Publications

Displaying 1 - 14 of 14
  • D’Onofrio, G., Accogli, A., Severino, M., Caliskan, H., Kokotović, T., Blazekovic, A., Jercic, K. G., Markovic, S., Zigman, T., Goran, K., Barišić, N., Duranovic, V., Ban, A., Borovecki, F., Ramadža, D. P., Barić, I., Fazeli, W., Herkenrath, P., Marini, C., Vittorini, R. and 30 moreD’Onofrio, G., Accogli, A., Severino, M., Caliskan, H., Kokotović, T., Blazekovic, A., Jercic, K. G., Markovic, S., Zigman, T., Goran, K., Barišić, N., Duranovic, V., Ban, A., Borovecki, F., Ramadža, D. P., Barić, I., Fazeli, W., Herkenrath, P., Marini, C., Vittorini, R., Gowda, V., Bouman, A., Rocca, C., Alkhawaja, I. A., Murtaza, B. N., Rehman, M. M. U., Al Alam, C., Nader, G., Mancardi, M. M., Giacomini, T., Srivastava, S., Alvi, J. R., Tomoum, H., Matricardi, S., Iacomino, M., Riva, A., Scala, M., Madia, F., Pistorio, A., Salpietro, V., Minetti, C., Rivière, J.-B., Srour, M., Efthymiou, S., Maroofian, R., Houlden, H., Vernes, S. C., Zara, F., Striano, P., & Nagy, V. (2023). Genotype–phenotype correlation in contactin-associated protein-like 2 (CNTNAP-2) developmental disorder. Human Genetics, 142, 909-925. doi:10.1007/s00439-023-02552-2.

    Abstract

    Contactin-associated protein-like 2 (CNTNAP2) gene encodes for CASPR2, a presynaptic type 1 transmembrane protein, involved in cell–cell adhesion and synaptic interactions. Biallelic CNTNAP2 loss has been associated with “Pitt-Hopkins-like syndrome-1” (MIM#610042), while the pathogenic role of heterozygous variants remains controversial. We report 22 novel patients harboring mono- (n = 2) and bi-allelic (n = 20) CNTNAP2 variants and carried out a literature review to characterize the genotype–phenotype correlation. Patients (M:F 14:8) were aged between 3 and 19 years and affected by global developmental delay (GDD) (n = 21), moderate to profound intellectual disability (n = 17) and epilepsy (n = 21). Seizures mainly started in the first two years of life (median 22.5 months). Antiseizure medications were successful in controlling the seizures in about two-thirds of the patients. Autism spectrum disorder (ASD) and/or other neuropsychiatric comorbidities were present in nine patients (40.9%). Nonspecific midline brain anomalies were noted in most patients while focal signal abnormalities in the temporal lobes were noted in three subjects. Genotype–phenotype correlation was performed by also including 50 previously published patients (15 mono- and 35 bi-allelic variants). Overall, GDD (p < 0.0001), epilepsy (p < 0.0001), hyporeflexia (p = 0.012), ASD (p = 0.009), language impairment (p = 0.020) and severe cognitive impairment (p = 0.031) were significantly associated with the presence of biallelic versus monoallelic variants. We have defined the main features associated with biallelic CNTNAP2 variants, as severe cognitive impairment, epilepsy and behavioral abnormalities. We propose CASPR2-deficiency neurodevelopmental disorder as an exclusively recessive disease while the contribution of heterozygous variants is less likely to follow an autosomal dominant inheritance pattern.

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    supplementary tables
  • Lu, A. T., Fei, Z., Haghani, A., Robeck, T. R., Zoller, J. A., Li, C. Z., Lowe, R., Yan, Q., Zhang, J., Vu, H., Ablaeva, J., Acosta-Rodriguez, V. A., Adams, D. M., Almunia, J., Aloysius, A., Ardehali, R., Arneson, A., Baker, C. S., Banks, G., Belov, K. and 168 moreLu, A. T., Fei, Z., Haghani, A., Robeck, T. R., Zoller, J. A., Li, C. Z., Lowe, R., Yan, Q., Zhang, J., Vu, H., Ablaeva, J., Acosta-Rodriguez, V. A., Adams, D. M., Almunia, J., Aloysius, A., Ardehali, R., Arneson, A., Baker, C. S., Banks, G., Belov, K., Bennett, N. C., Black, P., Blumstein, D. T., Bors, E. K., Breeze, C. E., Brooke, R. T., Brown, J. L., Carter, G. G., Caulton, A., Cavin, J. M., Chakrabarti, L., Chatzistamou, I., Chen, H., Cheng, K., Chiavellini, P., Choi, O. W., Clarke, S. M., Cooper, L. N., Cossette, M. L., Day, J., DeYoung, J., DiRocco, S., Dold, C., Ehmke, E. E., Emmons, C. K., Emmrich, S., Erbay, E., Erlacher-Reid, C., Faulkes, C. G., Ferguson, S. H., Finno, C. J., Flower, J. E., Gaillard, J. M., Garde, E., Gerber, L., Gladyshev, V. N., Gorbunova, V., Goya, R. G., Grant, M. J., Green, C. B., Hales, E. N., Hanson, M. B., Hart, D. W., Haulena, M., Herrick, K., Hogan, A. N., Hogg, C. J., Hore, T. A., Huang, T., Izpisua Belmonte, J. C., Jasinska, A. J., Jones, G., Jourdain, E., Kashpur, O., Katcher, H., Katsumata, E., Kaza, V., Kiaris, H., Kobor, M. S., Kordowitzki, P., Koski, W. R., Krützen, M., Kwon, S. B., Larison, B., Lee, S. G., Lehmann, M., Lemaitre, J. F., Levine, A. J., Li, C., Li, X., Lim, A. R., Lin, D. T. S., Lindemann, D. M., Little, T. J., Macoretta, N., Maddox, D., Matkin, C. O., Mattison, J. A., McClure, M., Mergl, J., Meudt, J. J., Montano, G. A., Mozhui, K., Munshi-South, J., Naderi, A., Nagy, M., Narayan, P., Nathanielsz, P. W., Nguyen, N. B., Niehrs, C., O’Brien, J. K., O’Tierney Ginn, P., Odom, D. T., Ophir, A. G., Osborn, S., Ostrander, E. A., Parsons, K. M., Paul, K. C., Pellegrini, M., Peters, K. J., Pedersen, A. B., Petersen, J. L., Pietersen, D. W., Pinho, G. M., Plassais, J., Poganik, J. R., Prado, N. A., Reddy, P., Rey, B., Ritz, B. R., Robbins, J., Rodriguez, M., Russell, J., Rydkina, E., Sailer, L. L., Salmon, A. B., Sanghavi, A., Schachtschneider, K. M., Schmitt, D., Schmitt, T., Schomacher, L., Schook, L. B., Sears, K. E., Seifert, A. W., Seluanov, A., Shafer, A. B. A., Shanmuganayagam, D., Shindyapina, A. V., Simmons, M., Singh, K., Sinha, I., Slone, J., Snell, R. G., Soltanmaohammadi, E., Spangler, M. L., Spriggs, M. C., Staggs, L., Stedman, N., Steinman, K. J., Stewart, D. T., Sugrue, V. J., Szladovits, B., Takahashi, J. S., Takasugi, M., Teeling, E. C., Thompson, M. J., Van Bonn, B., Vernes, S. C., Villar, D., Vinters, H. V., Wallingford, M. C., Wang, N., Wayne, R. K., Wilkinson, G. S., Williams, C. K., Williams, R. W., Yang, X. W., Yao, M., Young, B. G., Zhang, B., Zhang, Z., Zhao, P., Zhao, Y., Zhou, W., Zimmermann, J., Ernst, J., Raj, K., & Horvath, S. (2023). Universal DNA methylation age across mammalian tissues. Nature aging, 3, 1144-1166. doi:10.1038/s43587-023-00462-6.

    Abstract

    Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.
  • Haghani, A., Li, C. Z., Robeck, T. R., Zhang, J., Lu, A. T., Ablaeva, J., Acosta-Rodríguez, V. A., Adams, D. M., Alagaili, A. N., Almunia, J., Aloysius, A., Amor, N. M. S., Ardehali, R., Arneson, A., Baker, C. S., Banks, G., Belov, K., Bennett, N. C., Black, P., Blumstein, D. T. and 170 moreHaghani, A., Li, C. Z., Robeck, T. R., Zhang, J., Lu, A. T., Ablaeva, J., Acosta-Rodríguez, V. A., Adams, D. M., Alagaili, A. N., Almunia, J., Aloysius, A., Amor, N. M. S., Ardehali, R., Arneson, A., Baker, C. S., Banks, G., Belov, K., Bennett, N. C., Black, P., Blumstein, D. T., Bors, E. K., Breeze, C. E., Brooke, R. T., Brown, J. L., Carter, G., Caulton, A., Cavin, J. M., Chakrabarti, L., Chatzistamou, I., Chavez, A. S., Chen, H., Cheng, K., Chiavellini, P., Choi, O.-W., Clarke, S., Cook, J. A., Cooper, L. N., Cossette, M.-L., Day, J., DeYoung, J., Dirocco, S., Dold, C., Dunnum, J. L., Ehmke, E. E., Emmons, C. K., Emmrich, S., Erbay, E., Erlacher-Reid, C., Faulkes, C. G., Fei, Z., Ferguson, S. H., Finno, C. J., Flower, J. E., Gaillard, J.-M., Garde, E., Gerber, L., Gladyshev, V. N., Goya, R. G., Grant, M. J., Green, C. B., Hanson, M. B., Hart, D. W., Haulena, M., Herrick, K., Hogan, A. N., Hogg, C. J., Hore, T. A., Huang, T., Izpisua Belmonte, J. C., Jasinska, A. J., Jones, G., Jourdain, E., Kashpur, O., Katcher, H., Katsumata, E., Kaza, V., Kiaris, H., Kobor, M. S., Kordowitzki, P., Koski, W. R., Krützen, M., Kwon, S. B., Larison, B., Lee, S.-G., Lehmann, M., Lemaître, J.-F., Levine, A. J., Li, X., Li, C., Lim, A. R., Lin, D. T. S., Lindemann, D. M., Liphardt, S. W., Little, T. J., Macoretta, N., Maddox, D., Matkin, C. O., Mattison, J. A., McClure, M., Mergl, J., Meudt, J. J., Montano, G. A., Mozhui, K., Munshi-South, J., Murphy, W. J., Naderi, A., Nagy, M., Narayan, P., Nathanielsz, P. W., Nguyen, N. B., Niehrs, C., Nyamsuren, B., O’Brien, J. K., Ginn, P. O., Odom, D. T., Ophir, A. G., Osborn, S., Ostrander, E. A., Parsons, K. M., Paul, K. C., Pedersen, A. B., Pellegrini, M., Peters, K. J., Petersen, J. L., Pietersen, D. W., Pinho, G. M., Plassais, J., Poganik, J. R., Prado, N. A., Reddy, P., Rey, B., Ritz, B. R., Robbins, J., Rodriguez, M., Russell, J., Rydkina, E., Sailer, L. L., Salmon, A. B., Sanghavi, A., Schachtschneider, K. M., Schmitt, D., Schmitt, T., Schomacher, L., Schook, L. B., Sears, K. E., Seifert, A. W., Shafer, A. B. A., Shindyapina, A. V., Simmons, M., Singh, K., Sinha, I., Slone, J., Snell, R. G., Soltanmohammadi, E., Spangler, M. L., Spriggs, M., Staggs, L., Stedman, N., Steinman, K. J., Stewart, D. T., Sugrue, V. J., Szladovits, B., Takahashi, J. S., Takasugi, M., Teeling, E. C., Thompson, M. J., Van Bonn, B., Vernes, S. C., Villar, D., Vinters, H. V., Vu, H., Wallingford, M. C., Wang, N., Wilkinson, G. S., Williams, R. W., Yan, Q., Yao, M., Young, B. G., Zhang, B., Zhang, Z., Zhao, Y., Zhao, P., Zhou, W., Zoller, J. A., Ernst, J., Seluanov, A., Gorbunova, V., Yang, X. W., Raj, K., & Horvath, S. (2023). DNA methylation networks underlying mammalian traits. Science, 381(6658): eabq5693. doi:10.1126/science.abq5693.

    Abstract

    INTRODUCTION
    Comparative epigenomics is an emerging field that combines epigenetic signatures with phylogenetic relationships to elucidate species characteristics such as maximum life span. For this study, we generated cytosine DNA methylation (DNAm) profiles (n = 15,456) from 348 mammalian species using a methylation array platform that targets highly conserved cytosines.
    RATIONALE
    Nature has evolved mammalian species of greatly differing life spans. To resolve the relationship of DNAm with maximum life span and phylogeny, we performed a large-scale cross-species unsupervised analysis. Comparative studies in many species enables the identification of epigenetic correlates of maximum life span and other traits.
    RESULTS
    We first tested whether DNAm levels in highly conserved cytosines captured phylogenetic relationships among species. We constructed phyloepigenetic trees that paralleled the traditional phylogeny. To avoid potential confounding by different tissue types, we generated tissue-specific phyloepigenetic trees. The high phyloepigenetic-phylogenetic congruence is due to differences in methylation levels and is not confounded by sequence conservation.
    We then interrogated the extent to which DNA methylation associates with specific biological traits. We used an unsupervised weighted correlation network analysis (WGCNA) to identify clusters of highly correlated CpGs (comethylation modules). WGCNA identified 55 distinct comethylation modules, of which 30 were significantly associated with traits including maximum life span, adult weight, age, sex, human mortality risk, or perturbations that modulate murine life span.
    Both the epigenome-wide association analysis (EWAS) and eigengene-based analysis identified methylation signatures of maximum life span, and most of these were independent of aging, presumably set at birth, and could be stable predictors of life span at any point in life. Several CpGs that are more highly methylated in long-lived species are located near HOXL subclass homeoboxes and other genes that play a role in morphogenesis and development. Some of these life span–related CpGs are located next to genes that are also implicated in our analysis of upstream regulators (e.g., ASCL1 and SMAD6). CpGs with methylation levels that are inversely related to life span are enriched in transcriptional start site (TSS1) and promoter flanking (PromF4, PromF5) associated chromatin states. Genes located in chromatin state TSS1 are constitutively active and enriched for nucleic acid metabolic processes. This suggests that long-living species evolved mechanisms that maintain low methylation levels in these chromatin states that would favor higher expression levels of genes essential for an organism’s survival.
    The upstream regulator analysis of the EWAS of life span identified the pluripotency transcription factors OCT4, SOX2, and NANOG. Other factors, such as POLII, CTCF, RAD21, YY1, and TAF1, showed the strongest enrichment for negatively life span–related CpGs.
    CONCLUSION
    The phyloepigenetic trees indicate that divergence of DNA methylation profiles closely parallels that of genetics through evolution. Our results demonstrate that DNA methylation is subjected to evolutionary pressures and selection. The publicly available data from our Mammalian Methylation Consortium are a rich source of information for different fields such as evolutionary biology, developmental biology, and aging.
  • Paulat, N. S., Storer, J. M., Moreno-Santillán, D. D., Osmanski, A. B., Sullivan, K. A. M., Grimshaw, J. R., Korstian, J., Halsey, M., Garcia, C. J., Crookshanks, C., Roberts, J., Smit, A. F. A., Hubley, R., Rosen, J., Teeling, E. C., Vernes, S. C., Myers, E., Pippel, M., Brown, T., Hiller, M. and 5 morePaulat, N. S., Storer, J. M., Moreno-Santillán, D. D., Osmanski, A. B., Sullivan, K. A. M., Grimshaw, J. R., Korstian, J., Halsey, M., Garcia, C. J., Crookshanks, C., Roberts, J., Smit, A. F. A., Hubley, R., Rosen, J., Teeling, E. C., Vernes, S. C., Myers, E., Pippel, M., Brown, T., Hiller, M., Zoonomia Consortium, Rojas, D., Dávalos, L. M., Lindblad-Toh, K., Karlsson, E. K., & Ray, D. A. (2023). Chiropterans are a hotspot for horizontal transfer of DNA transposons in mammalia. Molecular Biology and Evolution, 40(5): msad092. doi:10.1093/molbev/msad092.

    Abstract

    Horizontal transfer of transposable elements (TEs) is an important mechanism contributing to genetic diversity and innovation. Bats (order Chiroptera) have repeatedly been shown to experience horizontal transfer of TEs at what appears to be a high rate compared with other mammals. We investigated the occurrence of horizontally transferred (HT) DNA transposons involving bats. We found over 200 putative HT elements within bats; 16 transposons were shared across distantly related mammalian clades, and 2 other elements were shared with a fish and two lizard species. Our results indicate that bats are a hotspot for horizontal transfer of DNA transposons. These events broadly coincide with the diversification of several bat clades, supporting the hypothesis that DNA transposon invasions have contributed to genetic diversification of bats.

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  • Rutz, C., Bronstein, M., Raskin, A., Vernes, S. C., Zacarian, K., & Blasi, D. E. (2023). Using machine learning to decode animal communication. Science, 381(6654), 152-155. doi:10.1126/science.adg7314.

    Abstract

    The past few years have seen a surge of interest in using machine learning (ML) methods for studying the behavior of nonhuman animals (hereafter “animals”) (1). A topic that has attracted particular attention is the decoding of animal communication systems using deep learning and other approaches (2). Now is the time to tackle challenges concerning data availability, model validation, and research ethics, and to embrace opportunities for building collaborations across disciplines and initiatives.
  • Anijs, M., Devanna, P., & Vernes, S. C. (2022). ARHGEF39, a gene implicated in developmental language disorder, activates RHOA and is involved in cell de-adhesion and neural progenitor cell proliferation. Frontiers in Molecular Neuroscience, 15: 941494. doi:10.3389/fnmol.2022.941494.

    Abstract

    ARHGEF39 was previously implicated in developmental language disorder (DLD) via a functional polymorphism that can disrupt post-transcriptional regulation by microRNAs. ARHGEF39 is part of the family of Rho guanine nucleotide exchange factors (RhoGEFs) that activate small Rho GTPases to regulate a wide variety of cellular processes. However, little is known about the function of ARHGEF39, or how its function might contribute to neurodevelopment or related disorders. Here, we explore the molecular function of ARHGEF39 and show that it activates the Rho GTPase RHOA and that high ARHGEF39 expression in cell cultures leads to an increase of detached cells. To explore its role in neurodevelopment, we analyse published single cell RNA-sequencing data and demonstrate that ARHGEF39 is a marker gene for proliferating neural progenitor cells and that it is co-expressed with genes involved in cell division. This suggests a role for ARHGEF39 in neurogenesis in the developing brain. The co-expression of ARHGEF39 with other RHOA-regulating genes supports RHOA as substrate of ARHGEF39 in neural cells, and the involvement of RHOA in neuropsychiatric disorders highlights a potential link between ARHGEF39 and neurodevelopment and disorder. Understanding the GTPase substrate, co-expression network, and processes downstream of ARHGEF39 provide new avenues for exploring the mechanisms by which altered expression levels of ARHGEF39 may contribute to neurodevelopment and associated disorders.

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    tables figures
  • Doronina, L., Hughes, G. M., Moreno-Santillan, D., Lawless, C., Lonergan, T., Ryan, L., Jebb, D., Kirilenko, B. M., Korstian, J. M., Dávalos, L. M., Vernes, S. C., Myers, E. W., Teeling, E. C., Hiller, M., Jermiin, L. S., Schmitz, J., Springer, M. S., & Ray, D. A. (2022). Contradictory phylogenetic signals in the laurasiatheria anomaly zone. Genes, 13(5): 766. doi:10.3390/genes13050766.

    Abstract

    Relationships among laurasiatherian clades represent one of the most highly disputed topics in mammalian phylogeny. In this study, we attempt to disentangle laurasiatherian interordinal relationships using two independent genome-level approaches: (1) quantifying retrotransposon presence/absence patterns, and (2) comparisons of exon datasets at the levels of nucleotides and amino acids. The two approaches revealed contradictory phylogenetic signals, possibly due to a high level of ancestral incomplete lineage sorting. The positions of Eulipotyphla and Chiroptera as the first and second earliest divergences were consistent across the approaches. However, the phylogenetic relationships of Perissodactyla, Cetartiodactyla, and Ferae, were contradictory. While retrotransposon insertion analyses suggest a clade with Cetartiodactyla and Ferae, the exon dataset favoured Cetartiodactyla and Perissodactyla. Future analyses of hitherto unsampled laurasiatherian lineages and synergistic analyses of retrotransposon insertions, exon and conserved intron/intergenic sequences might unravel the conflicting patterns of relationships in this major mammalian clade.
  • Formenti, G., Theissinger, K., Fernandes, C., Bista, I., Bombarely, A., Bleidorn, C., Ciofi, C., Crottini, A., Godoy, J. A., Höglund, J., Malukiewicz, J., Mouton, A., Oomen, R. A., Sadye, P., Palsbøll, P. J., Pampoulie, C., Ruiz-López, M. J., Svardal, H., Theofanopoulou, C., De Vries, J. and 6 moreFormenti, G., Theissinger, K., Fernandes, C., Bista, I., Bombarely, A., Bleidorn, C., Ciofi, C., Crottini, A., Godoy, J. A., Höglund, J., Malukiewicz, J., Mouton, A., Oomen, R. A., Sadye, P., Palsbøll, P. J., Pampoulie, C., Ruiz-López, M. J., Svardal, H., Theofanopoulou, C., De Vries, J., Waldvogel, A.-M., Zhang, G., Mazzoni, C. J., Jarvis, E. D., Bálint, M., & European Reference Genome Atlas (ERGA) Consortium (2022). The era of reference genomes in conservation genomics. Trends in Ecology and Evolution, 37(3), 197-202. doi:10.1016/j.tree.2021.11.008.

    Abstract

    Progress in genome sequencing now enables the large-scale generation of reference genomes. Various international initiatives aim to generate reference genomes representing global biodiversity. These genomes provide unique insights into genomic diversity and architecture, thereby enabling comprehensive analyses of population and functional genomics, and are expected to revolutionize conservation genomics.
  • Hoeksema, N., Hagoort, P., & Vernes, S. C. (2022). Piecing together the building blocks of the vocal learning bat brain. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 294-296). Nijmegen: Joint Conference on Language Evolution (JCoLE).
  • Vernes, S. C., Devanna, P., Hörpel, S. G., Alvarez van Tussenbroek, I., Firzlaff, U., Hagoort, P., Hiller, M., Hoeksema, N., Hughes, G. M., Lavrichenko, K., Mengede, J., Morales, A. E., & Wiesmann, M. (2022). The pale spear‐nosed bat: A neuromolecular and transgenic model for vocal learning. Annals of the New York Academy of Sciences, 1517, 125-142. doi:10.1111/nyas.14884.

    Abstract

    Vocal learning, the ability to produce modified vocalizations via learning from acoustic signals, is a key trait in the evolution of speech. While extensively studied in songbirds, mammalian models for vocal learning are rare. Bats present a promising study system given their gregarious natures, small size, and the ability of some species to be maintained in captive colonies. We utilize the pale spear-nosed bat (Phyllostomus discolor) and report advances in establishing this species as a tractable model for understanding vocal learning. We have taken an interdisciplinary approach, aiming to provide an integrated understanding across genomics (Part I), neurobiology (Part II), and transgenics (Part III). In Part I, we generated new, high-quality genome annotations of coding genes and noncoding microRNAs to facilitate functional and evolutionary studies. In Part II, we traced connections between auditory-related brain regions and reported neuroimaging to explore the structure of the brain and gene expression patterns to highlight brain regions. In Part III, we created the first successful transgenic bats by manipulating the expression of FoxP2, a speech-related gene. These interdisciplinary approaches are facilitating a mechanistic and evolutionary understanding of mammalian vocal learning and can also contribute to other areas of investigation that utilize P. discolor or bats as study species.

    Additional information

    supplementary materials
  • Devanna, P., Dediu, D., & Vernes, S. C. (2019). The Genetics of Language: From complex genes to complex communication. In S.-A. Rueschemeyer, & M. G. Gaskell (Eds.), The Oxford Handbook of Psycholinguistics (2nd ed., pp. 865-898). Oxford: Oxford University Press.

    Abstract

    This chapter discusses the genetic foundations of the human capacity for language. It reviews the molecular structure of the genome and the complex molecular mechanisms that allow genetic information to influence multiple levels of biology. It goes on to describe the active regulation of genes and their formation of complex genetic pathways that in turn control the cellular environment and function. At each of these levels, examples of genes and genetic variants that may influence the human capacity for language are given. Finally, it discusses the value of using animal models to understand the genetic underpinnings of speech and language. From this chapter will emerge the complexity of the genome in action and the multidisciplinary efforts that are currently made to bridge the gap between genetics and language.
  • Lattenkamp, E. Z., Shields, S. M., Schutte, M., Richter, J., Linnenschmidt, M., Vernes, S. C., & Wiegrebe, L. (2019). The vocal repertoire of pale spear-nosed bats in a social roosting context. Frontiers in Ecology and Evolution, 7: 116. doi:10.3389/fevo.2019.00116.

    Abstract

    Commonly known for their ability to echolocate, bats also use a wide variety of social vocalizations to communicate with one another. However, the full vocal repertoires of relatively few bat species have been studied thus far. The present study examined the vocal repertoire of the pale spear-nosed bat, Phyllostomus discolor, in a social roosting context. Based on visual examination of spectrograms and subsequent quantitative analysis of syllables, eight distinct syllable classes were defined, and their prevalence in different behavioral contexts was examined. Four more syllable classes were observed in low numbers and are described here as well. These results show that P. discolor possesses a rich vocal repertoire, which includes vocalizations comparable to previously reported repertoires of other bat species as well as vocalizations previously undescribed. Our data provide detailed information about the temporal and spectral characteristics of syllables emitted by P. discolor, allowing for a better understanding of the communicative system and related behaviors of this species. Furthermore, this vocal repertoire will serve as a basis for future research using P. discolor as a model organism for vocal communication and vocal learning and it will allow for comparative studies between bat species.

    Additional information

    Supplementary material
  • Vernes, S. C. (2019). Neuromolecular approaches to the study of language. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 577-593). Cambridge, MA: MIT Press.
  • Wirthlin, M., Chang, E. F., Knörnschild, M., Krubitzer, L. A., Mello, C. V., Miller, C. T., Pfenning, A. R., Vernes, S. C., Tchernichovski, O., & Yartsev, M. M. (2019). A modular approach to vocal learning: Disentangling the diversity of a complex behavioral trait. Neuron, 104(1), 87-99. doi:10.1016/j.neuron.2019.09.036.

    Abstract

    Vocal learning is a behavioral trait in which the social and acoustic environment shapes the vocal repertoire of individuals. Over the past century, the study of vocal learning has progressed at the intersection of ecology, physiology, neuroscience, molecular biology, genomics, and evolution. Yet, despite the complexity of this trait, vocal learning is frequently described as a binary trait, with species being classified as either vocal learners or vocal non-learners. As a result, studies have largely focused on a handful of species for which strong evidence for vocal learning exists. Recent studies, however, suggest a continuum in vocal learning capacity across taxa. Here, we further suggest that vocal learning is a multi-component behavioral phenotype comprised of distinct yet interconnected modules. Discretizing the vocal learning phenotype into its constituent modules would facilitate integration of findings across a wider diversity of species, taking advantage of the ways in which each excels in a particular module, or in a specific combination of features. Such comparative studies can improve understanding of the mechanisms and evolutionary origins of vocal learning. We propose an initial set of vocal learning modules supported by behavioral and neurobiological data and highlight the need for diversifying the field in order to disentangle the complexity of the vocal learning phenotype.

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