Review reveals how single-cell transcriptomics maps brain regulatory networks in mammals, highlighting how molecular divergence drives complex behavioral evolution.
comparative genomics, evolution, neuroscience, artificial intelligence, computational biology, behaviorMammals and other vertebrates exhibit an incredible diversity of complex behaviors that have evolved as these species adapted to their environments. Underlying the phenotypic diversity is molecular diversity: The brain is composed of hundreds of molecularly distinct cell types that play a variety of roles in different behaviors and neural circuits. Single cell and spatial transcriptomic techniques are providing insights into which features of those neural cell types are conserved or divergent across mammals and, more broadly, vertebrates. The ability to genomically characterize individual neurons has created opportunities to link evolution at a molecular level to evolution at the circuit and behavioral levels. Although discoveries in evolutionary biology have been made by leveraging single cell genomics, fundamental methodological challenges remain to be addressed. New types and increased complexity of data sets have spurred the development of various new computational techniques. In parallel, new genomic technologies are being developed to better perturb and study brain regulatory networks. The methods for reconstructing regulatory networks in vitro have been advancing rapidly, but challenges still exist in reliably adapting those technologies for use in vivo across a wide variety of species. As the genomic technologies and computational approaches become tractable in the brains of animals, the field is poised to make big discoveries in how complex mammalian behaviors evolve.
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Ganesan et al. (2025) studied this question.
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