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1. Emx2 underlies the development and evolution of marsupial gliding membranes

   https://doi.org/10.1038/s41586-024-07305-3  

   Moreno, Jorge A; Dudchenko, Olga; Feigin, Charles Y; Mereby, Sarah A; Chen, Zhuoxin; Ramos, Raul; Almet, Axel A; Sen, Harsha; Brack, Benjamin J; Johnson, Matthew R; et al (May 2024, Nature)

   Abstract Phenotypic variation among species is a product of evolutionary changes to developmental programs^1,2. However, how these changes generate novel morphological traits remains largely unclear. Here we studied the genomic and developmental basis of the mammalian gliding membrane, or patagium—an adaptative trait that has repeatedly evolved in different lineages, including in closely related marsupial species. Through comparative genomic analysis of 15 marsupial genomes, both from gliding and non-gliding species, we find that theEmx2locus experienced lineage-specific patterns of acceleratedcis-regulatory evolution in gliding species. By combining epigenomics, transcriptomics and in-pouch marsupial transgenics, we show thatEmx2is a critical upstream regulator of patagium development. Moreover, we identify differentcis-regulatory elements that may be responsible for driving increasedEmx2expression levels in gliding species. Lastly, using mouse functional experiments, we find evidence thatEmx2expression patterns in gliders may have been modified from a pre-existing program found in all mammals. Together, our results suggest that patagia repeatedly originated through a process of convergent genomic evolution, whereby regulation ofEmx2was altered by distinctcis-regulatory elements in independently evolved species. Thus, different regulatory elements targeting the same key developmental gene may constitute an effective strategy by which natural selection has harnessed regulatory evolution in marsupial genomes to generate phenotypic novelty. 

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2. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

   https://doi.org/10.1126/science.abm7993  

   Kaplow, Irene M.; Lawler, Alyssa J.; Schäffer, Daniel E.; Srinivasan, Chaitanya; Sestili, Heather H.; Wirthlin, Morgan E.; Phan, BaDoi N.; Prasad, Kavya; Brown, Ashley R.; Zhang, Xiaomeng; et al (April 2023, Science)

   INTRODUCTION Diverse phenotypes, including large brains relative to body size, group living, and vocal learning ability, have evolved multiple times throughout mammalian history. These shared phenotypes may have arisen repeatedly by means of common mechanisms discernible through genome comparisons. RATIONALE Protein-coding sequence differences have failed to fully explain the evolution of multiple mammalian phenotypes. This suggests that these phenotypes have evolved at least in part through changes in gene expression, meaning that their differences across species may be caused by differences in genome sequence at enhancer regions that control gene expression in specific tissues and cell types. Yet the enhancers involved in phenotype evolution are largely unknown. Sequence conservation–based approaches for identifying such enhancers are limited because enhancer activity can be conserved even when the individual nucleotides within the sequence are poorly conserved. This is due to an overwhelming number of cases where nucleotides turn over at a high rate, but a similar combination of transcription factor binding sites and other sequence features can be maintained across millions of years of evolution, allowing the function of the enhancer to be conserved in a particular cell type or tissue. Experimentally measuring the function of orthologous enhancers across dozens of species is currently infeasible, but new machine learning methods make it possible to make reliable sequence-based predictions of enhancer function across species in specific tissues and cell types. RESULTS To overcome the limits of studying individual nucleotides, we developed the Tissue-Aware Conservation Inference Toolkit (TACIT). Rather than measuring the extent to which individual nucleotides are conserved across a region, TACIT uses machine learning to test whether the function of a given part of the genome is likely to be conserved. More specifically, convolutional neural networks learn the tissue- or cell type–specific regulatory code connecting genome sequence to enhancer activity using candidate enhancers identified from only a few species. This approach allows us to accurately associate differences between species in tissue or cell type–specific enhancer activity with genome sequence differences at enhancer orthologs. We then connect these predictions of enhancer function to phenotypes across hundreds of mammals in a way that accounts for species’ phylogenetic relatedness. We applied TACIT to identify candidate enhancers from motor cortex and parvalbumin neuron open chromatin data that are associated with brain size relative to body size, solitary living, and vocal learning across 222 mammals. Our results include the identification of multiple candidate enhancers associated with brain size relative to body size, several of which are located in linear or three-dimensional proximity to genes whose protein-coding mutations have been implicated in microcephaly or macrocephaly in humans. We also identified candidate enhancers associated with the evolution of solitary living near a gene implicated in separation anxiety and other enhancers associated with the evolution of vocal learning ability. We obtained distinct results for bulk motor cortex and parvalbumin neurons, demonstrating the value in applying TACIT to both bulk tissue and specific minority cell type populations. To facilitate future analyses of our results and applications of TACIT, we released predicted enhancer activity of >400,000 candidate enhancers in each of 222 mammals and their associations with the phenotypes we investigated. CONCLUSION TACIT leverages predicted enhancer activity conservation rather than nucleotide-level conservation to connect genetic sequence differences between species to phenotypes across large numbers of mammals. TACIT can be applied to any phenotype with enhancer activity data available from at least a few species in a relevant tissue or cell type and a whole-genome alignment available across dozens of species with substantial phenotypic variation. Although we developed TACIT for transcriptional enhancers, it could also be applied to genomic regions involved in other components of gene regulation, such as promoters and splicing enhancers and silencers. As the number of sequenced genomes grows, machine learning approaches such as TACIT have the potential to help make sense of how conservation of, or changes in, subtle genome patterns can help explain phenotype evolution. Tissue-Aware Conservation Inference Toolkit (TACIT) associates genetic differences between species with phenotypes. TACIT works by generating open chromatin data from a few species in a tissue related to a phenotype, using the sequences underlying open and closed chromatin regions to train a machine learning model for predicting tissue-specific open chromatin and associating open chromatin predictions across dozens of mammals with the phenotype. [Species silhouettes are from PhyloPic] 

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3. Auditory Communication Processing in Bats: What We Know and Where to Go

   https://doi.org/http://dx.doi.org/10.1037/bne0000308  

   Salles, A.; Bohn, K.; Moss, C.F. (June 2019, Behavioral neuroscience)

   Bats are the second largest mammalian order, with over 1,300 species. These animals show diverse behaviors, diets, and habitats. Most bats produce ultrasonic vocalizations and perceive their environment by processing information carried by returning echoes of their calls. Echolocation is achieved through a sophisticated audio-vocal system that allows bats to emit and detect frequencies that can range from ten to hundreds of kilohertz. In addition, most bat species are gregarious, and produce social communication calls that vary in complexity, form, and function across species. In this article, we (a) highlight the value of bats as model species for research on social communication, (b) review behavioral and neurophysiological studies of bat acoustic communication signal production and processing, and (c) discuss important directions for future research in this field. We propose that comparative studies of bat acoustic communication can provide new insights into sound processing and vocal learning across the animal kingdom. 

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4. Comparative analysis reveals distinctive epigenetic features of the human cerebellum

   https://doi.org/10.1371/journal.pgen.1009506  

   Guevara, Elaine E.; Hopkins, William D.; Hof, Patrick R.; Ely, John J.; Bradley, Brenda J.; Sherwood, Chet C. (May 2021, PLOS Genetics)

   Gojobori, Takashi (Ed.)

   Identifying the molecular underpinnings of the neural specializations that underlie human cognitive and behavioral traits has long been of considerable interest. Much research on human-specific changes in gene expression and epigenetic marks has focused on the prefrontal cortex, a brain structure distinguished by its role in executive functions. The cerebellum shows expansion in great apes and is gaining increasing attention for its role in motor skills and cognitive processing, including language. However, relatively few molecular studies of the cerebellum in a comparative evolutionary context have been conducted. Here, we identify human-specific methylation in the lateral cerebellum relative to the dorsolateral prefrontal cortex, in a comparative study with chimpanzees ( Pan troglodytes ) and rhesus macaques ( Macaca mulatta ). Specifically, we profiled genome-wide methylation levels in the three species for each of the two brain structures and identified human-specific differentially methylated genomic regions unique to each structure. We further identified which differentially methylated regions (DMRs) overlap likely regulatory elements and determined whether associated genes show corresponding species differences in gene expression. We found greater human-specific methylation in the cerebellum than the dorsolateral prefrontal cortex, with differentially methylated regions overlapping genes involved in several conditions or processes relevant to human neurobiology, including synaptic plasticity, lipid metabolism, neuroinflammation and neurodegeneration, and neurodevelopment, including developmental disorders. Moreover, our results show some overlap with those of previous studies focused on the neocortex, indicating that such results may be common to multiple brain structures. These findings further our understanding of the cerebellum in human brain evolution. 

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5. Ancestral regulatory mechanisms specify conserved midbrain circuitry in arthropods and vertebrates

   J. C. Bridi, Z. N. (August 2020, PNAS nexus)

   Corresponding attributes of neural development and functionsuggest arthropod and vertebrate brains may have an evolutionarily conserved organization. However, the underlying mechanisms have remained elusive. Here, we identify a gene regulatory and character identity network defining the deutocerebral– tritocerebral boundary (DTB) in Drosophila. This network comprises genes homologous to those directing midbrain-hindbrainboundary (MHB) formation in vertebrates and their closest chordate relatives.Genetic tracing reveals that the embryonic DTB gives rise to adult midbrain circuits that in flies control auditory and vestibular information processing and motor coordination, as do MHB-derived circuits in vertebrates. DTB-specific gene expression and function are directed by cis-regulatory elements of developmental control genes that include homologs of mammalian Zinc finger of the cerebellum and Purkinje cell protein 4. Drosophila DTB-specific cis-regulatory elements correspond to regulatory sequences of human ENGRAILED-2, PAX-2, and DACHSHUND-1 that direct MHB-specific expression in the embryonic mouse brain. We show that cis-regulatory elements and the gene networks they regulate direct the formation and function of midbrain circuits for balance and motor coordination in insects and mammals. Regulatory mechanisms mediating the genetic specification of cephalic neural circuits in arthropods correspond to those in chordates, thereby implying their origin before the divergence of deuterostomes and ecdysozoans. 

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