1
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Crossley ER, Fedorova L, Mulyar O, Freeman R, Khuder S, Fedorov A. Computational identification of ultra-conserved elements in the human genome: a hypothesis on homologous DNA pairing. NAR Genom Bioinform 2024; 6:lqae074. [PMID: 38962254 PMCID: PMC11217675 DOI: 10.1093/nargab/lqae074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 05/29/2024] [Accepted: 06/19/2024] [Indexed: 07/05/2024] Open
Abstract
Thousands of prolonged sequences of human ultra-conserved non-coding elements (UCNEs) share only one common feature: peculiarities in the unique composition of their dinucleotides. Here we investigate whether the numerous weak signals emanating from these dinucleotide arrangements can be used for computational identification of UCNEs within the human genome. For this purpose, we analyzed 4272 UCNE sequences, encompassing 1 393 448 nucleotides, alongside equally sized control samples of randomly selected human genomic sequences. Our research identified nine different features of dinucleotide arrangements that enable differentiation of UCNEs from the rest of the genome. We employed these nine features, implementing three Machine Learning techniques - Support Vector Machine, Random Forest, and Artificial Neural Networks - to classify UCNEs, achieving an accuracy rate of 82-84%, with specific conditions allowing for over 90% accuracy. Notably, the strongest feature for UCNE identification was the frequency ratio between GpC dinucleotides and the sum of GpG and CpC dinucleotides. Additionally, we investigated the entire pool of 31 046 SNPs located within UCNEs for their representation in the ClinVar database, which catalogs human SNPs with known phenotypic effects. The presence of UCNE-associated SNPs in ClinVar aligns with the expectation of a random distribution, emphasizing the enigmatic nature of UCNE phenotypic manifestation.
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Affiliation(s)
- Emily R Crossley
- Program of Bioinformatics and Proteomics/Genomics, University of Toledo, Toledo, OH 43606, USA
| | | | | | | | - Sadik Khuder
- Program of Bioinformatics and Proteomics/Genomics, University of Toledo, Toledo, OH 43606, USA
- Department of Medicine, University of Toledo, Toledo, OH 43606, USA
| | - Alexei Fedorov
- Program of Bioinformatics and Proteomics/Genomics, University of Toledo, Toledo, OH 43606, USA
- CRI Genetics LLC, Santa Monica, CA 90404, USA
- Department of Medicine, University of Toledo, Toledo, OH 43606, USA
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2
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Sullivan PF, Yao S, Hjerling-Leffler J. Schizophrenia genomics: genetic complexity and functional insights. Nat Rev Neurosci 2024; 25:611-624. [PMID: 39030273 DOI: 10.1038/s41583-024-00837-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/04/2024] [Indexed: 07/21/2024]
Abstract
Determining the causes of schizophrenia has been a notoriously intractable problem, resistant to a multitude of investigative approaches over centuries. In recent decades, genomic studies have delivered hundreds of robust findings that implicate nearly 300 common genetic variants (via genome-wide association studies) and more than 20 rare variants (via whole-exome sequencing and copy number variant studies) as risk factors for schizophrenia. In parallel, functional genomic and neurobiological studies have provided exceptionally detailed information about the cellular composition of the brain and its interconnections in neurotypical individuals and, increasingly, in those with schizophrenia. Taken together, these results suggest unexpected complexity in the mechanisms that drive schizophrenia, pointing to the involvement of ensembles of genes (polygenicity) rather than single-gene causation. In this Review, we describe what we now know about the genetics of schizophrenia and consider the neurobiological implications of this information.
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Affiliation(s)
- Patrick F Sullivan
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jens Hjerling-Leffler
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
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3
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Supple MA, Escalona M, Adkins J, Buchalski MR, Alexandre N, Sahasrabudhe RM, Nguyen O, Sacco S, Fairbairn C, Beraut E, Seligmann W, Green RE, Meredith E, Shapiro B. A genome assembly of the American black bear, Ursus americanus, from California. J Hered 2024; 115:498-506. [PMID: 39008331 PMCID: PMC11334205 DOI: 10.1093/jhered/esae037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 07/09/2024] [Indexed: 07/16/2024] Open
Abstract
The American black bear, Ursus americanus, is a widespread and ecologically important species in North America. In California, the black bear plays an important role in a variety of ecosystems and serves as an important species for recreational hunting. While research suggests that the populations in California are currently healthy, continued monitoring is critical, with genomic analyses providing an important surveillance tool. Here we report a high-quality, near chromosome-level genome assembly from a U. americanus sample from California. The primary assembly has a total length of 2.5 Gb contained in 316 scaffolds, a contig N50 of 58.9 Mb, a scaffold N50 of 67.6 Mb, and a BUSCO completeness score of 96%. This U. americanus genome assembly will provide an important resource for the targeted management of black bear populations in California, with the goal of achieving an appropriate balance between the recreational value of black bears and the maintenance of viable populations. The high quality of this genome assembly will also make it a valuable resource for comparative genomic analyses among black bear populations and among bear species.
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Affiliation(s)
- Megan A Supple
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, United States
- Howard Hughes Medical Institute, University of California, Santa Cruz, CA, United States
| | - Merly Escalona
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA, United States
| | - Jillian Adkins
- Wildlife Forensic Lab, Law Enforcement Division, California Department of Fish and Wildlife, Sacramento, CA, United States
| | - Michael R Buchalski
- Wildlife Genetics Research Unit, Wildlife Health Laboratory, California Department of Fish and Wildlife, Sacramento, CA, United States
| | - Nicolas Alexandre
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, United States
- Howard Hughes Medical Institute, University of California, Santa Cruz, CA, United States
| | - Ruta M Sahasrabudhe
- DNA Technologies and Expression Analysis Core Laboratory, Genome Center, University of California, Davis, CA, United States
| | - Oanh Nguyen
- DNA Technologies and Expression Analysis Core Laboratory, Genome Center, University of California, Davis, CA, United States
| | - Samuel Sacco
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, United States
| | - Colin Fairbairn
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, United States
| | - Eric Beraut
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, United States
| | - William Seligmann
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, United States
| | - Richard E Green
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA, United States
| | - Erin Meredith
- Wildlife Forensic Lab, Law Enforcement Division, California Department of Fish and Wildlife, Sacramento, CA, United States
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, United States
- Howard Hughes Medical Institute, University of California, Santa Cruz, CA, United States
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4
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Martinez Q, Amson E, Ruf I, Smith TD, Pirot N, Broyon M, Lebrun R, Captier G, Gascó Martín C, Ferreira G, Fabre PH. Turbinal bones are still one of the last frontiers of the tetrapod skull: hypotheses, challenges and perspectives. Biol Rev Camb Philos Soc 2024. [PMID: 39092480 DOI: 10.1111/brv.13122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 07/03/2024] [Accepted: 07/10/2024] [Indexed: 08/04/2024]
Abstract
Turbinals are bony or cartilaginous structures that are present in the nasal cavity of most tetrapods. They are involved in key functions such as olfaction, heat, and moisture conservation, as well as protection of the respiratory tract. Despite recent studies that challenged long-standing hypotheses about their physiological and genomic correlation, turbinals remain largely unexplored, particularly for non-mammalian species. Herein, we review and synthesise the current knowledge of turbinals using an integrative approach that includes comparative anatomy, physiology, histology and genomics. In addition, we provide synonyms and correspondences of tetrapod turbinals from about 80 publications. This work represents a first step towards drawing hypotheses of homology for the whole clade, and provides a strong basis to develop new research avenues.
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Affiliation(s)
- Quentin Martinez
- Institut des Sciences de l'Évolution (ISEM, UMR 5554 CNRS-IRD-UM), Université de Montpellier, Place E. Bataillon-CC 064 - 34095, Montpellier Cedex 5, France
- Staatliches Museum für Naturkunde Stuttgart, Stuttgart, DE-70191, Germany
| | - Eli Amson
- Staatliches Museum für Naturkunde Stuttgart, Stuttgart, DE-70191, Germany
| | - Irina Ruf
- Abteilung Messelforschung und Mammalogie, Senckenberg Forschungsinstitut und Naturmuseum Frankfurt, Frankfurt am Main, 60325, Germany
- Institut für Geowissenschaften, Goethe-Universität Frankfurt am Main, Frankfurt am Main, 60438, Germany
- Research Center of Paleontology and Stratigraphy, Jilin University, Changchun, 130026, China
| | - Timothy D Smith
- School of Physical Therapy, Slippery Rock University, Slippery Rock, PA, 16057, USA
| | - Nelly Pirot
- BioCampus Montpellier (BCM), Université de Montpellier, CNRS, INSERM, Montpellier, 34090, France
- Institut de Recherche en Cancérologie de Montpellier (IRCM), Université de Montpellier, Institut du Cancer de Montpellier (ICM), INSERM, Montpellier, 34298, France
| | - Morgane Broyon
- BioCampus Montpellier (BCM), Université de Montpellier, CNRS, INSERM, Montpellier, 34090, France
- Institut de Recherche en Cancérologie de Montpellier (IRCM), Université de Montpellier, Institut du Cancer de Montpellier (ICM), INSERM, Montpellier, 34298, France
| | - Renaud Lebrun
- Institut des Sciences de l'Évolution (ISEM, UMR 5554 CNRS-IRD-UM), Université de Montpellier, Place E. Bataillon-CC 064 - 34095, Montpellier Cedex 5, France
| | - Guillaume Captier
- Laboratoire d'anatomie, UFR médecine, Université Montpellier, Montpellier, 34060, France
- Département chirurgie pédiatrique, CHU Montpellier, université Montpellier, Montpellier, 34295, France
| | | | - Gabriel Ferreira
- Senckenberg Centre for Human Evolution and Palaeoenvironment at the Eberhard Karls University of Tübingen, Tübingen, 727074, Germany
- Department of Geosciences, Faculty of Sciences, Eberhard Karls University of Tübingen, Tübingen, 727074, Germany
| | - Pierre-Henri Fabre
- Institut des Sciences de l'Évolution (ISEM, UMR 5554 CNRS-IRD-UM), Université de Montpellier, Place E. Bataillon-CC 064 - 34095, Montpellier Cedex 5, France
- Mammal Section, Department of Life Sciences, The Natural History Museum, London, SW7 5DB, UK
- Institut Universitaire de France (IUF), Paris, 75231, France
- Division of Vertebrate Zoology (Mammalogy), American Museum of Natural History, Central Park West, 79th St, New York, NY, 10024-5192, USA
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5
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Okamoto AS, Capellini TD. Parallel Evolution at the Regulatory Base-Pair Level Contributes to Mammalian Interspecific Differences in Polygenic Traits. Mol Biol Evol 2024; 41:msae157. [PMID: 39073613 PMCID: PMC11321361 DOI: 10.1093/molbev/msae157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 07/02/2024] [Accepted: 07/23/2024] [Indexed: 07/30/2024] Open
Abstract
Parallel evolution occurs when distinct lineages with similar ancestral states converge on a new phenotype. Parallel evolution has been well documented at the organ, gene pathway, and amino acid sequence level but in theory, it can also occur at individual nucleotides within noncoding regions. To examine the role of parallel evolution in shaping the biology of mammalian complex traits, we used data on single-nucleotide polymorphisms (SNPs) influencing human intraspecific variation to predict trait values in other species for 11 complex traits. We found that the alleles at SNP positions associated with human intraspecific height and red blood cell (RBC) count variation are associated with interspecific variation in the corresponding traits across mammals. These associations hold for deeper branches of mammalian evolution as well as between strains of collaborative cross mice. While variation in RBC count between primates uses both ancient and more recently evolved genomic regions, we found that only primate-specific elements were correlated with primate body size. We show that the SNP positions driving these signals are flanked by conserved sequences, maintain synteny with target genes, and overlap transcription factor binding sites. This work highlights the potential of conserved but tunable regulatory elements to be reused in parallel to facilitate evolutionary adaptation in mammals.
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Affiliation(s)
- Alexander S Okamoto
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Terence D Capellini
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
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6
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Zhu Y, Watson C, Safonova Y, Pennell M, Bankevich A. Assessing Assembly Errors in Immunoglobulin Loci: A Comprehensive Evaluation of Long-read Genome Assemblies Across Vertebrates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.19.604360. [PMID: 39091785 PMCID: PMC11291089 DOI: 10.1101/2024.07.19.604360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Long-read sequencing technologies have revolutionized genome assembly producing near-complete chromosome assemblies for numerous organisms, which are invaluable to research in many fields. However, regions with complex repetitive structure continue to represent a challenge for genome assembly algorithms, particularly in areas with high heterozygosity. Robust and comprehensive solutions for the assessment of assembly accuracy and completeness in these regions do not exist. In this study we focus on the assembly of biomedically important antibody-encoding immunoglobulin (IG) loci, which are characterized by complex duplications and repeat structures. High-quality full-length assemblies for these loci are critical for resolving haplotype-level annotations of IG genes, without which, functional and evolutionary studies of antibody immunity across vertebrates are not tractable. To address these challenges, we developed a pipeline, "CloseRead", that generates multiple assembly verification metrics for analysis and visualization. These metrics expand upon those of existing quality assessment tools and specifically target complex and highly heterozygous regions. Using CloseRead, we systematically assessed the accuracy and completeness of IG loci in publicly available assemblies of 74 vertebrate species, identifying problematic regions. We also demonstrated that inspecting assembly graphs for problematic regions can both identify the root cause of assembly errors and illuminate solutions for improving erroneous assemblies. For a subset of species, we were able to correct assembly errors through targeted reassembly. Together, our analysis demonstrated the utility of assembly assessment in improving the completeness and accuracy of IG loci across species.
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Affiliation(s)
- Yixin Zhu
- Department of Quantitative and Computational Biology and Biological Sciences, University of Southern California, Los Angeles, CA, United States
| | - Corey Watson
- Department of Biochemistry and Molecular Biology, University of Louisville School of Medicine, Louisville, KY, United States
| | - Yana Safonova
- Department of Computer Science and Engineering, Pennsylvania State University, PA, United States
| | - Matt Pennell
- Department of Quantitative and Computational Biology and Biological Sciences, University of Southern California, Los Angeles, CA, United States
| | - Anton Bankevich
- Department of Computer Science and Engineering, Pennsylvania State University, PA, United States
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7
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Buckley RM, Ostrander EA. Large-scale genomic analysis of the domestic dog informs biological discovery. Genome Res 2024; 34:811-821. [PMID: 38955465 PMCID: PMC11293549 DOI: 10.1101/gr.278569.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/04/2024]
Abstract
Recent advances in genomics, coupled with a unique population structure and remarkable levels of variation, have propelled the domestic dog to new levels as a system for understanding fundamental principles in mammalian biology. Central to this advance are more than 350 recognized breeds, each a closed population that has undergone selection for unique features. Genetic variation in the domestic dog is particularly well characterized compared with other domestic mammals, with almost 3000 high-coverage genomes publicly available. Importantly, as the number of sequenced genomes increases, new avenues for analysis are becoming available. Herein, we discuss recent discoveries in canine genomics regarding behavior, morphology, and disease susceptibility. We explore the limitations of current data sets for variant interpretation, tradeoffs between sequencing strategies, and the burgeoning role of long-read genomes for capturing structural variants. In addition, we consider how large-scale collections of whole-genome sequence data drive rare variant discovery and assess the geographic distribution of canine diversity, which identifies Asia as a major source of missing variation. Finally, we review recent comparative genomic analyses that will facilitate annotation of the noncoding genome in dogs.
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Affiliation(s)
- Reuben M Buckley
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Elaine A Ostrander
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
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8
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Cummins M, Watson C, Edwards RJ, Mattick JS. The Evolution of Ultraconserved Elements in Vertebrates. Mol Biol Evol 2024; 41:msae146. [PMID: 39058500 PMCID: PMC11276968 DOI: 10.1093/molbev/msae146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 06/29/2024] [Accepted: 07/08/2024] [Indexed: 07/18/2024] Open
Abstract
Ultraconserved elements were discovered two decades ago, arbitrarily defined as sequences that are identical over a length ≥ 200 bp in the human, mouse, and rat genomes. The definition was subsequently extended to sequences ≥ 100 bp identical in at least three of five mammalian genomes (including dog and cow), and shown to have undergone rapid expansion from ancestors in fish and strong negative selection in birds and mammals. Since then, many more genomes have become available, allowing better definition and more thorough examination of ultraconserved element distribution and evolutionary history. We developed a fast and flexible analytical pipeline for identifying ultraconserved elements in multiple genomes, dedUCE, which allows manipulation of minimum length, sequence identity, and number of species with a detectable ultraconserved element according to specified parameters. We suggest an updated definition of ultraconserved elements as sequences ≥ 100 bp and ≥97% sequence identity in ≥50% of placental mammal orders (12,813 ultraconserved elements). By mapping ultraconserved elements to ∼200 species, we find that placental ultraconserved elements appeared early in vertebrate evolution, well before land colonization, suggesting that the evolutionary pressures driving ultraconserved element selection were present in aquatic environments in the Cambrian-Devonian periods. Most (>90%) ultraconserved elements likely appeared after the divergence of gnathostomes from jawless predecessors, were largely established in sequence identity by early Sarcopterygii evolution-before the divergence of lobe-finned fishes from tetrapods-and became near fixed in the amniotes. Ultraconserved elements are mainly located in the introns of protein-coding and noncoding genes involved in neurological and skeletomuscular development, enriched in regulatory elements, and dynamically expressed throughout embryonic development.
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Affiliation(s)
- Mitchell Cummins
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney, NSW 2052, Australia
| | - Cadel Watson
- School of Engineering, UNSW Sydney, Sydney, NSW 2052, Australia
| | - Richard J Edwards
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney, NSW 2052, Australia
| | - John S Mattick
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney, NSW 2052, Australia
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9
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Kim BY, Gellert HR, Church SH, Suvorov A, Anderson SS, Barmina O, Beskid SG, Comeault AA, Crown KN, Diamond SE, Dorus S, Fujichika T, Hemker JA, Hrcek J, Kankare M, Katoh T, Magnacca KN, Martin RA, Matsunaga T, Medeiros MJ, Miller DE, Pitnick S, Schiffer M, Simoni S, Steenwinkel TE, Syed ZA, Takahashi A, Wei KHC, Yokoyama T, Eisen MB, Kopp A, Matute D, Obbard DJ, O’Grady PM, Price DK, Toda MJ, Werner T, Petrov DA. Single-fly genome assemblies fill major phylogenomic gaps across the Drosophilidae Tree of Life. PLoS Biol 2024; 22:e3002697. [PMID: 39024225 PMCID: PMC11257246 DOI: 10.1371/journal.pbio.3002697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 06/03/2024] [Indexed: 07/20/2024] Open
Abstract
Long-read sequencing is driving rapid progress in genome assembly across all major groups of life, including species of the family Drosophilidae, a longtime model system for genetics, genomics, and evolution. We previously developed a cost-effective hybrid Oxford Nanopore (ONT) long-read and Illumina short-read sequencing approach and used it to assemble 101 drosophilid genomes from laboratory cultures, greatly increasing the number of genome assemblies for this taxonomic group. The next major challenge is to address the laboratory culture bias in taxon sampling by sequencing genomes of species that cannot easily be reared in the lab. Here, we build upon our previous methods to perform amplification-free ONT sequencing of single wild flies obtained either directly from the field or from ethanol-preserved specimens in museum collections, greatly improving the representation of lesser studied drosophilid taxa in whole-genome data. Using Illumina Novaseq X Plus and ONT P2 sequencers with R10.4.1 chemistry, we set a new benchmark for inexpensive hybrid genome assembly at US $150 per genome while assembling genomes from as little as 35 ng of genomic DNA from a single fly. We present 183 new genome assemblies for 179 species as a resource for drosophilid systematics, phylogenetics, and comparative genomics. Of these genomes, 62 are from pooled lab strains and 121 from single adult flies. Despite the sample limitations of working with small insects, most single-fly diploid assemblies are comparable in contiguity (>1 Mb contig N50), completeness (>98% complete dipteran BUSCOs), and accuracy (>QV40 genome-wide with ONT R10.4.1) to assemblies from inbred lines. We present a well-resolved multi-locus phylogeny for 360 drosophilid and 4 outgroup species encompassing all publicly available (as of August 2023) genomes for this group. Finally, we present a Progressive Cactus whole-genome, reference-free alignment built from a subset of 298 suitably high-quality drosophilid genomes. The new assemblies and alignment, along with updated laboratory protocols and computational pipelines, are released as an open resource and as a tool for studying evolution at the scale of an entire insect family.
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Affiliation(s)
- Bernard Y. Kim
- Department of Biology, Stanford University, Stanford, California, United States of America
| | - Hannah R. Gellert
- Department of Biology, Stanford University, Stanford, California, United States of America
| | - Samuel H. Church
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut United States of America
| | - Anton Suvorov
- Department of Biological Sciences, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Sean S. Anderson
- Department of Biology, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Olga Barmina
- Department of Evolution and Ecology, University of California Davis, Davis, California, United States of America
| | - Sofia G. Beskid
- Department of Biology, Stanford University, Stanford, California, United States of America
| | - Aaron A. Comeault
- School of Environmental and Natural Sciences, Bangor University, Bangor, United Kingdom
| | - K. Nicole Crown
- Department of Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Sarah E. Diamond
- Department of Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Steve Dorus
- Center for Reproductive Evolution, Department of Biology, Syracuse University, Syracuse, New York, United States of America
| | - Takako Fujichika
- Department of Biological Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - James A. Hemker
- Department of Developmental Biology, Stanford University, Stanford, California, United States of America
| | - Jan Hrcek
- Institute of Entomology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Maaria Kankare
- Department of Biological and Environmental Science, University of Jyväskylä, Jyväskylä, Finland
| | - Toru Katoh
- Department of Biological Sciences, Hokkaido University, Sapporo, Japan
| | - Karl N. Magnacca
- Hawaii Invertebrate Program, Division of Forestry & Wildlife, Honolulu, Hawaii, United States of America
| | - Ryan A. Martin
- Department of Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Teruyuki Matsunaga
- Department of Complexity Science and Engineering, The University of Tokyo, Tokyo, Japan
| | - Matthew J. Medeiros
- Pacific Biosciences Research Center, University of Hawaiʻi, Mānoa, Hawaii, United States of America
| | - Danny E. Miller
- Division of Genetic Medicine, Department of Pediatrics; Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, United States of America
| | - Scott Pitnick
- Center for Reproductive Evolution, Department of Biology, Syracuse University, Syracuse, New York, United States of America
| | - Michele Schiffer
- Daintree Rainforest Observatory, James Cook University, Townsville, Australia
| | - Sara Simoni
- Department of Biology, Stanford University, Stanford, California, United States of America
| | | | - Zeeshan A. Syed
- Center for Reproductive Evolution, Department of Biology, Syracuse University, Syracuse, New York, United States of America
| | - Aya Takahashi
- Department of Biological Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Kevin H-C. Wei
- Department of Zoology, The University of British Columbia, Vancouver, Canada
| | - Tsuya Yokoyama
- Department of Biology, Stanford University, Stanford, California, United States of America
| | - Michael B. Eisen
- Department of Cell and Molecular Biology, University of California Berkeley, Berkeley, California, United States of America
- Howard Hughes Medical Institute, University of California Berkeley, Berkeley, California, United States of America
| | - Artyom Kopp
- Department of Evolution and Ecology, University of California Davis, Davis, California, United States of America
| | - Daniel Matute
- Department of Biology, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Darren J. Obbard
- Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, United Kingdom
| | - Patrick M. O’Grady
- Department of Entomology, Cornell University, Ithaca, New York, United States of America
| | - Donald K. Price
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, Nevada, United States of America
| | | | - Thomas Werner
- Department of Biological Sciences, Michigan Technological University, Houghton, Michigan, United States of America
| | - Dmitri A. Petrov
- Department of Biology, Stanford University, Stanford, California, United States of America
- CZ Biohub, Investigator, San Francisco, California, United States of America
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10
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Yuan Z, Song Y, Zhang S, Chen Y, Xu M, Fan G, Liu X. The Chromosome-Scale Genome of Chitala ornata Illuminates the Evolution of Early Teleosts. BIOLOGY 2024; 13:478. [PMID: 39056673 PMCID: PMC11274187 DOI: 10.3390/biology13070478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 06/20/2024] [Accepted: 06/25/2024] [Indexed: 07/28/2024]
Abstract
Teleosts are the most prolific vertebrates, occupying the vast majority of aquatic environments, and their pectoral fins have undergone remarkable physiological transformations throughout their evolution. Studying early teleost fishes, such as those belonging to the Osteoglossiformes order, could offer crucial insights into the adaptive evolution of pectoral fins within this group. In this study, we have assembled a chromosomal-level genome for the Clown featherback (Chitala ornata), achieving the highest quality genome assembly for Osteoglossiformes to date, with a contig N50 of 32.78 Mb and a scaffold N50 of 40.73 Mb. By combining phylogenetic analysis, we determined that the Clown featherback diverged approximately 202 to 203 million years ago (Ma), aligning with continental separation events. Our analysis revealed the intriguing discovery that a unique deletion of regulatory elements is adjacent to the Gli3 gene, specifically in teleosts. This deletion might be tied to the specialized adaptation of their pectoral fins. Furthermore, our findings indicate that specific contractions and expansions of transposable elements (TEs) in teleosts, including the Clown featherback, could be connected to their adaptive evolution. In essence, this study not only provides a high-quality genomic resource for Osteoglossiformes but also sheds light on the evolutionary trajectory of early teleosts.
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Affiliation(s)
- Zengbao Yuan
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; (Z.Y.)
- BGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; (Y.S.); (Y.C.)
- BGI-Shenzhen, Shenzhen 518083, China
| | - Yue Song
- BGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; (Y.S.); (Y.C.)
- BGI-Shenzhen, Shenzhen 518083, China
| | - Suyu Zhang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; (Z.Y.)
- BGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; (Y.S.); (Y.C.)
- BGI-Shenzhen, Shenzhen 518083, China
| | - Yadong Chen
- BGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; (Y.S.); (Y.C.)
| | - Mengyang Xu
- BGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; (Y.S.); (Y.C.)
| | - Guangyi Fan
- BGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; (Y.S.); (Y.C.)
- BGI-Shenzhen, Shenzhen 518083, China
| | - Xin Liu
- BGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; (Y.S.); (Y.C.)
- BGI-Shenzhen, Shenzhen 518083, China
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11
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Ferris E, Gonzalez Murcia JD, Cristina Rodriguez A, Steinwand S, Stacher Hörndli C, Traenkner D, Maldonado-Catala PJ, Gregg C. Genomic Convergence in Hibernating Mammals Elucidates the Genetics of Metabolic Regulation in the Hypothalamus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.26.600891. [PMID: 38979381 PMCID: PMC11230405 DOI: 10.1101/2024.06.26.600891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Elucidating the genetic basis of mammalian metabolism could help define mechanisms central to health and disease. Here, we define conserved cis-regulatory elements (CREs) and programs for mammalian metabolic control. We delineate gene expression and chromatin responses in the mouse hypothalamus for 7 steps of the Fed-to-Fasted-to-Refed (FFR) response process. Comparative genomics of hibernating versus non-hibernating lineages then illuminates cis-elements showing convergent changes in hibernators. Hibernators accumulated loss-of-function effects for specific CREs regulating hypothalamic FFR responses. Multi-omics approaches pinpoint key CREs, genes, regulatory programs, and cell types in the divergence of hibernating and homeothermic lineages. The refeeding period after extended fasting is revealed as one critical period of chromatin remodeling with convergent genomic changes. This genetic framework is a step toward harnessing hibernator adaptations in medicine.
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Affiliation(s)
- Elliott Ferris
- Departments of Neurobiology, University of Utah; Salt Lake City, 84105, USA
| | | | | | - Susan Steinwand
- Departments of Neurobiology, University of Utah; Salt Lake City, 84105, USA
| | | | - Dimitri Traenkner
- Departments of Neurobiology, University of Utah; Salt Lake City, 84105, USA
| | - Pablo J Maldonado-Catala
- Departments of Neurobiology, University of Utah; Salt Lake City, 84105, USA
- Biomedical Informatics, University of Utah; Salt Lake City, 84105, USA
| | - Christopher Gregg
- Departments of Neurobiology, University of Utah; Salt Lake City, 84105, USA
- Human Genetics, University of Utah; Salt Lake City, 84105, USA
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12
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Murphy WJ, Harris AJ. Toward telomere-to-telomere cat genomes for precision medicine and conservation biology. Genome Res 2024; 34:655-664. [PMID: 38849156 PMCID: PMC11216403 DOI: 10.1101/gr.278546.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2024]
Abstract
Genomic data from species of the cat family Felidae promise to stimulate veterinary and human medical advances, and clarify the coherence of genome organization. We describe how interspecies hybrids have been instrumental in the genetic analysis of cats, from the first genetic maps to propelling cat genomes toward the T2T standard set by the human genome project. Genotype-to-phenotype mapping in cat models has revealed dozens of health-related genetic variants, the molecular basis for mammalian pigmentation and patterning, and species-specific adaptations. Improved genomic surveillance of natural and captive populations across the cat family tree will increase our understanding of the genetic architecture of traits, population dynamics, and guide a future of genome-enabled biodiversity conservation.
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Affiliation(s)
- William J Murphy
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas 77843-4458, USA;
- Department of Biology, Texas A&M University, College Station, Texas 77843-4458, USA
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, Texas 77843-4458, USA
| | - Andrew J Harris
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas 77843-4458, USA
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, Texas 77843-4458, USA
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13
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Wickenhagen A, van Tol S, Munster V. Molecular determinants of cross-species transmission in emerging viral infections. Microbiol Mol Biol Rev 2024:e0000123. [PMID: 38912755 DOI: 10.1128/mmbr.00001-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/25/2024] Open
Abstract
SUMMARYSeveral examples of high-impact cross-species transmission of newly emerging or re-emerging bat-borne viruses, such as Sudan virus, Nipah virus, and severe acute respiratory syndrome coronavirus 2, have occurred in the past decades. Recent advancements in next-generation sequencing have strengthened ongoing efforts to catalog the global virome, in particular from the multitude of different bat species. However, functional characterization of these novel viruses and virus sequences is typically limited with regard to assessment of their cross-species potential. Our understanding of the intricate interplay between virus and host underlying successful cross-species transmission has focused on the basic mechanisms of entry and replication, as well as the importance of host innate immune responses. In this review, we discuss the various roles of the respective molecular mechanisms underlying cross-species transmission using different recent bat-borne viruses as examples. To delineate the crucial cellular and molecular steps underlying cross-species transmission, we propose a framework of overall characterization to improve our capacity to characterize viruses as benign, of interest, or of concern.
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Affiliation(s)
- Arthur Wickenhagen
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, Montana, USA
| | - Sarah van Tol
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, Montana, USA
| | - Vincent Munster
- Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, Montana, USA
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14
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Edenhofer FC, Térmeg A, Ohnuki M, Jocher J, Kliesmete Z, Briem E, Hellmann I, Enard W. Generation and characterization of inducible KRAB-dCas9 iPSCs from primates for cross-species CRISPRi. iScience 2024; 27:110090. [PMID: 38947524 PMCID: PMC11214527 DOI: 10.1016/j.isci.2024.110090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 03/28/2024] [Accepted: 05/21/2024] [Indexed: 07/02/2024] Open
Abstract
Comparisons of molecular phenotypes across primates provide unique information to understand human biology and evolution, and single-cell RNA-seq CRISPR interference (CRISPRi) screens are a powerful approach to analyze them. Here, we generate and validate three human, three gorilla, and two cynomolgus iPS cell lines that carry a dox-inducible KRAB-dCas9 construct at the AAVS1 locus. We show that despite variable expression levels of KRAB-dCas9 among lines, comparable downregulation of target genes and comparable phenotypic effects are observed in a single-cell RNA-seq CRISPRi screen. Hence, we provide valuable resources for performing and further extending CRISPRi in human and non-human primates.
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Affiliation(s)
- Fiona C. Edenhofer
- Anthropology and Human Genomics, Faculty of Biology, Ludwig-Maximilians-Universität München, 82152 Planegg, Germany
| | - Anita Térmeg
- Anthropology and Human Genomics, Faculty of Biology, Ludwig-Maximilians-Universität München, 82152 Planegg, Germany
| | - Mari Ohnuki
- Anthropology and Human Genomics, Faculty of Biology, Ludwig-Maximilians-Universität München, 82152 Planegg, Germany
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto 606-8501, Japan
- Hakubi Center, Kyoto University, Kyoto 606-8501, Japan
| | - Jessica Jocher
- Anthropology and Human Genomics, Faculty of Biology, Ludwig-Maximilians-Universität München, 82152 Planegg, Germany
| | - Zane Kliesmete
- Anthropology and Human Genomics, Faculty of Biology, Ludwig-Maximilians-Universität München, 82152 Planegg, Germany
| | - Eva Briem
- Anthropology and Human Genomics, Faculty of Biology, Ludwig-Maximilians-Universität München, 82152 Planegg, Germany
| | - Ines Hellmann
- Anthropology and Human Genomics, Faculty of Biology, Ludwig-Maximilians-Universität München, 82152 Planegg, Germany
| | - Wolfgang Enard
- Anthropology and Human Genomics, Faculty of Biology, Ludwig-Maximilians-Universität München, 82152 Planegg, Germany
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15
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Feng B, Li Y, Liu H, Steenwyk JL, David KT, Tian X, Xu B, Gonçalves C, Opulente DA, LaBella AL, Harrison MC, Wolters JF, Shao S, Chen Z, Fisher KJ, Groenewald M, Hittinger CT, Shen XX, Rokas A, Zhou X, Li Y. Unique trajectory of gene family evolution from genomic analysis of nearly all known species in an ancient yeast lineage. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.05.597512. [PMID: 38895429 PMCID: PMC11185758 DOI: 10.1101/2024.06.05.597512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Gene gains and losses are a major driver of genome evolution; their precise characterization can provide insights into the origin and diversification of major lineages. Here, we examined gene family evolution of 1,154 genomes from nearly all known species in the medically and technologically important yeast subphylum Saccharomycotina. We found that yeast gene family and genome evolution are distinct from plants, animals, and filamentous ascomycetes and are characterized by small genome sizes and smaller gene numbers but larger gene family sizes. Faster-evolving lineages (FELs) in yeasts experienced significantly higher rates of gene losses-commensurate with a narrowing of metabolic niche breadth-but higher speciation rates than their slower-evolving sister lineages (SELs). Gene families most often lost are those involved in mRNA splicing, carbohydrate metabolism, and cell division and are likely associated with intron loss, metabolic breadth, and non-canonical cell cycle processes. Our results highlight the significant role of gene family contractions in the evolution of yeast metabolism, genome function, and speciation, and suggest that gene family evolutionary trajectories have differed markedly across major eukaryotic lineages.
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Affiliation(s)
- Bo Feng
- Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China
- Laboratory for Marine Biology and Biotechnology, Qingdao Marine Science and Technology Center, Qingdao 266237, China
| | - Yonglin Li
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Center, South China Agricultural University, Guangzhou 510642, China
| | - Hongyue Liu
- Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China
| | - Jacob L. Steenwyk
- Howards Hughes Medical Institute and the Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Kyle T. David
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
| | - Xiaolin Tian
- Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China
| | - Biyang Xu
- Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China
| | - Carla Gonçalves
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
- Associate Laboratory i4HB—Institute for Health and Bioeconomy and UCIBIO—Applied Molecular Biosciences Unit, Department of Life Sciences, NOVA School of Science and Technology, Universidade NOVA de Lisboa, Caparica, Portugal
- UCIBIO-i4HB, Departamento de Ciências da Vida, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal
| | - Dana A. Opulente
- Laboratory of Genetics, J. F. Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, Department of Energy (DOE) Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI 53726, USA
- Biology Department, Villanova University, Villanova, PA 19085, USA
| | - Abigail L. LaBella
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, North Carolina Research Campus, Kannapolis NC 28223, USA AND Center for Computational Intelligence to Predict Health and Environmental Risks (CIPHER), University of North Carolina at Charlotte, Charlotte, NC, 28233, USA
| | - Marie-Claire Harrison
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
| | - John F. Wolters
- Laboratory of Genetics, J. F. Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, Department of Energy (DOE) Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Shengyuan Shao
- Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China
| | - Zhaohao Chen
- Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China
| | - Kaitlin J. Fisher
- Laboratory of Genetics, J. F. Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, Department of Energy (DOE) Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI 53726, USA
- Department of Biological Sciences, State University of New York at Oswego, Oswego, NY, 13126, USA
| | | | - Chris Todd Hittinger
- Laboratory of Genetics, J. F. Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, Department of Energy (DOE) Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Xing-Xing Shen
- Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Insect Sciences, Zhejiang University, Hangzhou 310058, China
| | - Antonis Rokas
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
| | - Xiaofan Zhou
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Center, South China Agricultural University, Guangzhou 510642, China
| | - Yuanning Li
- Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China
- Laboratory for Marine Biology and Biotechnology, Qingdao Marine Science and Technology Center, Qingdao 266237, China
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16
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Caporale LH. Evolutionary feedback from the environment shapes mechanisms that generate genome variation. J Physiol 2024; 602:2601-2614. [PMID: 38194279 DOI: 10.1113/jp284411] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 12/14/2023] [Indexed: 01/10/2024] Open
Abstract
Darwin recognized that 'a grand and almost untrodden field of inquiry will be opened, on the causes and laws of variation.' However, because the Modern Synthesis assumes that the intrinsic probability of any individual mutation is unrelated to that mutation's potential adaptive value, attention has been focused on selection rather than on the intrinsic generation of variation. Yet many examples illustrate that the term 'random' mutation, as widely understood, is inaccurate. The probabilities of distinct classes of variation are neither evenly distributed across a genome nor invariant over time, nor unrelated to their potential adaptive value. Because selection acts upon variation, multiple biochemical mechanisms can and have evolved that increase the relative probability of adaptive mutations. In effect, the generation of heritable variation is in a feedback loop with selection, such that those mechanisms that tend to generate variants that survive recurring challenges in the environment would be captured by this survival and thus inherited and accumulated within lineages of genomes. Moreover, because genome variation is affected by a wide range of biochemical processes, genome variation can be regulated. Biochemical mechanisms that sense stress, from lack of nutrients to DNA damage, can increase the probability of specific classes of variation. A deeper understanding of evolution involves attention to the evolution of, and environmental influences upon, the intrinsic variation generated in gametes, in other words upon the biochemical mechanisms that generate variation across generations. These concepts have profound implications for the types of questions that can and should be asked, as omics databases become more comprehensive, detection methods more sensitive, and computation and experimental analyses even more high throughput and thus capable of revealing the intrinsic generation of variation in individual gametes. These concepts also have profound implications for evolutionary theory, which, upon reflection it will be argued, predicts that selection would increase the probability of generating adaptive mutations, in other words, predicts that the ability to evolve itself evolves.
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17
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Fegraeus K, Rosengren MK, Naboulsi R, Orlando L, Åbrink M, Jouni A, Velie BD, Raine A, Egner B, Mattsson CM, Lång K, Zhigulev A, Björck HM, Franco-Cereceda A, Eriksson P, Andersson G, Sahlén P, Meadows JRS, Lindgren G. An endothelial regulatory module links blood pressure regulation with elite athletic performance. PLoS Genet 2024; 20:e1011285. [PMID: 38885195 PMCID: PMC11182536 DOI: 10.1371/journal.pgen.1011285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 05/02/2024] [Indexed: 06/20/2024] Open
Abstract
The control of transcription is crucial for homeostasis in mammals. A previous selective sweep analysis of horse racing performance revealed a 19.6 kb candidate regulatory region 50 kb downstream of the Endothelin3 (EDN3) gene. Here, the region was narrowed to a 5.5 kb span of 14 SNVs, with elite and sub-elite haplotypes analyzed for association to racing performance, blood pressure and plasma levels of EDN3 in Coldblooded trotters and Standardbreds. Comparative analysis of human HiCap data identified the span as an enhancer cluster active in endothelial cells, interacting with genes relevant to blood pressure regulation. Coldblooded trotters with the sub-elite haplotype had significantly higher blood pressure compared to horses with the elite performing haplotype during exercise. Alleles within the elite haplotype were part of the standing variation in pre-domestication horses, and have risen in frequency during the era of breed development and selection. These results advance our understanding of the molecular genetics of athletic performance and vascular traits in both horses and humans.
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Affiliation(s)
- Kim Fegraeus
- Department of Medical Sciences, Science for life laboratory, Uppsala University, Sweden
| | - Maria K. Rosengren
- Department of Animal Biosciences, Swedish University of Agricultural Sciences Uppsala, Sweden
| | - Rakan Naboulsi
- Department of Animal Biosciences, Swedish University of Agricultural Sciences Uppsala, Sweden
- Childhood Cancer Research Unit, Department of Women’s and Children’s Health, Karolinska Institute, Stockholm
| | - Ludovic Orlando
- Centre d’Anthropobiologie et de Génomique de Toulouse (CNRS UMR 5288), Université Paul Sabatier, Toulouse, France
| | - Magnus Åbrink
- Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Ahmad Jouni
- Department of Animal Biosciences, Swedish University of Agricultural Sciences Uppsala, Sweden
| | - Brandon D. Velie
- School of Life & Environmental Sciences, University of Sydney, Sydney, Australia
| | - Amanda Raine
- Department of Medical Sciences, Science for life laboratory, Uppsala University, Sweden
| | - Beate Egner
- Department of Cardio-Vascular Research, Veterinary Academy of Higher Learning, Babenhausen, Germany
| | - C Mikael Mattsson
- Silicon Valley Exercise Analytics (svexa), MenloPark, CA, United States of America
| | - Karin Lång
- Division of Cardiovascular Medicine, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Karolinska University Hospital, Solna, Sweden
| | - Artemy Zhigulev
- KTH Royal Institute of Technology, School of Chemistry, Biotechnology and Health, Science for Life Laboratory, Stockholm, Sweden
| | - Hanna M. Björck
- Division of Cardiovascular Medicine, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Karolinska University Hospital, Solna, Sweden
| | - Anders Franco-Cereceda
- Section of Cardiothoracic Surgery, Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Per Eriksson
- Division of Cardiovascular Medicine, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Karolinska University Hospital, Solna, Sweden
| | - Göran Andersson
- Department of Animal Biosciences, Swedish University of Agricultural Sciences Uppsala, Sweden
| | - Pelin Sahlén
- KTH Royal Institute of Technology, School of Chemistry, Biotechnology and Health, Science for Life Laboratory, Stockholm, Sweden
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Gabriella Lindgren
- Department of Animal Biosciences, Swedish University of Agricultural Sciences Uppsala, Sweden
- Center for Animal Breeding and Genetics, Department of Biosystems, KU Leuven, Leuven, Belgium
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18
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Gupta A, Mirarab S, Turakhia Y. Accurate, scalable, and fully automated inference of species trees from raw genome assemblies using ROADIES. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.27.596098. [PMID: 38854139 PMCID: PMC11160643 DOI: 10.1101/2024.05.27.596098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Inference of species trees plays a crucial role in advancing our understanding of evolutionary relationships and has immense significance for diverse biological and medical applications. Extensive genome sequencing efforts are currently in progress across a broad spectrum of life forms, holding the potential to unravel the intricate branching patterns within the tree of life. However, estimating species trees starting from raw genome sequences is quite challenging, and the current cutting-edge methodologies require a series of error-prone steps that are neither entirely automated nor standardized. In this paper, we present ROADIES, a novel pipeline for species tree inference from raw genome assemblies that is fully automated, easy to use, scalable, free from reference bias, and provides flexibility to adjust the tradeoff between accuracy and runtime. The ROADIES pipeline eliminates the need to align whole genomes, choose a single reference species, or pre-select loci such as functional genes found using cumbersome annotation steps. Moreover, it leverages recent advances in phylogenetic inference to allow multi-copy genes, eliminating the need to detect orthology. Using the genomic datasets released from large-scale sequencing consortia across three diverse life forms (placental mammals, pomace flies, and birds), we show that ROADIES infers species trees that are comparable in quality with the state-of-the-art approaches but in a fraction of the time. By incorporating optimal approaches and automating all steps from assembled genomes to species and gene trees, ROADIES is poised to improve the accuracy, scalability, and reproducibility of phylogenomic analyses.
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Affiliation(s)
- Anshu Gupta
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA 92093, USA
| | - Siavash Mirarab
- Department of Electrical and Computer Engineering, University of California, San Diego; San Diego, CA 92093, USA
| | - Yatish Turakhia
- Department of Electrical and Computer Engineering, University of California, San Diego; San Diego, CA 92093, USA
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19
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Radrizzani S, Kudla G, Izsvák Z, Hurst LD. Selection on synonymous sites: the unwanted transcript hypothesis. Nat Rev Genet 2024; 25:431-448. [PMID: 38297070 DOI: 10.1038/s41576-023-00686-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/04/2023] [Indexed: 02/02/2024]
Abstract
Although translational selection to favour codons that match the most abundant tRNAs is not readily observed in humans, there is nonetheless selection in humans on synonymous mutations. We hypothesize that much of this synonymous site selection can be explained in terms of protection against unwanted RNAs - spurious transcripts, mis-spliced forms or RNAs derived from transposable elements or viruses. We propose not only that selection on synonymous sites functions to reduce the rate of creation of unwanted transcripts (for example, through selection on exonic splice enhancers and cryptic splice sites) but also that high-GC content (but low-CpG content), together with intron presence and position, is both particular to functional native mRNAs and used to recognize transcripts as native. In support of this hypothesis, transcription, nuclear export, liquid phase condensation and RNA degradation have all recently been shown to promote GC-rich transcripts and suppress AU/CpG-rich ones. With such 'traps' being set against AU/CpG-rich transcripts, the codon usage of native genes has, in turn, evolved to avoid such suppression. That parallel filters against AU/CpG-rich transcripts also affect the endosomal import of RNAs further supports the unwanted transcript hypothesis of synonymous site selection and explains the similar design rules that have enabled the successful use of transgenes and RNA vaccines.
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Affiliation(s)
- Sofia Radrizzani
- Milner Centre for Evolution, Department of Life Sciences, University of Bath, Bath, UK
- Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - Grzegorz Kudla
- MRC Human Genetics Unit, Institute for Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Zsuzsanna Izsvák
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Society, Berlin, Germany
| | - Laurence D Hurst
- Milner Centre for Evolution, Department of Life Sciences, University of Bath, Bath, UK.
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20
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Pratt HE, Andrews G, Shedd N, Phalke N, Li T, Pampari A, Jensen M, Wen C, Consortium P, Gandal MJ, Geschwind DH, Gerstein M, Moore J, Kundaje A, Colubri A, Weng Z. Using a comprehensive atlas and predictive models to reveal the complexity and evolution of brain-active regulatory elements. SCIENCE ADVANCES 2024; 10:eadj4452. [PMID: 38781344 PMCID: PMC11114231 DOI: 10.1126/sciadv.adj4452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 04/25/2024] [Indexed: 05/25/2024]
Abstract
Most genetic variants associated with psychiatric disorders are located in noncoding regions of the genome. To investigate their functional implications, we integrate epigenetic data from the PsychENCODE Consortium and other published sources to construct a comprehensive atlas of candidate brain cis-regulatory elements. Using deep learning, we model these elements' sequence syntax and predict how binding sites for lineage-specific transcription factors contribute to cell type-specific gene regulation in various types of glia and neurons. The elements' evolutionary history suggests that new regulatory information in the brain emerges primarily via smaller sequence mutations within conserved mammalian elements rather than entirely new human- or primate-specific sequences. However, primate-specific candidate elements, particularly those active during fetal brain development and in excitatory neurons and astrocytes, are implicated in the heritability of brain-related human traits. Additionally, we introduce PsychSCREEN, a web-based platform offering interactive visualization of PsychENCODE-generated genetic and epigenetic data from diverse brain cell types in individuals with psychiatric disorders and healthy controls.
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Affiliation(s)
- Henry E. Pratt
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Gregory Andrews
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Tongxin Li
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Khoury College of Computer Science, Northeastern University, Boston, MA 02115, USA
| | - Anusri Pampari
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Matthew Jensen
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Cindy Wen
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | | | - Michael J. Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Daniel H. Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Mark Gerstein
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Andrés Colubri
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
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21
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Rossen J, Shi H, Strober BJ, Zhang MJ, Kanai M, McCaw ZR, Liang L, Weissbrod O, Price AL. MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.13.24307291. [PMID: 38798542 PMCID: PMC11118590 DOI: 10.1101/2024.05.13.24307291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Leveraging data from multiple ancestries can greatly improve fine-mapping power due to differences in linkage disequilibrium and allele frequencies. We propose MultiSuSiE, an extension of the sum of single effects model (SuSiE) to multiple ancestries that allows causal effect sizes to vary across ancestries based on a multivariate normal prior informed by empirical data. We evaluated MultiSuSiE via simulations and analyses of 14 quantitative traits leveraging whole-genome sequencing data in 47k African-ancestry and 94k European-ancestry individuals from All of Us. In simulations, MultiSuSiE applied to Afr47k+Eur47k was well-calibrated and attained higher power than SuSiE applied to Eur94k; interestingly, higher causal variant PIPs in Afr47k compared to Eur47k were entirely explained by differences in the extent of LD quantified by LD 4th moments. Compared to very recently proposed multi-ancestry fine-mapping methods, MultiSuSiE attained higher power and/or much lower computational costs, making the analysis of large-scale All of Us data feasible. In real trait analyses, MultiSuSiE applied to Afr47k+Eur94k identified 579 fine-mapped variants with PIP > 0.5, and MultiSuSiE applied to Afr47k+Eur47k identified 44% more fine-mapped variants with PIP > 0.5 than SuSiE applied to Eur94k. We validated MultiSuSiE results for real traits via functional enrichment of fine-mapped variants. We highlight several examples where MultiSuSiE implicates well-studied or biologically plausible fine-mapped variants that were not implicated by other methods.
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22
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Chao KR, Wang L, Panchal R, Liao C, Abderrazzaq H, Ye R, Schultz P, Compitello J, Grant RH, Kosmicki JA, Weisburd B, Phu W, Wilson MW, Laricchia KM, Goodrich JK, Goldstein D, Goldstein JI, Vittal C, Poterba T, Baxter S, Watts NA, Solomonson M, Tiao G, Rehm HL, Neale BM, Talkowski ME, MacArthur DG, O'Donnell-Luria A, Karczewski KJ, Radivojac P, Daly MJ, Samocha KE. The landscape of regional missense mutational intolerance quantified from 125,748 exomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.11.588920. [PMID: 38645134 PMCID: PMC11030311 DOI: 10.1101/2024.04.11.588920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Missense variants can have a range of functional impacts depending on factors such as the specific amino acid substitution and location within the gene. To interpret their deleteriousness, studies have sought to identify regions within genes that are specifically intolerant of missense variation 1-12 . Here, we leverage the patterns of rare missense variation in 125,748 individuals in the Genome Aggregation Database (gnomAD) 13 against a null mutational model to identify transcripts that display regional differences in missense constraint. Missense-depleted regions are enriched for ClinVar 14 pathogenic variants, de novo missense variants from individuals with neurodevelopmental disorders (NDDs) 15,16 , and complex trait heritability. Following ClinGen calibration recommendations for the ACMG/AMP guidelines, we establish that regions with less than 20% of their expected missense variation achieve moderate support for pathogenicity. We create a missense deleteriousness metric (MPC) that incorporates regional constraint and outperforms other deleteriousness scores at stratifying case and control de novo missense variation, with a strong enrichment in NDDs. These results provide additional tools to aid in missense variant interpretation.
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23
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Rojo D, Hael CE, Soria A, de Souza FSJ, Low MJ, Franchini LF, Rubinstein M. A mammalian tripartite enhancer cluster controls hypothalamic Pomc expression, food intake, and body weight. Proc Natl Acad Sci U S A 2024; 121:e2322692121. [PMID: 38652744 PMCID: PMC11067048 DOI: 10.1073/pnas.2322692121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 03/12/2024] [Indexed: 04/25/2024] Open
Abstract
Food intake and energy balance are tightly regulated by a group of hypothalamic arcuate neurons expressing the proopiomelanocortin (POMC) gene. In mammals, arcuate-specific POMC expression is driven by two cis-acting transcriptional enhancers known as nPE1 and nPE2. Because mutant mice lacking these two enhancers still showed hypothalamic Pomc mRNA, we searched for additional elements contributing to arcuate Pomc expression. By combining molecular evolution with reporter gene expression in transgenic zebrafish and mice, here, we identified a mammalian arcuate-specific Pomc enhancer that we named nPE3, carrying several binding sites also present in nPE1 and nPE2 for transcription factors known to activate neuronal Pomc expression, such as ISL1, NKX2.1, and ERα. We found that nPE3 originated in the lineage leading to placental mammals and remained under purifying selection in all mammalian orders, although it was lost in Simiiformes (monkeys, apes, and humans) following a unique segmental deletion event. Interestingly, ablation of nPE3 from the mouse genome led to a drastic reduction (>70%) in hypothalamic Pomc mRNA during development and only moderate (<33%) in adult mice. Comparison between double (nPE1 and nPE2) and triple (nPE1, nPE2, and nPE3) enhancer mutants revealed the relative contribution of nPE3 to hypothalamic Pomc expression and its importance in the control of food intake and adiposity in male and female mice. Altogether, these results demonstrate that nPE3 integrates a tripartite cluster of partially redundant enhancers that originated upon a triple convergent evolutionary process in mammals and that is critical for hypothalamic Pomc expression and body weight homeostasis.
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Affiliation(s)
- Daniela Rojo
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular, Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires1428, Argentina
| | - Clara E. Hael
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular, Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires1428, Argentina
| | - Agustina Soria
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular, Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires1428, Argentina
- Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires1428, Argentina
| | - Flávio S. J. de Souza
- Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires1428, Argentina
- Instituto de Fisiología, Biología Molecular y Neurociencias, Universidad de Buenos Aires and Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires1428, Argentina
| | - Malcolm J. Low
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI48105
| | - Lucía F. Franchini
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular, Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires1428, Argentina
| | - Marcelo Rubinstein
- Instituto de Investigaciones en Ingeniería Genética y Biología Molecular, Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires1428, Argentina
- Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires1428, Argentina
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI48105
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24
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Sone M, Yamaguchi Y. Cold resistance of mammalian hibernators ∼ a matter of ferroptosis? Front Physiol 2024; 15:1377986. [PMID: 38725569 PMCID: PMC11079186 DOI: 10.3389/fphys.2024.1377986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Accepted: 04/08/2024] [Indexed: 05/12/2024] Open
Abstract
Most mammals adapt thermal physiology around 37°C and large deviations from their range, as observed in severe hypothermia and hyperthermia, resulting in organ dysfunction and individual death. A prominent exception is mammalian hibernation. Mammalian hibernators resist the long-term duration of severe low body temperature that is lethal to non-hibernators, including humans and mice. This cold resistance is supported, at least in part, by intrinsic cellular properties, since primary or immortalized cells from several hibernator species can survive longer than those from non-hibernators when cultured at cold temperatures. Recent studies have suggested that cold-induced cell death fulfills the hallmarks of ferroptosis, a type of necrotic cell death that accompanies extensive lipid peroxidation by iron-ion-mediated reactions. In this review, we summarize the current knowledge of cold resistance of mammalian hibernators at the cellular and molecular levels to organ and systemic levels and discuss key pathways that confer cold resistance in mammals.
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Affiliation(s)
- Masamitsu Sone
- Hibernation Metabolism, Physiology and Development Group, Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan
- Graduate School of Environmental Science, Hokkaido University, Sapporo, Japan
| | - Yoshifumi Yamaguchi
- Hibernation Metabolism, Physiology and Development Group, Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan
- Graduate School of Environmental Science, Hokkaido University, Sapporo, Japan
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25
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Domma AJ, Henderson LA, Nurdin JA, Kamil JP. Uncloaking the viral glycocalyx: How do viruses exploit glycoimmune checkpoints? Adv Virus Res 2024; 119:63-110. [PMID: 38897709 PMCID: PMC11192240 DOI: 10.1016/bs.aivir.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
The surfaces of cells and enveloped viruses alike are coated in carbohydrates that play multifarious roles in infection and immunity. Organisms across all kingdoms of life make use of a diverse set of monosaccharide subunits, glycosidic linkages, and branching patterns to encode information within glycans. Accordingly, sugar-patterning enzymes and glycan binding proteins play integral roles in cell and organismal biology, ranging from glycoprotein quality control within the endoplasmic reticulum to lymphocyte migration, coagulation, inflammation, and tissue homeostasis. Unsurprisingly, genes involved in generating and recognizing oligosaccharide patterns are playgrounds for evolutionary conflicts that abound in cross-species interactions, exemplified by the myriad plant lectins that function as toxins. In vertebrates, glycans bearing acidic nine-carbon sugars called sialic acids are key regulators of immune responses. Various bacterial and fungal pathogens adorn their cells in sialic acids that either mimic their hosts' or are stolen from them. Yet, how viruses commandeer host sugar-patterning enzymes to thwart immune responses remains poorly studied. Here, we review examples of viruses that interact with sialic acid-binding immunoglobulin-like lectins (Siglecs), a family of immune cell receptors that regulate toll-like receptor signaling and govern glycoimmune checkpoints, while highlighting knowledge gaps that merit investigation. Efforts to illuminate how viruses leverage glycan-dependent checkpoints may translate into new clinical treatments that uncloak viral antigens and infected cell surfaces by removing or masking immunosuppressive sialoglycans, or by inhibiting viral gene products that induce their biosynthesis. Such approaches may hold the potential to unleash the immune system to clear long intractable chronic viral infections.
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Affiliation(s)
- Anthony J Domma
- LSU Health Sciences Center at Shreveport, Shreveport, LA, United States
| | | | - Jeffery A Nurdin
- LSU Health Sciences Center at Shreveport, Shreveport, LA, United States
| | - Jeremy P Kamil
- LSU Health Sciences Center at Shreveport, Shreveport, LA, United States.
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26
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Oomen ME, Torres-Padilla ME. Jump-starting life: balancing transposable element co-option and genome integrity in the developing mammalian embryo. EMBO Rep 2024; 25:1721-1733. [PMID: 38528171 PMCID: PMC11015026 DOI: 10.1038/s44319-024-00118-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/23/2024] [Accepted: 03/05/2024] [Indexed: 03/27/2024] Open
Abstract
Remnants of transposable elements (TEs) are widely expressed throughout mammalian embryo development. Originally infesting our genomes as selfish elements and acting as a source of genome instability, several of these elements have been co-opted as part of a complex system of genome regulation. Many TEs have lost transposition ability and their transcriptional potential has been tampered as a result of interactions with the host throughout evolutionary time. It has been proposed that TEs have been ultimately repurposed to function as gene regulatory hubs scattered throughout our genomes. In the early embryo in particular, TEs find a perfect environment of naïve chromatin to escape transcriptional repression by the host. As a consequence, it is thought that hosts found ways to co-opt TE sequences to regulate large-scale changes in chromatin and transcription state of their genomes. In this review, we discuss several examples of TEs expressed during embryo development, their potential for co-option in genome regulation and the evolutionary pressures on TEs and on our genomes.
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Affiliation(s)
- Marlies E Oomen
- Institute of Epigenetics and Stem Cells, Helmholtz Zentrum München, München, Germany
| | - Maria-Elena Torres-Padilla
- Institute of Epigenetics and Stem Cells, Helmholtz Zentrum München, München, Germany.
- Faculty of Biology, Ludwig-Maximilians Universität, München, Germany.
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27
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Wilder AP, Steiner CC, Hendricks S, Haller BC, Kim C, Korody ML, Ryder OA. Genetic load and viability of a future restored northern white rhino population. Evol Appl 2024; 17:e13683. [PMID: 38617823 PMCID: PMC11009427 DOI: 10.1111/eva.13683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/04/2024] [Accepted: 03/06/2024] [Indexed: 04/16/2024] Open
Abstract
As biodiversity loss outpaces recovery, conservationists are increasingly turning to novel tools for preventing extinction, including cloning and in vitro gametogenesis of biobanked cells. However, restoration of populations can be hindered by low genetic diversity and deleterious genetic load. The persistence of the northern white rhino (Ceratotherium simum cottoni) now depends on the cryopreserved cells of 12 individuals. These banked genomes have higher genetic diversity than southern white rhinos (C. s. simum), a sister subspecies that successfully recovered from a severe bottleneck, but the potential impact of genetic load is unknown. We estimated how demographic history has shaped genome-wide genetic load in nine northern and 13 southern white rhinos. The bottleneck left southern white rhinos with more fixed and homozygous deleterious alleles and longer runs of homozygosity, whereas northern white rhinos retained more deleterious alleles masked in heterozygosity. To gauge the impact of genetic load on the fitness of a northern white rhino population restored from biobanked cells, we simulated recovery using fitness of southern white rhinos as a benchmark for a viable population. Unlike traditional restoration, cell-derived founders can be reintroduced in subsequent generations to boost lost genetic diversity and relieve inbreeding. In simulations with repeated reintroduction of founders into a restored population, the fitness cost of genetic load remained lower than that borne by southern white rhinos. Without reintroductions, rapid growth of the restored population (>20-30% per generation) would be needed to maintain comparable fitness. Our results suggest that inbreeding depression from genetic load is not necessarily a barrier to recovery of the northern white rhino and demonstrate how restoration from biobanked cells relieves some constraints of conventional restoration from a limited founder pool. Established conservation methods that protect healthy populations will remain paramount, but emerging technologies hold promise to bolster these tools to combat the extinction crisis.
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Affiliation(s)
- Aryn P. Wilder
- Conservation GeneticsSan Diego Zoo Wildlife AllianceEscondidoCaliforniaUSA
| | - Cynthia C. Steiner
- Conservation GeneticsSan Diego Zoo Wildlife AllianceEscondidoCaliforniaUSA
| | - Sarah Hendricks
- Conservation GeneticsSan Diego Zoo Wildlife AllianceEscondidoCaliforniaUSA
- Institute for Interdisciplinary Data SciencesUniversity of IdahoMoscowIdahoUSA
| | | | - Chang Kim
- University of CaliforniaSanta Cruz Genomics InstituteSanta CruzCaliforniaUSA
- Department of Neurological SurgeryUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Marisa L. Korody
- Conservation GeneticsSan Diego Zoo Wildlife AllianceEscondidoCaliforniaUSA
| | - Oliver A. Ryder
- Conservation GeneticsSan Diego Zoo Wildlife AllianceEscondidoCaliforniaUSA
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28
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Wirthlin ME, Schmid TA, Elie JE, Zhang X, Kowalczyk A, Redlich R, Shvareva VA, Rakuljic A, Ji MB, Bhat NS, Kaplow IM, Schäffer DE, Lawler AJ, Wang AZ, Phan BN, Annaldasula S, Brown AR, Lu T, Lim BK, Azim E, Clark NL, Meyer WK, Pond SLK, Chikina M, Yartsev MM, Pfenning AR. Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements. Science 2024; 383:eabn3263. [PMID: 38422184 PMCID: PMC11313673 DOI: 10.1126/science.abn3263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/20/2024] [Indexed: 03/02/2024]
Abstract
Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.
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Affiliation(s)
- Morgan E. Wirthlin
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
| | - Tobias A. Schmid
- Helen Wills Neuroscience Institute, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Julie E. Elie
- Helen Wills Neuroscience Institute, University of California, Berkeley; Berkeley, CA 94708, USA
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Xiaomeng Zhang
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Amanda Kowalczyk
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
| | - Ruby Redlich
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Varvara A. Shvareva
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Ashley Rakuljic
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Maria B. Ji
- Department of Psychology, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Ninad S. Bhat
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Irene M. Kaplow
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
| | - Daniel E. Schäffer
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Alyssa J. Lawler
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
- Department of Biological Sciences, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Andrew Z. Wang
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - BaDoi N. Phan
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
| | - Siddharth Annaldasula
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Ashley R. Brown
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
| | - Tianyu Lu
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Byung Kook Lim
- Neurobiology section, Division of Biological Science, University of California, San Diego; La Jolla, CA 92093, USA
| | - Eiman Azim
- Molecular Neurobiology Laboratory, Salk Institute for Biological Studies; La Jolla, CA 92037, USA
| | - Nathan L. Clark
- Department of Biological Sciences, University of Pittsburgh; Pittsburgh, PA 15213, USA
| | - Wynn K. Meyer
- Department of Biological Sciences, Lehigh University; Bethlehem, PA 18015, USA
| | | | - Maria Chikina
- Department of Computational and Systems Biology, University of Pittsburgh; Pittsburgh, PA 15213, USA
| | - Michael M. Yartsev
- Helen Wills Neuroscience Institute, University of California, Berkeley; Berkeley, CA 94708, USA
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
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29
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Hirose A, Nakamura G, Nikaido M, Fujise Y, Kato H, Kishida T. Localized Expression of Olfactory Receptor Genes in the Olfactory Organ of Common Minke Whales. Int J Mol Sci 2024; 25:3855. [PMID: 38612665 PMCID: PMC11012115 DOI: 10.3390/ijms25073855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 03/13/2024] [Accepted: 03/20/2024] [Indexed: 04/14/2024] Open
Abstract
Baleen whales (Mysticeti) possess the necessary anatomical structures and genetic elements for olfaction. Nevertheless, the olfactory receptor gene (OR) repertoire has undergone substantial degeneration in the cetacean lineage following the divergence of the Artiodactyla and Cetacea. The functionality of highly degenerated mysticete ORs within their olfactory epithelium remains unknown. In this study, we extracted total RNA from the nasal mucosae of common minke whales (Balaenoptera acutorostrata) to investigate ORs' localized expression. All three sections of the mucosae examined in the nasal chamber displayed comparable histological structure. However, the posterior portion of the frontoturbinal region exhibited notably high OR expression. Neither the olfactory bulb nor the external skin exhibited the expression of these genes. Although this species possesses four intact non-class-2 ORs, all the ORs expressed in the nasal mucosae belong to class-2, implying the loss of aversion to specific odorants. These anatomical and genomic analyses suggest that ORs are still responsible for olfaction within the nasal region of baleen whales, enabling them to detect desirable scents such as prey and potential mating partners.
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Affiliation(s)
- Ayumi Hirose
- School of Life Science and Technology, Tokyo Institute of Technology, Tokyo 152-8550, Japan;
- Department of Ocean Sciences, Tokyo University of Marine Science and Technology, Tokyo 108-8477, Japan
| | - Gen Nakamura
- Department of Ocean Sciences, Tokyo University of Marine Science and Technology, Tokyo 108-8477, Japan
| | - Masato Nikaido
- School of Life Science and Technology, Tokyo Institute of Technology, Tokyo 152-8550, Japan;
| | | | - Hidehiro Kato
- Department of Ocean Sciences, Tokyo University of Marine Science and Technology, Tokyo 108-8477, Japan
- The Institute of Cetacean Research, Tokyo 104-0055, Japan
| | - Takushi Kishida
- Museum of Natural and Environmental History, Shizuoka 422-8017, Japan;
- College of Bioresource Sciences, Nihon University, Fujisawa 252-0880, Japan
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30
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Fleck K, Luria V, Garag N, Karger A, Hunter T, Marten D, Phu W, Nam KM, Sestan N, O’Donnell-Luria AH, Erceg J. Functional associations of evolutionarily recent human genes exhibit sensitivity to the 3D genome landscape and disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.17.585403. [PMID: 38559085 PMCID: PMC10980080 DOI: 10.1101/2024.03.17.585403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Genome organization is intricately tied to regulating genes and associated cell fate decisions. In this study, we examine the positioning and functional significance of human genes, grouped by their evolutionary age, within the 3D organization of the genome. We reveal that genes of different evolutionary origin have distinct positioning relationships with both domains and loop anchors, and remarkably consistent relationships with boundaries across cell types. While the functional associations of each group of genes are primarily cell type-specific, such associations of conserved genes maintain greater stability across 3D genomic features and disease than recently evolved genes. Furthermore, the expression of these genes across various tissues follows an evolutionary progression, such that RNA levels increase from young genes to ancient genes. Thus, the distinct relationships of gene evolutionary age, function, and positioning within 3D genomic features contribute to tissue-specific gene regulation in development and disease.
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Affiliation(s)
- Katherine Fleck
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269
| | - Victor Luria
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115
| | - Nitanta Garag
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269
| | - Amir Karger
- IT-Research Computing, Harvard Medical School, Boston, MA 02115
| | - Trevor Hunter
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269
| | - Daniel Marten
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142
| | - William Phu
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142
| | - Kee-Myoung Nam
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06510
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510
| | - Anne H. O’Donnell-Luria
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142
- Department of Pediatrics, Harvard Medical School, Boston, MA 02115
| | - Jelena Erceg
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT 06030
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31
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Liu X, Xiao C, Xu X, Zhang J, Mo F, Chen JY, Delihas N, Zhang L, An NA, Li CY. Origin of functional de novo genes in humans from "hopeful monsters". WILEY INTERDISCIPLINARY REVIEWS. RNA 2024; 15:e1845. [PMID: 38605485 DOI: 10.1002/wrna.1845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 03/13/2024] [Accepted: 03/18/2024] [Indexed: 04/13/2024]
Abstract
For a long time, it was believed that new genes arise only from modifications of preexisting genes, but the discovery of de novo protein-coding genes that originated from noncoding DNA regions demonstrates the existence of a "motherless" origination process for new genes. However, the features, distributions, expression profiles, and origin modes of these genes in humans seem to support the notion that their origin is not a purely "motherless" process; rather, these genes arise preferentially from genomic regions encoding preexisting precursors with gene-like features. In such a case, the gene loci are typically not brand new. In this short review, we will summarize the definition and features of human de novo genes and clarify their process of origination from ancestral non-coding genomic regions. In addition, we define the favored precursors, or "hopeful monsters," for the origin of de novo genes and present a discussion of the functional significance of these young genes in brain development and tumorigenesis in humans. This article is categorized under: RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution.
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Affiliation(s)
- Xiaoge Liu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Chunfu Xiao
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Xinwei Xu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jie Zhang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Fan Mo
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Jia-Yu Chen
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing, China
| | - Nicholas Delihas
- Department of Microbiology and Immunology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
| | - Li Zhang
- Chinese Institute for Brain Research, Beijing, China
| | - Ni A An
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Chuan-Yun Li
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
- Southwest United Graduate School, Kunming, China
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32
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Sakamoto F, Kanamori S, Díaz LM, Cádiz A, Ishii Y, Yamaguchi K, Shigenobu S, Nakayama T, Makino T, Kawata M. Detection of evolutionary conserved and accelerated genomic regions related to adaptation to thermal niches in Anolis lizards. Ecol Evol 2024; 14:e11117. [PMID: 38455144 PMCID: PMC10920033 DOI: 10.1002/ece3.11117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 02/18/2024] [Accepted: 02/22/2024] [Indexed: 03/09/2024] Open
Abstract
Understanding the genetic basis for adapting to thermal environments is important due to serious effects of global warming on ectothermic species. Various genes associated with thermal adaptation in lizards have been identified mainly focusing on changes in gene expression or the detection of positively selected genes using coding regions. Only a few comprehensive genome-wide analyses have included noncoding regions. This study aimed to identify evolutionarily conserved and accelerated genomic regions using whole genomes of eight Anolis lizard species that have repeatedly adapted to similar thermal environments in multiple lineages. Evolutionarily conserved genomic regions were extracted as regions with overall sequence conservation (regions with fewer base substitutions) across all lineages compared with the neutral model. Genomic regions that underwent accelerated evolution in the lineage of interest were identified as those with more base substitutions in the target branch than in the entire background branch. Conserved elements across all branches were relatively abundant in "intergenic" genomic regions among noncoding regions. Accelerated regions (ARs) of each lineage contained a significantly greater proportion of noncoding RNA genes than the entire multiple alignment. Common genes containing ARs within 5 kb of their vicinity in lineages with similar thermal habitats were identified. Many genes associated with circadian rhythms and behavior were found in hot-open and cool-shaded habitat lineages. These genes might play a role in contributing to thermal adaptation and assist future studies examining the function of genes involved in thermal adaptation via genome editing.
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Affiliation(s)
- Fuku Sakamoto
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
| | | | - Luis M. Díaz
- National Museum of Natural History of CubaHavanaCuba
| | - Antonio Cádiz
- Faculty of BiologyUniversity of HavanaHavanaCuba
- Present address:
Department of BiologyUniversity of MiamiCoral GablesFloridaUSA
| | - Yuu Ishii
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
| | | | - Shuji Shigenobu
- Trans‐Omics FacilityNational Institute for Basic BiologyOkazakiJapan
- Department of Basic Biology, School of Life ScienceThe Graduate University for Advanced Studies, SOKENDAIOkazakiJapan
| | - Takuro Nakayama
- Division of Life Sciences, Center for Computational SciencesUniversity of TsukubaTsukubaJapan
| | - Takashi Makino
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
| | - Masakado Kawata
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
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33
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Wollenberg Valero KC. Brief Communication: The Predictable Network Topology of Evolutionary Genomic Constraint. Mol Biol Evol 2024; 41:msae033. [PMID: 38366776 PMCID: PMC10906983 DOI: 10.1093/molbev/msae033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 01/03/2024] [Accepted: 02/09/2024] [Indexed: 02/18/2024] Open
Abstract
Large-scale comparative genomics studies offer valuable resources for understanding both functional and evolutionary rate constraints. It is suggested that constraint aligns with the topology of genomic networks, increasing toward the center, with intermediate nodes combining relaxed constraint with higher contributions to the phenotype due to pleiotropy. However, this pattern has yet to be demonstrated in vertebrates. This study shows that constraint intensifies toward the network's center in placental mammals. Genes with rate changes associated with emergence of hibernation cluster mostly toward intermediate positions, with higher constraint in faster-evolving genes, which is indicative of a "sweet spot" for adaptation. If this trend holds universally, network node metrics could predict high-constraint regions even in clades lacking empirical constraint data.
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34
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Tang S, Peel E, Belov K, Hogg CJ, Farquharson KA. Multi-omics resources for the Australian southern stuttering frog (Mixophyes australis) reveal assorted antimicrobial peptides. Sci Rep 2024; 14:3991. [PMID: 38368484 PMCID: PMC10874372 DOI: 10.1038/s41598-024-54522-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 02/13/2024] [Indexed: 02/19/2024] Open
Abstract
The number of genome-level resources for non-model species continues to rapidly expand. However, frog species remain underrepresented, with up to 90% of frog genera having no genomic or transcriptomic data. Here, we assemble the first genomic and transcriptomic resources for the recently described southern stuttering frog (Mixophyes australis). The southern stuttering frog is ground-dwelling, inhabiting naturally vegetated riverbanks in south-eastern Australia. Using PacBio HiFi long-read sequencing and Hi-C scaffolding, we generated a high-quality genome assembly, with a scaffold N50 of 369.3 Mb and 95.1% of the genome contained in twelve scaffolds. Using this assembly, we identified the mitochondrial genome, and assembled six tissue-specific transcriptomes. We also bioinformatically characterised novel sequences of two families of antimicrobial peptides (AMPs) in the southern stuttering frog, the cathelicidins and β-defensins. While traditional peptidomic approaches to peptide discovery have typically identified one or two AMPs in a frog species from skin secretions, our bioinformatic approach discovered 12 cathelicidins and two β-defensins that were expressed in a range of tissues. We investigated the novelty of the peptides and found diverse predicted activities. Our bioinformatic approach highlights the benefits of multi-omics resources in peptide discovery and contributes valuable genomic resources in an under-represented taxon.
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Affiliation(s)
- Simon Tang
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia
- Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Emma Peel
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia
- Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Katherine Belov
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia
- Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Carolyn J Hogg
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia.
- Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Sydney, Sydney, NSW, 2006, Australia.
| | - Katherine A Farquharson
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia
- Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Sydney, Sydney, NSW, 2006, Australia
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35
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Fromm B, Sorger T. Rapid adaptation of cellular metabolic rate to the MicroRNA complements of mammals and its relevance to the evolution of endothermy. iScience 2024; 27:108740. [PMID: 38327773 PMCID: PMC10847693 DOI: 10.1016/j.isci.2023.108740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 09/13/2023] [Accepted: 12/12/2023] [Indexed: 02/09/2024] Open
Abstract
The metabolic efficiency of mammalian cells depends on the attenuation of intrinsic translation noise by microRNAs. We devised a metric of cellular metabolic rate (cMR), rMR/Mexp optimally fit to the number of microRNA families (mirFam), that is robust to variation in mass and sensitive to body temperature (Tb), consistent with the heat dissipation limit theory of Speakman and Król (2010). Using mirFam as predictor, an Ornstein-Uhlenbeck process of stabilizing selection, with an adaptive shift at the divergence of Boreoeutheria, accounted for 95% of the variation in cMR across mammals. Branchwise rates of evolution of cMR, mirFam and Tb concurrently increased 6- to 7-fold at the divergence of Boreoeutheria, independent of mass. Cellular MR variation across placental mammals was also predicted by the sum of model conserved microRNA-target interactions, revealing an unexpected degree of integration of the microRNA-target apparatus into the energy economy of the mammalian cell.
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Affiliation(s)
- Bastian Fromm
- The Arctic University Museum of Norway, UiT- The Arctic University of Norway, Tromsø, Norway
| | - Thomas Sorger
- Department of Biology, Roger Williams University, Bristol, RI 02809, USA
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36
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Policarpo M, Baldwin MW, Casane D, Salzburger W. Diversity and evolution of the vertebrate chemoreceptor gene repertoire. Nat Commun 2024; 15:1421. [PMID: 38360851 PMCID: PMC10869828 DOI: 10.1038/s41467-024-45500-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 01/23/2024] [Indexed: 02/17/2024] Open
Abstract
Chemoreception - the ability to smell and taste - is an essential sensory modality of most animals. The number and type of chemical stimuli that animals can perceive depends primarily on the diversity of chemoreceptors they possess and express. In vertebrates, six families of G protein-coupled receptors form the core of their chemosensory system, the olfactory/pheromone receptor gene families OR, TAAR, V1R and V2R, and the taste receptors T1R and T2R. Here, we study the vertebrate chemoreceptor gene repertoire and its evolutionary history. Through the examination of 1,527 vertebrate genomes, we uncover substantial differences in the number and composition of chemoreceptors across vertebrates. We show that the chemoreceptor gene families are co-evolving, highly dynamic, and characterized by lineage-specific expansions (for example, OR in tetrapods; TAAR, T1R in teleosts; V1R in mammals; V2R, T2R in amphibians) and losses. Overall, amphibians, followed by mammals, are the vertebrate clades with the largest chemoreceptor repertoires. While marine tetrapods feature a convergent reduction of chemoreceptor numbers, the number of OR genes correlates with habitat in mammals and birds and with migratory behavior in birds, and the taste receptor repertoire correlates with diet in mammals and with aquatic environment in fish.
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Affiliation(s)
- Maxime Policarpo
- Zoological Institute, Department of Environmental Sciences, University of Basel, Basel, Switzerland.
| | - Maude W Baldwin
- Evolution of Sensory Systems Research Group, Max Planck Institute for Biological Intelligence, Seewiesen, Germany
| | - Didier Casane
- Université Paris-Saclay, CNRS, IRD, UMR Évolution, Génomes, Comportement et Écologie, Gif-sur-Yvette, France
- Université Paris Cité, UFR Sciences du Vivant, Paris, France
| | - Walter Salzburger
- Zoological Institute, Department of Environmental Sciences, University of Basel, Basel, Switzerland.
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37
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Hruska-Plochan M, Wiersma VI, Betz KM, Mallona I, Ronchi S, Maniecka Z, Hock EM, Tantardini E, Laferriere F, Sahadevan S, Hoop V, Delvendahl I, Pérez-Berlanga M, Gatta B, Panatta M, van der Bourg A, Bohaciakova D, Sharma P, De Vos L, Frontzek K, Aguzzi A, Lashley T, Robinson MD, Karayannis T, Mueller M, Hierlemann A, Polymenidou M. A model of human neural networks reveals NPTX2 pathology in ALS and FTLD. Nature 2024; 626:1073-1083. [PMID: 38355792 PMCID: PMC10901740 DOI: 10.1038/s41586-024-07042-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 01/08/2024] [Indexed: 02/16/2024]
Abstract
Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1, which involve human-specific mechanisms2-5 that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors6. Single-cell transcriptomics and comparison to independent neural stem cells7 showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids8. Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3' untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity.
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Affiliation(s)
| | - Vera I Wiersma
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Katharina M Betz
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- SIB Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
| | - Izaskun Mallona
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- SIB Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
| | - Silvia Ronchi
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
- MaxWell Biosystems AG, Zurich, Switzerland
| | - Zuzanna Maniecka
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Eva-Maria Hock
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Elena Tantardini
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Florent Laferriere
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Sonu Sahadevan
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Vanessa Hoop
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Igor Delvendahl
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | | | - Beatrice Gatta
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Martina Panatta
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | | | - Dasa Bohaciakova
- Department of Histology and Embryology, Faculty of Medicine, Masaryk University Brno, Brno, Czech Republic
| | - Puneet Sharma
- Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern, Switzerland
- NCCR RNA and Disease Technology Platform, Bern, Switzerland
| | - Laura De Vos
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Karl Frontzek
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Adriano Aguzzi
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Tammaryn Lashley
- Queen Square Brain Bank for Neurological diseases, Department of Movement Disorders, UCL Institute of Neurology, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Mark D Robinson
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- SIB Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
| | | | - Martin Mueller
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
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38
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Ports BL, Jensen-Seaman MI. Convergent rates of protein evolution identify novel targets of sexual selection in primates. Evolution 2024; 78:364-377. [PMID: 37864838 PMCID: PMC10834059 DOI: 10.1093/evolut/qpad188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 10/02/2023] [Accepted: 10/19/2023] [Indexed: 10/23/2023]
Abstract
Sexual selection is the differential reproductive success of individuals, resulting from competition for mates, mate choice, or success in fertilization. In primates, this selective pressure often leads to the development of exaggerated traits which play a role in sexual competition and successful reproduction. In order to gain insight into the mechanisms driving the development of sexually selected traits, we used an unbiased genome-wide approach across 21 primate species to correlate individual rates of protein evolution to relative testes size and sexual dimorphism in body size, 2 anatomical hallmarks of sexual selection in mammals. Among species with presumed high levels of sperm competition, we detected strong conservation of testes-specific proteins responsible for spermatogenesis and ciliary form and function. In contrast, we identified accelerated evolution of female reproductive proteins expressed in the vagina, cervix, and fallopian tubes in these same species. Additionally, we found accelerated protein evolution in lymphoid tissue, indicating that adaptive immune functions may also be influenced by sexual selection. This study demonstrates the distinct complexity of sexual selection in primates revealing contrasting patterns of protein evolution between male and female reproductive tissues.
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Affiliation(s)
- Bri L Ports
- Department of Biological Sciences, Duquesne University, Pittsburgh, PA, United States
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39
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Jern P, Greenwood AD. Wildlife endogenous retroviruses: colonization, consequences, and cooption. Trends Genet 2024; 40:149-159. [PMID: 37985317 DOI: 10.1016/j.tig.2023.10.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/24/2023] [Accepted: 10/31/2023] [Indexed: 11/22/2023]
Abstract
Endogenous retroviruses (ERVs) are inherited genomic remains of past germline retroviral infections. Research on human ERVs has focused on medical implications of their dysregulation on various diseases. However, recent studies incorporating wildlife are yielding remarkable perspectives on long-term retrovirus-host interactions. These initial forays into broader taxonomic analysis, including sequencing of multiple individuals per species, show the incredible plasticity and variation of ERVs within and among wildlife species. This demonstrates that stochastic processes govern much of the vertebrate genome. In this review, we elaborate on discoveries pertaining to wildlife ERV origins and evolution, genome colonization, and consequences for host biology.
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Affiliation(s)
- Patric Jern
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
| | - Alex D Greenwood
- Department of Wildlife Diseases, Leibniz Institute for Zoo and Wildlife Research, Berlin, Germany; School of Veterinary Medicine, Freie Unversität Berlin, Berlin, Germany.
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40
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Uebbing S, Kocher AA, Baumgartner M, Ji Y, Bai S, Xing X, Nottoli T, Noonan JP. Evolutionary innovation in conserved regulatory elements across the mammalian tree of life. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578197. [PMID: 38352419 PMCID: PMC10862883 DOI: 10.1101/2024.01.31.578197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Transcriptional enhancers orchestrate cell type- and time point-specific gene expression programs. Evolution of enhancer sequences can alter target gene expression without causing detrimental misexpression in other contexts. It has long been thought that this modularity allows evolutionary changes in enhancers to escape pleiotropic constraints, which is especially important for evolutionary constrained developmental patterning genes. However, there is still little data supporting this hypothesis. Here we identified signatures of accelerated evolution in conserved enhancer elements across the mammalian phylogeny. We found that pleiotropic genes involved in gene regulatory and developmental processes were enriched for accelerated sequence evolution within their enhancer elements. These genes were associated with an excess number of enhancers compared to other genes, and due to this they exhibit a substantial degree of sequence acceleration over all their enhancers combined. We provide evidence that sequence acceleration is associated with turnover of regulatory function. We studied one acceleration event in depth and found that its sequence evolution led to the emergence of a new enhancer activity domain that may be involved in the evolution of digit reduction in hoofed mammals. Our results provide tangible evidence that enhancer evolution has been a frequent contributor to modifications involving constrained developmental signaling genes in mammals.
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Affiliation(s)
- Severin Uebbing
- Department of Genetics, Yale School of Medicine, New Haven CT, USA
- Genome Biology and Epigenetics, Institute of Biodynamics and Biocomplexity, Department of Biology, Utrecht University, Utrecht, The Netherlands
| | - Acadia A Kocher
- Department of Genetics, Yale School of Medicine, New Haven CT, USA
- Present address: Division of Molecular Genetics, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Yu Ji
- Department of Genetics, Yale School of Medicine, New Haven CT, USA
| | - Suxia Bai
- Yale Genome Editing Center, Yale School of Medicine, New Haven CT, USA
| | - Xiaojun Xing
- Yale Genome Editing Center, Yale School of Medicine, New Haven CT, USA
| | - Timothy Nottoli
- Yale Genome Editing Center, Yale School of Medicine, New Haven CT, USA
| | - James P Noonan
- Department of Genetics, Yale School of Medicine, New Haven CT, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven CT, USA
- Wu Tsai Institute, Yale University, New Haven CT, USA
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41
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Steinbinder J, Sachslehner AP, Holthaus KB, Eckhart L. Comparative genomics of monotremes provides insights into the early evolution of mammalian epidermal differentiation genes. Sci Rep 2024; 14:1437. [PMID: 38228724 PMCID: PMC10791643 DOI: 10.1038/s41598-024-51926-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 01/11/2024] [Indexed: 01/18/2024] Open
Abstract
The function of the skin as a barrier against the environment depends on the differentiation of epidermal keratinocytes into highly resilient corneocytes that form the outermost skin layer. Many genes encoding structural components of corneocytes are clustered in the epidermal differentiation complex (EDC), which has been described in placental and marsupial mammals as well as non-mammalian tetrapods. Here, we analyzed the genomes of the platypus (Ornithorhynchus anatinus) and the echidna (Tachyglossus aculeatus) to determine the gene composition of the EDC in the basal clade of mammals, the monotremes. We report that mammal-specific subfamilies of EDC genes encoding small proline-rich proteins (SPRRs) and late cornified envelope proteins as well as single-copy EDC genes such as involucrin are conserved in monotremes, suggesting that they have originated in stem mammals. Monotremes have at least one gene homologous to the group of filaggrin (FLG), FLG2 and hornerin (HRNR) in placental mammals, but no clear one-to-one pairwise ortholog of either FLG, FLG2 or HRNR. Caspase-14, a keratinocyte differentiation-associated protease implicated in the processing of filaggrin, is encoded by at least 3 gene copies in the echidna. Our results reveal evolutionarily conserved and clade-specific features of the genetic regulation of epidermal differentiation in monotremes.
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Affiliation(s)
- Julia Steinbinder
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | | | | | - Leopold Eckhart
- Department of Dermatology, Medical University of Vienna, Vienna, Austria.
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42
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Schubach M, Maass T, Nazaretyan L, Röner S, Kircher M. CADD v1.7: using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions. Nucleic Acids Res 2024; 52:D1143-D1154. [PMID: 38183205 PMCID: PMC10767851 DOI: 10.1093/nar/gkad989] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 10/14/2023] [Accepted: 10/17/2023] [Indexed: 01/07/2024] Open
Abstract
Machine Learning-based scoring and classification of genetic variants aids the assessment of clinical findings and is employed to prioritize variants in diverse genetic studies and analyses. Combined Annotation-Dependent Depletion (CADD) is one of the first methods for the genome-wide prioritization of variants across different molecular functions and has been continuously developed and improved since its original publication. Here, we present our most recent release, CADD v1.7. We explored and integrated new annotation features, among them state-of-the-art protein language model scores (Meta ESM-1v), regulatory variant effect predictions (from sequence-based convolutional neural networks) and sequence conservation scores (Zoonomia). We evaluated the new version on data sets derived from ClinVar, ExAC/gnomAD and 1000 Genomes variants. For coding effects, we tested CADD on 31 Deep Mutational Scanning (DMS) data sets from ProteinGym and, for regulatory effect prediction, we used saturation mutagenesis reporter assay data of promoter and enhancer sequences. The inclusion of new features further improved the overall performance of CADD. As with previous releases, all data sets, genome-wide CADD v1.7 scores, scripts for on-site scoring and an easy-to-use webserver are readily provided via https://cadd.bihealth.org/ or https://cadd.gs.washington.edu/ to the community.
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Affiliation(s)
- Max Schubach
- Exploratory Diagnostic Sciences, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Thorben Maass
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck, Lübeck, Germany
| | - Lusiné Nazaretyan
- Exploratory Diagnostic Sciences, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Sebastian Röner
- Exploratory Diagnostic Sciences, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Martin Kircher
- Exploratory Diagnostic Sciences, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck, Lübeck, Germany
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Kuderna LFK, Ulirsch JC, Rashid S, Ameen M, Sundaram L, Hickey G, Cox AJ, Gao H, Kumar A, Aguet F, Christmas MJ, Clawson H, Haeussler M, Janiak MC, Kuhlwilm M, Orkin JD, Bataillon T, Manu S, Valenzuela A, Bergman J, Rouselle M, Silva FE, Agueda L, Blanc J, Gut M, de Vries D, Goodhead I, Harris RA, Raveendran M, Jensen A, Chuma IS, Horvath JE, Hvilsom C, Juan D, Frandsen P, Schraiber JG, de Melo FR, Bertuol F, Byrne H, Sampaio I, Farias I, Valsecchi J, Messias M, da Silva MNF, Trivedi M, Rossi R, Hrbek T, Andriaholinirina N, Rabarivola CJ, Zaramody A, Jolly CJ, Phillips-Conroy J, Wilkerson G, Abee C, Simmons JH, Fernandez-Duque E, Kanthaswamy S, Shiferaw F, Wu D, Zhou L, Shao Y, Zhang G, Keyyu JD, Knauf S, Le MD, Lizano E, Merker S, Navarro A, Nadler T, Khor CC, Lee J, Tan P, Lim WK, Kitchener AC, Zinner D, Gut I, Melin AD, Guschanski K, Schierup MH, Beck RMD, Karakikes I, Wang KC, Umapathy G, Roos C, Boubli JP, Siepel A, Kundaje A, Paten B, Lindblad-Toh K, Rogers J, Marques Bonet T, Farh KKH. Identification of constrained sequence elements across 239 primate genomes. Nature 2024; 625:735-742. [PMID: 38030727 PMCID: PMC10808062 DOI: 10.1038/s41586-023-06798-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 10/30/2023] [Indexed: 12/01/2023]
Abstract
Noncoding DNA is central to our understanding of human gene regulation and complex diseases1,2, and measuring the evolutionary sequence constraint can establish the functional relevance of putative regulatory elements in the human genome3-9. Identifying the genomic elements that have become constrained specifically in primates has been hampered by the faster evolution of noncoding DNA compared to protein-coding DNA10, the relatively short timescales separating primate species11, and the previously limited availability of whole-genome sequences12. Here we construct a whole-genome alignment of 239 species, representing nearly half of all extant species in the primate order. Using this resource, we identified human regulatory elements that are under selective constraint across primates and other mammals at a 5% false discovery rate. We detected 111,318 DNase I hypersensitivity sites and 267,410 transcription factor binding sites that are constrained specifically in primates but not across other placental mammals and validate their cis-regulatory effects on gene expression. These regulatory elements are enriched for human genetic variants that affect gene expression and complex traits and diseases. Our results highlight the important role of recent evolution in regulatory sequence elements differentiating primates, including humans, from other placental mammals.
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Affiliation(s)
- Lukas F K Kuderna
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Jacob C Ulirsch
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Sabrina Rashid
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Mohamed Ameen
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Laksshman Sundaram
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Glenn Hickey
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Anthony J Cox
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Hong Gao
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Arvind Kumar
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Francois Aguet
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Matthew J Christmas
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Hiram Clawson
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | | | - Mareike C Janiak
- School of Science, Engineering and Environment, University of Salford, Salford, UK
| | - Martin Kuhlwilm
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
- Human Evolution and Archaeological Sciences (HEAS), University of Vienna, Vienna, Austria
| | - Joseph D Orkin
- Département d'Anthropologie, Université de Montréal, Montréal, Quebec, Canada
| | - Thomas Bataillon
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Shivakumara Manu
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
| | - Alejandro Valenzuela
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Juraj Bergman
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
- Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, Aarhus, Denmark
| | | | - Felipe Ennes Silva
- Research Group on Primate Biology and Conservation, Mamirauá Institute for Sustainable Development, Tefé, Brazil
- Evolutionary Biology and Ecology (EBE), Département de Biologie des Organismes, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Lidia Agueda
- Centro Nacional de Analisis Genomico (CNAG), Barcelona, Spain
| | - Julie Blanc
- Centro Nacional de Analisis Genomico (CNAG), Barcelona, Spain
| | - Marta Gut
- Centro Nacional de Analisis Genomico (CNAG), Barcelona, Spain
| | - Dorien de Vries
- School of Science, Engineering and Environment, University of Salford, Salford, UK
| | - Ian Goodhead
- School of Science, Engineering and Environment, University of Salford, Salford, UK
| | - R Alan Harris
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Axel Jensen
- Department of Ecology and Genetics, Animal Ecology, Uppsala University, Uppsala, Sweden
| | | | - Julie E Horvath
- North Carolina Museum of Natural Sciences, Raleigh, NC, USA
- Department of Biological and Biomedical Sciences, North Carolina Central University, Durham, NC, USA
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - David Juan
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | | | - Joshua G Schraiber
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | | | - Fabrício Bertuol
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Brazil
| | - Hazel Byrne
- Department of Anthropology, University of Utah, Salt Lake City, UT, USA
| | | | - Izeni Farias
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Brazil
| | - João Valsecchi
- Research Group on Terrestrial Vertebrate Ecology, Mamirauá Institute for Sustainable Development, Tefé, Brazil
- Rede de Pesquisa em Diversidade, Conservação e Uso da Fauna da Amazônia - RedeFauna, Manaus, Brazil
- Comunidad de Manejo de Fauna Silvestre en la Amazonía y en Latinoamérica-ComFauna, Iquitos, Peru
| | - Malu Messias
- Universidade Federal de Rondônia, Porto Velho, Brazil
| | | | - Mihir Trivedi
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
| | - Rogerio Rossi
- Instituto de Biociências, Universidade Federal do Mato Grosso, Cuiabá, Brazil
| | - Tomas Hrbek
- Universidade Federal do Amazonas, Departamento de Genética, Laboratório de Evolução e Genética Animal (LEGAL), Manaus, Brazil
- Department of Biology, Trinity University, San Antonio, TX, USA
| | - Nicole Andriaholinirina
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, Madagascar
| | - Clément J Rabarivola
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, Madagascar
| | - Alphonse Zaramody
- Life Sciences and Environment, Technology and Environment of Mahajanga, University of Mahajanga, Mahajanga, Madagascar
| | - Clifford J Jolly
- Department of Anthropology, New York University, New York, NY, USA
| | - Jane Phillips-Conroy
- Department of Neuroscience, Washington University School of Medicine in St Louis, St Louis, MO, USA
| | - Gregory Wilkerson
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Bastrop, TX, USA
| | - Christian Abee
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Bastrop, TX, USA
| | - Joe H Simmons
- Keeling Center for Comparative Medicine and Research, MD Anderson Cancer Center, Bastrop, TX, USA
| | | | - Sree Kanthaswamy
- School of Interdisciplinary Forensics, Arizona State University, Phoenix, AZ, USA
- California National Primate Research Center, University of California, Davis, CA, USA
| | - Fekadu Shiferaw
- Guinea Worm Eradication Program, The Carter Center Ethiopia, Addis Ababa, Ethiopia
| | - Dongdong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Long Zhou
- Center for Evolutionary and Organismal Biology, Zhejiang University School of Medicine, Hangzhou, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Guojie Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Center for Evolutionary and Organismal Biology, Zhejiang University School of Medicine, Hangzhou, China
- Villum Centre for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
- Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Julius D Keyyu
- Tanzania Wildlife Research Institute (TAWIRI), Arusha, Tanzania
| | - Sascha Knauf
- Institute of International Animal Health/One Health, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Greifswald-Insel Riems, Germany
- Professorship for International Animal Health/One Health, Faculty of Veterinary Medicine, Justus Liebig University, Giessen, Germany
| | - Minh D Le
- Department of Environmental Ecology, Faculty of Environmental Sciences, University of Science and Central Institute for Natural Resources and Environmental Studies, Vietnam National University, Hanoi, Vietnam
| | - Esther Lizano
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Stefan Merker
- Department of Zoology, State Museum of Natural History Stuttgart, Stuttgart, Germany
| | - Arcadi Navarro
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Tilo Nadler
- Cuc Phuong Commune, Nho Quan District, Vietnam
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | | | - Patrick Tan
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Singapore, Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore, Singapore
| | - Weng Khong Lim
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Singapore, Singapore
- Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore, Singapore
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
| | - Andrew C Kitchener
- Department of Natural Sciences, National Museums Scotland, Edinburgh, UK
- School of Geosciences, Edinburgh, UK
| | - Dietmar Zinner
- Cognitive Ethology Laboratory, Germany Primate Center, Leibniz Institute for Primate Research, Göttingen, Germany
- Department of Primate Cognition, Georg-August-Universität Göttingen, Göttingen, Germany
- Leibniz ScienceCampus Primate Cognition, Göttingen, Germany
| | - Ivo Gut
- Centro Nacional de Analisis Genomico (CNAG), Barcelona, Spain
| | - Amanda D Melin
- Department of Anthropology and Archaeology, University of Calgary, Calgary, Alberta, Canada
- Department of Medical Genetics, University of Calgary, Calgary, Alberta, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Katerina Guschanski
- Department of Ecology and Genetics, Animal Ecology, Uppsala University, Uppsala, Sweden
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Robin M D Beck
- School of Science, Engineering and Environment, University of Salford, Salford, UK
| | - Ioannis Karakikes
- Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA
| | - Kevin C Wang
- Department of Cancer Biology, Stanford University, Stanford, CA, USA
- Department of Dermatology, Stanford University School of Medicine, Stanford, CA, USA
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA
| | - Govindhaswamy Umapathy
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
- Laboratory for the Conservation of Endangered Species, CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
| | - Christian Roos
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, Göttingen, Germany
| | - Jean P Boubli
- School of Science, Engineering and Environment, University of Salford, Salford, UK
| | - Adam Siepel
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Anshul Kundaje
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
| | - Tomas Marques Bonet
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
- Centro Nacional de Analisis Genomico (CNAG), Barcelona, Spain.
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain.
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
- Universitat Pompeu Fabra, Barcelona, Spain.
| | - Kyle Kai-How Farh
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA.
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Zhao Y, Zhong G, Hagen J, Pan H, Chung WK, Shen Y. A probabilistic graphical model for estimating selection coefficient of missense variants from human population sequence data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.11.23299809. [PMID: 38168397 PMCID: PMC10760286 DOI: 10.1101/2023.12.11.23299809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Accurately predicting the effect of missense variants is a central problem in interpretation of genomic variation. Commonly used computational methods does not capture the quantitative impact on fitness in populations. We developed MisFit to estimate missense fitness effect using biobank-scale human population genome data. MisFit jointly models the effect at molecular level ( d ) and population level (selection coefficient, s ), assuming that in the same gene, missense variants with similar d have similar s . MisFit is a probabilistic graphical model that integrates deep neural network components and population genetics models efficiently with inductive bias based on biological causality of variant effect. We trained it by maximizing probability of observed allele counts in 236,017 European individuals. We show that s is informative in predicting frequency across ancestries and consistent with the fraction of de novo mutations given s . Finally, MisFit outperforms previous methods in prioritizing missense variants in individuals with neurodevelopmental disorders.
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Affiliation(s)
- Yige Zhao
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- The Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY 10032
| | - Guojie Zhong
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- The Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY 10032
| | - Jake Hagen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY 10032
| | - Hongbing Pan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032
| | - Wendy K. Chung
- Department of Pediatrics, Boston Children’s Hospital and Harvard Medical School, Boston, MA 02115
| | - Yufeng Shen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032
- JP Sulzberger Columbia Genome Center, Columbia University, New York, NY 10032
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Wilson AE, Liberles DA. Expectations of duplicate gene retention under the gene duplicability hypothesis. BMC Ecol Evol 2023; 23:76. [PMID: 38097959 PMCID: PMC10720195 DOI: 10.1186/s12862-023-02174-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 11/02/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Gene duplication is an important process in evolution. What causes some genes to be retained after duplication and others to be lost is a process not well understood. The most prevalent theory is the gene duplicability hypothesis, that something about the function and number of interacting partners (number of subunits of protein complex, etc.), determines whether copies have more opportunity to be retained for long evolutionary periods. Some genes are also more susceptible to dosage balance effects following WGD events, making them more likely to be retained for longer periods of time. One would expect these processes that affect the retention of duplicate copies to affect the conditional probability ratio after consecutive whole genome duplication events. The probability that a gene will be retained after a second whole genome duplication event (WGD2), given that it was retained after the first whole genome duplication event (WGD1) versus the probability a gene will be retained after WGD2, given it was lost after WGD1 defines the probability ratio that is calculated. RESULTS Since duplicate gene retention is a time heterogeneous process, the time between the events (t1) and the time since the most recent event (t2) are relevant factors in calculating the expectation for observation in any genome. Here, we use a survival analysis framework to predict the probability ratio for genomes with different values of t1 and t2 under the gene duplicability hypothesis, that some genes are more susceptible to selectable functional shifts, some more susceptible to dosage compensation, and others only drifting. We also predict the probability ratio with different values of t1 and t2 under the mutational opportunity hypothesis, that probability of retention for certain genes changes in subsequent events depending upon how they were previously retained. These models are nested such that the mutational opportunity model encompasses the gene duplicability model with shifting duplicability over time. Here we present a formalization of the gene duplicability and mutational opportunity hypotheses to characterize evolutionary dynamics and explanatory power in a recently developed statistical framework. CONCLUSIONS This work presents expectations of the gene duplicability and mutational opportunity hypotheses over time under different sets of assumptions. This expectation will enable formal testing of processes leading to duplicate gene retention.
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Affiliation(s)
- Amanda E Wilson
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, 1900 N. 12th Street, Philadelphia, PA, 19122, USA
| | - David A Liberles
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, 1900 N. 12th Street, Philadelphia, PA, 19122, USA.
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Redlich R, Kowalczyk A, Tene M, Sestili HH, Foley K, Saputra E, Clark N, Chikina M, Meyer WK, Pfenning A. RERconverge Expansion: Using Relative Evolutionary Rates to Study Complex Categorical Trait Evolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.06.570425. [PMID: 38106136 PMCID: PMC10723433 DOI: 10.1101/2023.12.06.570425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Comparative genomics approaches seek to associate evolutionary genetic changes with the evolution of phenotypes across a phylogeny. Many of these methods, including our evolutionary rates based method, RERconverge, lack the capability of analyzing non-ordinal, multicategorical traits. To address this limitation, we introduce an expansion to RERconverge that associates shifts in evolutionary rates with the convergent evolution of multi-categorical traits. The categorical RERconverge expansion includes methods for performing categorical ancestral state reconstruction, statistical tests for associating relative evolutionary rates with categorical variables, and a new method for performing phylogenetic permulations on multi-categorical traits. In addition to demonstrating our new method on a three-category diet phenotype, we compare its performance to naive pairwise binary RERconverge analyses and two existing methods for comparative genomic analyses of categorical traits: phylogenetic simulations and a phylogenetic signal based method. We also present a diagnostic analysis of the new permulations approach demonstrating how the method scales with the number of species and the number of categories included in the analysis. Our results show that our new categorical method outperforms phylogenetic simulations at identifying genes and enriched pathways significantly associated with the diet phenotype and that the new ancestral reconstruction drives an improvement in our ability to capture diet-related enriched pathways. Our categorical permulations were able to account for non-uniform null distributions and correct for non-independence in gene rank during pathway enrichment analysis. The categorical expansion to RERconverge will provide a strong foundation for applying the comparative method to categorical traits on larger data sets with more species and more complex trait evolution.
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47
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Butt Z, Tinning H, O'Connell MJ, Fenn J, Alberio R, Forde N. Understanding conceptus-maternal interactions: what tools do we need to develop? Reprod Fertil Dev 2023; 36:81-92. [PMID: 38064186 DOI: 10.1071/rd23181] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2023] Open
Abstract
Communication between the maternal endometrium and developing embryo/conceptus is critical to support successful pregnancy to term. Studying the peri-implantation period of pregnancy is critical as this is when most pregnancy loss occurs in cattle. Our current understanding of these interactions is limited, due to the lack of appropriate in vitro models to assess these interactions. The endometrium is a complex and heterogeneous tissue that is regulated in a transcriptional and translational manner throughout the oestrous cycle. While there are in vitro models to study endometrial function, they are static and 2D in nature or explant models and are limited in how well they recapitulate the in vivo endometrium. Recent developments in organoid systems, microfluidic approaches, extracellular matrix biology, and in silico approaches provide a new opportunity to develop in vitro systems that better model the in vivo scenario. This will allow us to investigate in a more high-throughput manner the fundamental molecular interactions that are required for successful pregnancy in cattle.
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Affiliation(s)
- Zenab Butt
- Discovery and Translational Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds LS2 9JT, UK
| | - Haidee Tinning
- Discovery and Translational Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds LS2 9JT, UK
| | - Mary J O'Connell
- Computational and Molecular Evolutionary Biology Group, School of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Jonathan Fenn
- Computational and Molecular Evolutionary Biology Group, School of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Ramiro Alberio
- School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, UK
| | - Niamh Forde
- Discovery and Translational Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds LS2 9JT, UK
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48
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Whole-genome alignment with primates reveals DNA elements conserved in humans. Nature 2023:10.1038/d41586-023-03641-y. [PMID: 38030758 DOI: 10.1038/d41586-023-03641-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
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49
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Li S, Vazquez JM, Sudmant PH. The evolution of aging and lifespan. Trends Genet 2023; 39:830-843. [PMID: 37714733 PMCID: PMC11147682 DOI: 10.1016/j.tig.2023.08.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/18/2023] [Accepted: 08/21/2023] [Indexed: 09/17/2023]
Abstract
Aging is a nearly inescapable trait among organisms yet lifespan varies tremendously across different species and spans several orders of magnitude in vertebrates alone. This vast phenotypic diversity is driven by distinct evolutionary trajectories and tradeoffs that are reflected in patterns of diversification and constraint in organismal genomes. Age-specific impacts of selection also shape allele frequencies in populations, thus impacting disease susceptibility and environment-specific mortality risk. Further, the mutational processes that spawn this genetic diversity in both germline and somatic cells are strongly influenced by age and life history. We discuss recent advances in our understanding of the evolution of aging and lifespan at organismal, population, and cellular scales, and highlight outstanding questions that remain unanswered.
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Affiliation(s)
- Stacy Li
- Department of Integrative Biology, University of California, Berkeley, CA, USA; Center for Computational Biology, University of California, Berkeley, CA. USA
| | - Juan Manuel Vazquez
- Department of Integrative Biology, University of California, Berkeley, CA, USA
| | - Peter H Sudmant
- Department of Integrative Biology, University of California, Berkeley, CA, USA; Center for Computational Biology, University of California, Berkeley, CA. USA.
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Kim BY, Gellert HR, Church SH, Suvorov A, Anderson SS, Barmina O, Beskid SG, Comeault AA, Crown KN, Diamond SE, Dorus S, Fujichika T, Hemker JA, Hrcek J, Kankare M, Katoh T, Magnacca KN, Martin RA, Matsunaga T, Medeiros MJ, Miller DE, Pitnick S, Simoni S, Steenwinkel TE, Schiffer M, Syed ZA, Takahashi A, Wei KHC, Yokoyama T, Eisen MB, Kopp A, Matute D, Obbard DJ, O'Grady PM, Price DK, Toda MJ, Werner T, Petrov DA. Single-fly assemblies fill major phylogenomic gaps across the Drosophilidae Tree of Life. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.02.560517. [PMID: 37873137 PMCID: PMC10592941 DOI: 10.1101/2023.10.02.560517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Long-read sequencing is driving rapid progress in genome assembly across all major groups of life, including species of the family Drosophilidae, a longtime model system for genetics, genomics, and evolution. We previously developed a cost-effective hybrid Oxford Nanopore (ONT) long-read and Illumina short-read sequencing approach and used it to assemble 101 drosophilid genomes from laboratory cultures, greatly increasing the number of genome assemblies for this taxonomic group. The next major challenge is to address the laboratory culture bias in taxon sampling by sequencing genomes of species that cannot easily be reared in the lab. Here, we build upon our previous methods to perform amplification-free ONT sequencing of single wild flies obtained either directly from the field or from ethanol-preserved specimens in museum collections, greatly improving the representation of lesser studied drosophilid taxa in whole-genome data. Using Illumina Novaseq X Plus and ONT P2 sequencers with R10.4.1 chemistry, we set a new benchmark for inexpensive hybrid genome assembly at US $150 per genome while assembling genomes from as little as 35 ng of genomic DNA from a single fly. We present 183 new genome assemblies for 179 species as a resource for drosophilid systematics, phylogenetics, and comparative genomics. Of these genomes, 62 are from pooled lab strains and 121 from single adult flies. Despite the sample limitations of working with small insects, most single-fly diploid assemblies are comparable in contiguity (>1Mb contig N50), completeness (>98% complete dipteran BUSCOs), and accuracy (>QV40 genome-wide with ONT R10.4.1) to assemblies from inbred lines. We present a well-resolved multi-locus phylogeny for 360 drosophilid and 4 outgroup species encompassing all publicly available (as of August 2023) genomes for this group. Finally, we present a Progressive Cactus whole-genome, reference-free alignment built from a subset of 298 suitably high-quality drosophilid genomes. The new assemblies and alignment, along with updated laboratory protocols and computational pipelines, are released as an open resource and as a tool for studying evolution at the scale of an entire insect family.
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Affiliation(s)
| | | | - Samuel H Church
- Department of Ecology and Evolutionary Biology, Yale University, USA
| | - Anton Suvorov
- Department of Biological Sciences, Virginia Tech, USA
| | - Sean S Anderson
- Department of Biology, University of North Carolina Chapel Hill, USA
| | - Olga Barmina
- Department of Evolution and Ecology, University of California Davis, USA
| | | | - Aaron A Comeault
- School of Environmental and Natural Sciences, Bangor University, UK
| | - K Nicole Crown
- Department of Biology, Case Western Reserve University, USA
| | | | - Steve Dorus
- Center for Reproductive Evolution, Department of Biology, Syracuse University, USA
| | - Takako Fujichika
- Department of Biological Sciences, Tokyo Metropolitan University, Japan
| | - James A Hemker
- Department of Developmental Biology, Stanford University, USA
| | - Jan Hrcek
- Institute of Entomology, Biology Centre, Czech Academy of Sciences, Czechia
| | - Maaria Kankare
- Department of Biological and Environmental Science, University of Jyväskylä, Finland
| | - Toru Katoh
- Department of Biological Sciences, Hokkaido University, Japan
| | - Karl N Magnacca
- Hawaii Invertebrate Program, Division of Forestry & Wildlife, State of Hawaii, USA
| | - Ryan A Martin
- Department of Biology, Case Western Reserve University, USA
| | - Teruyuki Matsunaga
- Department of Complexity Science and Engineering, The University of Tokyo, Japan
| | | | - Danny E Miller
- Division of Genetic Medicine, Department of Pediatrics; Department of Laboratory Medicine and Pathology, University of Washington, USA
| | - Scott Pitnick
- Center for Reproductive Evolution, Department of Biology, Syracuse University, USA
| | - Sara Simoni
- Department of Biology, Stanford University, USA
| | | | - Michele Schiffer
- Daintree Rainforest Observatory, James Cook University, Australia
| | - Zeeshan A Syed
- Center for Reproductive Evolution, Department of Biology, Syracuse University, USA
| | - Aya Takahashi
- Department of Biological Sciences, Tokyo Metropolitan University, Japan
| | - Kevin H-C Wei
- Department of Zoology, The University of British Columbia
| | | | - Michael B Eisen
- Department of Cell and Molecular Biology, University of California Berkeley, United States
- Howard Hughes Medical Institute,University of California Berkeley, United States
| | - Artyom Kopp
- Department of Evolution and Ecology, University of California Davis, USA
| | - Daniel Matute
- Department of Biology, University of North Carolina Chapel Hill, USA
| | - Darren J Obbard
- Institute of Ecology and Evolution, University of Edinburgh, UK
| | | | - Donald K Price
- School of Life Sciences, University of Nevada Las Vegas, USA
| | | | - Thomas Werner
- Department of Biological Sciences, Michigan Technological University, USA
| | - Dmitri A Petrov
- Department of Biology, Stanford University, USA
- CZ Biohub, Investigator
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