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Why isolated human groups speak more diverse languages even as genetic diversity shrinks

Languages and human DNA both capture aspects of human diversity. But how are they related? A new international study led by the University of Zurich finds a clear but counterintuitive pattern: regions with high genetic diversity tend to have more similar languages, while isolated populations with low genetic diversity show greater linguistic diversity. The research is published in the journal Proceedings of the National Academy of Sciences.

At first glance, the findings seem surprising. One might expect regions with greater genetic diversity, often shaped by migration and population mixing, to also show greater diversity in language. But the study reveals the opposite.

“We were struck by how robust this inverse relationship is across the globe,” says Anna Graff, lead author of the study and linguist at the University of Zurich. “Places where people have mixed more tend to be genetically diverse, but their languages are structurally more similar. In contrast, places with long-term isolation show less genetic diversity, yet much greater diversity in how languages are structured. Crucially, this relationship holds after adjusting for a wide range of confounding factors, including deep population history such as the timing of continental settlement.”

Genome Music: Rare Disease Sequences Turn Into Songs

The performance garnered a huge media attendance, allowing the team to accomplish their goal of bringing attention to SCID. Frishkopf hopes to perform the piece in a concert in the future.

Genome Music Raises Rare Disease Awareness from Concerts to Contests

From a serendipitous idea to physical compositions, Kantipuly and her collaborators have demonstrated the power of music to bring people together and work for a good cause. Recently, the team connected with another composer, Casey McPherson, who also produces genetic music but in more modern styles and the founder of To Cure a Rose, a nonprofit organization focused on developing a cure for a rare genetic disease.

Epigenetic Skin Aging and Its Reversal to Improve Skin Longevity across Ethnicities and Phototypes Using a Dihydromyricetin-Containing Serum: Results from a Prospective, Single-Cohort Study — Dermatology and Therapy

Skin aging is driven by intrinsic and extrinsic factors. Epigenetic alterations are one primary hallmark of aging and powerful biomarkers of biological skin age. To investigate epigenetic skin aging mechanisms and their regulation as a skin longevity approach across diverse ethnicities and phototypes, we assessed epidermal methylomes from white, African, and Asian donors.

We collected epidermis samples from 17 multi-ethnic donors with diverse phototypes using a newly established tape-stripping method followed by array-based DNA methylation profiling to investigate the robustness of DNA methylation clocks across diverse ethnic backgrounds. Additionally, we conducted a clinical study with 60 participants representing Fitzpatrick phototypes I–VI. Diverse clinical parameters and biological skin age of the volunteers were determined at baseline and after applying a serum containing the natural epigenetic inhibitor dihydromyricetin (DHM) for 8 weeks to investigate skin longevity effects across phototypes.

Data analysis revealed that age-dependent DNA hypermethylation is conserved across populations and affects genes essential for keratinocyte vitality and longevity. A newly developed epidermal methylation clock accurately predicted biological age in multi-ethnic cohorts, confirming the robustness of epigenetic age estimation across phototypes. Topical application of a DHM-containing serum significantly reduced epidermal DNA methylation age. Epigenetic rejuvenation was associated with clinical improvements, including reduced skin roughness and wrinkle visibility and occupancy, and increased dermal echogenicity.

DNA-reading AI reconstructs ancestry in minutes, matching top statistical methods

Researchers at the University of Oregon have developed an artificial intelligence tool that can read genetic code the way large language models like ChatGPT read text. Scanning the genome for biological mutation patterns, the computer model traces pairs of genes back in time to their last common ancestor.

It’s the first language model designed for population genetics, said Andrew Kern, a computational biologist in the UO College of Arts and Sciences. As described in a paper published April 10 in the Proceedings of the National Academy of Sciences, the AI tool offers scientists a fast and flexible alternative to classical methods for reconstructing evolutionary history.

In practice, it can help researchers like Kern understand when disease-resistance genes emerged in a population, for example, or when species evolved key traits.

Genetic parallelism underpins convergent mimicry coloration in Lepidoptera across 120 million years of evolution

The repeated evolution of similar phenotypes, or convergent evolution, is widespread in nature, but there are few studies investigating the genetic mechanisms across wide evolutionary timescales. This study examines convergent wing pattern evolution across highly divergent Lepidopteran lineages and reports parallel genetic reuse, indicating strong constraints and high predictability in evolutionary outcomes.

An ultrasound-scanning in vivo light source

Beautifully executed paper on putting mechanoluminescent nanoparticles into blood circulation of mice which express optogenetic channels. Focused ultrasound can then trigger targeted light emission and control of neural activity in the brain and elsewhere.


A deep-tissue light source made from mechanoluminescent transducers stimulated by focused ultrasound enables wide imaging of live animal vasculature, and modulation of neuronal activity and behaviour.

A simple filter swap could advance marine eDNA biomonitoring

Researchers at Aarhus University have demonstrated that a simple adjustment to water filtration methods can dramatically improve the detection of marine animal DNA when using advanced, PCR-free sequencing. This methodological optimization could help clear a major bottleneck in aquatic biomonitoring and marine conservation efforts. The study is published in Metabarcoding and Metagenomics.

Over the past two decades, environmental DNA (eDNA) analysis has become a crucial tool for monitoring aquatic ecosystems. The most common method, metabarcoding, relies on PCR amplification of a smaller genetic region to identify specific taxa. However, PCR can lead to “significant taxonomic bias” because it often amplifies the DNA of different organisms unequally, making quantitative estimates difficult.

To avoid this, scientists have increasingly explored “shotgun sequencing”—a broad approach that sequences the DNA in a sample much more broadly—across the entire tree of life and across the genome.

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