Positive selection in noncoding genomic regions of vocal learning birds is associated with genes implicated in vocal learning and speech functions in humans

Evolutionary feedback from the environment shapes mechanisms that generate genome variation

Darwin recognized that 'a grand and almost untrodden field of inquiry will be opened, on the causes and laws of variation.' However, because the Modern Synthesis assumes that the intrinsic probability of any individual mutation is unrelated to that mutation's potential adaptive value, attention has been focused on selection rather than on the intrinsic generation of variation. Yet many examples illustrate that the term 'random' mutation, as widely understood, is inaccurate. The probabilities of distinct classes of variation are neither evenly distributed across a genome nor invariant over time, nor unrelated to their potential adaptive value. Because selection acts upon variation, multiple biochemical mechanisms can and have evolved that increase the relative probability of adaptive mutations. In effect, the generation of heritable variation is in a feedback loop with selection, such that those mechanisms that tend to generate variants that survive recurring challenges in the environment would be captured by this survival and thus inherited and accumulated within lineages of genomes. Moreover, because genome variation is affected by a wide range of biochemical processes, genome variation can be regulated. Biochemical mechanisms that sense stress, from lack of nutrients to DNA damage, can increase the probability of specific classes of variation. A deeper understanding of evolution involves attention to the evolution of, and environmental influences upon, the intrinsic variation generated in gametes, in other words upon the biochemical mechanisms that generate variation across generations. These concepts have profound implications for the types of questions that can and should be asked, as omics databases become more comprehensive, detection methods more sensitive, and computation and experimental analyses even more high throughput and thus capable of revealing the intrinsic generation of variation in individual gametes. These concepts also have profound implications for evolutionary theory, which, upon reflection it will be argued, predicts that selection would increase the probability of generating adaptive mutations, in other words, predicts that the ability to evolve itself evolves.

A genomic basis of vocal rhythm in birds

Vocal rhythm plays a fundamental role in sexual selection and species recognition in birds, but little is known of its genetic basis due to the confounding effect of vocal learning in model systems. Uncovering its genetic basis could facilitate identifying genes potentially important in speciation. Here we investigate the genomic underpinnings of rhythm in vocal non-learning Pogoniulus tinkerbirds using 135 individual whole genomes distributed across a southern African hybrid zone. We find rhythm speed is associated with two genes that are also known to affect human speech, Neurexin-1 and Coenzyme Q8A. Models leveraging ancestry reveal these candidate loci also impact rhythmic stability, a trait linked with motor performance which is an indicator of quality. Character displacement in rhythmic stability suggests possible reinforcement against hybridization, supported by evidence of asymmetric assortative mating in the species producing faster, more stable rhythms. Because rhythm is omnipresent in animal communication, candidate genes identified here may shape vocal rhythm across birds and other vertebrates.

Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements

Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.

Divergent contributions of coding and noncoding sequences to initial high-altitude adaptation in passerine birds endemic to the Qinghai-Tibet Plateau

Early events in the evolution of an ancestral lineage can shape the adaptive patterns of descendant species, but the evolutionary mechanisms driving initial adaptation from an ancestor remain largely unexplored. High-altitude adaptations have been extensively explored from the viewpoint of protein-coding genes; however, the contribution of noncoding regions remains relatively neglected. Here, we integrate genomic and transcriptomic data to investigate adaptive evolution in the ancestor of three high-altitude snowfinch species endemic to the Qinghai-Tibet Plateau. Our genome-wide scan for adaptation in the snowfinch ancestor identifies strong adaptation signals in functions of development and metabolism for the coding genes, but in functions of the nervous system development for noncoding regions. This pattern is exclusive to the snowfinch ancestor compared to a control ancestral lineage subject to weak selection. Changes in noncoding regions in the snowfinch ancestor, especially those nearest to coding genes, may be disproportionately associated with the differential expression of genes in the brain tissue compared to other tissues. Extensive gene expression in the brain tissue can be further altered via genetic regulatory networks of transcription factors harbouring potential accelerated regulatory regions (e.g., the development-related transcription factor YEATS4). Altogether, our study provides new evidence concerning how coding and noncoding sequences work through decoupled pathways in initial adaptation to the selective pressure of high-altitude environments. The analysis highlights the idea that noncoding sequences may be promising elements in facilitating the rapid evolution and adaptation to high altitudes.

Universality, domain-specificity, and development of psychological responses to music

Humans can find music happy, sad, fearful, or spiritual. They can be soothed by it or urged to dance. Whether these psychological responses reflect cognitive adaptations that evolved expressly for responding to music is an ongoing topic of study. In this Review, we examine three features of music-related psychological responses that help to elucidate whether the underlying cognitive systems are specialized adaptations: universality, domain-specificity, and early expression. Focusing on emotional and behavioural responses, we find evidence that the relevant psychological mechanisms are universal and arise early in development. However, the existing evidence cannot establish that these mechanisms are domain-specific. To the contrary, many findings suggest that universal psychological responses to music reflect more general properties of emotion, auditory perception, and other human cognitive capacities that evolved for non-musical purposes. Cultural evolution, driven by the tinkering of musical performers, evidently crafts music to compellingly appeal to shared psychological mechanisms, resulting in both universal patterns (such as form-function associations) and culturally idiosyncratic styles.

Transcription factor binding sites are frequently under accelerated evolution in primates

Recent comparative genomic studies have identified many human accelerated elements (HARs) with elevated substitution rates in the human lineage. However, it remains unknown to what extent transcription factor binding sites (TFBSs) are under accelerated evolution in humans and other primates. Here, we introduce two pooling-based phylogenetic methods with dramatically enhanced sensitivity to examine accelerated evolution in TFBSs. Using these new methods, we show that more than 6000 TFBSs annotated in the human genome have experienced accelerated evolution in Hominini, apes, and Old World monkeys. Although these TFBSs individually show relatively weak signals of accelerated evolution, they collectively are more abundant than HARs. Also, we show that accelerated evolution in Pol III binding sites may be driven by lineage-specific positive selection, whereas accelerated evolution in other TFBSs might be driven by nonadaptive evolutionary forces. Finally, the accelerated TFBSs are enriched around developmental genes, suggesting that accelerated evolution in TFBSs may drive the divergence of developmental processes between primates.

Birdsong neuroscience and the evolutionary substrates of learned vocalization

Oscine songbirds have served as a model for speech and its evolution since the discovery that birds in this clade learn to produce their songs by imitating conspecifics. We discuss the initial characterization of neural substrates for song learning and highlight several avenues of neuroscientific, phylogenetic, and genomic research that have advanced our understanding of how songbirds evolved to produce this behavior.

On the representation of hierarchical structure: Revisiting Darwin's musical protolanguage

In this article, we address the tenability of Darwin's musical protolanguage, arguing that a more compelling evolutionary scenario is one where a prosodic protolanguage is taken to be the preliminary step to represent the hierarchy involved in linguistic structures within a linear auditory signal. We hypothesize that the establishment of a prosodic protolanguage results from an enhancement of a rhythmic system that transformed linear signals into speech prosody, which in turn can mark syntactic hierarchical relations. To develop this claim, we explore the role of prosodic cues on the parsing of syntactic structures, as well as neuroscientific evidence connecting the evolutionary development of music and linguistic capacities. Finally, we entertain the assumption that the capacity to generate hierarchical structure might have developed as part of tool-making in human prehistory, and hence was established prior to the enhancement of a prosodic protolinguistic system.

Physical, language, neurodevelopment and phenotype-genotype correlation of Chinese patients with Mowat-Wilson syndrome

Background: To report detailed knowledge about the clinical manifestations, genetic spectrum as well as physical, language, neurodevelopment features and genotype-phenotype correlations of Chinese patients with Mowat-Wilson syndrome (MWS).

Methods: We retrospectively collected and analyzed clinical data for twenty-two patients with molecularly confirmed diagnoses. We used Gesell Developmental Schedules (GDS) to assess their neurodevelopment and the Diagnostic Receptive and Expressive Assessment of Mandarin-Infant & Toddler (DREAM-IT) to evaluate their language ability and compared the data with the two types of underlying pathogenic variations.

Results: The height and weight of all patients were below the 75th percentile, and microcephaly was observed in 16 of 22 patients (72.7%). Four patients carrying chromosome deletions encompassing the ZEB2 gene were more severely affected. All MWS patients exhibited better performance in cognitive play and social communication than in receptive and expressive language. In the receptive language area, the types of words that children with MWS understood most were nouns, followed by adjectives and verbs.

Conclusion: This study delineated the phenotypic spectrum of the largest MWS cohort in China and provided comprehensive profiling of their physical, language, neurodevelopment features and genotype-phenotype correlations.

Avian models for brain mechanisms underlying altered social behavior in autism

The current review is an update on experimental approaches in which birds serve as model species for the investigation of typical failure symptoms associated with autism spectrum disorder (ASD). The discussion is focused on deficiencies of social behavior, from social interactions of domestic chicks, based on visual and auditory cues, to vocal communication in songbirds. Two groups of pathogenetic/risk factors are discussed: 1) non-genetic (environmental/epigenetic) factors, exemplified by embryonic exposure to valproic acid (VPA), and 2) genetic factors, represented by a list of candidate genes and signaling pathways of diagnostic or predictive value in ASD patients. Given the similarities of birds as experimental models to humans (visual orientation, vocal learning, social cohesions), avian models usefully contribute toward the elucidation of the neural systems and developmental factors underlying ASD, improving the applicability of preclinical results obtained on laboratory rodents. Furthermore, they may predict potential susceptibility factors worthy of investigation (both by animal studies and by monitoring human babies at risk), with potential therapeutic consequence.

Corticogenesis across species at single-cell resolution

The neocortex (or pallium) consists of diverse cell types that are organized in a highly species-specific manner under strict spatiotemporal control during development. Many of the cell types are present transiently throughout development but contribute to permanent species-specific cortical features that are acquired through evolution. Therefore, capturing cell type-specific biological information has always been an important quest in the field of neurodevelopment. The progress in achieving fine cellular resolution has been slow due to technical challenges. However, with recent advancements in single-cell and multi-omics technologies, many laboratories have begun to successfully interrogate cellular and molecular mechanisms driving corticogenesis at single-cell resolution. In this review, we provide summarized results from many primary publications and several in-depth review articles that utilize or address single-cell genomics techniques to understand important topics, such as cellular and molecular mechanisms governing cortical progenitor proliferation, cell lineage progression, neuronal specification, and arealization, across multiple gyrencephalic (i.e., human and non-human primates) and lissencephalic species (i.e., mouse, reptiles, and songbirds). We also examine findings from recent studies involving epigenomic and posttranscriptional regulation of corticogenesis. In the discussion section, we provide our insights on the challenges the field currently faces as well as promising future applications of single cell technologies.

Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin

BACKGROUND

Evolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation of many enhancers, distal regulatory elements that control spatial and temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high.

RESULTS

We present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that can predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Next, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss of regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity have a stronger tendency than the general population to have predicted lineage-specific open chromatin.

CONCLUSION

The framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.