Brain cells snap strands of DNA in many more places and cell types than researchers previously thought.
The urgency to remember a dangerous experience requires the brain to make a series of potentially dangerous moves: Neurons and other brain cells snap open their DNA in numerous locations — more than previously realized, according to a new study — to provide quick access to genetic instructions for the mechanisms of memory storage.
The extent of these DNA double-strand breaks (DSBs) in multiple key brain regions is surprising and concerning, says study senior author Li-Huei Tsai, Picower Professor of Neuroscience at MIT and director of The Picower Institute for Learning and Memory, because while the breaks are routinely repaired, that process may become more flawed and fragile with age. Tsai's lab has shown that lingering DSBs are associated with neurodegeneration and cognitive decline and that repair mechanisms can falter.
"We wanted to understand exactly how widespread and extensive this natural activity is in the brain upon memory formation because that can give us insight into how genomic instability could undermine brain health down the road," says Tsai, who is also a professor in the Department of Brain and Cognitive Sciences and a leader of MIT's Aging Brain Initiative. "Clearly, memory formation is an urgent priority for healthy brain function, but these new results showing that several types of brain cells break their DNA in so many places to quickly express genes is still striking."
In 2015, Tsai's lab provided the first demonstration that neuronal activity caused DSBs and that they induced rapid gene expression. But those findings, mostly made in lab preparations of neurons, did not capture the full extent of the activity in the context of memory formation in a behaving animal, and did not investigate what happened in cells other than neurons.
In the new study published July 1 in PLOS ONE, lead author and former graduate student Ryan Stott and co-author and former research technician Oleg Kritsky sought to investigate the full landscape of DSB activity in learning and memory. To do so, they gave mice little electrical zaps to the feet when they entered a box, to condition a fear memory of that context. They then used several methods to assess DSBs and gene expression in the brains of the mice over the next half-hour, particularly among a variety of cell types in the prefrontal cortex and hippocampus, two regions essential for the formation and storage of conditioned fear memories. They also made measurements in the brains of mice that did not experience the foot shock to establish a baseline of activity for comparison.
The creation of a fear memory doubled the number of DSBs among neurons in the hippocampus and the prefrontal cortex, affecting more than 300 genes in each region. Among 206 affected genes common to both regions, the researchers then looked at what those genes do. Many were associated with the function of the connections neurons make with each other, called synapses. This makes sense because learning arises when neurons change their connections (a phenomenon called "synaptic plasticity") and memories are formed when groups of neurons connect together into ensembles called engrams.
"Many genes essential for neuronal function and memory formation, and significantly more of them than expected based on previous observations in cultured neurons … are potentially hotspots of DSB formation," the authors wrote in the study.
In another analysis, the researchers confirmed through measurements of RNA that the increase in DSBs indeed correlated closely with increased transcription and expression of affected genes, including ones affecting synapse function, as quickly as 10-30 minutes after the foot shock exposure.
"Overall, we find transcriptional changes are more strongly associated with [DSBs] in the brain than anticipated," they wrote. "Previously we observed 20 gene-associated [DSB] loci following stimulation of cultured neurons, while in the hippocampus and prefrontal cortex we see more than 100-150 gene associated [DSB] loci that are transcriptionally induced."
Snapping with stress
In the analysis of gene expression, the neuroscientists looked at not only neurons but also non-neuronal brain cells, or glia, and found that they also showed changes in expression of hundreds of genes after fear conditioning. Glia called astrocytes are known to be involved in fear learning, for instance, and they showed significant DSB and gene expression changes after fear conditioning.
Among the most important functions of genes associated with fear conditioning-related DSBs in glia was the response to hormones. The researchers therefore looked to see which hormones might be particularly involved and discovered that it was glutocortocoids, which are secreted in response to stress. Sure enough, the study data showed that in glia, many of the DSBs that occurred following fear conditioning occurred at genomic sites related to glutocortocoid receptors. Further tests revealed that directly stimulating those hormone receptors could trigger the same DSBs that fear conditioning did and that blocking the receptors could prevent transcription of key genes after fear conditioning.
Tsai says the finding that glia are so deeply involved in establishing memories from fear conditioning is an important surprise of the new study.
"The ability of glia to mount a robust transcriptional response to glutocorticoids suggest that glia may have a much larger role to play in the response to stress and its impact on the brain during learning than previously appreciated," she and her co-authors wrote.
Damage and danger?
More research will have to be done to prove that the DSBs required for forming and storing fear memories are a threat to later brain health, but the new study only adds to evidence that it may be the case, the authors say.
"Overall we have identified sites of DSBs at genes important for neuronal and glial functions, suggesting that impaired DNA repair of these recurrent DNA breaks which are generated as part of brain activity could result in genomic instability that contribute to aging and disease in the brain," they wrote.
The National Institutes of Health, The Glenn Foundation for Medical Research, and the JPB Foundation provided funding for the research.
The oldest person in history lived to 122
The oldest person in history – a French woman named Jeanne Calment – lived to 122. When she was born in 1875, the average life expectancy was roughly 43.
But just how long could a human actually live? It's a question people have been asking for centuries. While average life expectancy (the number of years a person can expect to live) is relatively easy to calculate, maximum lifespan estimates (the greatest age a human could possibly reach) are much harder to make. Previous studies have placed this limit close to 140 years of age. But a more recent study proposes that the limit to human lifespan is closer to 150.
The oldest and still most widely used method for calculating life expectancy, and thus lifespan, relies on the Gompertz equation. This is the observation, first made in the 19th century, that human death rates from disease increase exponentially with time. Essentially, this means your chance of death – from cancer, heart disease and many infections, for example – roughly doubles every eight to nine years.
There are many ways the formula can be tweaked to account for how different factors (such as sex or disease) affect the lifespan within a population. Gompertz calculations are even used to calculate health insurance premiums – which is why these companies are so interested in whether you smoke, whether you are married and anything else that might allow them to more accurately judge the age at which you will die.
Another approach to figuring out how long we can live is to look at how our organs decline with age, and run that rate of decline against the age at which they stop working. For example, eye function and how much oxygen we use while exercising show a general pattern of decline with ageing, with most calculations indicating organs will only function until the average person is around 120 years old.
But these studies also unmask increasing variation between people as they grow older. For example, some peoples' kidney function declines rapidly with age while in others it hardly changes at all.
Now researchers in Singapore, Russia, and the US have taken a different approach to estimate the maximum human lifespan. Using a computer model, they estimate that the limit of human lifespan is about 150 years.
Living to 150
Intuitively, there should be a relationship between your chance of death and how rapidly and completely you recover from illness. This parameter is a measure of your ability to maintain homeostasis – your normal physiological equilibrium – and is known as resilience. In fact, ageing can be defined as the loss of ability to maintain homeostasis. Typically, the younger the person, the better they are at recovering rapidly from illness.
To conduct the modelling study, the researchers took blood samples from over 70,000 participants aged up to 85 and looked at short-term changes in their blood cell counts. The number of white blood cells a person has can indicate the level of inflammation (disease) in their body, while the volume of red blood cells can indicate a person's risk of heart disease or stroke, or cognitive impairment, such as memory loss. The researchers then simplified this data into a single parameter, which they called the dynamic organisms state indicator (Dosi).
Changes in Dosi values across the participants predicted who would get age-related diseases, how this varied from person to person, and modelled the loss of resilience with age. These calculations predicted that for everyone – regardless of their health or genetics – resilience failed completely at 150, giving a theoretical limit to human lifespan.
But estimates of this type assume that nothing new will be done to a population, such as, no new medical treatments will be found for common diseases. This is a major flaw, since significant progress occurs over a lifetime and this benefits some people more than others.
For example, a baby born today can rely on about 85 years of medical progress to enhance their life expectancy, while an 85-year-old alive now is limited by current medical technologies. As such, the calculation used by these researchers will be relatively accurate for old people but will become progressively less so the younger the person you're looking at.
The Dosi limit for maximum lifespan is about 25% longer than Jeanne Calment lived. So if you're planning to beat it (and her), you need three important things. First is good genes, which makes living to be more than a hundred unassisted a good bet. Second, an excellent diet and exercise plan, which can add up to 15 years to life expectancy. And lastly, a breakthrough in turning our knowledge of the biology of ageing into treatments and medicines that can increase healthy lifespan.
Currently, adding more than 15-20% to healthy lifespan in normal mammals is extremely difficult, partly because our understanding of the biology of ageing remains incomplete. But it's possible to increase the lifespan of much simpler organisms – such as roundworms – by up to ten times.
Even given the current pace of progress, we can confidently expect life expectancy to increase because it has been doing this since Gompertz was alive in the 1860s. In fact, if you spend half an hour reading this article average life expectancy will have increased by six minutes. Unfortunately, at that rate, the average person won't live to 150 for another three centuries.
In 1933, the skull of a 50-year-old male of the Homo longi species was found in China, puzzling researchers.
Despite being nearly perfectly preserved – with square eye sockets, thick brow ridges and large teeth – nobody could work out exactly what it was. The skull is much bigger than that of Homo sapiens and other human species – and its brain size is similar to that of our own species. Historical events left it without a secure place of origin or date, until today.
Now a team of Chinese, Australian and British researchers has finally solved the puzzle – the skull represents a previously unknown extinct human species. The research, published as three studies in the journal Innovation, suggests this is our closest relative in the human family tree.
Dubbed Homo longi, which can be translated as “dragon river", it is named after the province in which it was found. The identification of the skull, thought to have come from a 50-year-old male, was partly based on chemical analysis of sediments trapped inside it.
This confirmed it comes from the upper part of the Huangshan rock formation near Harbin City. The formation was reliably dated to the Middle Pleistocene – 125,000 to 800,000 years ago. Uranium series dating, which involves using the known rate of decay of radioactive uranium atoms in a sample to work out its age, showed that the fossil itself is at least 146,000 years old.
Homo longi can now takes its place among an ever increasing number of hominin species across Africa, Europe and Asia.
Constructing a family tree
Determining the historical relationship between fossil species, however, remains one of the most difficult tasks in the study of human evolution. In recent years, the analysis of ancient DNA has transformed our understanding of the relationship between early populations of modern humans. It has also highlighted how we are different - and similar – to our most immediate relatives, the Neanderthals.
Surviving DNA, however, is very rare for fossil hominins from the Middle Pleistocene, as it tends to degrade over time. Evolutionary relationships must therefore be determined using other evidence. This is usually data on the shape - morphology - of fossils, their age and geographical location.
The Harbin team generated a family tree (“phylogeny") of human lineages to work out how the species relates to modern humans. This tree is based on morphological data from 95 largely complete fossil specimens of different hominin species living during the Middle Pleistocene, including Homo erectus, Homo neanderthalensis, Homo heidelbergensis and Homo sapiens along with their known ages. The tree also suggests that five previously unidentified fossils from northeastern China are from Homo longi.
(Ni et al.)
It predicts that the common ancestor of Homo longi and Homo sapiens lived approximately 950,000 years ago. Furthermore, it suggests that both species shared a common ancestor with Neanderthals a bit more than 1 million years ago, meaning we may have split from Neanderthals 400,000 earlier than previously thought (we used to think it was 600,000 years ago).
Until now, the Neanderthals were considered our closest relative (according to the study, we split from Homo heidelbergensis some 1.3 million years ago). Debates about the evolution of modern humans and what it is that makes us “human" therefore relied heavily on comparisons to Neanderthals. But the new discovery pushes Neanderthals one step further away from ourselves and makes simple comparisons between two species much less important to understanding what ultimately makes us who we are.
There are, however, still significant points of concern about the dating of this phylogenetic model, as recognised by the authors. The predicted dates for the common ancestors between human lineages do not match the dates of actual discovered fossils, or those predicted by the analysis of DNA.
For example, this study proposes that there was Homo sapiens in Eurasia at about 400,000 years ago. But the oldest fossil for this species known outside Africa is little more than half this age. At the same time, the split between Homo sapiens and Neanderthals predicted here at more than 1 million years old does not match the prediction of nuclear DNA analysis, which suggests it happened much later. However, it can be backed up by doing DNA analysis with genetic material taken from the cell's engine, called the mitochondria.
The older estimates presented by this study may result from the use of new techniques, called Bayesian tip dating, which aren't normally used in evolutionary studies. These can take into account both morphological and molecular data and make predictions about the possible sequence and date of the divergence of species.
While the shape of the family tree presented here is likely to stand the test of time, it is still too early to accept these predicted divergence dates as definitive. That said, the research also sheds important light on how human species occurred and spread through the Middle Pleistocene – into all areas of our planet. Crucially, many of these species may have interbreed.
(CREDIT Chuang Zhao)
Europe was the origin point for Neanderthals. Meanwhile, the Asian human species Homo erectus was a critical evolutionary step, giving rise to all later hominin species. And now we know that Homo longi evolved in Asia too. It therefore looks like Africa was a destination as well as a point of origin for the spread of human species.
The Harbin cranium also tells another story about human evolution as a science and as an international discipline. Human evolution was originally a European area of interest, focused on evidence from sites in western and central Europe. The discovery of fossils in Africa added great time depth to the origins of the human lineage and led to a common story of the spread of new species out of Africa.
The Harbin cranium reminds us of the vast expanse of Asia, whose fossils and scientists are now coming to the fore. Further insights may come both from the discovery of new species and old figurative art. In the case of the Harbin cranium, it is the application of new techniques of analysis that has brought old specimens back into active use. Asia is now in the driving seat of the study of human evolution.
Many thousands of different genetic variants are responsible for complex behavior.
- Genome-wide association studies (GWAS) allow us to correlate genetic differences with behavioral traits.
- There is no single gene that explains behavior; rather, behavior arises from the complex interaction of many different genes, each of which only plays a small role.
- Society must be cautious as we learn more about behavioral genetics.
Life flourishes with diversity, as diversity gives nature something to choose from, providing flexibility to adapt to change. Variation between humans seems endless, both in appearance and in behavior. Variation between humans is largely due to our flexible nature that allows us to adapt to a wide variety of potential life trajectories, and partly due to set dimensions of variation in our biological make-up carefully molded by the hands of time.
Genome-wide association studies
Four billion years of natural selection crafted the refined machinery we all share — encoded in most of our DNA — as well as carefully selected room for variation — encoded in a minority of DNA differences. If the 3.2 billion nucleotides in our DNA would fit into a 300-page book, the differences between two random people would barely add up to two pages. Many decades of research in twins and family members suggest that considerable portions of differences in human behavior are associated with some of the tiny differences within those two pages.
If the 3.2 billion nucleotides in our DNA would fit into a 300-page book, the differences between two random people would barely add up to two pages.
It is hard to uncover the evolutionary stories behind these differences, but it would probably help to first find out how these genetic differences exactly give rise to the diversity in our behavioral repertoire. Recent advances in genetics research allow us to link specific DNA nucleotides on those two pages to complex behavioral outcomes. Studies that link genetic variation on a molecular level with complex traits are called genome-wide association studies (GWAS). In a GWAS, millions of single DNA nucleotides are tested one by one in order to quantify their relationship with the most complex of human traits, including behavior.
Professor Karin Verweij and I recently published an article in Nature Human Behavior, in which we review what we have learned so far from GWAS on human behavior and what steps we need to take to learn more. Here, I will summarize some highlights from our article and reflect on their societal relevance.
Many genes with tiny effects
In the last decade or so, we have been able to link thousands of genetic variants to human behavioral traits, including personality, education, cognition, sexuality, and mental health. The effects of these genetic variants on behavior are, individually, very weak. Twin and family studies have estimated that, on average, about half of the individual differences in behavioral outcomes are due to genetic differences, which would mean that tens of thousands of genetic variants would be needed to account for these heritability estimates.
The tiny effects of individual genetic variants are hard to estimate, unless unusually large groups are studied. In a typical GWAS, we study millions of DNA variants from hundreds of thousands of individuals. The sum of these small effects can be used to predict people's genetic risk for all kinds of outcomes. The predictive power of DNA is increasing as our studies grow, but we still understand very little about the nature of these predictions.
There are probably no genes that directly influence complex behavioral outcomes. Instead, the many small genetic effects travel through many cascades of mostly unknown biological processes that react to and influence the physical and social environments that people live in.
Before we let DNA prediction reach the clinic or other uses with unpredictable ramifications, such as embryo selection or mate selection, it is important that we first invest in better understanding the nature of the relationship between genetic differences and behavioral outcomes.
Everything is connected
The physical machinery that carries our emergent minds and behaviors consists of many intricate and interconnected systems. Modifying one part will affect multiple other outcomes. This is visible at the level of genes: genetic effects are often shared between different behavioral outcomes in a systematic way. Genes that increase the chances of getting addicted to alcohol tend to increase the risk of feeling lonely. Genes that increase the risk for autism increase the chances of a higher IQ. Genes that increase the risk for anorexia increase the chances of getting a higher education.
These shared genetic effects are widespread among behavioral outcomes. The genetic effects we estimate reflect a patchwork of multiple underlying behavioral outcomes. While many are eager to use these genetic effects to dive into the biology of behavior, we argue that we first need to put more effort into dissecting these genetic effects into their subcomponents.
For educational attainment, for example, we recently split up the part of the genetic effects associated with IQ, which makes up 43 percent of genetic effects on educational attainment, and a "non-IQ" part, making up the remaining 57 percent. We are not sure yet what that remaining 57 percent exactly entails, but we do see that those genes increase the risk for schizophrenia and bipolar disorder. This could be because people with a higher genetic risk for schizophrenia or bipolar disorder tend to be more creative and more open to new experiences.
These shared genetic effects teach us a lot about the genetic architecture of human behavior and also make us realize that it is difficult to select for one trait without also influencing many others. This is a strong argument against using DNA prediction to influence your offspring's DNA through embryo selection, a service that, unfortunately, some companies have already started to offer.
Behavioral genetics is controversial
The highest portion of shared genetic effects was observed between educational attainment and income. These associations have been reported in separate publications, and the genetic effect on each is roughly the same. Both publications received much attention in the media and on social media. While for educational attainment, the reactions were mostly positive, the publication on genetic effects on income was met mostly with criticism.
These opposite reactions to the same genetic signal might have to do with income being more closely associated in people's minds with social inequalities. Trying to explain social inequalities in terms of something that people are born with may instill the fear that science is being misused to justify the position of marginalized groups. Instead, these molecular genetic effects are helping to elucidate an inherent unfairness in the way we organize our societies.
A closer look at these genetic effects shows that they contain substantial amounts of environmental influences. Our initial studies had trouble separating the two because they are highly correlated. When your genes predispose you to a higher education, that means that your parents also carry those genes and are thus more likely to also have a higher education, giving them better resources (money) to nurture you with a better environment. If you are born with genes that make it easier for you to learn, it will also increase the chances that you will move to a richer neighborhood with healthier living circumstances. These "double advantages" and "double disadvantages" make us mistake the impact of systematic social disadvantages for genetic effects, inflating heritability estimates.
These gene-environment correlations were recently detected studying DNA from people that were exclusively of white European origin. Systematic differences in environmental influences are likely much worse between different ethnic groups, casting more doubts on white supremacists' claims who love to use these inflated heritability estimates to support their genetic explanations for socio-economic group differences.
After two decades of reading out human genomes, we are still only scratching their surface. We are just starting to dissect only a fraction of the total heritability that we are currently able to capture with molecular genetic data. Large parts of humanity are still underrepresented in our measurements, which makes it difficult to make more general claims. We outline in more detail in our Nature Human Behavior paper which steps we need to take in our methods and data collection strategies to better understand the differences in our DNA.
Abdel Abdellaoui & Karin J.H. Verweij (2021). Dissecting polygenic signals from genome-wide association studies on human behavior. Nature Human Behavior. https://doi.org/10.1038/s41562-021-01110-y
Could this spell the end for mosquitos?
Researchers have used CRISPR/Cas9 gene editing to target a specific gene tied to fertility in male mosquitoes.
The researchers were then able to discern how this mutation can suppress the fertility of female mosquitoes.
Mosquitoes are one of humanity's greatest nemeses, estimated to spread infections to nearly 700 million people per year and cause more than one million deaths.
As reported in the Proceedings of the National Academy of Sciences, the discovery represents a breakthrough in one technique for controlling populations of Aedes aegypti, a mosquito that transmits dengue, yellow fever, Zika, and other viruses.
Craig Montell, professor of molecular, cellular, and developmental biology at the University of California, Santa Barbara, and coauthors were working to improve a vector-control practice called the sterile insect technique (SIT). To manage populations, scientists raise a lot of sterile male insects. They then release these males in numbers that overwhelm their wild counterparts.
The idea is that females that mate with sterile males before finding a fertile one are themselves rendered infertile, thereby decreasing the size of the next generation. Repeating this technique several times has the potential to crash the population. What's more, because each generation is smaller than the last, releasing a similar number of sterile males has a stronger effect over time.
CRISPR IS A BETTER ALTERNATIVE TO CHEMICALS
SIT has proven effective in managing a number of agricultural pests, including the medfly (Mediterranean fruit fly), a major pest in California. It has also been attempted with A. aegypti mosquitoes, which originated in Africa, but have since become invasive across many parts of the world, due in no small part to climate change and global travel.
In the past, scientists used chemicals or radiation to sterilize male A. aegypti.
"There are enough genes that affect fertility that just a random approach of blasting a large number of genes will cause the males to be infertile," says Montell. However, the chemicals or radiation affected the animals' health to such an extent that they were less successful in mating with females, which undercuts the effectiveness of the sterile insect technique.
Montell figured there had to be a more targeted approach with less collateral damage. He and his colleagues, including co-first authors Jieyan Chen and Junjie Luo, set out to mutate a gene in mosquitoes that specifically caused male sterility without otherwise affecting the insects' health. The best candidate they found was b2-tubulin (B2t); mutation of the related B2t gene in fruit flies is known to cause male sterility.
Using CRISPR/Cas9, the researchers knocked out B2t in male A. aegypti. They found that the mutant males produced no sperm, but unlike in previous efforts, the sterile studs were otherwise completely healthy. There was some debate over whether sperm—albeit defective sperm from the sterile males—was needed to render female mosquitoes infertile, or whether transfer of seminal fluid was all it took.
In one experiment, the researchers introduced 15 mutant males into a group of 15 females for 24 hours. Then they swapped the B2t males for 15 wild-type males, and left them there. "Essentially, all of the females remained sterile," Montell says. This confirmed that B2t males could suppress female fertility without producing sperm.
"THERE IS A PANDEMIC EVERY YEAR FROM MOSQUITO-BORNE DISEASES."
Next the team set out to determine how timing played into the effect. They exposed the females to mutant males for different lengths of time. The scientists noticed little difference after 30 minutes, but female fertility quickly dropped after that. Montell notes that females copulated twice on average even during the first 10 minutes. This indicated to him that females have to mate with many sterile males before being rendered infertile themselves.
Combining the females with the B2t males for four hours cut female fertility to 20% of normal levels. After eight hours the numbers began leveling out around 10%.
MOSQUITO MATING BEHAVIORS
With the insights from the time trials, the team sought to approximate SIT under more natural conditions. They added different ratios of B2t and wild-type males at the same time to a population of 15 females for one week, and recorded female fertility. A ratio of about 5 or 6 sterile males to one wild-type male reduced female fertility by half. A ratio of 15 to 1 suppressed fertility to about 20%, where it leveled off.
Now, Aedes aegypti populations could easily bounce back from an 80% drop in fertility, Montell says. The success of SIT comes from subsequent, successive releases of sterile males, where each release will be more effective than the last as sterile males account for an ever-growing proportion of the population.
Montell plans to continue investigating mosquito mating behaviors and fertility. They are devising a way to maintain stocks of B2t males so they are only sterile in the wild and not in the lab. In addition, they are characterizing male mating behavior to uncover new ways to suppress mosquito populations.
"We've become very interested in studying many aspects of behavior in Aedes aegypti because these mosquitoes impact the health of so many people," says Montell, who has conducted a lot of research using fruit flies in the past. "There is a pandemic every year from mosquito-borne diseases."
"When CRISPR/Cas9 came out several years ago it just offered new opportunities to do things that you couldn't do before. So, the time seemed right to for us to start working on Aedes aegypti."