Evo 2 now includes information from humans, plants, and other eukaryotic species to expand its capabilities in generative functional genomics.
Category: genetics – Page 72
Generative AI tool marks a milestone in biology
Imagine being able to speed up evolution – hypothetically – to learn which genes might have a harmful or beneficial effect on human health. Imagine, further, being able to rapidly generate new genetic sequences that could help cure disease or solve environmental challenges.
Now, scientists have developed a generative AI tool that can predict the form and function of proteins coded in the DNA of all domains of life, identify molecules that could be useful for bioengineering and medicine, and allow labs to run dozens of other standard experiments with a virtual query – in minutes or hours instead of years (or millennia).
Trained on a dataset that includes all known living species – and a few extinct ones – Evo 2 can predict the form and function of proteins in the DNA of all domains of life.
Your Next Pet Could Be a Glowing Rabbit
Humans have been selectively breeding cats and dogs for thousands of years to make more desirable pets. A new startup called the Los Angeles Project aims to speed up that process with genetic engineering to make glow-in-the-dark rabbits, hypoallergenic cats and dogs, and possibly, one day, actual unicorns.
The Los Angeles Project is the brainchild of biohacker Josie Zayner, who in 2017 publicly injected herself with the gene-editing tool Crispr during a conference in San Francisco and livestreamed it. “I want to help humans genetically modify themselves,” she said at the time. She’s also given herself a fecal transplant and a DIY Covid vaccine and is the founder and CEO of The Odin, a company that sells home genetic-engineering kits.
Now, Zayner wants to create the next generation of pets. “I think, as a human species, it’s kind of our moral prerogative to level up animals,” she says.
Integrating the environmental and genetic architectures of aging and mortality
Based on a systematic analysis of environmental exposures associated with aging and mortality in the UK Biobank, the relative contributions of such exposures and genetic risk for mortality and a range of age-related diseases were compared, highlighting the potential beneficial effects of environment-focused interventions.
19y Younger Biological Age (Blood Test #1 In 2025)
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Stress could affect the development of the fetal brain
Disruptions in brain development are linked to higher risks of brain and mental illnesses. While genetics are known to play a role, environmental factors at the molecular and cellular levels have been less studied.
The international team of researchers from Karolinska Institutet, the Max Planck Institute of Psychiatry, and Helmholtz Munich aimed to understand how glucocorticoids — hormones involved in the body’s stress response and crucial for normal fetal development — affect brain development when overexposed.
The findings reveal that fetuses are more vulnerable to external influences like stress than previously thought. This stress can impact fetal brain development.
NanoCas, a smaller version of CRISPR tested with a single AAV, delivers on-target results
Mammoth Biosciences researchers have developed NanoCas, an ultracompact CRISPR nuclease, demonstrating its ability to perform gene editing in non-liver tissues, including skeletal muscle, using a single adeno-associated virus (AAV) vector. Experiments in non-human primates (NHPs) resulted in editing efficiencies exceeding 30% in muscle tissues.
CRISPR gene editing has revolutionized genetics, but delivery challenges have restricted its clinical applications primarily to ex vivo and liver-directed therapies. Conventional CRISPR nucleases, including Cas9 and Cas12a, exceed the packaging limits of a single AAV vector, necessitating dual-AAV strategies that reduce efficiency.
Smaller CRISPR systems such as Cas12i and CasX have been identified, but they remain too large or exhibit low editing efficiency. Existing compact systems like Cas14 and IscB have not demonstrated robust efficacy in large animal models.
How Good (Or Not) Is The Biological Age Calculator, PhenoAge?
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AI Reveals How Brain Cells Evolved Over 320 Million Years
Summary: A new study reveals how AI-driven deep learning models can decode the genetic regulatory switches that define brain cell types across species. By analyzing human, mouse, and chicken brains, researchers found that some brain cell types remain highly conserved over 320 million years, while others have evolved uniquely.
This regulatory code not only sheds light on brain evolution but also provides new tools for studying gene regulation in health and disease. The findings highlight how AI can identify preserved and divergent genetic instructions controlling brain function across species.
The study also has implications for understanding neurological disorders by linking genetic variants to cognitive traits. Researchers are now expanding their models to study the brains of various animals and human disease states like Parkinson’s.