Yaelyn's Blog Posts

MIT neuroscientists have identified rare variants of a gene called ABCA7. These rare variants, when dysfunctional, contribute to the development of Alzheimer’s disease in people who already carry it. ABCA7 encodes a protein that transports lipids across the cell membrane. The mutations of ABCA7 alter the metabolic activity of a molecule called phosphatidylcholine. These mutations cause neurons to become hyperexcitable, damaging DNA and other crucial cellular components. However, researchers have discovered a way to reverse this with choline, a protein precursor that helps build cell membranes. With choline treatment, not only are the functional defects reversed, but hyperexcitability also decreases. Additionally, individuals carrying ABCA7 variants that produce low levels of functional ABCA7 have twice the risk of developing Alzheimer’s compared to those not carrying the variants. The study revealed the importance of ABCA7 in maintaining lipid homeostasis in the brain. Links: https://...

   Researchers at the Children’s Hospital of Philadelphia (CHOP) have applied long-read RNA sequencing at scale to discover disease-causing variants in pediatric patients, helping to detect rare diseases. This versatile, low-cost sequencing tool is called STRIPE (Sequencing Targeted RNAs Identifies Pathogenic Events). Its novel diagnostic workflow allows researchers to identify diagnoses missed by other genetic tests and to discover unexpected molecular insights into previously identified pathogenic variants.     While exome and genome sequencing are most commonly used to identify genetic variants responsible for rare diseases, these tools have a diagnostic yield of only 20% to 50%, signifying that over half of the patients with suspected rare diseases are unable to receive a molecular diagnosis. However, with the implementation of long-read sequencing, scientists can observe how genetic variants disrupt function in real-time by capturing full-length RNA molecu...

Figure 1. The diagram above depicts the genomic and structural architecture of ΦX174-like bacteriophages which specifically target E.coli. ​   Genomes encode complex interactions that express vital biological functions. With the assistance of two Artificial Intelligence (AI) models, viable bacteriophage genomes have been generated by computational biologist Brian Hie and other colleagues from Stanford University. A mixture of these AI-generated bacteriophages prevented virus-resistant Escherichia coli (E.coli ) from growing. Hie and his colleagues leveraged two AI genome language models, Evo 1 and Evo 2, to develop entire genome sequences with realistic genetic structure and desirable host characteristics, using the lytic phage ΦX174 as the design template. Bacteriophage ΦX174 was the first DNA-based genome ever. It was sequenced back in 1977 and has been well researched, with a wide range of information published on it.    Experimental testing of the AI-generated ...

  Figure 1. A group of Amazon molly ( Poecilia formosa ) huddled together, all a mirror image of each other due to cloning and genetic conversion.      A unique cross-species mating from nearly 100,000 years ago between a female Atlantic molly ( Poecilia mexicana ) and Sailfin molly ( Poecilia latipinna ) birthed a hybrid called the Amazon molly ( Poecilia formosa ) - an all-female species. While the mating of the two different species should have produced a sterile offspring, a hybrid animal that is unable to reproduce themselves, the Amazon molly possesses the ability to birth genetic clones of herself. Through an asexual reproduction process called gynogenesis, the Amazon molly mates with closely related males to trigger embryonic development. While the male’s sperm is required for the reproduction of the embryo, the male’s genetic material is bypassed and not inherited by the offspring.      Generations of clones often lead to extinction due to a ...