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Biology

Network-driven cancer cell avatars for combination discovery and biomarker identification for DNA damage response … – Nature.com

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Network-driven cancer cell avatars for combination discovery and biomarker identification for DNA damage response ... - Nature.com

Biology

Armenian students win eight medals at 4th International Applied Biology Olympiad Public Radio of Armenia – Public Radio of Armenia Official Web site

Armenian representatives won 2 gold, 5 silver and 1 bronze medals at the 4th International Applied Biology Olympiad (IABO) held on June 20-23 in Bali, Indonesia.

All eight students representing the three educational centers of Armenia won medals.

The Armenian team was led by Vahagn Gevorgyan, a biology teacher at Quantum college.

11th-grade student of Quantum College Aram Kerobyan and 10th-grade student of YSU STEM School Mariam Galstyan won gold medals. Silver medals were won by Ara Melkonyan and Hrachya Sevoyan, 11th grade students of Quantum College. Ani Gevorgyan, 9th grade student of Quantum College, Nane Ananikyan, 10th grade student of YSU STEM School, and 10th grade student of Hrazdan High School No. 10, Ellen Danielyan. Hayk Harutyunyan, a student of the 10th grade of Quantum College, won a bronze medal.

The students had previously participated in the online format and passed the preliminary two rounds and had the opportunity to participate in the final round.

More than 100 students from Armenia, US, Bangladesh, Indonesia, Thailand, Malaysia, Nepal and Philippines participated in the final round.

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Armenian students win eight medals at 4th International Applied Biology Olympiad Public Radio of Armenia - Public Radio of Armenia Official Web site

Biology

New tomato, potato family tree shows that fruit color and size evolved together – EurekAlert

image:

Fruits of plants in the genus Solanumare incredibly diverse in color and size. A new family tree of this genus, created by a team led by Penn State researchers, helps explain this striking diversity andhow the fruits might have evolved.

Credit: Joo Vitor Messeder / Penn State

UNIVERSITY PARK, Pa. Fruits of Solanum plants, a group in the nightshade family, are incredibly diverse, ranging from sizable red tomatoes and purple eggplants to the poisonous green berries on potato plants. A new and improved family tree of this group, produced by an international team led by researchers at Penn State, helps explain the striking diversity of fruit colors and sizes and how they might have evolved.

The team found that the size and color of fruits evolved together and that fruit-eating animals were like not the primary drivers of the fruits evolution, as had been previously thought. The study, published in the journal New Phytologist, may also provide insight into breeding agriculturally important plants with more desirable traits, the researchers said.

There are about 1,300 species in the genus Solanum, making it one of the most diverse plant genera in the world, said Joo Vitor Messeder, graduate student in ecology and biology in the Penn State Eberly College of Science and Huck Institutes for the Life Sciences and lead author of the paper. Since the 1970s and 80s, researchers have suggested that birds, bats and other fruit-eating animals have driven the evolution of fruits like those in Solanum. However, the importance of the evolutionary history of the plants has been underestimated or rarely considered when evaluating the diversification of fleshy fruits. To better test this hypothesis, we needed first to produce a more robust phylogeny, or family tree, of this plant group to improve our understanding of the relationships between species.

Plants in the genus Solanum produce fruits with a wide variety of sizes, colors and nutritional values. They can appear black, purple, red, green, yellow or orange and range in size from less than a quarter of an inch to as much as 8 inches, or 0.5 to 20 centimeters. In addition to agriculturally important plants, some plants in the group are cultivated for their ornamental flowers, and the fruits of many of these plants are eaten by humans and a large diversity of animals, including birds, bats, reptiles, primates and other land mammals.

The researchers collected samples of plants from across the world, including wild plants from Brazil, Peru and Puerto Rico and plants from botanical gardens, and sequenced their genes from RNA. They supplemented with previously collected samples and publicly available data, ultimately comparing the sequences of 1,786 genes from a total of 247 species to reconstruct the Solanum family tree. This included representatives from all 10 of the major clades the branches of the tree and 39 of 47 minor clades within the genus.

By using thousands of genes shared among species that effectively represented the entire genus, we significantly improved the Solanum family tree, making it the most comprehensive to date, said Messeder, who conducted the research in the lab of Hong Ma, Huck Chair in Plant Reproductive Development and Evolution and professor of biology at Penn State and a co-corresponding author of the paper. Recent advances in technology allowed us to use more genes than previous studies, which faced many challenges in resolving relationships between species and clades. This improved tree helps us understand when different fruit colors and sizes originated or how they changed as new plant species came about.

The researchers added considerable resolution of the smaller branches in the group that includes potatoes and tomatoes, as well as their closely and more distantly related wild species. The insights gained, the researchers said, could support crop improvement programs for these species and other crops in the genus.

If the closest wild relatives of important agricultural crops have desirable traits, it is possible to breed crops with those species or borrow their genes, for example to improve resistance to temperature or pests or to produce larger fruits or fruits of a certain color, Messeder said.

The researchers found that the color and size of Solanum fruits was fairly conserved over evolutionary history, meaning that closely related species tend to have similar fruits. The evolution of fruit color and size is also correlated, with changes in one trait often corresponding to changes in the other, leading fruits of certain colors to be bigger than fruits of other colors.

These results suggest that physiological and molecular mechanisms may play a role in keeping the evolution of fruit color and size tied together, Messeder said. While frugivores or animals that primarily eat fruit and seed dispersers may influence diversification, we need to consider all of the possibilities when studying how fruits became so diverse.

The researchers also clarified the origin and diversification timeline of this genus, in part by including recent information from the oldest nightshade family fossil from a different genus in the Nightshade family whose fossil was dated to about 52 million years ago and from particular genes that improved estimates of the length of evolutionary branches. The researchers dated the origin of Solanum to about 53.1 million years ago a full 30 million years earlier than prior estimates that were based on genes from other parts of the plant cell. This paints a new picture of the environment that might have shaped how these plants diversified into new groups and species.

The Earths environment changed dramatically during the 30 million years in terms of temperature, carbon dioxide in the atmosphere, geography and animal diversity, Messeder said. Now that we know when Solanum and its subgroups originated, we can think about the conditions that might have promoted the diversification of that group, as well as how other organisms might have played a role.

The team found that the earliest members of Solanum had medium-sized berries that remained green when ripe, and that green and yellow fruits of this group became more diverse around 14 million years ago. The researchers speculated that bats might have played a role in this diversification, given their similar evolutionary timeline and that they are the primary dispersers of modern green and yellow Solanum fruits. As new bat species arose and expanded where they were living during this time, they ate Solanum fruits and carried their seeds to new environments. Next, the researchers plan to explore how modern interactions between animals and the fruit they eat may shed light on the evolution of both groups as well as explore the evolution of certain genes relevant to fruit color and size.

In addition to Messeder and Ma, the research team includes Toms Carlo, professor of biology at Penn State; Guojin Zhang, postdoctoral researcher at Penn State at the time of the research; Juan David Tovar at the National Institute of Amazonian Research in Brazil; Csar Arana at the National University of San Marcos in Peru; and Jie Huang and Chien-Hsun Huang at Fudan University in China.

Funding from the Fulbright Commission, the CAPES Foundation in Brazil, the Penn State Department of Biology, the Hill Memorial Fund from the Pen State Eberly College of Science, the Association for Tropical Biology and Conservation, the U.S. National Science Foundation, the International Association for Plant Taxonomy and the Society of Herbarium Curators supported this research.

Experimental study

Not applicable

A highly resolved nuclear phylogeny uncovers strong phylogenetic conservatism and correlated evolution of fruit color and size in Solanum L.

27-May-2024

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New tomato, potato family tree shows that fruit color and size evolved together - EurekAlert

Biology

Exploring the biology behind maternal mental health disorders – News-Medical.Net

Pregnancy and new motherhood transform a woman's body as well as her life. While this is often a joyous time, it can sometime lead to mental health disorders, most often anxiety and depression. These conditions can be detrimental to the mother's health and that of her child, but despite the high stakes, modern medicine often fails to address them. By teasing out the biological mechanisms underlying these pregnancy-related disorders, investigators at Weill Cornell Medicine are laying the groundwork for new ways to detect and treat women at risk.

The statistics for depression that occurs after delivery, or postpartum, reflect a particularly abysmal reality: Clinicians successfully treat only about three percent of women with this disorder. For those who become depressed before giving birth, that number rises only slightly, to around five percent.

We do a shockingly bad job in this country of detecting and treating women who have pregnancy-related depression."

Dr. Lauren M. Osborne, associate professor of obstetrics and gynecology at Weill Cornell Medicine andreproductive psychiatrist at NewYork-Presbyterian/Weill Cornell Medical Center

In one effort to ameliorate this problem, she and her colleagues have begun a perinatal wellness program that embeds experts in pregnancy and postpartum mental health into obstetric care.

Left untreated, anxiety and depression can cause significant harm, potentially negatively affecting a child's development and behavior over time and putting mothers at increased risk of substance abuse and suicide. The low rates of successful treatment reflect a series of shortfalls in the healthcare system's capacity to intervene, beginning with difficulty predicting who is at heightened risk.

Studies have established that certain psychological and social factors, such as a history of mental illness, low education level, or a lack of support, increase risk for pregnancy-related mental health illnesses. But scientists know less about the biological dimensions of these conditions.

"We have this special window of time, where something makes women vulnerable to mood and anxiety disorders," said Dr. Jonathan Power, an assistant professor of psychiatry at Weill Cornell Medicine, who is tracking women to see how their brain activity changes with pregnancy and into motherhood. "We don't know definitively what that is, but we have some likely candidates."

These potential culprits are changes in the immune system and fluctuations in hormones, according to Dr. Power. By investigating them in detail, he and Dr. Osborne hope, over the long term, to help turn medicine's track record around.

Dr. Osborne's research on the first of these potential culprits has pointed toward the possibility of pre-empting postpartum depression.

During pregnancy, the immune system's complex, defensive network must adapt to tolerate another living being within its perimeter, while still defending against threats from outside. Dr. Osborne's research has offered some clues, such as differences in T-cell activity, linking abnormal immunological activity during pregnancy with anxiety and depression.

In a study in Molecular Psychiatry, her team identified another key difference, shifts in a particular type of intercellular communication package released by two types of immune cells, macrophages and monocytes.

Under normal circumstances, cells expel bits of RNA, a relative of DNA, into the bloodstream, bundled within tiny packages. These packages increase in pregnancy, and the RNA found within them may contribute to implantation of the embryo and other processes.

Dr. Osborne and her colleagues examined the RNA within blood samples taken from women during pregnancy and up to six months after they had delivered. Among the women who were not depressed in pregnancy but went on to develop postpartum depression, the researchers saw a warning sign. During the 2nd and 3rd trimester of their pregnancies, the presence of a certain type of RNA package from the immune cells dropped off a change not seen among the women who did not become depressed.

This clear difference could provide the basis for a blood test to predict risk, according to Dr. Osborne.

"If we knew who would become sick, we could direct mental health resources to the people at highest risk early on, so we would be engaging in prevention rather than treatment," she said.

For those women who do develop postpartum depression and anxiety, treatment, including psychotherapy and medication, is currently available. Dr. Osborne notes that anti-anxiety and antidepressant medications, while not risk free, are compatible with pregnancy and breastfeeding. However, pregnant women and mothers are often concerned about the medication's potential effects on their babies.

In her own experience, Dr. Osborne has found that women want medications developed specifically for pregnancy-related conditions. However, until relatively recently, their only options were medications used to treat anxiety and depression in the general populations. A new class of drugs for postpartum depression shows that a more targeted approach is possible. These new medications, brexanolone and zuranolone, rely on a synthetic version of a hormone, allopregnanolone (a metabolite of progesterone produced in the brain), which fluctuates dramatically with pregnancy and delivery.

Shifts in hormone levels are the second likely candidate Dr. Osborne and Dr. Power are pursuing. During pregnancy, levels of estrogen, progesterone and allopregnanolone rise dramatically. Then, within 24 hours of delivery, they plummet. These fluctuations appear to cause problems for certain women.

With support from a pilot grant, the 1907 Trailblazer Award from the 1907 Foundation, Dr. Power has begun looking for three-way relationships among changes in hormone levels, mood, and brain activity detected by MRI scans. His goal is to track all three from before conception up to a year after delivery.

To find women before they become pregnant, he has partnered with the Ronald O. Perelman and Claudia Cohen Center for Reproductive Medicine to recruit those undergoing fertility treatments. Once enrolled, the participants complete daily, roughly one-minute, digital surveys about their mood, sleep, exercise and other activities.

Statistically, some of the women who are trying to become pregnant will go on to struggle with mood or anxiety after they conceive. "So, is there something about the brain scans beforehand that leads to a prediction about who's going to be troubled and who's going to do OK?" Dr. Power said.

Any such insight remains far off, however. He views the stage of current brain imaging research as similar to the studies in the 1990s that examined the role of hormones, including allopregnanolone, in the brain and so laid the foundation for the recently approved drugs for postpartum depression.

Like that research, the studies he and Dr. Osborne are conducting could one day make similar advancements possible.

"This is about understanding why it's happening, which then gradually serves as the basis for developing therapies," he said.

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Exploring the biology behind maternal mental health disorders - News-Medical.Net

Biology

Bending the Rules of Biology: Stanford Scientists Unveil Cellular Origami in Microscopic Predators – SciTechDaily

A side-by-side comparison of Lacrymaria olor, a remarkable ciliate with its neck extended and retracted. Researchers discovered origami-like folds make this morphing possible where microtubules define folding pleats. Credit: Prakash Lab

Stanford scientists have unveiled lacrygami, a phenomenon where Lacrymaria olor extends its structure dramatically, influenced by its cytoskeletal design, promising advances in microscopic technology.

There are some things in life you can watch and then never unwatch, said Manu Prakash, associate professor of bioengineering at Stanford University, calling up a video of his latest fascination, the single-cell organism Lacrymaria olor, a free-living protist he stumbled upon playing with his paper Foldscope. Its just its mesmerizing.

From the minute Manu showed it to me, I have just been transfixed by this cell, said Eliott Flaum, a graduate student in the curiosity-driven Prakash Lab. Prakash and Flaum spent the last seven years studying Lacrymaria olors every move and recently published a paper on their work in the journal Science.

The first time I came back with a fluorescence micrograph, it was just breathtaking, Flaum said. That image is in the paper.

The video Prakash queued up reveals why this organism is much more than a pretty picture: a single teardrop-shaped cell swims in a droplet of pond water. In an instant, a long, thin neck projects out from the bulbous lower end. And it keeps going. And going. Then, just as quickly, the neck retracts back, as if nothing had happened.

In seconds, a cell that was just 40 microns tip-to-tail sprouted a neck that extended 1500 microns or more out into the world. It is the equivalent of a 6-foot human projecting its head more than 200 feet. All from a cell without a nervous system.

It is incredibly complex behavior, Prakash said with a smile.

L. olor is featured in the journal Science because Prakash and Flaum have discovered in this behavior a new geometric mechanism previously unknown in biology. And they are the first to explain how such a simple cell can produce such incredible morphodynamics, beautiful folding and unfolding aka origami at the scale of a single cell, time and again without fail.

It is geometry. L. olors behavior is encoded in its cytoskeletal structure, just like human behavior is encoded in neural circuits.

This is the first example of cellular origami, Prakash said. Were thinking of calling it lacrygami.

Specifically, it is a subset of traditional origami known as curved-crease origami. It is all based on a structure of thin, helical microtubules ribs that wrap inside the cells membrane. These microtubule ribs are encased in a delicate diaphanous membrane, defining the crease pattern of peaks in a series of mountain-and-valley folds.

Prakash and Flaum used transmission electron microscopy and other state-of-the-art investigatory techniques to show there are actually 15 of these stiff, helical microtubule ribbons enshrouding L. olors cell membrane a cytoskeleton. These tubules coil and uncoil, leading to long projection and retraction, nesting back into themselves like the bellows of a compressed helical accordion. The gossamer of membrane tucks away inside the cell in neat, well-defined pleats.

When you store pleats on the helical angle in this way, you can store an infinite amount of material, Flaum explained. Biology has figured this out.

The elegance is in the arithmetic. It is mathematically impossible for this structure to unfold in any other way and, conversely, only one way it can retract. What is perhaps more striking to Prakash is the robustness of the architecture. In its lifetime, L. olor will perform this projection and retraction 50,000 times without flaw. He said: L. olor is bound by its geometry to fold and unfold in this particular way.

The key is an under-studied mathematical phenomenon occurring at the precise point where the ribs twist and the folded membrane begins to unfurl. It is a singularity a point where the structure is folded and unfolded at the same time. It is both and neither singular.

Grabbing a piece of paper, Prakash folds it into a cone shape and then pulls on one corner of the paper to demonstrate how this singularity (called d-cone) travels across the sheet in a neat line. And, by pushing back on the corner how the singularity travels back the exact same path to its original position.

It unfolds and folds at this singularity every time, acting as a controller. This is the first time a geometric controller of behavior has been described in a living cell. Prakash explained.

A constant theme running throughout the Prakash Labs work is a profound sense of wonder and playfulness that results in the energetic curiosity necessary to pursue such an idea for such a long time. It is, to put it in Prakashs terms, old-school science. He also refers to it as recreational biology.

To demonstrate his inspiration, Prakash displayed a family tree of other single-celled organisms that he has chosen to study. True, none can do what L. olor can do, he said. But these intricate geometries come in thousands of forms. Beautiful? Certainly, but each is also hiding wonderful and unwritten rules under their sleeves.

We started with a puzzle, Prakash explained with all the seriousness a scientist can muster. Ellie and I asked a very simple question: Where does this material come from? And where does it go? As our playground, we chose Tree of Life. Seven years later, here we are.

As for practical applications, Prakash the engineer is already imagining a new era of deployable microscale living machines that could transform everything from space telescopes to miniature surgical robots in the operating room.

Reference: Curved crease origami and topological singularities enable hyperextensibility of L. olor by Eliott Flaum and Manu Prakash, 7 June 2024, Science. DOI: 10.1126/science.adk5511

Prakash is also a senior fellow at the Stanford Woods Institute for the Environment, associate professor (by courtesy) of biology and of oceans, a member of Stanford Bio-X, the Wu Tsai Human Performance Alliance, the Maternal & Child Health Research Institute, and the Wu Tsai Neurosciences Institute.

This research was funded by the National Institutes of Health, the National Science Foundation, the Moore Foundation, the Howard Hughes Medical Institute, the Schmidt Foundation, and the Chan Zuckerberg Biohub San Francisco. Some of this work was performed at the Cell Sciences Imaging Facility at Stanford.

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Bending the Rules of Biology: Stanford Scientists Unveil Cellular Origami in Microscopic Predators - SciTechDaily

Biology

Popular Theory Debunked: Scientists Identify Unexpected Drivers Behind Giraffes’ Long Necks – SciTechDaily

A Penn State study suggests that giraffes long necks may have evolved due to the high nutritional needs of females, who require deep foraging into trees for food. While the necks-for-sex hypothesis posits that male competition drove neck length evolution, findings show females have proportionally longer necks. This research, published in Mammalian Biology, highlights the importance of conserving giraffe habitats to support their unique ecological needs.

Why do giraffes have long necks? A new study by biologists from Penn State examines the evolutionary development of this distinctive feature, providing fresh insights into a classic question. While the prevailing theory attributes the long necks to male competition, the researchers observed that female giraffes actually have proportionally longer necks compared to males. This suggests that the high nutritional demands of females might have been a key factor in the evolution of the giraffes long neck.

The study, which explored body proportions of both wild and captive giraffes, is described in a paper that was recently published in the journal Mammalian Biology. The findings, the team said, indicate that neck length may be the result of females foraging deeply into trees for otherwise difficult-to-reach leaves.

In their classic theories of evolution, both Jean Baptiste Lamarck and Charles Darwin suggested that giraffes long necks evolved to help them reach leaves high up in a tree, avoiding competition with other herbivores. However, a more recent hypothesis called necks-for-sex suggests that the evolution of long necks was driven by competition among males, who swing their necks into each other to assert dominance, called neck sparring. That is, males with longer necks might have been more successful in the competition, leading to reproducing and passing their genes to offspring.

The necks-for-sex hypothesis predicted that males would have longer necks than females, said Doug Cavener, Dorothy Foehr Huck and J. Lloyd Huck Distinguished Chair in Evolutionary Genetics and professor of biology at Penn State and lead author of the study. And technically they do have longer necks, but everything about males is longer; they are 30% to 40% bigger than females. In this study, we analyzed photos of hundreds of wild and captive Masai giraffes to investigate the relative body proportions of each species and how they might change as giraffes grow and mature.

Although male and female giraffes have the same body proportions at birth, they are significantly different as they reach sexual maturity. Females have proportionally longer necks and longer bodies than males, which might help with foraging and child-rearing, while males have wider necks and longer front legs, which might help win fights against other males and with mating. Credit: Penn State

The researchers gathered thousands of photos of captive Masai giraffes from the publicly accessible photo repositories Flickr and SmugMug as well as photos of wild adult animals that they have taken over the past decade. Because absolute measurements like overall height are difficult to determine from a photograph without a point of reference of known length, the researchers instead focused on measurements relative to one another, or body proportions for example, the length of the neck relative to the entire height of the animal. They restricted their analysis to images that met strict criteria, such as only using images of giraffes perpendicular to the camera, so they could consistently take a variety of measurements.

We can identify individual giraffes by their unique spot pattern, Cavener said. Thanks to the Association of Zoos and Aquariums, we also have the full pedigree, or family tree, of all Masai giraffes in North America in zoos and wildlife parks, as well as their birthdates and transfer history. So, by carefully considering this information, when the photo was taken and the approximate age of the animal, we could identify the specific individual in nearly every photo of a captive giraffe. This information was critical to understanding when male and female giraffes start to exhibit size differences and whether they grow differently.

At birth, male and female giraffes have the same body proportions. The researchers found that, although males generally grow faster in the first year, body proportions are not significantly different until they start to research sexual maturity around three years of age. Because body proportions change early in life, the team limited their study of wild animals whose ages are largely unknown to fully grown adults.

In adult giraffes, the researchers found that females have proportionally longer necks and trunks or the main section of their body, which does not include legs or the neck and head. Adult males, on the other hand, have longer forelegs and wider necks. This pattern was the same in both captive and wild giraffes.

Rather than stretching out to eat leaves on the tallest branches, you often see giraffes especially females reaching deep into the trees, Cavener said. Giraffes are picky eaters they eat the leaves of only a few tree species, and longer necks allow them to reach deeper into the trees to get the leaves no one else can. Once females reach four or five years of age, they are almost always pregnant and lactating, so we think the increased nutritional demands of females drove the evolution of giraffes long necks.

The researchers noted that sexual selection either competition among males or preference among females for larger mates was likely responsible for the overall size difference between males in females, as is the case in many other large, hoofed mammals that are polygynous where one male mates with many females. They suggest that, following the evolution of the long neck, sexual selection including male body pushing and neck sparring behaviors may have contributed to males wider necks. Additionally, the longer forelegs of males may assist in mating, which the researchers said is a brief and challenging affair that is rarely observed.

Interestingly, giraffes are one of few animals whose height we measure to the top of the head like humans rather than to their withersthe highest part of the back, like in horses and other livestock, Cavener said. The female has a proportionally longer axial skeleton a longer neck and trunk and are more sloped in appearance, while the males are more vertical.

The research team is also using genetics to identify relationships in groups of wild giraffes to better understand which males are successful at breeding. The goal is to shed additional light on mate choice and sexual selection, as well as guide conservation efforts for this endangered species.

If female foraging is driving this iconic trait as we suspect, it really highlights the importance of conserving their dwindling habitat, Cavener said. Populations of Masai giraffes have declined rapidly in the last 30 years, in part due to habitat loss and poaching, and it is critical that we understand the key aspects of their ecology and genetics in order devise the most efficacious conservation strategies to save these majestic animals.

Reference: Sexual dimorphisms in body proportions of Masai giraffes and the evolution of the giraffes neck by Douglas R. Cavener, Monica L. Bond, Lan Wu-Cavener, George G. Lohay, Mia W. Cavener, Xiaoyi Hou, David L. Pearce and Derek E. Lee, 3 June 2024, Mammalian Biology. DOI: 10.1007/s42991-024-00424-4

In addition to Cavener, the research team at Penn State includes Monica Bond, academic affiliate of biology; Lan Wu-Cavener, academic affiliate of biology; George Lohay, a postdoctoral researcher at the time of the research who is now at the Grumeti Fund; Mia Cavener, a graduate student at the time of the research; Xiaoyi Hou, graduate student in the Molecular, Cellular, and Integrative Biosciences program; David Pearce, an undergraduate student at the time of the research; and Derek Lee, academic affiliate of biology.

Funding from Penn State, the Penn State Huck Institutes of the Life Sciences and the Wild Nature Institute supported this research.

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Popular Theory Debunked: Scientists Identify Unexpected Drivers Behind Giraffes' Long Necks - SciTechDaily

Biology

Changes Upstream: RIPE team uses CRISPR/Cas9 to alter photosynthesis for the first time – EurekAlert

image:

A RIPE team used CRISPR/Cas9 to increase gene expression in rice by changing its upstream regulatory DNA. While other studies have used the technology to knock out or decrease the expression of genes, their research is the first unbiased gene-editing approach to increase gene expression and downstream photosynthetic activity.

Credit: RIPE Project

A team from the Innovative Genomics Institute at the University of California, Berkeley (UCB) has produced an increase in gene expression in a food crop by changing its upstream regulatory DNA. While other studies have used CRISPR/Cas9 gene-editing to knock out or decrease the expression of genes, new research published in Science Advances is the first unbiased gene-editing approach to increase gene expression and downstream photosynthetic activity.

Tools like CRISPR/Cas9 are accelerating our ability to fine-tune gene expression in crops, rather than just knocking out genes or turning them off. Past research has shown that this tool can be used to decrease expression of genes involved in important trade-offs, such as those between plant architecture and fruit size, said Dhruv Patel-Tupper, lead author on the study and former postdoctoral researcher in the Niyogi Lab at UCB. This is the first study, to our knowledge, where we asked if we can use the same approach to increase the expression of a gene and improve downstream activity in an unbiased way.

Unlike synthetic biology strategies that use genes from other organisms to improve photosynthesis, the genes involved in the photoprotection process are naturally found in all plants. Inspired by a 2018 Nature Communications paper that improved the water-use efficiency of a model crop by overexpressing one of these genes, PsbS, in plants, the Niyogi lab, and its leader Kris Niyogi, wanted to figure out how to change the expression of a plants native genes without adding foreign DNA. According to the Food and Agriculture Organization, rice supplies at least 20% of the worlds calories, and because it has only one copy of each of the three key photoprotection genes in plants, it was an ideal model system for this gene editing study.

The Niyogi lab pursued this work as part of Realizing Increased Photosynthetic Efficiency (RIPE), an international research project led by the University of Illinois that aims to increase global food production by developing food crops that turn the suns energy into food more efficiently with support from the Bill & Melinda Gates Foundation, Foundation for Food & Agriculture Research, and U.K. Foreign, Commonwealth & Development Office.

The labs plan was to use CRISPR/Cas9 to change the DNA upstream of the target gene, which controls how much of the gene is expressed and when. They wondered if making those changes would have an impact on downstream activity and by how much. Even they were surprised at the results.

The changes in the DNA that increased gene expression were much bigger than we expected and bigger than weve really seen reported in other similar stories, said Patel-Tupper, now an AAAS Science and Technology Policy Fellow at the USDA. We were a little bit surprised, but I think it goes to show how much plasticity plants and crops have. Theyre used to these big changes in their DNA from millions of years of evolution and thousands of years of domestication. As plant biologists, we can leverage that wiggle room to make large changes in just a handful of years to help plants grow more efficiently or adapt to climate change.

In this study, RIPE researchers learned that inversions, or flipping of the regulatory DNA, resulted in increased gene expression of PsbS. Unique to this project, after the largest inversion was made to the DNA, the team members conducted an RNA sequencing experiment to compare how the activity of all genes in the rice genome changed with and without their modifications. What they found was a very small number of differentially expressed genes, much smaller than similar transcriptome studies, suggesting their approach did not compromise the activity of other essential processes.

Patel-Tupper added that while the team showed that this method is possible, its still relatively rare. Around 1% of the plants they generated had the desired phenotype.

We showed a proof-of-concept here, that we can use CRISPR/Cas9 to generate variants in key crop genes and get the same leaps as we would in traditional plant breeding approaches, but on a very focused trait that we want to engineer and at a much faster timescale, said Patel-Tupper. Its definitely more difficult than using a transgenic plant approach, but by changing something that is already there, we may be able to preempt regulatory issues that can slow how quickly we get tools like this into the hands of farmers.

Experimental study

Not applicable

Multiplexed CRISPR/Cas9 mutagenesis of rice PSBS1 non-coding sequences for transgene-free overexpression

7-Jun-2024

The researchers do not report any conflicting interests.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Changes Upstream: RIPE team uses CRISPR/Cas9 to alter photosynthesis for the first time - EurekAlert

Biology

Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and … – Nature.com

Ethics statement

All studies were approved by the respective local ethical committees, and all participants provided informed consent. The EU-RLS-GENE study was approved by an institutional review board at the University Hospital of the Technical University of Munich (2488/09). The INTERVAL dataset was approved by the National Research Ethics Service Committee East of EnglandCambridge East (REC 11/EE/0538). Participants of 23andMe provided informed consent under a protocol approved by the external AAHRPP-accredited IRB, Ethical and Independent (E&I) Review Services. As of 2022, E&I Review Services is part of Salus IRB (https://www.versiticlinicaltrials.org/salusirb). The deCODE dataset was approved by the National Bioethics Committee of Iceland. The Danish Blood Donor Study (DBDS) dataset was approved by the Scientific Ethical Committee of Central Denmark (M-20090237) and by the Danish Data Protection agency (30-0444). GWAS studies in the DBDS were approved by the National Ethical Committee (NVK-1700407). The Emory dataset was approved by an institutional review board at Emory University, Atlanta, GA, USA (HIC ID 133-98).

Some of the samples were included already in our previous GWAS meta-analysis3. The reported sample numbers are the final sample numbers after quality control. Additional details are provided in the Supplementary Note.

RLS cases were recruited in specialized outpatient clinics for movement disorders and in sleep clinics in European countries (Austria, Czech Republic, Estonia, Finland, France, Germany and Greece), Canada (Quebec) and the USA. RLS was diagnosed in a face-to-face interview by an expert neurologist or sleep specialist based on IRLSSG diagnostic criteria1. Controls were either population-based unscreened controls (Austria, Estonia, Finland, France, Germany) or healthy individuals recruited in hospitals (Canada, Czech Republic, Greece, USA). A total of 6,228 cases and 10,992 ancestry-matched controls had been genotyped on the Axiom array and were the study sample used in our previous meta-analysis. For the current study, 1,020 cases and 8,810 ancestry-matched controls were added who were genotyped on the Infinium Global Screening Array-24 version 1.0. Genotype calling was performed in GenomeStudio 2.0 according to the GenomeStudio Framework User Guide, and identical quality-control criteria were used for both datasets. Imputation was performed on the UK10K haplotype and 1000 Genomes Phase 3 reference panel using the EAGLE2 (version 2.0.5) and PBWT (version 3.1) imputation tools as implemented in the Sanger imputation server. Imputed SNPs with pHWE1105 or an INFO score <0.5 were filtered out.

The INTERVAL study includes whole-blood donors recruited in England between 2012 and 2014. The Cambridge-Hopkins Restless Legs questionnaire was used to define RLS cases, and probable and definite cases were combined to form a binary phenotype as described previously3. A detailed description of Axiom Biobank array genotyping and the imputation procedure plus related quality control in the INTERVAL trial can be found elsewhere34. Briefly, imputation was performed using a joint UK10K and 1,000 Genomes Phase 3 (May 2013 release) reference panel via the Sanger imputation server, and variants with MAF0.1% and INFO score0.4 were retained for analysis.

This study includes research participants of 23andMe who agreed to participate in research studies. The RLS phenotype was defined by self-reported responses to survey questions that assessed whether someone had ever been diagnosed with RLS or had ever received treatment for RLS as described previously3. Participants were genotyped on one of five platforms, all using Illumina arrays with added custom content (HumanHap550+ BeadChip, OmniExpress+ BeadChip, Infinium Global Screening Array). Participant genotype data were imputed in a two-step procedure using a reference panel created by combining the May 2015 release of the 1000 Genomes Phase 3 haplotypes with the UK10K imputation reference panel. Pre-phasing was carried out using either the internally developed tool Finch, which implements the Beagle algorithm, or EAGLE2. Imputation was performed with Minimac3.

This cohort includes only individuals who had not been part of the 23andMe GWAS used in the discovery meta-analysis. Cases and controls were defined as described above.

Individuals in this cohort do not overlap with samples included in the INTERVAL GWAS used in the discovery meta-analysis. RLS status was assessed with a single question on having received a diagnosis of RLS.

For 23andMe and INTERVAL, genotyping and imputation was carried out as described for the discovery stage.

This dataset included the DBDS, a cohort from deCODE Genetics, Iceland, the Emory Hospital Atlanta, USA and the Donor InSight-III study. Phenotyping and genotyping procedures have been described in detail previously4.

First, the Axiom- and the GSA-genotyped datasets were analyzed separately using SNPTEST version 2.5.4 with genotype dosages and assuming an additive model. Age, sex and the first ten PCs from the MDS analysis in PLINK were included as covariates. These summary statistics of the two datasets were then combined by fixed-effect inverse-variance meta-analysis (STERR scheme) using METAL (release 2011-03-25)35. One round of genomic control was performed in each dataset before meta-analysis.

Assuming an additive genetic model, genotype dosages were analyzed in SAIGE (0.35.8.8) using a linear mixed model to account for cryptic relatedness and saddle point approximation to account for casecontrol imbalance36. Age, sex and the first ten PCs of ancestry were included as potential genomic confounders. The analysis was restricted to genetic variants with MAF0.001, INFO0.4 and a minor allele count of 10.

Association analysis was conducted by logistic regression (LRT) assuming additive allelic effects and imputed dosages. Age, sex, genotyping platform and the first ten PCs were included as covariates.

In all individual GWAS, sex-specific analyses were performed using the same pipelines as those for the pooled analyses minus adjustment for sex as a covariate.

We applied the same methods for both the pooled and the sex-specific GWAS. The three independent datasets were combined in a multivariate GWAS meta-analysis using the N-weighted-GWAMA R function (version 1.2.6)37. To assess the possibility of heterogeneity of SNP effects between the studies, Cochrans Q-test was applied as described in METAL.

Data for the X chromosome were available in two of the discovery-stage datasets: EU-RLS-GENE and 23andMe.

For the pooled association analysis, male genotypes were coded as 0/2 (assuming no dosage compensation in males). All other methods were identical to those of the autosomal analyses. In sex-stratified analyses, males were coded as 0/1 and females as 0/1/2.

In both pooled and sex-stratified analyses, males were coded as 0/2 and females as 0/1/2.

Pooled and sex-specific meta-analyses were performed using the N-GWAMA R function as in the autosomal analysis. Because N-GWAMA operates with Z scores, the type of male allele coding did not affect the results.

We performed sex-specific (male-only and female-only) meta-analyses of the corresponding GWAS using the N-GWAMA approach as described above. The results were used to estimate sex-specific heritability and genetic correlation between the sexes.

To detect sex-specific effects, we tested all independent (r2<0.2) genome-wide significant SNPs of the pooled and sex-specific meta-analyses for heterogeneity of effect sizes between the two sexes using Cochrans Q-test (one-sided) and a Bonferroni-corrected significance threshold of Padj0.05/221.

For 23andMe and INTERVAL, quality control and statistical analysis were performed as described for the discovery stage. Statistical analysis for the DBDS, deCODEEmory and Donor Insight studies has been described previously4. Meta-analysis was performed using Han and Eskins random-effects model in METASOFT (RE2, METASOFT version 2.0.1)38.

To define independent risk loci, we first used the --clump command in PLINK (version 1.90b6.7)39 to collapse multiple genome-wide significant association signals based on linkage disequilibrium (LD) and distance (clump-r2>0.05, clump-kb<500kb clump-p1<5108, clump-p2p-value<105). We then performed conditional analyses to identify secondary independent signals in risk loci using GCTA (version 1.93.0beta) with the -cojo-slct option, the P-value threshold for genome-wide significance set at 5108, the distance window set at 10Mb and the colinearity cutoff set at 0.9 (ref. 40). LD was derived from EU-RLS-GENE genotype data. Independent genome-wide significant signals were merged into one genomic risk locus if either their LD block distance was <500kb or their clumped regions were overlapping.

Heritability is reported on the liability scale unless otherwise indicated. Prevalence estimates were derived from the population cohorts INTERVAL and 23andMe themselves. For the EU-RLS-GENE casecontrol dataset and for the meta-analysis, prevalence estimates were derived from previous publications on European ancestries.

We estimated SNP-based heritability under several different heritability models. LDSC (version 1.0.1) was used with standard settings, invoking a model where SNPs with different MAFs are expected to contribute equally to heritability41. LDAK (version 5.0) was used with standard settings to implement the LDAK model, where SNP contributions depend on LD structure and MAF as well as the BLD-LDAK and BLD-LDAK+Alpha models, which incorporate additional annotation-based features42. All analyses were based on summary statistics and filtering according to LDSC default settings, that is, HapMap3 non-HLA SNPs with MAF>0.01 and INFO0.9. The Akaike information criterion of each of these models was reported for model comparison. Further details are provided in the Supplementary Note.

For X chromosome heritability estimation, we followed the approach described by Lee et al. and used the summary statistics of the N-GWAMA meta-analysis43. For sex k, the SNP heritability ({h}_{k}^{2}) relates to the expected 2 statistics as ({mathbb{E}}({chi }_{k}^{2})approx 1+{N}_{k}{h}_{k}^{2}/{M}_{{rm{eff}}}), where Nk is the GWAS sample size, and Meff is the effective number of loci within the examined genomic region (assumed to be the same in males and females). For calculation of the (sex-specific) relative heritability contribution of the X chromosome, 2 statistic-based h2 was also calculated for the autosomes.

For autosomal data, genetic correlations were calculated using LDSC (version 1.0.1) using the same SNP filtering criteria and the two-step estimation option as in the heritability estimation. Because the LDSC framework is not applicable for chromosome X, the genetic correlation coefficient ({hat{r}}_{rm{g}}) was estimated as ({hat{r}}_{rm{g}}=,frac{widehat{{Z}_{rm{m}}{Z}_{rm{f}}}}{sqrt{(;{hat{chi }}_{rm{f},}^{2}-,1)(;{hat{chi }}_{rm{m},}^{2}-,1)}}), where Z and 2 are the Z scores and mean 2 estimates from the female (f) and male (m)-specific studies.

In addition to between-study and between-sex genetic correlations, we performed a large-scale genetic correlation screen for RLS (represented by the pooled autosomal meta-analysis data) and other traits using LDSC as described above. Sources and filtering criteria for summary statistics included in this screen are provided in the Supplementary Note.

Traits significantly correlated with RLS (FDR<0.05, one-sample two-sided Z-test) were taken forward to a bi-serial genetic correlation analysis. Here, we computed the pairwise ({hat{r}}_{rm{g}}) between all traits.

An unsigned weighted correlation matrix was built using the pairwise ({hat{r}}_{rm{g}}) and used as input for a weighted correlation matrix analysis to perform hierarchical clustering and to detect modules with the WGCNA package (version 1.69)44. The following settings were applied in WGCNA: softPower, 6; network type, unsigned; TOMDenom, min; Dynamic-cutree, method=hybrid; deepSplit, 2; minModuleSize, 30; pamStage, TRUE; pamRespectsDendro, FALSE; useMedoids, FALSE. The defining trait categories in each module were determined by consensus through independent review of the within-module cluster structure by visual inspection of network plots at two sites (Helmholtz and Cambridge).

To select traits for MR, we defined two to eight clusters in a module based on its complexity. In each cluster, the traits were ranked according to the significance of their correlation with RLS, and we selected the most significantly correlated medical conditions or potentially modifiable lifestyle factors. We supplemented this list with traits for which an association with RLS has been described in the literature.

Using R version 4.0.4, we filtered GWAS datasets to uncorrelated SNPs (r2<0.01 in the European 1000 Genomes Phase 3 data), aligned them to GRCh37 and mapped them to dbSNP 153 with the gwasvcf package (version 0.1.0). We harmonized effect alleles across studies using the TwoSampleMR package (version 0.5.6)45. Palindromic variants with ambiguous allele frequencies and those with unresolved strand issues were excluded from analysis.

To avoid violations of the classical MR assumptions when studying correlated and likely pleiotropic traits, we used a robust method for bidirectional MR, LHC-MR (version 0.0.0.9000)32. Traits with low heritability (h2<2.5%, ({P_{h^2}})>0.05) were excluded from the analysis. Significance of directionality and confounding effect were tested by comparing the goodness of fit of six degenerate LHC-MR models (only latent effect, only causal effect, only causal effect to RLS, only causal effect from RLS, no causal effect to RLS and no causal effect from RLS) to the full model. We supplemented these analyses with those based on the IVW and MR-Egger methods.

All analyses were performed on the N-GWAMA results of the pooled meta-analysis. We applied several complementary approaches to prioritize candidate genes in the genome-wide significant risk loci. These included the gene-prioritization pipeline of DEPICT (version 1.rel194), three prioritization workflows (positional, eQTL-based and topology-based mapping) provided on the FUMA platform (https://fuma.ctglab.nl/, version 1.3.6a), a gene-level GWAS using MAGMA version 1.08, a transcriptome-wide association study using S-PrediXcan and S-MultiXcan (MetaXcan package version 0.7.4), a colocalization analysis with eCAVIAR (version 2.2) and statistical fine-mapping with CAVIARBF (version 0.2.1)46,47,48,49,50,51,52. In the DEPICT, FUMA eQTL-based mapping, MAGMA and transcriptome-wide association study analyses, a gene was considered prioritized if it had an FDR <0.05; in FUMA topology-based mapping, if it had an FDR <1105; and in eCAVIAR, if it had a colocalization posterior probability >0.1. In FUMA positional mapping, a gene was considered prioritized if genome-wide significant SNPs physically mapped to it. In statistical fine-mapping, a gene was considered prioritized if an SNP in the 95% credible set of the risk locus could be linked to it by either eQTL, chromatin interaction or positional mapping. In addition, we checked whether a gene contained genome-wide significant coding variants (the gene was considered prioritized if it did) and whether a gene mapped to a gene set that was significant in our enrichment analyses (the gene was considered prioritized if it did). We combined the results of all approaches per gene in a prioritization score by summing up the individual results, counting not prioritized as 0 and prioritized as 1. Further details are provided in the Supplementary Note.

We ran DEPICT to detect enrichment of gene sets across risk loci as well as to identify tissue and cell types where expression is enriched for genes across risk loci. We set the significance thresholds for lead SNPs at 1105 and at 5104 for null GWAS; all other settings were the same as those used for gene prioritization (see above). DEPICT was run with all built-in datasets. eQTL mapping and functional prioritization were evaluated in DEPICTs built-in eQTL and reconstituted gene sets.

Excluding 12 SNPs not reaching genome-wide significance in the joint analysis of discovery and validation did not change the main results (Supplementary Table 25).

MAGMA (version 1.08) was used to perform gene set enrichment testing for pathway identification. MAGMA conducts competitive gene set tests with correction for gene size, variant density and LD structure. A total of 7,522 gene sets representing the GO biological process ontology (MSigDB version 7.1, C5 collection, GO:BP subset) were tested for association. We adopted a significance threshold of FDR<0.05 (one-sided t-test).

Using the settings described above, we tested enrichment of RLS heritability with DEPICT across 209 different tissue types covered in the built-in dataset. For an independent validation on the tissue level as well as for the analyses on the cell type level, we mainly used the CELLEX and CELLECT tools53. CELLECT provides two different gene-prioritization approaches for heritability enrichment testing, S-LDSC and MAGMA covariate analysis54,55. For compatibility of the results, the summary statistics of the pooled N-GWAMA analysis were filtered using settings identical to those in our LDSC heritability analyses. Following the recommendations by Timshel et al.53, we applied a tiered approach by starting with body-wide datasets and then focusing on CNS-centric datasets. We used CELLECT software (version 1.3.0) with default settings but updated to MAGMA version 1.08 to test enrichment of RLS heritability in cell type- or tissue-specific genes for datasets with publicly available RNA-seq data. These analyses require a measure of expression specificity for each gene in a cell or tissue type. We either used CELLEX (version 1.2.1) to compute expression specificity or relied on precomputed CELLEX expression specificity scores. Human adult datasets without publicly available raw RNA-seq data were analyzed using MAGMA_Celltyping (version 2.0.0) in top10 mode. The list of input datasets is provided in the Supplementary Note, and results of our evaluation of both approaches showing high correlation are presented in Supplementary Fig. 1 and Supplementary Table 26.

We applied three types of models for genetic risk evaluation and RLS risk prediction: GLM with and without interaction terms, RF models and DNN models. These were implemented as binary classifiers as well as time-to-event classifiers.

Training of the models and evaluation by tenfold cross-validation were based on the EU-RLS-GENE Axiom subset. Therefore, we first conducted a meta-analysis excluding this dataset to generate unbiased summary statistics to be used in all models. Because GWAS have an ascertainment bias, we constructed a simulation cohort dataset by resampling of the EU-RLS-GENE Axiom subset based on the year of birth of the sampled individuals, their ages at onset and the demographic composition of the German population (Supplementary Note). We calculated the PRS using dosages of 216 independent lead SNPs of our discovery meta-analyses.

For a baseline comparison of the predictive power of this score to a PRS based on genome-wide data, we calculated a genome-wide PRS using the LDpred2-auto option of LDpred2 (R package bigsnpr version 1.12.2)56. Variants and the LD reference panel were based on the HapMap3 EUR dataset, and window size for calculating SNP correlation was set to 3cM.

Binary classification models were evaluated by Nagelkerkes pseudo-R2, receiver operator characteristic AUC and precisionrecall AUC. A 5-year binary classifier was constructed for each of the time-to-event models by predicting the label until the next 5 years and evaluated by the metrics for binary classification.

To evaluate the contribution of the interaction effects to model performance, we estimated the effect sizes of interaction terms such as PRSage by logistic regression:

$$begin{array}{l}P({rm{RLS}}=1|{rm{PRS}},{rm{sex}},{rm{age}},{bf{PC}})\=displaystylefrac{1}{1+{e}^{-left({beta }_{0}+{beta }_{1}{rm{PRS}}+{beta }_{2}{rm{sex}}+{{beta }}_{3}{rm{age}}+{beta }_{4}{rm{PRS}}times {rm{sex}}+{{beta }}_{5}{ {rm{PRS}timesrm{age}}}+{{beta }}_{6}{{rm{sex}}timesrm{age}} +{{beta }}_{7}{{rm{PRS}}times {rm{sex}timesrm{age}}}+{boldsymbol{gamma }}cdot{bf{PC}}right)}},end{array}$$

where age is the dummy variable of age in bins of 20 years, PC indicates the first ten PCs from the MDS analysis in PLINK, is a vector of effect sizes of PCs and the PRS=jwjgj, where wj and gj are the per-allele effect size and dosage of the j-th SNP, respectively.

For the DNN and RF models, we used these logistic regression estimates as the baseline and then further estimated the interaction effect sizes indirectly by calculating the incremental gain in explained variance (Nagelkerkes pseudo-R2) from model0 to model1 as:

$${R}^{2}=left(1-left(Lleft(rm{model}_{0}right)/{it{L}}(rm{model}_{1})right)^{frac{2}{it{N}}}right)left(1-{it{L}}(rm{model}_{0})^{frac{2}{it{N}}}right)^{-1},$$

where L is the likelihood function for a logistic regression model with the first ten PCs included as covariates.

Binary classification models, GLMs and RF and DNN models were built, optimized and trained by H2O AutoML (version 3.36.0.2) in R (version 4.0.2)57. Time-to-event models were implemented with randomForestSRC (version 3.0.1) in R (version 4.0.2) and PyTorch58 (pycox version 0.2.1 and PyTorch version 1.6.0). Cross-validation-based Nagelkerkes pseudo-R2 was calculated in R version 4.0.2.

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and ... - Nature.com

Biology

WT Biology Professor Wins Grant to Study Panhandle’s Pheasant Population – West Texas A&M University

Copy by Chip Chandler, 806-651-2124, cchandler@wtamu.edu

CANYON, Texas A West Texas A&M University faculty member recently earned an $860,000 grant to study the declining population of an economically important Panhandle bird.

Dr. Joshua Brown, assistant professor of biology in the Department of Life, Earth and Environmental Sciences in WTs Paul Engler College of Agriculture and Natural Sciences, is actively seeking area landowners to participate in a study of ring-necked pheasants in the High Plains.

The grant comes from Texas Parks and Wildlife Department, which has monitored the birds population since 1976 and have noticed a decline for decades. The department will use funds from the Federal Aid in Wildlife Restoration Act, which provides resources for state wildlife conservation agencies.

Browns study will examine the birds nesting habits, movements and population genetics to see if any new conservation strategies might be devised.

In doing so, hell utilize state-of-the-art technology.

Well trap birds, attach a 15-gram GPS tracker with a Teflon harness, take some blood, then let them go, Brown said. Well see where the birds are going with real-time information that will help us identify their potential nesting sites. Its a new use of GPS trackers. Traditionally, nest searching has been time intensive, requiring people in the field to manually search through brush for signs of a nest.

Once nests are located, Brown, two graduate students and his research technicians will do vegetation assessments and a modeling analysis to see what the characteristics of successful and unsuccessful nests are.

Eventually, well develop information that Texas Parks and Wildlife can disseminate to farmers and private landowners that they can incorporate on their property if theyre interested in conserving pheasants, Brown said.

Securing the grant is a significant accomplishment for Brown, said Dr. Jason Yarbrough, head of the Department of Life, Earth and Environmental Sciences.

Dr. Brown has proven to be an exceptional faculty member, Yarbrough said. He is a great colleague and a dedicated scientist who is off to a great start. We are proud to have him in the department.

Brown, who won his Colleges Young Faculty Award, said the grant was a perfect fit for him, both because he recently completed his first year as an assistant professor at WT and because the University is perfectly positioned to lead such research.

Pheasants, which arent native to the region, were first brought here because theyre fun to hunt and usually have self-sustaining populations, Brown said. In the 1980s and 90s, agricultural practices changed as far as harvesting and watering, and those changes resulted in habitats that arent as conducive to pheasants. The birds can certainly coexist with agriculture, but there are certain conditions for which that is more conducive.

Brown has already reached out to conservation group Pheasants Forever to help find landowners willing to let the research team do field work on their property. Others interested in taking part may contact Brown at 806-651-5217 or jbrown@wtamu.edu.

Leading such impactful studies as a Regional Research University is in line with the Universitys long-range plan, WT 125: From the Panhandle to the World.

That plan is fueled by the historicOne Westcomprehensive fundraising campaign, which reached its initial $125 million goal 18 months after publicly launching in September 2021. The campaigns new goal is to reach $175 million by 2025; currently, it has raised nearly $160 million.

About West Texas A&M University

WT is located in Canyon, Texas, on a 342-acre residential campus. Established in 1910, the University has been part of The Texas A&M University System since 1990. WT, a Hispanic Serving Institution since 2016, boasts an enrollment of about 10,000 and offers 59 undergraduate degree programs and more than 40 graduate degrees, including two doctoral degrees. The University is also home to the Panhandle-Plains Historical Museum, the largest history museum in the state and the home of one of the Southwests finest art collections. The Buffaloes are a member of the NCAA Division II Lone Star Conference and offers 14 mens and womens athletics programs.

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WT Biology Professor Wins Grant to Study Panhandle's Pheasant Population - West Texas A&M University