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Human genome is like a time machine, says researcher

Human genome is like a time machine, says researcher

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The human genome is a bit like a time machine, says Ben Voight, an associate professor in Systems Pharmacology and Translational Therapeutics and of Genetics in Penn’s Perelman School of Medicine. “If scrutinized in just the right way, it can give us a lens into the past and perhaps infer what factors may have shaped our ancestors’ DNA tens of thousands of years ago. While natural selection may still be acting to shape contemporary genomes, we’d need to wait five to ten millennia to see what was targeted.”

Voight is not alone in thinking that studying human genetic evolution can provide insight on current disorders including obesity, diabetes, addiction, malaria, skin, and reproductive ailments. A group of Penn researchers hopes to improve the understanding of these present-day ailments by looking at the very engine of evolution: natural selection in humans, in which individuals better adapted to their environment tend to survive and produce more offspring to carry their genomes into the future.

Led by his graduate student Kelsey Johnson, they recently published a study exploring data obtained from the 1,000 Genome Project, an international research database that has catalogued human genetic variation across multiple human populations of unique and diverse ancestry. They modified a statistical approach Voight developed in graduate school to identify genetic variants that are unexpectedly identical across many individuals in a population of interest. This scan identified regions related to malaria resistance, enzymes that metabolize alcohol, and several others.

“The key insight addressed in our work is that places exist in our genome where multiple human populations across diverse ancestries – Asian, African, European, for example – show signs of selection in the same place,” Voight said. One example maps to a spot associated with how abundantly alcohol metabolism genes are expressed. Previous studies have reported selection for this trait in populations of East Asian ancestry, but Johnson and Voight also identified selection for this trait in populations of African ancestry.

“This new signal also appears to be tightly linked to a previous association in African-Americans that protects some individuals against alcohol dependence,” Voight said. “While this may not be the trait that was selected for in the past, it does reinforce an important idea: understanding our past may help interpret and potentially improve clinical care today.”

Another example from the Johnson and Voight study involves glycophorin, a protein present on the outer surface of red blood cells that is expressed widely across multiple human populations. Previous work indicated that variation in the genes that encode glycophorins is associated with differences in susceptibility to the deadliest form of malaria, which is endemic to Africa. The species of parasite that causes this has evolved multiple proteins that bind to specific molecules on the surface of red blood cells that facilitate its entry into the cell, a common feature of this pathogen. A large study published last year found that some people in East Africa carry a glycophorin variant that bestows a 40 percent reduced risk of severe malaria.

Variation that provides some protection against malaria was likely targeted by natural selection in humans, but also resulted in blood disorders such as sickle-cell anemia and glucose-6-phosphate dehydrogenase deficiency (G6PD). Johnson and Voight found sites of genetic variation associated with glycophorin across multiple populations of African, European, Southern, and East Asian ancestries. “We have been in a constant battle with pathogens since modern humans evolved, including malaria,” Voight said.

How evolution has shaped human skin and skin-related organs such as sweat glands, hair follicles, and mammary glands is at the core of work by Yana G. Kamberov, PhD, an assistant professor of Genetics. “We aim to define the genetic basis for the evolution of ancient human-specific traits such as the loss of fur and the dramatically elaborated density of sweat glands that define our species,” she said.

In 2015, Kamberov examined how mice generate variation in sweat gland and hair density. The study revealed that the number of sweat glands is closely and inversely connected to the production of hair. When a certain gene was more active, the mice had more sweat glands than hair, but if the gene’s activity was reduced, the mice had more hair and fewer sweat glands.

Kamberov is also studying evolution of the placenta with a special interest in pre-eclampsia, a pregnancy-related condition characterized by high blood pressure, which is more prevalent in humans compared to other primates. Informed by evolutionary biology, she is looking for ways to alleviate disease, especially in areas of dermatology and reproductive pathology. For this, she has set her sights on regenerating sweat glands in skin substitutes and identifying gene variants involved in the risk of developing pre-eclampsia.

Taking a slightly different tack, Iain Mathieson, PhD, an assistant professor of Genetics, uses computational tools and data from both ancient and present-day human DNA to track historical movements and relationships between populations. His most recent work used ancient DNA to investigate changes in the human genome during the transition from a hunter-gatherer to an agricultural lifestyle. Specifically, the team documented the mixing of two genetically distinct groups of people, as farmers from regions near modern-day Turkey moved into southeastern Europe occupied by hunter-gatherers.

Prior to the 2018 study on human migration, Mathieson and colleagues conducted a genome-wide scan for natural selection events in ancient DNA from 230 West Eurasians who lived between 6500 and 300 bc. They found differences in genes associated with diet, pigmentation, and the immune system. “It’s actually very simple at heart – we count the frequency of variants in ancient populations and compare them to modern populations,” he said. For the most part in his line of research, evolutionary geneticists do not speculate about this type of variation and specific modern diseases.

However, some researchers have hypothesized about so-called “thrifty gene” effects on the incidence of current-day diabetes. This hypothesis centers on the notion that because of differences in lifestyle in the past compared to the present, genetic variants that are deleterious (because they increase BMI and diabetes risk) are common now because in the past they were comparatively advantageous.

But Mathieson says he hopes to focus in on this pathway: “I’m interested in using computational approaches, combined with what we have learned about the genomics of common diseases in present-day populations, to better understand how the risk of diseases like diabetes has been driven by natural selection.”

Source:

https://www.pennmedicine.org/news/news-blog/2018/march/genome-time-machine

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