51
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Teeling EC, Vernes SC, Dávalos LM, Ray DA, Gilbert MTP, Myers E. Bat Biology, Genomes, and the Bat1K Project: To Generate Chromosome-Level Genomes for All Living Bat Species. Annu Rev Anim Biosci 2017; 6:23-46. [PMID: 29166127 DOI: 10.1146/annurev-animal-022516-022811] [Citation(s) in RCA: 121] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Bats are unique among mammals, possessing some of the rarest mammalian adaptations, including true self-powered flight, laryngeal echolocation, exceptional longevity, unique immunity, contracted genomes, and vocal learning. They provide key ecosystem services, pollinating tropical plants, dispersing seeds, and controlling insect pest populations, thus driving healthy ecosystems. They account for more than 20% of all living mammalian diversity, and their crown-group evolutionary history dates back to the Eocene. Despite their great numbers and diversity, many species are threatened and endangered. Here we announce Bat1K, an initiative to sequence the genomes of all living bat species (n∼1,300) to chromosome-level assembly. The Bat1K genome consortium unites bat biologists (>148 members as of writing), computational scientists, conservation organizations, genome technologists, and any interested individuals committed to a better understanding of the genetic and evolutionary mechanisms that underlie the unique adaptations of bats. Our aim is to catalog the unique genetic diversity present in all living bats to better understand the molecular basis of their unique adaptations; uncover their evolutionary history; link genotype with phenotype; and ultimately better understand, promote, and conserve bats. Here we review the unique adaptations of bats and highlight how chromosome-level genome assemblies can uncover the molecular basis of these traits. We present a novel sequencing and assembly strategy and review the striking societal and scientific benefits that will result from the Bat1K initiative.
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Affiliation(s)
- Emma C Teeling
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland;
| | - Sonja C Vernes
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, 6500 AH, The Netherlands.,Donders Centre for Cognitive Neuroimaging, Nijmegen, 6525 EN, The Netherlands
| | - Liliana M Dávalos
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York 11794-5245, USA
| | - David A Ray
- Department of Biological Sciences, Texas Tech University, Lubbock, Texas 79409, USA
| | - M Thomas P Gilbert
- Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen, Denmark.,University Museum, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Eugene Myers
- Max Planck Institute for Molecular Cell Biology and Genetics, 01307 Dresden, Germany
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- *Full list of Bat1K Consortium members in Supplemental Appendix
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52
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Herold C, Paulitschek C, Palomero-Gallagher N, Güntürkün O, Zilles K. Transmitter receptors reveal segregation of the arcopallium/amygdala complex in pigeons (Columba livia). J Comp Neurol 2017; 526:439-466. [PMID: 29063593 DOI: 10.1002/cne.24344] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 10/09/2017] [Accepted: 10/10/2017] [Indexed: 12/21/2022]
Abstract
At the beginning of the 20th century it was suggested that a complex group of nuclei in the avian posterior ventral telencephalon is comparable to the mammalian amygdala. Subsequent findings, however, revealed that most of these structures share premotor characteristics, while some indeed constitute the avian amygdala. These developments resulted in 2004 in a change of nomenclature of these nuclei, which from then on were named arcopallial or amygdala nuclei and referred to as the arcopallium/amygdala complex. The structural basis for the similarities between avian and mammalian arcopallial and amygdala subregions is poorly understood. Therefore, we analyzed binding site densities for glutamatergic AMPA, NMDA and kainate, GABAergic GABAA , muscarinic M1 , M2 and nicotinic acetylcholine (nACh; α4 β2 subtype), noradrenergic α1 and α2 , serotonergic 5-HT1A and dopaminergic D1/5 receptors using quantitative in vitro receptor autoradiography combined with a detailed analysis of the cyto- and myelo-architecture. Our approach supports a segregation of the pigeon's arcopallium/amygdala complex into the following subregions: the arcopallium anterius (AA), the arcopallium ventrale (AV), the arcopallium dorsale (AD), the arcopallium intermedium (AI), the arcopallium mediale (AM), the arcopallium posterius (AP), the nucleus posterioris amygdalopallii pars basalis (PoAb) and pars compacta (PoAc), the nucleus taeniae amgygdalae (TnA) and the area subpallialis amygdalae (SpA). Some of these subregions showed further subnuclei and each region of the arcopallium/amygdala complex are characterized by a distinct multi-receptor density expression. Here we provide a new detailed map of the pigeon's arcopallium/amygdala complex and compare the receptor architecture of the subregions to their possible mammalian counterparts.
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Affiliation(s)
- Christina Herold
- C. and O. Vogt Institute of Brain Research, Medical Faculty, Heinrich-Heine University of Düsseldorf, Düsseldorf, Germany
| | - Christina Paulitschek
- C. and O. Vogt Institute of Brain Research, Medical Faculty, Heinrich-Heine University of Düsseldorf, Düsseldorf, Germany
| | | | - Onur Güntürkün
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr-University Bochum, Bochum, Germany
| | - Karl Zilles
- Institute of Neuroscience and Medicine INM-1, Research Center Jülich, Jülich, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, and JARA - Translational Brain Medicine, Aachen, Germany
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53
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Garcia SM, Kopuchian C, Mindlin GB, Fuxjager MJ, Tubaro PL, Goller F. Evolution of Vocal Diversity through Morphological Adaptation without Vocal Learning or Complex Neural Control. Curr Biol 2017; 27:2677-2683.e3. [PMID: 28867206 DOI: 10.1016/j.cub.2017.07.059] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Revised: 06/15/2017] [Accepted: 07/26/2017] [Indexed: 11/25/2022]
Abstract
The evolution of complex behavior is driven by the interplay of morphological specializations and neuromuscular control mechanisms [1-3], and it is often difficult to tease apart their respective contributions. Avian vocal learning and associated neural adaptations are thought to have played a major role in bird diversification [4-8], whereas functional significance of substantial morphological diversity of the vocal organ remains largely unexplored. Within the most species-rich order, Passeriformes, "tracheophones" are a suboscine group that, unlike their oscine sister taxon, does not exhibit vocal learning [9] and is thought to phonate with tracheal membranes [10, 11] instead of the two independent sources found in other passerines [12-14]. Here we show tracheophones possess three sound sources, two oscine-like labial pairs and the unique tracheal membranes, which collectively represent the largest described number of sound sources for a vocal organ. Birds with experimentally disabled tracheal membranes were still able to phonate. Instead of the main sound source, the tracheal membranes constitute a morphological specialization, which, through interaction with bronchial labia, contributes to different acoustic features such as spectral complexity, amplitude modulation, and enhanced sound amplitude. In contrast, these same features arise in oscines from neuromuscular control of two labial sources [15-17]. These findings are supported by a modeling approach and provide a clear example for how a morphological adaptation of the tracheophone vocal organ can generate specific, complex sound features. Morphological specialization therefore constitutes an alternative path in the evolution of acoustic diversity to that of oscine vocal learning and complex neural control.
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Affiliation(s)
- Sarah M Garcia
- Department of Biology, University of Utah, 257 South 1400 East, Salt Lake City, UT 84112, USA.
| | - Cecilia Kopuchian
- CECOAL (Centro de Ecología Aplicada del Litoral) CONICET, Corrientes, Argentina; División Ornitología, Museo Argentino de Ciencias Naturales "Bernardino Rivadavia" MACN-CONICET, Avenida Ángel Gallardo 470, Ciudad Autónoma de Buenos Aires, Argentina
| | - Gabriel B Mindlin
- Depto. Física, FCEyN, Universidad de Buenos Aires, C. Universitaria, Pab I, Buenos Aires, Argentina
| | - Matthew J Fuxjager
- Department of Biology, Wake Forest University, Winston-Salem, NC 27109, USA
| | - Pablo L Tubaro
- División Ornitología, Museo Argentino de Ciencias Naturales "Bernardino Rivadavia" MACN-CONICET, Avenida Ángel Gallardo 470, Ciudad Autónoma de Buenos Aires, Argentina
| | - Franz Goller
- Department of Biology, University of Utah, 257 South 1400 East, Salt Lake City, UT 84112, USA
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54
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Saul MC, Seward CH, Troy JM, Zhang H, Sloofman LG, Lu X, Weisner PA, Caetano-Anolles D, Sun H, Zhao SD, Chandrasekaran S, Sinha S, Stubbs L. Transcriptional regulatory dynamics drive coordinated metabolic and neural response to social challenge in mice. Genome Res 2017; 27:959-972. [PMID: 28356321 PMCID: PMC5453329 DOI: 10.1101/gr.214221.116] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Accepted: 03/24/2017] [Indexed: 12/22/2022]
Abstract
Agonistic encounters are powerful effectors of future behavior, and the ability to learn from this type of social challenge is an essential adaptive trait. We recently identified a conserved transcriptional program defining the response to social challenge across animal species, highly enriched in transcription factor (TF), energy metabolism, and developmental signaling genes. To understand the trajectory of this program and to uncover the most important regulatory influences controlling this response, we integrated gene expression data with the chromatin landscape in the hypothalamus, frontal cortex, and amygdala of socially challenged mice over time. The expression data revealed a complex spatiotemporal patterning of events starting with neural signaling molecules in the frontal cortex and ending in the modulation of developmental factors in the amygdala and hypothalamus, underpinned by a systems-wide shift in expression of energy metabolism-related genes. The transcriptional signals were correlated with significant shifts in chromatin accessibility and a network of challenge-associated TFs. Among these, the conserved metabolic and developmental regulator ESRRA was highlighted for an especially early and important regulatory role. Cell-type deconvolution analysis attributed the differential metabolic and developmental signals in this social context primarily to oligodendrocytes and neurons, respectively, and we show that ESRRA is expressed in both cell types. Localizing ESRRA binding sites in cortical chromatin, we show that this nuclear receptor binds both differentially expressed energy-related and neurodevelopmental TF genes. These data link metabolic and neurodevelopmental signaling to social challenge, and identify key regulatory drivers of this process with unprecedented tissue and temporal resolution.
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Affiliation(s)
- Michael C Saul
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Christopher H Seward
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Joseph M Troy
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Illinois Informatics Institute, Urbana, Illinois 61801, USA
| | - Huimin Zhang
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Laura G Sloofman
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Xiaochen Lu
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Patricia A Weisner
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Derek Caetano-Anolles
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Hao Sun
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Sihai Dave Zhao
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Statistics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Sriram Chandrasekaran
- Harvard Society of Fellows, Harvard University, Cambridge, Massachusetts 02138, USA
- Faculty of Arts and Sciences, Harvard University, Cambridge, Massachusetts 02138, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Saurabh Sinha
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Computer Science
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Lisa Stubbs
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
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55
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Chakraborty M, Chen LF, Fridel EE, Klein ME, Senft RA, Sarkar A, Jarvis ED. Overexpression of human NR2B receptor subunit in LMAN causes stuttering and song sequence changes in adult zebra finches. Sci Rep 2017; 7:942. [PMID: 28432288 PMCID: PMC5430713 DOI: 10.1038/s41598-017-00519-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2016] [Accepted: 03/03/2017] [Indexed: 01/04/2023] Open
Abstract
Zebra finches (Taeniopygia guttata) learn to produce songs in a manner reminiscent of spoken language development in humans. One candidate gene implicated in influencing learning is the N-methyl-D-aspartate (NMDA) subtype 2B glutamate receptor (NR2B). Consistent with this idea, NR2B levels are high in the song learning nucleus LMAN (lateral magnocellular nucleus of the anterior nidopallium) during juvenile vocal learning, and decreases to low levels in adults after learning is complete and the song becomes more stereotyped. To test for the role of NR2B in generating song plasticity, we manipulated NR2B expression in LMAN of adult male zebra finches by increasing its protein levels to those found in juvenile birds, using a lentivirus containing the full-length coding sequence of the human NR2B subunit. We found that increased NR2B expression in adult LMAN induced increases in song sequence diversity and slower song tempo more similar to juvenile songs, but also increased syllable repetitions similar to stuttering. We did not observe these effects in control birds with overexpression of NR2B outside of LMAN or with the green fluorescent protein (GFP) in LMAN. Our results suggest that low NR2B subunit expression in adult LMAN is important in conserving features of stereotyped adult courtship song.
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Affiliation(s)
- Mukta Chakraborty
- Department of Neurobiology, Duke University Medical Center, Durham, NC, 27710, USA. .,Howard Hughes Medical Institute, Chevy Chase, MD, USA.
| | - Liang-Fu Chen
- Department of Neurobiology, Duke University Medical Center, Durham, NC, 27710, USA
| | - Emma E Fridel
- Department of Neurobiology, Duke University Medical Center, Durham, NC, 27710, USA
| | - Marguerita E Klein
- Neurotransgenic Laboratory, Department of Neurobiology, Duke University, Durham, NC, 27710, USA
| | - Rebecca A Senft
- Department of Neurobiology, Duke University Medical Center, Durham, NC, 27710, USA.,Howard Hughes Medical Institute, Chevy Chase, MD, USA.,Department of Neurobiology, Harvard University, Cambridge, MA, 02138, USA
| | - Abhra Sarkar
- Department of Statistical Science, Duke University, Durham, NC, 27710, USA
| | - Erich D Jarvis
- Department of Neurobiology, Duke University Medical Center, Durham, NC, 27710, USA. .,Howard Hughes Medical Institute, Chevy Chase, MD, USA. .,Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, 10065, USA.
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56
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Shpigler HY, Saul MC, Murdoch EE, Cash-Ahmed AC, Seward CH, Sloofman L, Chandrasekaran S, Sinha S, Stubbs LJ, Robinson GE. Behavioral, transcriptomic and epigenetic responses to social challenge in honey bees. GENES BRAIN AND BEHAVIOR 2017; 16:579-591. [DOI: 10.1111/gbb.12379] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Revised: 03/03/2017] [Accepted: 03/14/2017] [Indexed: 01/06/2023]
Affiliation(s)
- H. Y. Shpigler
- Carl R. Woese Institute for Genomic Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
| | - M. C. Saul
- Carl R. Woese Institute for Genomic Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
| | - E. E. Murdoch
- Carl R. Woese Institute for Genomic Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
| | - A. C. Cash-Ahmed
- Carl R. Woese Institute for Genomic Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
| | - C. H. Seward
- Carl R. Woese Institute for Genomic Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
- Department of Cell and Developmental Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
| | - L. Sloofman
- Carl R. Woese Institute for Genomic Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
- Center for Biophysics and Quantitative Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
| | - S. Chandrasekaran
- Harvard Society of Fellows; Harvard University; Cambridge MA USA
- Faculty of Arts and Sciences; Harvard University; Cambridge MA USA
- Broad Institute of MIT and Harvard; Cambridge MA USA
- Department of Biomedical Engineering; University of Michigan; Ann Arbor MI USA
| | - S. Sinha
- Carl R. Woese Institute for Genomic Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
- Center for Biophysics and Quantitative Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
- Department of Computer Science; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
- Department of Entomology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
| | - L. J. Stubbs
- Carl R. Woese Institute for Genomic Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
- Department of Cell and Developmental Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
- Neuroscience Program; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
| | - G. E. Robinson
- Carl R. Woese Institute for Genomic Biology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
- Department of Entomology; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
- Neuroscience Program; University of Illinois at Urbana-Champaign (UIUC); Urbana IL USA
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57
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Perrone-Capano C, Volpicelli F, di Porzio U. Biological bases of human musicality. Rev Neurosci 2017; 28:235-245. [PMID: 28107174 DOI: 10.1515/revneuro-2016-0046] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Accepted: 11/04/2016] [Indexed: 11/15/2022]
Abstract
Music is a universal language, present in all human societies. It pervades the lives of most human beings and can recall memories and feelings of the past, can exert positive effects on our mood, can be strongly evocative and ignite intense emotions, and can establish or strengthen social bonds. In this review, we summarize the research and recent progress on the origins and neural substrates of human musicality as well as the changes in brain plasticity elicited by listening or performing music. Indeed, music improves performance in a number of cognitive tasks and may have beneficial effects on diseased brains. The emerging picture begins to unravel how and why particular brain circuits are affected by music. Numerous studies show that music affects emotions and mood, as it is strongly associated with the brain's reward system. We can therefore assume that an in-depth study of the relationship between music and the brain may help to shed light on how the mind works and how the emotions arise and may improve the methods of music-based rehabilitation for people with neurological disorders. However, many facets of the mind-music connection still remain to be explored and enlightened.
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58
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Abstract
Understanding the biological foundations of language is vital to gaining insight into how the capacity for language may have evolved in humans. Animal models can be exploited to learn about the biological underpinnings of shared human traits, and although no other animals display speech or language, a range of behaviors found throughout the animal kingdom are relevant to speech and spoken language. To date, such investigations have been dominated by studies of our closest primate relatives searching for shared traits, or more distantly related species that are sophisticated vocal communicators, like songbirds. Herein I make the case for turning our attention to the Chiropterans, to shed new light on the biological encoding and evolution of human language-relevant traits. Bats employ complex vocalizations to facilitate navigation as well as social interactions, and are exquisitely tuned to acoustic information. Furthermore, bats display behaviors such as vocal learning and vocal turn-taking that are directly pertinent for human spoken language. Emerging technologies are now allowing the study of bat vocal communication, from the behavioral to the neurobiological and molecular level. Although it is clear that no single animal model can reflect the complexity of human language, by comparing such findings across diverse species we can identify the shared biological mechanisms likely to have influenced the evolution of human language.
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Affiliation(s)
- Sonja C Vernes
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
- Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands.
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59
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Hou PS, Kumamoto T, Hanashima C. A Sensitive and Versatile In Situ Hybridization Protocol for Gene Expression Analysis in Developing Amniote Brains. Methods Mol Biol 2017; 1650:319-334. [PMID: 28809032 DOI: 10.1007/978-1-4939-7216-6_22] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The detection of specific RNA molecules in embryonic tissues has wide research applications including studying gene expression dynamics in brain development and evolution. Recent advances in sequencing technologies have introduced new animal models to explore the molecular principles underlying the assembly and diversification of brain circuits between different amniote species. Here, we provide a step-by-step protocol for a versatile in situ hybridization method that is immediately applicable to a range of amniote embryos including zebra finch and Madagascar ground gecko, two new model organisms that have rapidly emerged for comparative brain studies over recent years. The sensitive detection of transcripts from low to high abundance expression range using the same platform enables direct comparison of gene of interest among different amniotes, providing high-resolution spatiotemporal information of gene expression to dissect the molecular principles underlying brain evolution.
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Affiliation(s)
- Pei-Shan Hou
- Laboratory for Neocortical Development, RIKEN Center for Developmental Biology, Kobe, 650-0047, Japan
| | - Takuma Kumamoto
- Laboratory for Neocortical Development, RIKEN Center for Developmental Biology, Kobe, 650-0047, Japan
- Sorbonne Universités, UPMC Univ Paris 06, INSERM U968, CNRS UMR 7210, Institut de la Vision, 17 rue Moreau, 75012, Paris, France
| | - Carina Hanashima
- Laboratory for Neocortical Development, RIKEN Center for Developmental Biology, Kobe, 650-0047, Japan.
- Department of Biology, Graduate School of Science, Kobe University, Kobe, 657-8501, Japan.
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60
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Jarvis ED. Perspectives from the Avian Phylogenomics Project: Questions that Can Be Answered with Sequencing All Genomes of a Vertebrate Class. Annu Rev Anim Biosci 2016; 4:45-59. [PMID: 26884102 DOI: 10.1146/annurev-animal-021815-111216] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The rapid pace of advances in genome technology, with concomitant reductions in cost, makes it feasible that one day in our lifetime we will have available extant genomes of entire classes of species, including vertebrates. I recently helped cocoordinate the large-scale Avian Phylogenomics Project, which collected and sequenced genomes of 48 bird species representing most currently classified orders to address a range of questions in phylogenomics and comparative genomics. The consortium was able to answer questions not previously possible with just a few genomes. This success spurred on the creation of a project to sequence the genomes of at least one individual of all extant ∼10,500 bird species. The initiation of this project has led us to consider what questions now impossible to answer could be answered with all genomes, and could drive new questions now unimaginable. These include the generation of a highly resolved family tree of extant species, genome-wide association studies across species to identify genetic substrates of many complex traits, redefinition of species and the species concept, reconstruction of the genomes of common ancestors, and generation of new computational tools to address these questions. Here I present visions for the future by posing and answering questions regarding what scientists could potentially do with available genomes of an entire vertebrate class.
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Affiliation(s)
- Erich D Jarvis
- Department of Neurobiology, Duke University Medical Center, Durham, North Carolina 27710
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61
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Abstract
I believe the evidence will show that the science we conduct and discoveries we make are influenced by our cultural experience, whether they be positive, negative, or neutral. I grew up as a person of color in the United States of America, faced with challenges that many had as members of an underrepresented minority group. I write here about some of the lessons I have learned that have allowed me to survive as an underrepresented minority scientist in a majority environment.
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Affiliation(s)
- Erich D Jarvis
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710; Howard Hughes Medical Institute, Chevy Chase, MD 20815
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62
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Adam I, Mendoza E, Kobalz U, Wohlgemuth S, Scharff C. FoxP2 directly regulates the reelin receptor VLDLR developmentally and by singing. Mol Cell Neurosci 2016; 74:96-105. [PMID: 27105823 DOI: 10.1016/j.mcn.2016.04.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2015] [Revised: 03/10/2016] [Accepted: 04/18/2016] [Indexed: 12/15/2022] Open
Abstract
Mutations of the transcription factor FOXP2 cause a severe speech and language disorder. In songbirds, FoxP2 is expressed in the medium spiny neurons (MSNs) of the avian basal ganglia song nucleus, Area X, which is crucial for song learning and adult song performance. Experimental downregulation of FoxP2 in Area X affects spine formation, prevents neuronal plasticity induced by social context and impairs song learning. Direct target genes of FoxP2 relevant for song learning and song production are unknown. Here we show that a lentivirally mediated FoxP2 knockdown in Area X of zebra finches downregulates the expression of VLDLR, one of the two reelin receptors. Zebra finch FoxP2 binds to the promoter of VLDLR and activates it, establishing VLDLR as a direct FoxP2 target. Consistent with these findings, VLDLR expression is co-regulated with FoxP2 as a consequence of adult singing and during song learning. We also demonstrate that knockdown of FoxP2 affects glutamatergic transmission at the corticostriatal MSN synapse. These data raise the possibility that the regulatory relationship between FoxP2 and VLDLR guides structural plasticity towards the subset of FoxP2-positive MSNs in an activity dependent manner via the reelin pathway.
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Affiliation(s)
- Iris Adam
- Department for Animal Behavior, Freie Universität Berlin, Takustr. 6, 14195 Berlin, Germany.
| | - Ezequiel Mendoza
- Department for Animal Behavior, Freie Universität Berlin, Takustr. 6, 14195 Berlin, Germany.
| | - Ursula Kobalz
- Department for Animal Behavior, Freie Universität Berlin, Takustr. 6, 14195 Berlin, Germany.
| | - Sandra Wohlgemuth
- Department for Animal Behavior, Freie Universität Berlin, Takustr. 6, 14195 Berlin, Germany.
| | - Constance Scharff
- Department for Animal Behavior, Freie Universität Berlin, Takustr. 6, 14195 Berlin, Germany.
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63
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Lea AJ, Altmann J, Alberts SC, Tung J. Resource base influences genome-wide DNA methylation levels in wild baboons (Papio cynocephalus). Mol Ecol 2016; 25:1681-96. [PMID: 26508127 PMCID: PMC4846536 DOI: 10.1111/mec.13436] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2015] [Revised: 10/19/2015] [Accepted: 10/22/2015] [Indexed: 12/31/2022]
Abstract
Variation in resource availability commonly exerts strong effects on fitness-related traits in wild animals. However, we know little about the molecular mechanisms that mediate these effects, or about their persistence over time. To address these questions, we profiled genome-wide whole-blood DNA methylation levels in two sets of wild baboons: (i) 'wild-feeding' baboons that foraged naturally in a savanna environment and (ii) 'Lodge' baboons that had ready access to spatially concentrated human food scraps, resulting in high feeding efficiency and low daily travel distances. We identified 1014 sites (0.20% of sites tested) that were differentially methylated between wild-feeding and Lodge baboons, providing the first evidence that resource availability shapes the epigenome in a wild mammal. Differentially methylated sites tended to occur in contiguous stretches (i.e., in differentially methylated regions or DMRs), in promoters and enhancers, and near metabolism-related genes, supporting their functional importance in gene regulation. In agreement, reporter assay experiments confirmed that methylation at the largest identified DMR, located in the promoter of a key glycolysis-related gene, was sufficient to causally drive changes in gene expression. Intriguingly, all dispersing males carried a consistent epigenetic signature of their membership in a wild-feeding group, regardless of whether males dispersed into or out of this group as adults. Together, our findings support a role for DNA methylation in mediating ecological effects on phenotypic traits in the wild and emphasize the dynamic environmental sensitivity of DNA methylation levels across the life course.
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Affiliation(s)
- Amanda J. Lea
- Department of Biology, Duke University, Box 90338, Durham, NC 27708, USA
| | - Jeanne Altmann
- Department of Ecology and Evolution, Princeton University, 106A Guyot Hall, Princeton, NJ 08544, USA
- Institute of Primate Research, National Museums of Kenya, P. O. Box 24481, Karen 00502, Nairobi, Kenya
| | - Susan C. Alberts
- Department of Biology, Duke University, Box 90338, Durham, NC 27708, USA
- Institute of Primate Research, National Museums of Kenya, P. O. Box 24481, Karen 00502, Nairobi, Kenya
| | - Jenny Tung
- Department of Biology, Duke University, Box 90338, Durham, NC 27708, USA
- Institute of Primate Research, National Museums of Kenya, P. O. Box 24481, Karen 00502, Nairobi, Kenya
- Department of Evolutionary Anthropology, Box 90383, Durham, NC 27708, USA
- Duke University Population Research Institute, Box 90420, Durham, NC 27708, USA
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64
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Detecting signatures of positive selection associated with musical aptitude in the human genome. Sci Rep 2016; 6:21198. [PMID: 26879527 PMCID: PMC4754774 DOI: 10.1038/srep21198] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2015] [Accepted: 01/19/2016] [Indexed: 01/18/2023] Open
Abstract
Abilities related to musical aptitude appear to have a long history in human evolution. To elucidate the molecular and evolutionary background of musical aptitude, we compared genome-wide genotyping data (641 K SNPs) of 148 Finnish individuals characterized for musical aptitude. We assigned signatures of positive selection in a case-control setting using three selection methods: haploPS, XP-EHH and FST. Gene ontology classification revealed that the positive selection regions contained genes affecting inner-ear development. Additionally, literature survey has shown that several of the identified genes were known to be involved in auditory perception (e.g. GPR98, USH2A), cognition and memory (e.g. GRIN2B, IL1A, IL1B, RAPGEF5), reward mechanisms (RGS9), and song perception and production of songbirds (e.g. FOXP1, RGS9, GPR98, GRIN2B). Interestingly, genes related to inner-ear development and cognition were also detected in a previous genome-wide association study of musical aptitude. However, the candidate genes detected in this study were not reported earlier in studies of musical abilities. Identification of genes related to language development (FOXP1 and VLDLR) support the popular hypothesis that music and language share a common genetic and evolutionary background. The findings are consistent with the evolutionary conservation of genes related to auditory processes in other species and provide first empirical evidence for signatures of positive selection for abilities that contribute to musical aptitude.
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65
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Lyons MR, Chen LF, Deng JV, Finn C, Pfenning AR, Sabhlok A, Wilson KM, West AE. The transcription factor calcium-response factor limits NMDA receptor-dependent transcription in the developing brain. J Neurochem 2016; 137:164-76. [PMID: 26826701 DOI: 10.1111/jnc.13556] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2015] [Revised: 12/31/2015] [Accepted: 01/20/2016] [Indexed: 12/21/2022]
Abstract
Neuronal activity sculpts brain development by inducing the transcription of genes such as brain-derived neurotrophic factor (Bdnf) that modulate the function of synapses. Sensory experience is transduced into changes in gene transcription via the activation of calcium signaling pathways downstream of both L-type voltage-gated calcium channels (L-VGCCs) and NMDA-type glutamate receptors (NMDARs). These signaling pathways converge on the regulation of transcription factors including calcium-response factor (CaRF). Although CaRF is dispensable for the transcriptional induction of Bdnf following the activation of L-VGCCs, here we show that the loss of CaRF leads to enhanced NMDAR-dependent transcription of Bdnf as well as Arc. We identify the NMDAR subunit-encoding gene Grin3a as a regulatory target of CaRF, and we show that expression of both Carf and Grin3a is depressed by the elevation of intracellular calcium, linking the function of this transcriptional regulatory pathway to neuronal activity. We find that light-dependent activation of Bdnf and Arc transcription is enhanced in the visual cortex of young CaRF knockout mice, suggesting a role for CaRF-dependent dampening of NMDAR-dependent transcription in the developing brain. Finally, we demonstrate that enhanced Bdnf expression in CaRF-lacking neurons increases inhibitory synapse formation. Taken together, these data reveal a novel role for CaRF as an upstream regulator of NMDAR-dependent gene transcription and synapse formation in the developing brain. NMDARs promote brain development by inducing the transcription of genes, including brain-derived neurotrophic factor (BDNF). We show that the transcription factor calcium-response factor (CaRF) limits NMDAR-dependent BDNF induction by regulating expression of the NMDAR subunit GluN3A. Loss of CaRF leads to enhanced BDNF-dependent GABAergic synapse formation indicating the importance of this process for brain development. Our observation that both CaRF and GluN3A are down-regulated by intracellular calcium suggests that this may be a mechanism for experience-dependent modulation of synapse formation.
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Affiliation(s)
- Michelle R Lyons
- Department of Neurobiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Liang-Fu Chen
- Department of Neurobiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Jie V Deng
- Department of Neurobiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Caitlin Finn
- Department of Neurobiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Andreas R Pfenning
- Department of Neurobiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Aditi Sabhlok
- Department of Neurobiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Kelli M Wilson
- Department of Neurobiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Anne E West
- Department of Neurobiology, Duke University Medical Center, Durham, North Carolina, USA
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66
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Genomic Views of Transcriptional Enhancers: Essential Determinants of Cellular Identity and Activity-Dependent Responses in the CNS. J Neurosci 2016; 35:13819-26. [PMID: 26468181 DOI: 10.1523/jneurosci.2622-15.2015] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
UNLABELLED Sprinkled throughout the genome are a million regulatory sequences called transcriptional enhancers that activate gene promoters in the right cells, at the right time. Enhancers endow the brain with its incredible diversity of cell types and also translate neural activity into gene induction. Thanks to rapid advances in genomic technologies, it is now possible to identify thousands of enhancers rapidly, test their transcriptional function en masse, and address their neurobiological functions via genome editing. Enhancers also promise to be a great technological opportunity for neuroscience, offering the potential for cell-type-specific genetic labeling and manipulation without the need for transgenesis. The objective of this review and the accompanying 2015 SfN mini-symposium is to highlight the use of new and emerging genomic technologies to probe enhancer function in the nervous system. SIGNIFICANCE STATEMENT Transcriptional enhancers turn on genes in the right cells, at the right time. Enhancers are also the genomic sequences that encode the incredible diversity of cell types in the brain and enable the brain to turn genes on in response to new experiences. New technology enables enhancers to be found and manipulated. The study of enhancers promises to inform our understanding of brain development and function. The application of enhancer technology holds promise in accelerating basic neuroscience research and enabling gene therapies to be targeted to specific cell types in the brain.
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Larson TA, Lent KL, Bammler TK, MacDonald JW, Wood WE, Caras ML, Thatra NM, Budzillo A, Perkel DJ, Brenowitz EA. Network analysis of microRNA and mRNA seasonal dynamics in a highly plastic sensorimotor neural circuit. BMC Genomics 2015; 16:905. [PMID: 26545368 PMCID: PMC4636775 DOI: 10.1186/s12864-015-2175-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2015] [Accepted: 10/31/2015] [Indexed: 12/31/2022] Open
Abstract
Background Adult neurogenesis and the incorporation of adult-born neurons into functional circuits requires precise spatiotemporal coordination across molecular networks regulating a wide array of processes, including cell proliferation, apoptosis, neurotrophin signaling, and electrical activity. MicroRNAs (miRs) - short, non-coding RNA sequences that alter gene expression by post-transcriptional inhibition or degradation of mRNA sequences - may be involved in the global coordination of such diverse biological processes. To test the hypothesis that miRs related to adult neurogenesis and related cellular processes are functionally regulated in the nuclei of the avian song control circuit, we used microarray analyses to quantify changes in expression of miRs and predicted target mRNAs in the telencephalic nuclei HVC, the robust nucleus of arcopallium (RA), and the basal ganglia homologue Area X in breeding and nonbreeding Gambel’s white-crowned sparrows (Zonotrichia leucophrys gambelli). Results We identified 46 different miRs that were differentially expressed across seasons in the song nuclei. miR-132 and miR-210 showed the highest differential expression in HVC and Area X, respectively. Analyzing predicted mRNA targets of miR-132 identified 33 candidate target genes that regulate processes including cell cycle control, calcium signaling, and neuregulin signaling in HVC. Likewise, miR-210 was predicted to target 14 mRNAs differentially expressed across seasons that regulate serotonin, GABA, and dopamine receptor signaling and inflammation. Conclusions Our results identify potential miR–mRNA regulatory networks related to adult neurogenesis and provide opportunities to discover novel genetic control of the diverse biological processes and factors related to the functional incorporation of new neurons to the adult brain. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2175-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tracy A Larson
- Department of Biology, University of Washington, Seattle, WA, 98195, USA.,Present Address: Basic Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, 98109, USA
| | - Karin L Lent
- Department of Psychology, University of Washington, Seattle, WA, 98195, USA
| | - Theo K Bammler
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, 98195, USA
| | - James W MacDonald
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, 98195, USA
| | - William E Wood
- Department of Otolaryngology, University of Washington, Seattle, WA, 98195, USA.,Graduate Program in Neuroscience, University of Washington, Seattle, WA, 98195, USA.,Present address: Centre National de la Recherche Scientifique, Laboratoire de Neurophysique et Physiologie, UMR 8119, Université Paris Descartes, 45, rue des Saints Pères, 75006, Paris, France
| | - Melissa L Caras
- Department of Psychology, University of Washington, Seattle, WA, 98195, USA.,Graduate Program in Neuroscience, University of Washington, Seattle, WA, 98195, USA.,Present address: Center for Neural Science, New York University, 4 Washington Place, New York, NY, 10003, USA
| | - Nivretta M Thatra
- Department of Biology, University of Washington, Seattle, WA, 98195, USA.,Department of Psychology, University of Washington, Seattle, WA, 98195, USA
| | - Agata Budzillo
- Department of Otolaryngology, University of Washington, Seattle, WA, 98195, USA.,Graduate Program in Neuroscience, University of Washington, Seattle, WA, 98195, USA
| | - David J Perkel
- Department of Biology, University of Washington, Seattle, WA, 98195, USA.,Department of Otolaryngology, University of Washington, Seattle, WA, 98195, USA
| | - Eliot A Brenowitz
- Department of Biology, University of Washington, Seattle, WA, 98195, USA.
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Zinzow-Kramer WM, Horton BM, McKee CD, Michaud JM, Tharp GK, Thomas JW, Tuttle EM, Yi S, Maney DL. Genes located in a chromosomal inversion are correlated with territorial song in white-throated sparrows. GENES BRAIN AND BEHAVIOR 2015; 14:641-54. [PMID: 26463687 DOI: 10.1111/gbb.12252] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Revised: 08/28/2015] [Accepted: 09/09/2015] [Indexed: 01/10/2023]
Abstract
The genome of the white-throated sparrow (Zonotrichia albicollis) contains an inversion polymorphism on chromosome 2 that is linked to predictable variation in a suite of phenotypic traits including plumage color, aggression and parental behavior. Differences in gene expression between the two color morphs, which represent the two common inversion genotypes (ZAL2/ZAL2 and ZAL2/ZAL2(m) ), may therefore advance our understanding of the molecular underpinnings of these phenotypes. To identify genes that are differentially expressed between the two morphs and correlated with behavior, we quantified gene expression and terrirorial aggression, including song, in a population of free-living white-throated sparrows. We analyzed gene expression in two brain regions, the medial amygdala (MeA) and hypothalamus. Both regions are part of a 'social behavior network', which is rich in steroid hormone receptors and previously linked with territorial behavior. Using weighted gene co-expression network analyses, we identified modules of genes that were correlated with both morph and singing behavior. The majority of these genes were located within the inversion, showing the profound effect of the inversion on the expression of genes captured by the rearrangement. These modules were enriched with genes related to retinoic acid signaling and basic cellular functioning. In the MeA, the most prominent pathways were those related to steroid hormone receptor activity. Within these pathways, the only gene encoding such a receptor was ESR1 (estrogen receptor 1), a gene previously shown to predict song rate in this species. The set of candidate genes we identified may mediate the effects of a chromosomal inversion on territorial behavior.
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Affiliation(s)
| | - B M Horton
- Department of Psychology, Emory University, Atlanta, GA
| | - C D McKee
- Department of Psychology, Emory University, Atlanta, GA
| | - J M Michaud
- Department of Psychology, Emory University, Atlanta, GA
| | - G K Tharp
- Yerkes Nonhuman Primate Genomics Core, Emory University, Atlanta, GA
| | - J W Thomas
- NIH Intramural Sequencing Center, National Human Genome Research Institute, NIH, Rockville, MD
| | - E M Tuttle
- Department of Biology, Indiana State University, Terre Haute, IN.,The Center for Genomic Advocacy, Indiana State University, Terre Haute, IN
| | - S Yi
- School of Biology, Georgia Institute of Technology, Atlanta, GA, USA
| | - D L Maney
- Department of Psychology, Emory University, Atlanta, GA
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Schmid M, Smith J, Burt DW, Aken BL, Antin PB, Archibald AL, Ashwell C, Blackshear PJ, Boschiero C, Brown CT, Burgess SC, Cheng HH, Chow W, Coble DJ, Cooksey A, Crooijmans RPMA, Damas J, Davis RVN, de Koning DJ, Delany ME, Derrien T, Desta TT, Dunn IC, Dunn M, Ellegren H, Eöry L, Erb I, Farré M, Fasold M, Fleming D, Flicek P, Fowler KE, Frésard L, Froman DP, Garceau V, Gardner PP, Gheyas AA, Griffin DK, Groenen MAM, Haaf T, Hanotte O, Hart A, Häsler J, Hedges SB, Hertel J, Howe K, Hubbard A, Hume DA, Kaiser P, Kedra D, Kemp SJ, Klopp C, Kniel KE, Kuo R, Lagarrigue S, Lamont SJ, Larkin DM, Lawal RA, Markland SM, McCarthy F, McCormack HA, McPherson MC, Motegi A, Muljo SA, Münsterberg A, Nag R, Nanda I, Neuberger M, Nitsche A, Notredame C, Noyes H, O'Connor R, O'Hare EA, Oler AJ, Ommeh SC, Pais H, Persia M, Pitel F, Preeyanon L, Prieto Barja P, Pritchett EM, Rhoads DD, Robinson CM, Romanov MN, Rothschild M, Roux PF, Schmidt CJ, Schneider AS, Schwartz MG, Searle SM, Skinner MA, Smith CA, Stadler PF, Steeves TE, Steinlein C, Sun L, Takata M, Ulitsky I, Wang Q, Wang Y, Warren WC, Wood JMD, Wragg D, Zhou H. Third Report on Chicken Genes and Chromosomes 2015. Cytogenet Genome Res 2015; 145:78-179. [PMID: 26282327 PMCID: PMC5120589 DOI: 10.1159/000430927] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Michael Schmid
- Department of Human Genetics, University of Würzburg, Würzburg, Germany
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Feng NY, Fergus DJ, Bass AH. Neural transcriptome reveals molecular mechanisms for temporal control of vocalization across multiple timescales. BMC Genomics 2015; 16:408. [PMID: 26014649 PMCID: PMC4446069 DOI: 10.1186/s12864-015-1577-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2015] [Accepted: 04/24/2015] [Indexed: 12/13/2022] Open
Abstract
Background Vocalization is a prominent social behavior among vertebrates, including in the midshipman fish, an established model for elucidating the neural basis of acoustic communication. Courtship vocalizations produced by territorial males are essential for reproductive success, vary over daily and seasonal cycles, and last up to hours per call. Vocalizations rely upon extreme synchrony and millisecond precision in the firing of a homogeneous population of motoneurons, the vocal motor nucleus (VMN). Although studies have identified neural mechanisms driving rapid, precise, and stable neuronal firing over long periods of calling, little is known about underlying genetic/molecular mechanisms. Results We used RNA sequencing-based transcriptome analyses to compare patterns of gene expression in VMN to the surrounding hindbrain across three daily and seasonal time points of high and low sound production to identify candidate genes that underlie VMN’s intrinsic and network neuronal properties. Results from gene ontology enrichment, enzyme pathway mapping, and gene category-wide expression levels highlighted the importance of cellular respiration in VMN function, consistent with the high energetic demands of sustained vocal behavior. Functionally important candidate genes upregulated in the VMN, including at time points corresponding to high natural vocal activity, encode ion channels and neurotransmitter receptors, hormone receptors and biosynthetic enzymes, neuromodulators, aerobic respiration enzymes, and antioxidants. Quantitative PCR and RNA-seq expression levels for 28 genes were significantly correlated. Many candidate gene products regulate mechanisms of neuronal excitability, including those previously identified in VMN motoneurons, as well as novel ones that remain to be investigated. Supporting evidence from previous studies in midshipman strongly validate the value of transcriptomic analyses for linking genes to neural characters that drive behavior. Conclusions Transcriptome analyses highlighted a suite of molecular mechanisms that regulate vocalization over behaviorally relevant timescales, spanning milliseconds to hours and seasons. To our knowledge, this is the first comprehensive characterization of gene expression in a dedicated vocal motor nucleus. Candidate genes identified here may belong to a conserved genetic toolkit for vocal motoneurons facing similar energetic and neurophysiological demands. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1577-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Ni Y Feng
- Department of Neurobiology and Behavior, Cornell University, 14853, Ithaca, NY, USA.
| | - Daniel J Fergus
- Department of Neurobiology and Behavior, Cornell University, 14853, Ithaca, NY, USA. .,Current Address: North Carolina Museum of Natural Sciences, Genomics and Microbiology, 27601, Raleigh, NC, USA.
| | - Andrew H Bass
- Department of Neurobiology and Behavior, Cornell University, 14853, Ithaca, NY, USA.
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Wang R, Chen CC, Hara E, Rivas MV, Roulhac PL, Howard JT, Chakraborty M, Audet JN, Jarvis ED. Convergent differential regulation of SLIT-ROBO axon guidance genes in the brains of vocal learners. J Comp Neurol 2015; 523:892-906. [PMID: 25424606 PMCID: PMC4329046 DOI: 10.1002/cne.23719] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2014] [Revised: 11/20/2014] [Accepted: 11/21/2014] [Indexed: 02/01/2023]
Abstract
Only a few distantly related mammals and birds have the trait of complex vocal learning, which is the ability to imitate novel sounds. This ability is critical for speech acquisition and production in humans, and is attributed to specialized forebrain vocal control circuits that have several unique connections relative to adjacent brain circuits. As a result, it has been hypothesized that there could exist convergent changes in genes involved in neural connectivity of vocal learning circuits. In support of this hypothesis, expanding on our related study (Pfenning et al. [2014] Science 346: 1256846), here we show that the forebrain part of this circuit that makes a relatively rare direct connection to brainstem vocal motor neurons in independent lineages of vocal learning birds (songbird, parrot, and hummingbird) has specialized regulation of axon guidance genes from the SLIT-ROBO molecular pathway. The SLIT1 ligand was differentially downregulated in the motor song output nucleus that makes the direct projection, whereas its receptor ROBO1 was developmentally upregulated during critical periods for vocal learning. Vocal nonlearning bird species and male mice, which have much more limited vocal plasticity and associated circuits, did not show comparable specialized regulation of SLIT-ROBO genes in their nonvocal motor cortical regions. These findings are consistent with SLIT and ROBO gene dysfunctions associated with autism, dyslexia, and speech sound language disorders and suggest that convergent evolution of vocal learning was associated with convergent changes in the SLIT-ROBO axon guidance pathway.
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Affiliation(s)
- Rui Wang
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical CenterDurham, North Carolina, 27710
- Computational Biology and Bioinformatics Program, Institute for Genome Science and Policy, Duke UniversityDurham, North Carolina, 27710
- Beijing Prosperous BiopharmBeijing, 100085, China
| | - Chun-Chun Chen
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical CenterDurham, North Carolina, 27710
| | - Erina Hara
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical CenterDurham, North Carolina, 27710
| | - Miriam V Rivas
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical CenterDurham, North Carolina, 27710
- Research Service, Veterans Affairs Medical CenterDurham North Carolina, 27710
| | - Petra L Roulhac
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical CenterDurham, North Carolina, 27710
| | - Jason T Howard
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical CenterDurham, North Carolina, 27710
| | - Mukta Chakraborty
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical CenterDurham, North Carolina, 27710
| | - Jean-Nicolas Audet
- Department of Biology, McGill UniversityMontreal, Quebec, H3A 1B1, Canada
| | - Erich D Jarvis
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical CenterDurham, North Carolina, 27710
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72
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Kanduri C, Kuusi T, Ahvenainen M, Philips AK, Lähdesmäki H, Järvelä I. The effect of music performance on the transcriptome of professional musicians. Sci Rep 2015; 5:9506. [PMID: 25806429 PMCID: PMC5380155 DOI: 10.1038/srep09506] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2014] [Accepted: 02/27/2015] [Indexed: 12/31/2022] Open
Abstract
Music performance by professional musicians involves a wide-spectrum of cognitive and multi-sensory motor skills, whose biological basis is unknown. Several neuroscientific studies have demonstrated that the brains of professional musicians and non-musicians differ structurally and functionally and that musical training enhances cognition. However, the molecules and molecular mechanisms involved in music performance remain largely unexplored. Here, we investigated the effect of music performance on the genome-wide peripheral blood transcriptome of professional musicians by analyzing the transcriptional responses after a 2-hr concert performance and after a 'music-free' control session. The up-regulated genes were found to affect dopaminergic neurotransmission, motor behavior, neuronal plasticity, and neurocognitive functions including learning and memory. Particularly, candidate genes such as SNCA, FOS and DUSP1 that are involved in song perception and production in songbirds, were identified, suggesting an evolutionary conservation in biological processes related to sound perception/production. Additionally, modulation of genes related to calcium ion homeostasis, iron ion homeostasis, glutathione metabolism, and several neuropsychiatric and neurodegenerative diseases implied that music performance may affect the biological pathways that are otherwise essential for the proper maintenance of neuronal function and survival. For the first time, this study provides evidence for the candidate genes and molecular mechanisms underlying music performance.
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Affiliation(s)
- Chakravarthi Kanduri
- Department of Medical Genetics, Haartman Institute, University of Helsinki, P.O. Box 720, 00014 University of Helsinki, Finland
| | - Tuire Kuusi
- DocMus doctoral school, Sibelius Academy, University of the Arts, P.O. Box 30, FI 0097 Uniarts, Finland
| | - Minna Ahvenainen
- Department of Medical Genetics, Haartman Institute, University of Helsinki, P.O. Box 720, 00014 University of Helsinki, Finland
| | - Anju K. Philips
- Department of Medical Genetics, Haartman Institute, University of Helsinki, P.O. Box 720, 00014 University of Helsinki, Finland
| | - Harri Lähdesmäki
- Department of Information and Computer Science, Aalto University, FI-00076 AALTO, Finland
| | - Irma Järvelä
- Department of Medical Genetics, Haartman Institute, University of Helsinki, P.O. Box 720, 00014 University of Helsinki, Finland
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Blatti C, Kazemian M, Wolfe S, Brodsky M, Sinha S. Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism. Nucleic Acids Res 2015; 43:3998-4012. [PMID: 25791631 PMCID: PMC4417154 DOI: 10.1093/nar/gkv195] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2015] [Accepted: 02/24/2015] [Indexed: 11/17/2022] Open
Abstract
Characterization of cell type specific regulatory networks and elements is a major challenge in genomics, and emerging strategies frequently employ high-throughput genome-wide assays of transcription factor (TF) to DNA binding, histone modifications or chromatin state. However, these experiments remain too difficult/expensive for many laboratories to apply comprehensively to their system of interest. Here, we explore the potential of elucidating regulatory systems in varied cell types using computational techniques that rely on only data of gene expression, low-resolution chromatin accessibility, and TF–DNA binding specificities (‘motifs’). We show that static computational motif scans overlaid with chromatin accessibility data reasonably approximate experimentally measured TF–DNA binding. We demonstrate that predicted binding profiles and expression patterns of hundreds of TFs are sufficient to identify major regulators of ∼200 spatiotemporal expression domains in the Drosophila embryo. We are then able to learn reliable statistical models of enhancer activity for over 70 expression domains and apply those models to annotate domain specific enhancers genome-wide. Throughout this work, we apply our motif and accessibility based approach to comprehensively characterize the regulatory network of fruitfly embryonic development and show that the accuracy of our computational method compares favorably to approaches that rely on data from many experimental assays.
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Affiliation(s)
- Charles Blatti
- Department of Computer Science, University of Illinois, Urbana, IL 61801, USA
| | - Majid Kazemian
- National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Scot Wolfe
- Program in Gene Function and Expression, University of Massachusetts Medical School, Worcester, MA 01655, USA Department of Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Michael Brodsky
- Program in Gene Function and Expression, University of Massachusetts Medical School, Worcester, MA 01655, USA Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Saurabh Sinha
- Department of Computer Science, University of Illinois, Urbana, IL 61801, USA Institute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA
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74
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Pfenning AR, Hara E, Whitney O, Rivas MV, Wang R, Roulhac PL, Howard JT, Wirthlin M, Lovell PV, Ganapathy G, Mouncastle J, Moseley MA, Thompson JW, Soderblom EJ, Iriki A, Kato M, Gilbert MTP, Zhang G, Bakken T, Bongaarts A, Bernard A, Lein E, Mello CV, Hartemink AJ, Jarvis ED. Convergent transcriptional specializations in the brains of humans and song-learning birds. Science 2014; 346:1256846. [PMID: 25504733 DOI: 10.1126/science.1256846] [Citation(s) in RCA: 285] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Song-learning birds and humans share independently evolved similarities in brain pathways for vocal learning that are essential for song and speech and are not found in most other species. Comparisons of brain transcriptomes of song-learning birds and humans relative to vocal nonlearners identified convergent gene expression specializations in specific song and speech brain regions of avian vocal learners and humans. The strongest shared profiles relate bird motor and striatal song-learning nuclei, respectively, with human laryngeal motor cortex and parts of the striatum that control speech production and learning. Most of the associated genes function in motor control and brain connectivity. Thus, convergent behavior and neural connectivity for a complex trait are associated with convergent specialized expression of multiple genes.
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Affiliation(s)
- Andreas R Pfenning
- Department of Neurobiology, Howard Hughes Medical Institute, and Duke University Medical Center, Durham, NC 27710, USA.
| | - Erina Hara
- Department of Neurobiology, Howard Hughes Medical Institute, and Duke University Medical Center, Durham, NC 27710, USA
| | - Osceola Whitney
- Department of Neurobiology, Howard Hughes Medical Institute, and Duke University Medical Center, Durham, NC 27710, USA
| | - Miriam V Rivas
- Department of Neurobiology, Howard Hughes Medical Institute, and Duke University Medical Center, Durham, NC 27710, USA
| | - Rui Wang
- Department of Neurobiology, Howard Hughes Medical Institute, and Duke University Medical Center, Durham, NC 27710, USA
| | - Petra L Roulhac
- Department of Neurobiology, Howard Hughes Medical Institute, and Duke University Medical Center, Durham, NC 27710, USA
| | - Jason T Howard
- Department of Neurobiology, Howard Hughes Medical Institute, and Duke University Medical Center, Durham, NC 27710, USA
| | - Morgan Wirthlin
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | - Peter V Lovell
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | - Ganeshkumar Ganapathy
- Department of Neurobiology, Howard Hughes Medical Institute, and Duke University Medical Center, Durham, NC 27710, USA
| | - Jacquelyn Mouncastle
- Department of Neurobiology, Howard Hughes Medical Institute, and Duke University Medical Center, Durham, NC 27710, USA
| | - M Arthur Moseley
- Duke Proteomics and Metabolomics Core Facility, Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - J Will Thompson
- Duke Proteomics and Metabolomics Core Facility, Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Erik J Soderblom
- Duke Proteomics and Metabolomics Core Facility, Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Atsushi Iriki
- Laboratory for Symbolic Cognitive Development, Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Masaki Kato
- Laboratory for Symbolic Cognitive Development, Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - M Thomas P Gilbert
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen, Denmark. Trace and Environmental DNA Laboratory, Department of Environment and Agriculture, Curtin University, Perth, Western Australia 6102, Australia
| | - Guojie Zhang
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China. Centre for Social Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
| | - Trygve Bakken
- Allen Institute for Brain Science, Seattle, WA 98103, USA
| | | | - Amy Bernard
- Allen Institute for Brain Science, Seattle, WA 98103, USA
| | - Ed Lein
- Allen Institute for Brain Science, Seattle, WA 98103, USA
| | - Claudio V Mello
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | | | - Erich D Jarvis
- Department of Neurobiology, Howard Hughes Medical Institute, and Duke University Medical Center, Durham, NC 27710, USA.
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75
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Zhang G, Li C, Li Q, Li B, Larkin DM, Lee C, Storz JF, Antunes A, Greenwold MJ, Meredith RW, Ödeen A, Cui J, Zhou Q, Xu L, Pan H, Wang Z, Jin L, Zhang P, Hu H, Yang W, Hu J, Xiao J, Yang Z, Liu Y, Xie Q, Yu H, Lian J, Wen P, Zhang F, Li H, Zeng Y, Xiong Z, Liu S, Zhou L, Huang Z, An N, Wang J, Zheng Q, Xiong Y, Wang G, Wang B, Wang J, Fan Y, da Fonseca RR, Alfaro-Núñez A, Schubert M, Orlando L, Mourier T, Howard JT, Ganapathy G, Pfenning A, Whitney O, Rivas MV, Hara E, Smith J, Farré M, Narayan J, Slavov G, Romanov MN, Borges R, Machado JP, Khan I, Springer MS, Gatesy J, Hoffmann FG, Opazo JC, Håstad O, Sawyer RH, Kim H, Kim KW, Kim HJ, Cho S, Li N, Huang Y, Bruford MW, Zhan X, Dixon A, Bertelsen MF, Derryberry E, Warren W, Wilson RK, Li S, Ray DA, Green RE, O'Brien SJ, Griffin D, Johnson WE, Haussler D, Ryder OA, Willerslev E, Graves GR, Alström P, Fjeldså J, Mindell DP, Edwards SV, Braun EL, Rahbek C, Burt DW, Houde P, Zhang Y, Yang H, Wang J, Jarvis ED, Gilbert MTP, Wang J. Comparative genomics reveals insights into avian genome evolution and adaptation. Science 2014; 346:1311-20. [PMID: 25504712 PMCID: PMC4390078 DOI: 10.1126/science.1251385] [Citation(s) in RCA: 665] [Impact Index Per Article: 66.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits.
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Affiliation(s)
- Guojie Zhang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China. Centre for Social Evolution, Department of Biology, Universitetsparken 15, University of Copenhagen, DK-2100 Copenhagen, Denmark.
| | - Cai Li
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China. Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Qiye Li
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China. Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Bo Li
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Denis M Larkin
- Royal Veterinary College, University of London, London, UK
| | - Chul Lee
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-742, Republic of Korea. Cho and Kim Genomics, Seoul National University Research Park, Seoul 151-919, Republic of Korea
| | - Jay F Storz
- School of Biological Sciences, University of Nebraska, Lincoln, NE 68588, USA
| | - Agostinho Antunes
- Centro de Investigación en Ciencias del Mar y Limnología (CIMAR)/Centro Interdisciplinar de Investigação Marinha e Ambiental (CIIMAR), Universidade do Porto, Rua dos Bragas, 177, 4050-123 Porto, Portugal. Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal
| | - Matthew J Greenwold
- Department of Biological Sciences, University of South Carolina, Columbia, SC, USA
| | - Robert W Meredith
- Department of Biology and Molecular Biology, Montclair State University, Montclair, NJ 07043, USA
| | - Anders Ödeen
- Department of Animal Ecology, Uppsala University, Norbyvägen 18D, S-752 36 Uppsala, Sweden
| | - Jie Cui
- Marie Bashir Institute for Infectious Diseases and Biosecurity, Charles Perkins Centre, School of Biological Sciences and Sydney Medical School, The University of Sydney, Sydney, NSW 2006, Australia. Program in Emerging Infectious Diseases, Duke-NUS Graduate Medical School, Singapore 169857, Singapore
| | - Qi Zhou
- Department of Integrative Biology University of California, Berkeley, CA 94720, USA
| | - Luohao Xu
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China. College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Hailin Pan
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Zongji Wang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China. School of Bioscience and Bioengineering, South China University of Technology, Guangzhou 510006, China
| | - Lijun Jin
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Pei Zhang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Haofu Hu
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Wei Yang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Jiang Hu
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Jin Xiao
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Zhikai Yang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Yang Liu
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Qiaolin Xie
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Hao Yu
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Jinmin Lian
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Ping Wen
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Fang Zhang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Hui Li
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Yongli Zeng
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Zijun Xiong
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Shiping Liu
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China. School of Bioscience and Bioengineering, South China University of Technology, Guangzhou 510006, China
| | - Long Zhou
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Zhiyong Huang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Na An
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Jie Wang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China. BGI Education Center,University of Chinese Academy of Sciences,Shenzhen, 518083, China
| | - Qiumei Zheng
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Yingqi Xiong
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Guangbiao Wang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Bo Wang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Jingjing Wang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Yu Fan
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan 650223, China
| | - Rute R da Fonseca
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Alonzo Alfaro-Núñez
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Mikkel Schubert
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Ludovic Orlando
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Tobias Mourier
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Jason T Howard
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical Center, Durham, NC 27710, USA
| | - Ganeshkumar Ganapathy
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical Center, Durham, NC 27710, USA
| | - Andreas Pfenning
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical Center, Durham, NC 27710, USA
| | - Osceola Whitney
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical Center, Durham, NC 27710, USA
| | - Miriam V Rivas
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical Center, Durham, NC 27710, USA
| | - Erina Hara
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical Center, Durham, NC 27710, USA
| | - Julia Smith
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical Center, Durham, NC 27710, USA
| | - Marta Farré
- Royal Veterinary College, University of London, London, UK
| | - Jitendra Narayan
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK
| | - Gancho Slavov
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK
| | | | - Rui Borges
- Centro de Investigación en Ciencias del Mar y Limnología (CIMAR)/Centro Interdisciplinar de Investigação Marinha e Ambiental (CIIMAR), Universidade do Porto, Rua dos Bragas, 177, 4050-123 Porto, Portugal. Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal
| | - João Paulo Machado
- Centro de Investigación en Ciencias del Mar y Limnología (CIMAR)/Centro Interdisciplinar de Investigação Marinha e Ambiental (CIIMAR), Universidade do Porto, Rua dos Bragas, 177, 4050-123 Porto, Portugal. Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, Portugal
| | - Imran Khan
- Centro de Investigación en Ciencias del Mar y Limnología (CIMAR)/Centro Interdisciplinar de Investigação Marinha e Ambiental (CIIMAR), Universidade do Porto, Rua dos Bragas, 177, 4050-123 Porto, Portugal. Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal
| | - Mark S Springer
- Department of Biology, University of California Riverside, Riverside, CA 92521, USA
| | - John Gatesy
- Department of Biology, University of California Riverside, Riverside, CA 92521, USA
| | - Federico G Hoffmann
- Department of Biochemistry, Molecular Biology, Entomology and Plant Pathology, Mississippi State University, Mississippi State, MS 39762, USA. Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Mississippi State, MS 39762, USA
| | - Juan C Opazo
- Instituto de Ciencias Ambientales y Evolutivas, Facultad de Ciencias, Universidad Austral de Chile, Valdivia, Chile
| | - Olle Håstad
- Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Post Office Box 7011, S-750 07, Uppsala, Sweden
| | - Roger H Sawyer
- Department of Biological Sciences, University of South Carolina, Columbia, SC, USA
| | - Heebal Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-742, Republic of Korea. Cho and Kim Genomics, Seoul National University Research Park, Seoul 151-919, Republic of Korea. Department of Agricultural Biotechnology and Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 151-742, Republic of Korea
| | - Kyu-Won Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-742, Republic of Korea
| | - Hyeon Jeong Kim
- Cho and Kim Genomics, Seoul National University Research Park, Seoul 151-919, Republic of Korea
| | - Seoae Cho
- Cho and Kim Genomics, Seoul National University Research Park, Seoul 151-919, Republic of Korea
| | - Ning Li
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100094, China
| | - Yinhua Huang
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100094, China. College of Animal Science and Technology, China Agricultural University, Beijing 100094, China
| | - Michael W Bruford
- Organisms and Environment Division, Cardiff School of Biosciences, Cardiff University, Cardiff CF10 3AX, Wales, UK
| | - Xiangjiang Zhan
- Organisms and Environment Division, Cardiff School of Biosciences, Cardiff University, Cardiff CF10 3AX, Wales, UK. Key Lab of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101 China
| | - Andrew Dixon
- International Wildlife Consultants, Carmarthen SA33 5YL, Wales, UK
| | - Mads F Bertelsen
- Centre for Zoo and Wild Animal Health, Copenhagen Zoo, Roskildevej 38, DK-2000 Frederiksberg, Denmark
| | - Elizabeth Derryberry
- Department of Ecology and Evolutionary Biology, Tulane University, New Orleans, LA, USA. Museum of Natural Science, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Wesley Warren
- The Genome Institute at Washington University, St. Louis, MO 63108, USA
| | - Richard K Wilson
- The Genome Institute at Washington University, St. Louis, MO 63108, USA
| | - Shengbin Li
- College of Medicine and Forensics, Xi'an Jiaotong University, Xi'an, 710061, China
| | - David A Ray
- Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Mississippi State, MS 39762, USA
| | - Richard E Green
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064, USA
| | - Stephen J O'Brien
- Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia. Nova Southeastern University Oceanographic Center 8000 N Ocean Drive, Dania, FL 33004, USA
| | - Darren Griffin
- School of Biosciences, University of Kent, Canterbury CT2 7NJ, UK
| | - Warren E Johnson
- Smithsonian Conservation Biology Institute, National Zoological Park, 1500 Remount Road, Front Royal, VA 22630, USA
| | - David Haussler
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064, USA
| | - Oliver A Ryder
- Genetics Division, San Diego Zoo Institute for Conservation Research, 15600 San Pasqual Valley Road, Escondido, CA 92027, USA
| | - Eske Willerslev
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Gary R Graves
- Department of Vertebrate Zoology, MRC-116, National Museum of Natural History, Smithsonian Institution, Post Office Box 37012, Washington, DC 20013-7012, USA. Center for Macroecology, Evolution and Climate, the Natural History Museum of Denmark, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen O, Denmark
| | - Per Alström
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, 1 Beichen West Road, Chaoyang District, Beijing 100101, China. Swedish Species Information Centre, Swedish University of Agricultural Sciences, Box 7007, SE-750 07 Uppsala, Sweden
| | - Jon Fjeldså
- Center for Macroecology, Evolution and Climate, the Natural History Museum of Denmark, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen O, Denmark
| | - David P Mindell
- Department of Biochemistry & Biophysics, University of California, San Francisco, CA 94158, USA
| | - Scott V Edwards
- Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, 26 Oxford Street, Cambridge, MA 02138, USA
| | - Edward L Braun
- Department of Biology and Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | - Carsten Rahbek
- Center for Macroecology, Evolution and Climate, the Natural History Museum of Denmark, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen O, Denmark. Imperial College London, Grand Challenges in Ecosystems and the Environment Initiative, Silwood Park Campus, Ascot, Berkshire SL5 7PY, UK
| | - David W Burt
- Division of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, The Roslin Institute Building, University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
| | - Peter Houde
- Department of Biology, New Mexico State University, Box 30001 MSC 3AF, Las Cruces, NM 88003, USA
| | - Yong Zhang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Huanming Yang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China. Macau University of Science and Technology, Avenida Wai long, Taipa, Macau 999078, China
| | - Jian Wang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China
| | - Erich D Jarvis
- Department of Neurobiology, Howard Hughes Medical Institute, Duke University Medical Center, Durham, NC 27710, USA.
| | - M Thomas P Gilbert
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark. Trace and Environmental DNA Laboratory, Department of Environment and Agriculture, Curtin University, Perth, Western Australia, 6102, Australia.
| | - Jun Wang
- China National GeneBank, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518083, China. Macau University of Science and Technology, Avenida Wai long, Taipa, Macau 999078, China. Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200 Copenhagen, Denmark. Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia. Department of Medicine, University of Hong Kong, Hong Kong.
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