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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.


[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.


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

A Real-Time Look at Value-Based Decision Making

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All of us make many decisions every day. For most things, such as which jacket to wear or where to grab a cup of coffee, there’s usually no right answer, so we often decide using values rooted in our past experiences. Now, neuroscientists have identified the part of the mammalian brain that stores information essential to such value-based decision making.

Researchers zeroed in on this particular brain region, known as the retrosplenial cortex (RSC), by analyzing movies—including the clip shown about 32 seconds into this video—that captured in real time what goes on in the brains of mice as they make decisions. Each white circle is a neuron, and the flickers of light reflect their activity: the brighter the light, the more active the neuron at that point in time.

All told, the NIH-funded team, led by Ryoma Hattori and Takaki Komiyama, University of California at San Diego, La Jolla, made recordings of more than 45,000 neurons across six regions of the mouse brain [1]. Neural activity isn’t usually visible. But, in this case, researchers used mice that had been genetically engineered so that their neurons, when activated, expressed a protein that glowed.

Their system was also set up to encourage the mice to make value-based decisions, including choosing between two drinking tubes, each with a different probability of delivering water. During this decision-making process, the RSC proved to be the region of the brain where neurons persistently lit up, reflecting how the mouse evaluated one option over the other.

The new discovery, described in the journal Cell, comes as something of a surprise to neuroscientists because the RSC hadn’t previously been implicated in value-based decisions. To gather additional evidence, the researchers turned to optogenetics, a technique that enabled them to use light to inactivate neurons in the RSC’s of living animals. These studies confirmed that, with the RSC turned off, the mice couldn’t retrieve value information based on past experience.

The researchers note that the RSC is heavily interconnected with other key brain regions, including those involved in learning, memory, and controlling movement. This indicates that the RSC may be well situated to serve as a hub for storing value information, allowing it to be accessed and acted upon when it is needed.

The findings are yet another amazing example of how advances coming out of the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative are revolutionizing our understanding of the brain. In the future, the team hopes to learn more about how the RSC stores this information and sends it to other parts of the brain. They note that it will also be important to explore how activity in this brain area may be altered in schizophrenia, dementia, substance abuse, and other conditions that may affect decision-making abilities. It will also be interesting to see how this develops during childhood and adolescence.


[1] Area-Specificity and Plasticity of History-Dependent Value Coding During Learning. Hattori R, Danskin B, Babic Z, Mlynaryk N, Komiyama T. Cell. 2019 Jun 13;177(7):1858-1872.e15.


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

Komiyama Lab (UCSD, La Jolla)

NIH Support: National Institute of Neurological Disorders and Stroke; National Eye Institute; National Institute on Deafness and Other Communication Disorders

A Neuronal Light Show

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Credit: Chen X, Cell, 2019

These colorful lights might look like a video vignette from one of the spectacular evening light shows taking place this holiday season. But they actually aren’t. These lights are illuminating the way to a much fuller understanding of the mammalian brain.

The video features a new research method called BARseq (Barcoded Anatomy Resolved by Sequencing). Created by a team of NIH-funded researchers led by Anthony Zador, Cold Spring Harbor Laboratory, NY, BARseq enables scientists to map in a matter of weeks the location of thousands of neurons in the mouse brain with greater precision than has ever been possible before.

How does it work? With BARseq, researchers generate uniquely identifying RNA barcodes and then tag one to each individual neuron within brain tissue. As reported recently in the journal Cell, those barcodes allow them to keep track of the location of an individual cell amid millions of neurons [1]. This also enables researchers to map the tangled paths of individual neurons from one region of the mouse brain to the next.

The video shows how the researchers read the barcodes. Each twinkling light is a barcoded neuron within a thin slice of mouse brain tissue. The changing colors from frame to frame correspond to one of the four letters, or chemical bases, in RNA (A=purple, G=blue, U=yellow, and C=white). A neuron that flashes blue, purple, yellow, white is tagged with a barcode that reads GAUC, while yellow, white, white, white is UCCC.

By sequencing and reading the barcodes to distinguish among seemingly identical cells, the researchers mapped the connections of more than 3,500 neurons in a mouse’s auditory cortex, a part of the brain involved in hearing. In fact, they report they’re now able to map tens of thousands of individual neurons in a mouse in a matter of weeks.

What makes BARseq even better than the team’s previous mapping approach, called MAPseq, is its ability to read the barcodes at their original location in the brain tissue [2]. As a result, they can produce maps with much finer resolution. It’s also possible to maintain other important information about each mapped neuron’s identity and function, including the expression of its genes.

Zador reports that they’re continuing to use BARseq to produce maps of other essential areas of the mouse brain with more detail than had previously been possible. Ultimately, these maps will provide a firm foundation for better understanding of human thought, consciousness, and decision-making, along with how such mental processes get altered in conditions such as autism spectrum disorder, schizophrenia, and depression.

Here’s wishing everyone a safe and happy holiday season. It’s been a fantastic year in science, and I look forward to bringing you more cool NIH-supported research in 2020!


[1] High-Throughput Mapping of Long-Range Neuronal Projection Using In Situ Sequencing. Chen X, Sun YC, Zhan H, Kebschull JM, Fischer S, Matho K, Huang ZJ, Gillis J, Zador AM. Cell. 2019 Oct 17;179(3):772-786.e19.

[2] High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA. Kebschull JM, Garcia da Silva P, Reid AP, Peikon ID, Albeanu DF, Zador AM. Neuron. 2016 Sep 7;91(5):975-987.


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

Zador Lab (Cold Spring Harbor Laboratory, Cold Spring Harbor, NY)

NIH Support: National Institute of Neurological Disorders and Stroke; National Institute on Drug Abuse; National Cancer Institute

Multiplex Rainbow Technology Offers New View of the Brain

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Proteins imaged with this new approach
Caption: Confocal LNA-PRISM imaging of neuronal synapses. Conventional images of cell nuclei and two proteins (top row, three images on the left), along with 11 PRISM images of proteins and one composite, multiplexed image (bottom row, right). Credit: Adapted from Guo SM, Nature Communications, 2019

The NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative is revolutionizing our understanding of how the brain works through its creation of new imaging tools. One of the latest advances—used to produce this rainbow of images—makes it possible to view dozens of proteins in rapid succession in a single tissue sample containing thousands of neural connections, or synapses.

Apart from their colors, most of these images look nearly identical at first glance. But, upon closer inspection, you’ll see some subtle differences among them in both intensity and pattern. That’s because the images capture different proteins within the complex network of synapses—and those proteins may be present in that network in different amounts and locations. Such findings may shed light on key differences among synapses, as well as provide new clues into the roles that synaptic proteins may play in schizophrenia and various other neurological disorders.

Synapses contain hundreds of proteins that regulate the release of chemicals called neurotransmitters, which allow neurons to communicate. Each synaptic protein has its own specific job in the process. But there have been longstanding technical difficulties in observing synaptic proteins at work. Conventional fluorescence microscopy can visualize at most four proteins in a synapse.

As described in Nature Communications [1], researchers led by Mark Bathe, Massachusetts Institute of Technology (MIT), Cambridge, and Jeffrey Cottrell, Broad Institute of MIT and Harvard, Cambridge, have just upped this number considerably while delivering high quality images. They did it by adapting an existing imaging method called DNA PAINT [2]. The researchers call their adapted method PRISM. It is short for: Probe-based Imaging for Sequential Multiplexing.

Here’s how it works: First, researchers label proteins or other molecules of interest using antibodies that recognize those proteins. Those antibodies include a unique DNA probe that helps with the next important step: making the proteins visible under a microscope.

To do it, they deliver short snippets of complementary fluorescent DNA, which bind the DNA-antibody probes. While each protein of interest is imaged separately, researchers can easily wash the probes from a sample to allow a series of images to be generated, each capturing a different protein of interest.

In the original DNA PAINT, the DNA strands bind and unbind periodically to create a blinking fluorescence that can be captured using super-resolution microscopy. But that makes the process slow, requiring about half an hour for each protein.

To speed things up with PRISM, Bathe and his colleagues altered the fluorescent DNA probes. They used synthetic DNA that’s specially designed to bind more tightly or “lock” to the DNA-antibody. This gives a much brighter signal without the blinking effect. As a result, the imaging can be done faster, though at slightly lower resolution.

Though the team now captures images of 12 proteins within a sample in about an hour, this is just a start. As more DNA-antibody probes are developed for synaptic proteins, the team can readily ramp up this number to 30 protein targets.

Thanks to the BRAIN Initiative, researchers now possess a powerful new tool to study neurons. PRISM will help them learn more mechanistically about the inner workings of synapses and how they contribute to a range of neurological conditions.


[1] Multiplexed and high-throughput neuronal fluorescence imaging with diffusible probes. Guo SM, Veneziano R, Gordonov S, Li L, Danielson E, Perez de Arce K, Park D, Kulesa AB, Wamhoff EC, Blainey PC, Boyden ES, Cottrell JR, Bathe M. Nat Commun. 2019 Sep 26;10(1):4377.

[2] Super-resolution microscopy with DNA-PAINT. Schnitzbauer J, Strauss MT, Schlichthaerle T, Schueder F, Jungmann R. Nat Protoc. 2017 Jun;12(6):1198-1228.


Schizophrenia (National Institute of Mental Health)

Mark Bathe (Massachusetts Institute of Technology, Cambridge)

Jeffrey Cottrell (Broad Institute of MIT and Harvard, Cambridge)

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

NIH Support: National Institute of Mental Health; National Human Genome Research Institute; National Institute of Neurological Disorders and Stroke; National Institute of Environmental Health Sciences

People Read Facial Expressions Differently

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Credit: Lydia Polimeni, NIH

What do you see in the faces above? We constantly make assumptions about what others are feeling based on their facial expressions, such as smiling or frowning. Many have even suggested that human facial expressions represent a universal language. But an NIH-funded research team recently uncovered evidence that different people may read common facial expressions in surprisingly different ways.

In a study published in Nature Human Behaviour, the researchers found that each individual’s past experience, beliefs, and conceptual knowledge of emotions will color how he or she interprets facial expressions [1]. These findings are not only fascinating, they might lead to new ways to help people who sometimes struggle with reading social cues, including those with anxiety, depression, bipolar disorder, schizophrenia, or autism spectrum disorder.

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