#noncoding-dna

#noncoding-dna

Asexual reproduction is ultimately unsustainable for mice, and potentially other mammals, too. The clones looked normal and lived as long as normal mice. But large mutations - including the loss of an entire chromosome - accumulated in the cloned lineage at an unusually high rate.

To characterize CREs and TFs for neocortical ExNs, we used Arpp21-Gfp or Fezf2-Gfp transgenic mice and enriched GFP-expressing neocortical upper layer (L2-4) intratelencephalic (IT) neurons or deep layer (L5-6) predominantly extratelencephalic (ET) neurons, respectively, from neonatal mice (postnatal day (PD) 0), an age at which neocortical ExN identity and connectivity are established.

Using CRISPR-Cas9 and adeno-associated virus (AAV)-mediated homology-directed repair, we targeted CAR integration into the endogenous human TCR alpha locus (TRAC). TRAC-CAR T cells display dynamic CAR expression that delays exhaustion and improves tumour control in xenograft and immunocompetent models. This work has been critical for the development of allogeneic CAR T cell therapy, as it disrupts the TCR after transgene insertion—a necessary step to limit graft-versus-host disease.

Scientists in the laboratory of Rendong Yang, PhD, associate professor of Urology, have developed a new large language model that can interpret transcriptomic data in cancer cell lines more accurately than conventional approaches, as detailed in a recent study published in Nature Communications. Long-read RNA sequencing technologies have transformed transcriptomics research by detecting complex RNA splicing and gene fusion events that have often been missed by conventional short-read RNA-sequencing methods.

Biology is undergoing a transformation. After centuries of studying life as it evolves naturally, researchers are now using a combination of computation and genome engineering to intervene, generating new proteins and even whole bacteria from scratch. The use of artificial-intelligence tools to design biological components, an approach known as generative biology, is set to turbocharge this area of research. Just last year, scientists used AI-assisted design to produce artificial genes that can be expressed in mammalian cells.

Martschenko's argument is largely that genetic research and data have almost always been used thus far as a justification to further entrench extant social inequalities. But we know the solutions to many of the injustices in our world-trying to lift people out of poverty, for example-and we certainly don't need more genetic research to implement them. Trejo's point is largely that more information is generally better than less.

In the originally published version of this article, Extended Data Fig. 4 contained inadvertent duplications introduced during figure assembly: panel 4c (the bottom of the second column) erroneously reused images from panel 4a (the bottom of the third column); panel 4c (the upper panel of the third column) erroneously reused images from panel 4a (the upper panel of the rightmost column);