor-DNA interactions in live mouse tissues. Cammack AJ, Moudgil A, Chen J, Vasek MJ, Shabsovich M, McCullough K, Yen A, Lagunas T, Maloney SE, He J, Chen X, Hooda M, Wilkinson MN, Miller TM, Mitra RD, Dougherty JD. Proc Natl Acad Sci U S A. 2020 May 5;117(18):10003-10014.

[2] A MYT1L Syndrome mouse model recapitulates patient phenotypes and reveals altered brain development due to disrupted neuronal maturation. Jiayang Chen, Mary E. Lambo, Xia Ge, Joshua T. Dearborn, Yating Liu, Katherine B. McCullough, Raylynn G. Swift, Dora R. Tabachnick, Lucy Tian, Kevin Noguchi, Joel R. Garbow, John N. Constantino. bioRxiv. May 27, 2021.

Links:

Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)

Autism Spectrum Disorder (National Institute of Mental Health/NIH)

Dougherty Lab (Washington University School of Medicine, St. Louis)

Mitra Lab (Washington University School of Medicine)

Show Us Your BRAINs! Photo and Video Contest (BRAIN Initiative/NIH)

NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Center for Advancing Translational Sciences; National Human Genome Research Institute; National Institute of General Medical Sciences


The Amazing Brain: A Sharper Image of the Pyramidal Tract

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Flip the image above upside down, and the shape may remind you of something. If you think it resembles a pyramid, then you and a lot of great neuroscientists are thinking alike. What you are viewing is a colorized, 3D reconstruction of a pyramidal tract, which are bundles of nerve fibers that originate from the brain’s cerebral cortex and relay signals to the brainstem or the spinal cord. These signals control many important activities, including the voluntary movement of our arms, legs, head, and face.

For a while now, it’s been possible to combine a specialized form of magnetic resonance imaging (MRI) with computer modeling tools to produce 3D reconstructions of complicated networks of nerve fibers, such as the pyramidal tract. Still, for technical reasons, the quality of these reconstructions has remained poor in parts of the brain where nerve fibers cross at angles of 40 degrees or less.

The video above demonstrates how adding a sophisticated algorithm, called Orientation Distribution Function (ODF)-Fingerprinting, to such modeling can help overcome this problem when reconstructing a pyramidal tract. It has potential to enhance the reliability of these 3D reconstructions as neurosurgeons begin to use them to plan out their surgeries to help ensure they are carried out with the utmost safety and precision.

In the first second of the video, you see gray, fuzzy images from a diffusion MRI of the pyramidal tract. But, very quickly, a more colorful, detailed 3D reconstruction begins to appear, swiftly filling in from the top down. Colors are used to indicate the primary orientations of the nerve fibers: left to right (red), back to front (green), and top to bottom (blue). The orange, magenta, and other colors represent combinations of these primary directional orientations.

About three seconds into the video, a rough draft of the 3D reconstruction is complete. The top of the pyramidal tract looks pretty good. However, looking lower down, you can see distortions in color and relatively poor resolution of the nerve fibers in the middle of the tract—exactly where the fibers cross each other at angles of less than 40 degrees. So, researchers tapped into the power of their new ODF-Fingerprinting software to improve the image—and, starting about nine seconds into the video, you can see an impressive final result.

The researchers who produced this amazing video are Patryk Filipiak and colleagues in the NIH-supported lab of Steven Baete, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York. The work paired diffusion MRI data from the NIH Human Connectome Project with the ODF-Fingerprinting algorithm, which was created by Baete to incorporate additional MRI imaging data on the shape of nerve fibers to infer their directionality [1].

This innovative approach to imaging recently earned Baete’s team second place in the 2021 “Show Us Your BRAINs” Photo and Video contest, sponsored by the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. But researchers aren’t stopping there! They are continuing to refine ODF-Fingerprinting, with the aim of modeling the pyramidal tract in even higher resolution for use in devising new and better ways of helping people undergoing neurosurgery.

Reference:

[1] Fingerprinting Orientation Distribution Functions in diffusion MRI detects smaller crossing angles. Baete SH, Cloos MA, Lin YC, Placantonakis DG, Shepherd T, Boada FE. Neuroimage. 2019 Sep;198:231-241.

Links:

Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)

Human Connectome Project (University of Southern California, Los Angeles)

Steven Baete (Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York)

Show Us Your BRAINs! Photo and Video Contest (BRAIN Initiative/NIH)

NIH Support: National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Cancer Institute


How Our Brains Replay Memories

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Retrieving a Memory
Caption: Encoding and replaying learned memory. Left panel shows the timed sequence of neurons firing in a part of a person’s brain involved in memory as it encodes the random pair of words, “crow” and “jeep.” Colors are assigned to different neurons to differentiate their firing within the sequence. Right panel shows a highly similar timed sequence of those same neurons firing just before a person given the word “jeep,” recalled and said the correct answer “crow.” Credit: Vaz AP, Science, 2020.

Note to my blog readers: the whole world is now facing a major threat from the COVID-19 pandemic. We at NIH are doing everything we can to apply the best and most powerful science to the development of diagnostics, therapeutics, and vaccines, while also implementing public health measures to protect our staff and the patients in our hospital. This crisis is expected to span many weeks, and I will occasionally report on COVID-19 in this blog format. Meanwhile, science continues to progress on many other fronts—and so I will continue to try to bring you stories across a wide range of topics. Perhaps everyone can use a little break now and then from the coronavirus news? Today’s blog takes you into the intricacies of memory.

When recalling the name of an acquaintance, you might replay an earlier introduction, trying to remember the correct combination of first and last names. (Was it Scott James? Or James Scott?) Now, neuroscientists have found that in the split second before you come up with the right answer, your brain’s neurons fire in the same order as when you first learned the information [1].

This new insight into memory retrieval comes from recording the electrical activity of thousands of neurons in the brains of six people during memory tests of random word pairs, such as “jeep” and “crow.” While similar firing patterns had been described before in mice, the new study is the first to confirm that the human brain stores memories in specific sequences of neural activity that can be replayed again and again.

The new study, published in the journal Science, is the latest insight from neurosurgeon and researcher Kareem Zaghloul at NIH’s National Institute of Neurological Disorders and Stroke (NINDS). Zaghloul’s team has for years been involved in an NIH Clinical Center study for patients with drug-resistant epilepsy whose seizures cannot be controlled with drugs.

As part of this work, his surgical team often temporarily places a 4 millimeter-by-4 millimeter array of tiny electrodes on the surface of the brains of the study’s participants. They do this in an effort to pinpoint brain tissues that may be the source of their seizures before performing surgery to remove them. With a patient’s informed consent to take part in additional research, the procedure also has led to a series of insights into what happens in the human brain when we make and later retrieve new memories.

Here’s how it works: The researchers record electrical currents as participants are asked to learn random word pairs presented to them on a computer screen, such as “cake” and “fox,” or “lime” and “camel.” After a period of rest, their brain activity is again recorded as they are given a word and asked to recall the matching word.

Last year, the researchers reported that the split second before a person got the right answer, tiny ripples of electrical activity appeared in two specific areas of the brain [2]. The team also had shown that, when a person correctly recalled a word pair, the brain showed patterns of activity that corresponded to those formed when he or she first learned to make a word association.

The new work takes this a step further. As study participants learned a word pair, the researchers noticed not only the initial rippling wave of electricity, but also that particular neurons in the brain’s cerebral cortex fired repeatedly in a sequential order. In fact, with each new word pair, the researchers observed unique firing patterns among the active neurons.

If the order of neuronal firing was essential for storing new memories, the researchers reasoned that the same would be true for correctly retrieving the information. And, indeed, that’s what they were able to show. For example, when individuals were shown “cake” for a second time, they replayed a very similar firing pattern to the one recorded initially for this word just milliseconds before correctly recalling the paired word “fox.”

The researchers then calculated the average sequence similarity between the firing patterns of learning and retrieval. They found that as a person recalled a word, those patterns gradually became more similar. Just before a correct answer was given, the recorded neurons locked onto the right firing sequence. That didn’t happen when a person gave an incorrect answer.

Further analysis confirmed that the exact order of neural firing was specific to each word pair. The findings show that our memories are encoded as unique sequences that must be replayed for accurate retrieval, though we still don’t understand the molecular mechanisms that undergird this.

Zaghloul reports that there’s still more to learn about how these processes are influenced by other factors such as our attention. It’s not yet known whether the brain replays sequences similarly when retrieving longer-term memories. Along with these intriguing insights into normal learning and memory, the researchers think this line of research will yield important clues as to what changes in people who suffer from memory disorders, with potentially important implications for developing the next generation of treatments.

Reference:

[1] Replay of cortical spiking sequences during human memory retrieval. Vaz AP, Wittig JH Jr, Inati SK, Zaghloul KA. Science. 2020 Mar 6;367(6482):1131-1134.

[2] Coupled ripple oscillations between the medial temporal lobe and neocortex retrieve human memory. Vaz AP, Inati SK, Brunel N, Zaghloul KA. Science. 2019 Mar 1;363(6430):975-978.

Links:

Epilepsy Information Page (National Institute of Neurological Disorders and Stroke/NIH)

Brain Basics (NINDS)

Zaghloul Lab (NINDS)

NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences


Largest-Ever Genetic Study of Autism Yields New Insights

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Baby and DNA Strands

Anyone who’s spent time with people affected by autism spectrum disorder (ASD) can tell you that it’s a very complex puzzle. The wide variability seen among individuals with this group of developmental brain disorders, which can disrupt communication, behavior control, and social skills, has also posed a huge challenge for researchers trying to identify underlying genetic and environmental factors. So, it’s no surprise that there’s been considerable interest in the recent findings of the largest-ever genetic study of ASD.

In a landmark study that analyzed the DNA of more than 35,000 people from around the world, the NIH-funded international Autism Sequencing Consortium (ASC) identified variants in 102 genes associated with increased risk of developing ASD, up from 65 identified previously. Of the 102 genes, 60 had not been previously linked to ASD and 53 appeared to be primarily connected to ASD as opposed to other types of intellectual disability or developmental delay. It is expected that this newfound genetic knowledge will serve to improve understanding of the complex biological mechanisms involved in ASD, ultimately paving the way for new approaches to diagnosis and treatment.

The study reported in the journal Cell was led by Joseph Buxbaum, Icahn School of Medicine at Mount Sinai, New York; Stephan Sanders, University of California, San Francisco; Kathryn Roeder, Carnegie Mellon University, Pittsburgh, PA; and Mark Daly, Massachusetts General Hospital, Boston, MA and the Broad Institute of MIT and Harvard, Cambridge, MA. These researchers and their teams faced what might seem like a rather daunting task.

While common genetic variants collectively are known to contribute substantially to ASD, rare variants have been recognized individually as more major contributors to a person’s risk of developing ASD. The challenge was how to find such rare variants—whether inherited or newly arising.

To do so, the researchers needed to analyze a enormous amount of DNA data. Fortunately, they and their ASC colleagues already had assembled a vast trove of data. Over the last decade, the ASC had collected DNA samples with full consent from thousands of people with and without ASD, including unaffected siblings and parents. All were aggregated with other studies, and, at the time of this investigation, they had gathered 35,584 unique samples. Those included more than 21,000 family-based samples and almost 12,000 samples from people diagnosed with ASD.

In search of rare genetic alterations, they sequenced whole exomes, the approximately 1.5 percent of the genome that codes for proteins. Their search produced a list of 102 ASD-associated genes, including 30 that had never been implicated in any developmental brain disorder previously.

But that was just the beginning. Next, the ASC team dug deeper into this list. The researchers knew from previous work that up to half of people with ASD also have an intellectual disability or developmental delay. Many of the associated genes overlap, meaning they play roles in both outcomes. So, in one set of analyses, the team compared the list to the results of another genetic study of people diagnosed with developmental delays, including problems with learning or gross motor skills such as delayed walking.

The detailed comparison allowed them to discern genes that are more associated with features of ASD, as opposed to those that are more specific to these developmental delays. It turns out that 49 of the 102 autism-associated genes were altered more often in people with developmental delay than in those diagnosed with ASD. The other 53 were altered more often in ASD, suggesting that they may be more closely linked to this condition’s unique features.

Further study also showed that people who carried alterations in genes found predominantly in ASD also had better intellectual function. They also were more likely to have learned to walk without a developmental delay.

The 102 new genes fell primarily into one of two categories. Many play a role in the brain’s neural connections. The rest are involved primarily in switching other genes on and off in brain development. Interestingly, they are expressed both in excitatory neurons, which are active in sending signals in the brain, and in inhibitory neurons that squelch such activity. Many of these genes are also commonly expressed in the brain’s cerebral cortex, the outermost part of the brain that is responsible for many complex behaviors.

Overall, these findings underscore that ASD truly does exist on a spectrum. Indeed, there are many molecular paths to this disorder. The ASC researchers continue to collect samples, so we can expect this list of 102 genes will continue to expand in the future.

With these gene discoveries in hand, the researchers will now also turn their attention to unravelling additional details about how these genes function in the brain. The hope is that this growing list of genes will converge on a smaller number of important molecular pathways, pointing the way to new and more precise ways of treating ASD in all its complexity.

Reference:

[1] Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Satterstrom FK, Kosmicki JA, Wang J, Breen MS, De Rubeis S, An JY, Peng M, Collins R, Grove J, Klei L, Stevens C, Reichert J, Mulhern MS, Artomov M, Gerges S, Sheppard B, Xu X, Bhaduri A, Norman U, Brand H, Schwartz G, Nguyen R, Guerrero EE, Dias C; Autism Sequencing Consortium; iPSYCH-Broad Consortium, Betancur C, Cook EH, Gallagher L, Gill M, Sutcliffe JS, Thurm A, Zwick ME, Børglum AD, State MW, Cicek AE, Talkowski ME, Cutler DJ, Devlin B, Sanders SJ, Roeder K, Daly MJ, Buxbaum JD.Cell. 2020 Jan 23. {Epub ahead of print]

Links:

Autism Spectrum Disorder (NIH/National Institute of Mental Health)

Joseph Buxbaum (Icahn School of Medicine at Mount Sinai, New York)

Sanders Lab (University of California, San Francisco)

Kathryn Roeder (Carnegie Mellon University, Pittsburgh, PA)

Mark Daly (Broad Institute of MIT and Harvard, Cambridge, MA)

Autism Sequencing Consortium (Emory University, Atlanta)

NIH Support: National Institute Mental Health; National Human Genome Research Institute


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