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33 results on '"Meyer, Wynn K."'

1. A genomic timescale for placental mammal evolution

Author

Foley, Nicole M, Mason, Victor C, Harris, Andrew J, Bredemeyer, Kevin R, Damas, Joana, Lewin, Harris A, Eizirik, Eduardo, Gatesy, John, Karlsson, Elinor K, Lindblad-Toh, Kerstin, Springer, Mark S, Murphy, William J, Andrews, Gregory, Armstrong, Joel C, Bianchi, Matteo, Birren, Bruce W, Breit, Ana M, Christmas, Matthew J, Clawson, Hiram, Di Palma, Federica, Diekhans, Mark, Dong, Michael X, Fan, Kaili, Fanter, Cornelia, Forsberg-Nilsson, Karin, Garcia, Carlos J, Gazal, Steven, Genereux, Diane P, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Hickey, Glenn, Hiller, Michael, Hindle, Allyson G, Hubley, Robert M, Hughes, Graham M, Johnson, Jeremy, Juan, David, Kaplow, Irene M, Keough, Kathleen C, Kirilenko, Bogdan, Koepfli, Klaus-Peter, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawler, Alyssa J, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Li, Xue, Lind, Abigail, Mackay-Smith, Ava, Marinescu, Voichita D, Marques-Bonet, Tomas, Meadows, Jennifer RS, Meyer, Wynn K, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Navarro, Arcadi, Nweeia, Martin, Ortmann, Sylvia, Osmanski, Austin, Paten, Benedict, Paulat, Nicole S, Pfenning, Andreas R, Phan, BaDoi N, Pollard, Katherine S, Pratt, Henry E, Ray, David A, Reilly, Steven K, Rosen, Jeb R, Ruf, Irina, Ryan, Louise, Ryder, Oliver A, Sabeti, Pardis C, Schäffer, Daniel E, Serres, Aitor, Shapiro, Beth, Smit, Arian FA, Springer, Mark, Srinivasan, Chaitanya, Steiner, Cynthia, Storer, Jessica M, Sullivan, Kevin AM, Sullivan, Patrick F, and Sundström, Elisabeth

Subjects
Genetics, Human Genome, Biotechnology, Animals, Female, Biological Evolution, Eutheria, Evolution, Molecular, Fossils, Genomics, Phylogeny, Genetic Variation, Time Factors, Zoonomia Consortium‡, General Science & Technology
Abstract

The precise pattern and timing of speciation events that gave rise to all living placental mammals remain controversial. We provide a comprehensive phylogenetic analysis of genetic variation across an alignment of 241 placental mammal genome assemblies, addressing prior concerns regarding limited genomic sampling across species. We compared neutral genome-wide phylogenomic signals using concatenation and coalescent-based approaches, interrogated phylogenetic variation across chromosomes, and analyzed extensive catalogs of structural variants. Interordinal relationships exhibit relatively low rates of phylogenomic conflict across diverse datasets and analytical methods. Conversely, X-chromosome versus autosome conflicts characterize multiple independent clades that radiated during the Cenozoic. Genomic time trees reveal an accumulation of cladogenic events before and immediately after the Cretaceous-Paleogene (K-Pg) boundary, implying important roles for Cretaceous continental vicariance and the K-Pg extinction in the placental radiation.

Published
2023

2. Comparative genomics of Balto, a famous historic dog, captures lost diversity of 1920s sled dogs

Author

Moon, Katherine L, Huson, Heather J, Morrill, Kathleen, Wang, Ming-Shan, Li, Xue, Srikanth, Krishnamoorthy, Lindblad-Toh, Kerstin, Svenson, Gavin J, Karlsson, Elinor K, Shapiro, Beth, Andrews, Gregory, Armstrong, Joel C, Bianchi, Matteo, Birren, Bruce W, Bredemeyer, Kevin R, Breit, Ana M, Christmas, Matthew J, Clawson, Hiram, Damas, Joana, Di Palma, Federica, Diekhans, Mark, Dong, Michael X, Eizirik, Eduardo, Fan, Kaili, Fanter, Cornelia, Foley, Nicole M, Forsberg-Nilsson, Karin, Garcia, Carlos J, Gatesy, John, Gazal, Steven, Genereux, Diane P, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Harris, Andrew J, Hickey, Glenn, Hiller, Michael, Hindle, Allyson G, Hubley, Robert M, Hughes, Graham M, Johnson, Jeremy, Juan, David, Kaplow, Irene M, Keough, Kathleen C, Kirilenko, Bogdan, Koepfli, Klaus-Peter, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawler, Alyssa J, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Lewin, Harris A, Lind, Abigail, Mackay-Smith, Ava, Marinescu, Voichita D, Marques-Bonet, Tomas, Mason, Victor C, Meadows, Jennifer RS, Meyer, Wynn K, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Murphy, William J, Navarro, Arcadi, Nweeia, Martin, Ortmann, Sylvia, Osmanski, Austin, Paten, Benedict, Paulat, Nicole S, Pfenning, Andreas R, Phan, BaDoi N, Pollard, Katherine S, Pratt, Henry E, Ray, David A, Reilly, Steven K, Rosen, Jeb R, Ruf, Irina, Ryan, Louise, Ryder, Oliver A, Sabeti, Pardis C, Schäffer, Daniel E, Serres, Aitor, Smit, Arian FA, Springer, Mark, Srinivasan, Chaitanya, Steiner, Cynthia, Storer, Jessica M, Sullivan, Kevin AM, Sullivan, Patrick F, Sundström, Elisabeth, Supple, Megan A, and Swofford, Ross

Subjects
Agricultural, Veterinary and Food Sciences, Biological Sciences, Genetics, Animals, Dogs, Male, Genome, Genomics, Genotype, Phenotype, Wolves, Biodiversity, Genetic Variation, Zoonomia Consortium, General Science & Technology
Abstract

We reconstruct the phenotype of Balto, the heroic sled dog renowned for transporting diphtheria antitoxin to Nome, Alaska, in 1925, using evolutionary constraint estimates from the Zoonomia alignment of 240 mammals and 682 genomes from dogs and wolves of the 21st century. Balto shares just part of his diverse ancestry with the eponymous Siberian husky breed. Balto's genotype predicts a combination of coat features atypical for modern sled dog breeds, and a slightly smaller stature. He had enhanced starch digestion compared with Greenland sled dogs and a compendium of derived homozygous coding variants at constrained positions in genes connected to bone and skin development. We propose that Balto's population of origin, which was less inbred and genetically healthier than that of modern breeds, was adapted to the extreme environment of 1920s Alaska.

Published
2023

3. The contribution of historical processes to contemporary extinction risk in placental mammals

Author

Wilder, Aryn P, Supple, Megan A, Subramanian, Ayshwarya, Mudide, Anish, Swofford, Ross, Serres-Armero, Aitor, Steiner, Cynthia, Koepfli, Klaus-Peter, Genereux, Diane P, Karlsson, Elinor K, Lindblad-Toh, Kerstin, Marques-Bonet, Tomas, Munoz Fuentes, Violeta, Foley, Kathleen, Meyer, Wynn K, Ryder, Oliver A, Shapiro, Beth, Andrews, Gregory, Armstrong, Joel C, Bianchi, Matteo, Birren, Bruce W, Bredemeyer, Kevin R, Breit, Ana M, Christmas, Matthew J, Clawson, Hiram, Damas, Joana, Di Palma, Federica, Diekhans, Mark, Dong, Michael X, Eizirik, Eduardo, Fan, Kaili, Fanter, Cornelia, Foley, Nicole M, Forsberg-Nilsson, Karin, Garcia, Carlos J, Gatesy, John, Gazal, Steven, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Harris, Andrew J, Hickey, Glenn, Hiller, Michael, Hindle, Allyson G, Hubley, Robert M, Hughes, Graham M, Johnson, Jeremy, Juan, David, Kaplow, Irene M, Keough, Kathleen C, Kirilenko, Bogdan, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawler, Alyssa J, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Lewin, Harris A, Li, Xue, Lind, Abigail, Mackay-Smith, Ava, Marinescu, Voichita D, Mason, Victor C, Meadows, Jennifer RS, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Murphy, William J, Navarro, Arcadi, Nweeia, Martin, Ortmann, Sylvia, Osmanski, Austin, Paten, Benedict, Paulat, Nicole S, Pfenning, Andreas R, Phan, BaDoi N, Pollard, Katherine S, Pratt, Henry E, Ray, David A, Reilly, Steven K, Rosen, Jeb R, Ruf, Irina, Ryan, Louise, Sabeti, Pardis C, Schäffer, Daniel E, Serres, Aitor, Smit, Arian FA, Springer, Mark, and Srinivasan, Chaitanya

Subjects
Biological Sciences, Evolutionary Biology, Genetics, Behavioral and Social Science, Human Genome, Basic Behavioral and Social Science, Life on Land, Animals, Female, Pregnancy, Eutheria, Extinction, Biological, Genetic Variation, Genome, Population Density, Risk, Zoonomia Consortium‡, General Science & Technology
Abstract

Species persistence can be influenced by the amount, type, and distribution of diversity across the genome, suggesting a potential relationship between historical demography and resilience. In this study, we surveyed genetic variation across single genomes of 240 mammals that compose the Zoonomia alignment to evaluate how historical effective population size (Ne) affects heterozygosity and deleterious genetic load and how these factors may contribute to extinction risk. We find that species with smaller historical Ne carry a proportionally larger burden of deleterious alleles owing to long-term accumulation and fixation of genetic load and have a higher risk of extinction. This suggests that historical demography can inform contemporary resilience. Models that included genomic data were predictive of species' conservation status, suggesting that, in the absence of adequate census or ecological data, genomic information may provide an initial risk assessment.

Published
2023

4. The functional and evolutionary impacts of human-specific deletions in conserved elements

Author

Xue, James R, Mackay-Smith, Ava, Mouri, Kousuke, Garcia, Meilin Fernandez, Dong, Michael X, Akers, Jared F, Noble, Mark, Li, Xue, Lindblad-Toh, Kerstin, Karlsson, Elinor K, Noonan, James P, Capellini, Terence D, Brennand, Kristen J, Tewhey, Ryan, Sabeti, Pardis C, Reilly, Steven K, Andrews, Gregory, Armstrong, Joel C, Bianchi, Matteo, Birren, Bruce W, Bredemeyer, Kevin R, Breit, Ana M, Christmas, Matthew J, Clawson, Hiram, Damas, Joana, Di Palma, Federica, Diekhans, Mark, Eizirik, Eduardo, Fan, Kaili, Fanter, Cornelia, Foley, Nicole M, Forsberg-Nilsson, Karin, Garcia, Carlos J, Gatesy, John, Gazal, Steven, Genereux, Diane P, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Harris, Andrew J, Hickey, Glenn, Hiller, Michael, Hindle, Allyson G, Hubley, Robert M, Hughes, Graham M, Johnson, Jeremy, Juan, David, Kaplow, Irene M, Keough, Kathleen C, Kirilenko, Bogdan, Koepfli, Klaus-Peter, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawler, Alyssa J, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Lewin, Harris A, Lind, Abigail, Marinescu, Voichita D, Marques-Bonet, Tomas, Mason, Victor C, Meadows, Jennifer RS, Meyer, Wynn K, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Murphy, William J, Navarro, Arcadi, Nweeia, Martin, Ortmann, Sylvia, Osmanski, Austin, Paten, Benedict, Paulat, Nicole S, Pfenning, Andreas R, Phan, BaDoi N, Pollard, Katherine S, Pratt, Henry E, Ray, David A, Rosen, Jeb R, Ruf, Irina, Ryan, Louise, Ryder, Oliver A, Schäffer, Daniel E, Serres, Aitor, Shapiro, Beth, Smit, Arian FA, Springer, Mark, Srinivasan, Chaitanya, and Steiner, Cynthia

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Neurosciences, Human Genome, 1.1 Normal biological development and functioning, Underpinning research, Generic health relevance, Neurological, Humans, Conserved Sequence, Evolution, Molecular, Genome, Genomics, RNA-Binding Proteins, Sequence Deletion, Brain, Gene Expression Regulation, Developmental, Zoonomia Consortium†, General Science & Technology
Abstract

Conserved genomic sequences disrupted in humans may underlie uniquely human phenotypic traits. We identified and characterized 10,032 human-specific conserved deletions (hCONDELs). These short (average 2.56 base pairs) deletions are enriched for human brain functions across genetic, epigenomic, and transcriptomic datasets. Using massively parallel reporter assays in six cell types, we discovered 800 hCONDELs conferring significant differences in regulatory activity, half of which enhance rather than disrupt regulatory function. We highlight several hCONDELs with putative human-specific effects on brain development, including HDAC5, CPEB4, and PPP2CA. Reverting an hCONDEL to the ancestral sequence alters the expression of LOXL2 and developmental genes involved in myelination and synaptic function. Our data provide a rich resource to investigate the evolutionary mechanisms driving new traits in humans and other species.

Published
2023

5. Integrating gene annotation with orthology inference at scale

Author

Kirilenko, Bogdan M, Munegowda, Chetan, Osipova, Ekaterina, Jebb, David, Sharma, Virag, Blumer, Moritz, Morales, Ariadna E, Ahmed, Alexis-Walid, Kontopoulos, Dimitrios-Georgios, Hilgers, Leon, Lindblad-Toh, Kerstin, Karlsson, Elinor K, Hiller, Michael, Andrews, Gregory, Armstrong, Joel C, Bianchi, Matteo, Birren, Bruce W, Bredemeyer, Kevin R, Breit, Ana M, Christmas, Matthew J, Clawson, Hiram, Damas, Joana, Di Palma, Federica, Diekhans, Mark, Dong, Michael X, Eizirik, Eduardo, Fan, Kaili, Fanter, Cornelia, Foley, Nicole M, Forsberg-Nilsson, Karin, Garcia, Carlos J, Gatesy, John, Gazal, Steven, Genereux, Diane P, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Harris, Andrew J, Hickey, Glenn, Hindle, Allyson G, Hubley, Robert M, Hughes, Graham M, Johnson, Jeremy, Juan, David, Kaplow, Irene M, Keough, Kathleen C, Kirilenko, Bogdan, Koepfli, Klaus-Peter, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawler, Alyssa J, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Lewin, Harris A, Li, Xue, Lind, Abigail, Mackay-Smith, Ava, Marinescu, Voichita D, Marques-Bonet, Tomas, Mason, Victor C, Meadows, Jennifer RS, Meyer, Wynn K, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Murphy, William J, Navarro, Arcadi, Nweeia, Martin, Ortmann, Sylvia, Osmanski, Austin, Paten, Benedict, Paulat, Nicole S, Pfenning, Andreas R, Phan, BaDoi N, Pollard, Katherine S, Pratt, Henry E, Ray, David A, Reilly, Steven K, Rosen, Jeb R, Ruf, Irina, Ryan, Louise, Ryder, Oliver A, Sabeti, Pardis C, Schäffer, Daniel E, Serres, Aitor, Shapiro, Beth, Smit, Arian FA, Springer, Mark, Srinivasan, Chaitanya, Steiner, Cynthia, Storer, Jessica M, Sullivan, Kevin AM, and Sullivan, Patrick F

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Human Genome, Generic health relevance, Animals, Female, Mice, Eutheria, Genome, Genomics, Molecular Sequence Annotation, Birds, Zoonomia Consortium‡, General Science & Technology
Abstract

Annotating coding genes and inferring orthologs are two classical challenges in genomics and evolutionary biology that have traditionally been approached separately, limiting scalability. We present TOGA (Tool to infer Orthologs from Genome Alignments), a method that integrates structural gene annotation and orthology inference. TOGA implements a different paradigm to infer orthologous loci, improves ortholog detection and annotation of conserved genes compared with state-of-the-art methods, and handles even highly fragmented assemblies. TOGA scales to hundreds of genomes, which we demonstrate by applying it to 488 placental mammal and 501 bird assemblies, creating the largest comparative gene resources so far. Additionally, TOGA detects gene losses, enables selection screens, and automatically provides a superior measure of mammalian genome quality. TOGA is a powerful and scalable method to annotate and compare genes in the genomic era.

Published
2023

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

Author

Kaplow, Irene M, Lawler, Alyssa J, Schäffer, Daniel E, Srinivasan, Chaitanya, Sestili, Heather H, Wirthlin, Morgan E, Phan, BaDoi N, Prasad, Kavya, Brown, Ashley R, Zhang, Xiaomeng, Foley, Kathleen, Genereux, Diane P, Karlsson, Elinor K, Lindblad-Toh, Kerstin, Meyer, Wynn K, Pfenning, Andreas R, Andrews, Gregory, Armstrong, Joel C, Bianchi, Matteo, Birren, Bruce W, Bredemeyer, Kevin R, Breit, Ana M, Christmas, Matthew J, Clawson, Hiram, Damas, Joana, Di Palma, Federica, Diekhans, Mark, Dong, Michael X, Eizirik, Eduardo, Fan, Kaili, Fanter, Cornelia, Foley, Nicole M, Forsberg-Nilsson, Karin, Garcia, Carlos J, Gatesy, John, Gazal, Steven, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Harris, Andrew J, Hickey, Glenn, Hiller, Michael, Hindle, Allyson G, Hubley, Robert M, Hughes, Graham M, Johnson, Jeremy, Juan, David, Keough, Kathleen C, Kirilenko, Bogdan, Koepfli, Klaus-Peter, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Lewin, Harris A, Li, Xue, Lind, Abigail, Mackay-Smith, Ava, Marinescu, Voichita D, Marques-Bonet, Tomas, Mason, Victor C, Meadows, Jennifer RS, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Murphy, William J, Navarro, Arcadi, Nweeia, Martin, Ortmann, Sylvia, Osmanski, Austin, Paten, Benedict, Paulat, Nicole S, Pollard, Katherine S, Pratt, Henry E, Ray, David A, Reilly, Steven K, Rosen, Jeb R, Ruf, Irina, Ryan, Louise, Ryder, Oliver A, Sabeti, Pardis C, Serres, Aitor, Shapiro, Beth, Smit, Arian FA, Springer, Mark, and Steiner, Cynthia

Subjects
Biological Sciences, Genetics, Pediatric, Human Genome, Rare Diseases, Congenital Structural Anomalies, Underpinning research, 1.1 Normal biological development and functioning, Neurological, Mental health, Animals, Enhancer Elements, Genetic, Genetic Variation, Machine Learning, Mammals, Phenotype, Zoonomia Consortium**, General Science & Technology
Abstract

Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.

Published
2023

7. Three-dimensional genome rewiring in loci with human accelerated regions

Author

Keough, Kathleen C, Whalen, Sean, Inoue, Fumitaka, Przytycki, Pawel F, Fair, Tyler, Deng, Chengyu, Steyert, Marilyn, Ryu, Hane, Lindblad-Toh, Kerstin, Karlsson, Elinor, Nowakowski, Tomasz, Ahituv, Nadav, Pollen, Alex, Pollard, Katherine S, Andrews, Gregory, Armstrong, Joel C, Bianchi, Matteo, Birren, Bruce W, Bredemeyer, Kevin R, Breit, Ana M, Christmas, Matthew J, Clawson, Hiram, Damas, Joana, Di Palma, Federica, Diekhans, Mark, Dong, Michael X, Eizirik, Eduardo, Fan, Kaili, Fanter, Cornelia, Foley, Nicole M, Forsberg-Nilsson, Karin, Garcia, Carlos J, Gatesy, John, Gazal, Steven, Genereux, Diane P, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Harris, Andrew J, Hickey, Glenn, Hiller, Michael, Hindle, Allyson G, Hubley, Robert M, Hughes, Graham M, Johnson, Jeremy, Juan, David, Kaplow, Irene M, Karlsson, Elinor K, Kirilenko, Bogdan, Koepfli, Klaus-Peter, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawler, Alyssa J, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Lewin, Harris A, Li, Xue, Lind, Abigail, Mackay-Smith, Ava, Marinescu, Voichita D, Marques-Bonet, Tomas, Mason, Victor C, Meadows, Jennifer RS, Meyer, Wynn K, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Murphy, William J, Navarro, Arcadi, Nweeia, Martin, Ortmann, Sylvia, Osmanski, Austin, Paten, Benedict, Paulat, Nicole S, Pfenning, Andreas R, Phan, BaDoi N, Pratt, Henry E, Ray, David A, Reilly, Steven K, Rosen, Jeb R, Ruf, Irina, Ryan, Louise, Ryder, Oliver A, Sabeti, Pardis C, Schäffer, Daniel E, Serres, Aitor, Shapiro, Beth, Smit, Arian FA, Springer, Mark, Srinivasan, Chaitanya, Steiner, Cynthia, Storer, Jessica M, and Sullivan, Kevin AM

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Stem Cell Research, Human Genome, Biotechnology, Underpinning research, 1.1 Normal biological development and functioning, Animals, Humans, Chromatin, Genome, Human, Genomics, Pan troglodytes, Genetic Loci, Neurogenesis, Deep Learning, Zoonomia Consortium§, General Science & Technology
Abstract

Human accelerated regions (HARs) are conserved genomic loci that evolved at an accelerated rate in the human lineage and may underlie human-specific traits. We generated HARs and chimpanzee accelerated regions with an automated pipeline and an alignment of 241 mammalian genomes. Combining deep learning with chromatin capture experiments in human and chimpanzee neural progenitor cells, we discovered a significant enrichment of HARs in topologically associating domains containing human-specific genomic variants that change three-dimensional (3D) genome organization. Differential gene expression between humans and chimpanzees at these loci suggests rewiring of regulatory interactions between HARs and neurodevelopmental genes. Thus, comparative genomics together with models of 3D genome folding revealed enhancer hijacking as an explanation for the rapid evolution of HARs.

Published
2023

8. Evolutionary constraint and innovation across hundreds of placental mammals

Author

Christmas, Matthew J, Kaplow, Irene M, Genereux, Diane P, Dong, Michael X, Hughes, Graham M, Li, Xue, Sullivan, Patrick F, Hindle, Allyson G, Andrews, Gregory, Armstrong, Joel C, Bianchi, Matteo, Breit, Ana M, Diekhans, Mark, Fanter, Cornelia, Foley, Nicole M, Goodman, Daniel B, Goodman, Linda, Keough, Kathleen C, Kirilenko, Bogdan, Kowalczyk, Amanda, Lawless, Colleen, Lind, Abigail L, Meadows, Jennifer RS, Moreira, Lucas R, Redlich, Ruby W, Ryan, Louise, Swofford, Ross, Valenzuela, Alejandro, Wagner, Franziska, Wallerman, Ola, Brown, Ashley R, Damas, Joana, Fan, Kaili, Gatesy, John, Grimshaw, Jenna, Johnson, Jeremy, Kozyrev, Sergey V, Lawler, Alyssa J, Marinescu, Voichita D, Morrill, Kathleen M, Osmanski, Austin, Paulat, Nicole S, Phan, BaDoi N, Reilly, Steven K, Schäffer, Daniel E, Steiner, Cynthia, Supple, Megan A, Wilder, Aryn P, Wirthlin, Morgan E, Xue, James R, Birren, Bruce W, Gazal, Steven, Hubley, Robert M, Koepfli, Klaus-Peter, Marques-Bonet, Tomas, Meyer, Wynn K, Nweeia, Martin, Sabeti, Pardis C, Shapiro, Beth, Smit, Arian FA, Springer, Mark S, Teeling, Emma C, Weng, Zhiping, Hiller, Michael, Levesque, Danielle L, Lewin, Harris A, Murphy, William J, Navarro, Arcadi, Paten, Benedict, Pollard, Katherine S, Ray, David A, Ruf, Irina, Ryder, Oliver A, Pfenning, Andreas R, Lindblad-Toh, Kerstin, Karlsson, Elinor K, Bredemeyer, Kevin R, Clawson, Hiram, Di Palma, Federica, Eizirik, Eduardo, Forsberg-Nilsson, Karin, Garcia, Carlos J, and Halsey, Michaela K

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Human Genome, Animals, Female, Humans, Conserved Sequence, Eutheria, Evolution, Molecular, Genome, Human, Zoonomia Consortium§, General Science & Technology
Abstract

Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.

Published
2023

9. Leveraging base-pair mammalian constraint to understand genetic variation and human disease

Author

Sullivan, Patrick F, Meadows, Jennifer RS, Gazal, Steven, Phan, BaDoi N, Li, Xue, Genereux, Diane P, Dong, Michael X, Bianchi, Matteo, Andrews, Gregory, Sakthikumar, Sharadha, Nordin, Jessika, Roy, Ananya, Christmas, Matthew J, Marinescu, Voichita D, Wang, Chao, Wallerman, Ola, Xue, James, Yao, Shuyang, Sun, Quan, Szatkiewicz, Jin, Wen, Jia, Huckins, Laura M, Lawler, Alyssa, Keough, Kathleen C, Zheng, Zhili, Zeng, Jian, Wray, Naomi R, Li, Yun, Johnson, Jessica, Chen, Jiawen, Paten, Benedict, Reilly, Steven K, Hughes, Graham M, Weng, Zhiping, Pollard, Katherine S, Pfenning, Andreas R, Forsberg-Nilsson, Karin, Karlsson, Elinor K, Lindblad-Toh, Kerstin, Armstrong, Joel C, Birren, Bruce W, Bredemeyer, Kevin R, Breit, Ana M, Clawson, Hiram, Damas, Joana, Di Palma, Federica, Diekhans, Mark, Eizirik, Eduardo, Fan, Kaili, Fanter, Cornelia, Foley, Nicole M, Garcia, Carlos J, Gatesy, John, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Harris, Andrew J, Hickey, Glenn, Hiller, Michael, Hindle, Allyson G, Hubley, Robert M, Johnson, Jeremy, Juan, David, Kaplow, Irene M, Kirilenko, Bogdan, Koepfli, Klaus-Peter, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawler, Alyssa J, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Lewin, Harris A, Lind, Abigail, Mackay-Smith, Ava, Marques-Bonet, Tomas, Mason, Victor C, Meyer, Wynn K, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Murphy, William J, and Navarro, Arcadi

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Clinical Research, Human Genome, Brain Disorders, Generic health relevance, Animals, Humans, Biological Evolution, Genetic Variation, Genome, Human, Genome-Wide Association Study, Genomics, Molecular Sequence Annotation, Polymorphism, Single Nucleotide, Disease, Zoonomia Consortium§, General Science & Technology
Abstract

Thousands of genomic regions have been associated with heritable human diseases, but attempts to elucidate biological mechanisms are impeded by an inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function, agnostic to cell type or disease mechanism. Single-base phyloP scores from 240 mammals identified 3.3% of the human genome as significantly constrained and likely functional. We compared phyloP scores to genome annotation, association studies, copy-number variation, clinical genetics findings, and cancer data. Constrained positions are enriched for variants that explain common disease heritability more than other functional annotations. Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

Published
2023

10. Evolution of the ancestral mammalian karyotype and syntenic regions

Author

Damas, Joana, Corbo, Marco, Kim, Jaebum, Turner-Maier, Jason, Farré, Marta, Larkin, Denis M, Ryder, Oliver A, Steiner, Cynthia, Houck, Marlys L, Hall, Shaune, Shiue, Lily, Thomas, Stephen, Swale, Thomas, Daly, Mark, Korlach, Jonas, Uliano-Silva, Marcela, Mazzoni, Camila J, Birren, Bruce W, Genereux, Diane P, Johnson, Jeremy, Lindblad-Toh, Kerstin, Karlsson, Elinor K, Nweeia, Martin T, Johnson, Rebecca N, Lewin, Harris A, Andrews, Gregory, Armstrong, Joel C, Bianchi, Matteo, Bredemeyer, Kevin R, Breit, Ana M, Christmas, Matthew J, Clawson, Hiram, Di Palma, Federica, Diekhans, Mark, Dong, Michael X, Eizirik, Eduardo, Fan, Kaili, Fanter, Cornelia, Foley, Nicole M, Forsberg-Nilsson, Karin, Garcia, Carlos J, Gatesy, John, Gazal, Steven, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Harris, Andrew J, Hickey, Glenn, Hiller, Michael, Hindle, Allyson G, Hubley, Robert M, Hughes, Graham M, Juan, David, Kaplow, Irene M, Keough, Kathleen C, Kirilenko, Bogdan, Koepfli, Klaus-Peter, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawler, Alyssa J, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Li, Xue, Lind, Abigail, Mackay-Smith, Ava, Marinescu, Voichita D, Marques-Bonet, Tomas, Mason, Victor C, Meadows, Jennifer RS, Meyer, Wynn K, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Murphy, William J, Navarro, Arcadi, Nweeia, Martin, Ortmann, Sylvia, Osmanski, Austin, Paten, Benedict, Paulat, Nicole S, Pfenning, Andreas R, Phan, BaDoi N, Pollard, Katherine S, Pratt, Henry E, Ray, David A, Reilly, Steven K, Rosen, Jeb R, Ruf, Irina, and Ryan, Louise

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Evolutionary Biology, Genetics, Human Genome, Generic health relevance, Animals, Cattle, Chromosomes, Mammalian, Eutheria, Evolution, Molecular, Humans, Karyotype, Mammals, Phylogeny, Sloths, Synteny, chromosome evolution, mammals, synteny conservation, ancestral genome reconstruction, topologically associating domains, Zoonomia Consortium
Abstract

Decrypting the rearrangements that drive mammalian chromosome evolution is critical to understanding the molecular bases of speciation, adaptation, and disease susceptibility. Using 8 scaffolded and 26 chromosome-scale genome assemblies representing 23/26 mammal orders, we computationally reconstructed ancestral karyotypes and syntenic relationships at 16 nodes along the mammalian phylogeny. Three different reference genomes (human, sloth, and cattle) representing phylogenetically distinct mammalian superorders were used to assess reference bias in the reconstructed ancestral karyotypes and to expand the number of clades with reconstructed genomes. The mammalian ancestor likely had 19 pairs of autosomes, with nine of the smallest chromosomes shared with the common ancestor of all amniotes (three still conserved in extant mammals), demonstrating a striking conservation of synteny for ∼320 My of vertebrate evolution. The numbers and types of chromosome rearrangements were classified for transitions between the ancestral mammalian karyotype, descendent ancestors, and extant species. For example, 94 inversions, 16 fissions, and 14 fusions that occurred over 53 My differentiated the therian from the descendent eutherian ancestor. The highest breakpoint rate was observed between the mammalian and therian ancestors (3.9 breakpoints/My). Reconstructed mammalian ancestor chromosomes were found to have distinct evolutionary histories reflected in their rates and types of rearrangements. The distributions of genes, repetitive elements, topologically associating domains, and actively transcribed regions in multispecies homologous synteny blocks and evolutionary breakpoint regions indicate that purifying selection acted over millions of years of vertebrate evolution to maintain syntenic relationships of developmentally important genes and regulatory landscapes of gene-dense chromosomes.

Published
2022

14. Reduction of Paraoxonase expression followed by inactivation across independent semiaquatic mammals suggests stepwise path to pseudogenization

Author

Graham, Allie M, primary, Jamison, Jerrica M, additional, Bustos, Marisol, additional, Cournoyer, Charlotte, additional, Michaels, Alexa, additional, Presnell, Jason S, additional, Richter, Rebecca, additional, Crocker, Daniel E, additional, Fustukjian, Ari, additional, Hunter, Margaret E, additional, Rea, Lorrie D, additional, Marsillach, Judit, additional, Furlong, Clement E, additional, Meyer, Wynn K, additional, and Clark, Nathan L, additional

Published
2023
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15. Evolutionary constraint and innovation across hundreds of placental mammals

Author

Christmas, Matthew, Kaplow, Irene M., Genereux, Diane P., Dong, Michael X., Hughes, Graham M., Li, Xue, Sullivan, Patrick F., Hindle, Allyson G., Andrews, Gregory, Armstrong, Joel C., Bianchi, Matteo, Breit, Ana M., Diekhans, Mark, Fanter, Cornelia, Foley, Nicole M., Goodman, Daniel B., Goodman, Linda, Keough, Kathleen C., Kirilenko, Bogdan, Kowalczyk, Amanda, Lawless, Colleen, Lind, Abigail L., Meadows, Jennifer R.S., Moreira, Lucas R., Redlich, Ruby W., Ryan, Louise, Swofford, Ross, Valenzuela, Alejandro, Wagner, Franziska, Wallerman, Ola, Brown, Ashley R., Damas, Joana, Fan, Kaili, Gatesy, John, Grimshaw, Jenna, Johnson, Jeremy, Kozyrev, Sergey V., Lawler, Alyssa J., Marinescu, Voichita, Morrill, Kathleen M., Osmanski, Austin, Paulat, Nicole S., Phan, BaDoi N., Reilly, Steven K., Schäffer, Daniel E., Steiner, Cynthia, Supple, Megan A., Wilder, Aryn P., Wirthlin, Morgan E., Xue, James R., Birren, Bruce W., Gazal, Steven, Hubley, Robert M., Koepfli, Klaus-Peter, Marques-Bonet, Tomas, Meyer, Wynn K., Nweela, Martin, Sabeti, Pardis C., Shapiro, Beth, Smit, Arian F. A., Springer, Mark S., Teeling, Emma C., Weng, Zhiping, Hiller, Michael, Levesque, Danielle L., Lewin, Harris A., Murphy, William J., Navarro, Arcadi, Paten, Benedict, Pollard, Katherine S., Ray, David A., Ruf, Irina, Ryder, Oliver A., Pfenning, Andreas R., Lindblad-Toh, Kerstin, Karlsson, Elinor K., Christmas, Matthew, Kaplow, Irene M., Genereux, Diane P., Dong, Michael X., Hughes, Graham M., Li, Xue, Sullivan, Patrick F., Hindle, Allyson G., Andrews, Gregory, Armstrong, Joel C., Bianchi, Matteo, Breit, Ana M., Diekhans, Mark, Fanter, Cornelia, Foley, Nicole M., Goodman, Daniel B., Goodman, Linda, Keough, Kathleen C., Kirilenko, Bogdan, Kowalczyk, Amanda, Lawless, Colleen, Lind, Abigail L., Meadows, Jennifer R.S., Moreira, Lucas R., Redlich, Ruby W., Ryan, Louise, Swofford, Ross, Valenzuela, Alejandro, Wagner, Franziska, Wallerman, Ola, Brown, Ashley R., Damas, Joana, Fan, Kaili, Gatesy, John, Grimshaw, Jenna, Johnson, Jeremy, Kozyrev, Sergey V., Lawler, Alyssa J., Marinescu, Voichita, Morrill, Kathleen M., Osmanski, Austin, Paulat, Nicole S., Phan, BaDoi N., Reilly, Steven K., Schäffer, Daniel E., Steiner, Cynthia, Supple, Megan A., Wilder, Aryn P., Wirthlin, Morgan E., Xue, James R., Birren, Bruce W., Gazal, Steven, Hubley, Robert M., Koepfli, Klaus-Peter, Marques-Bonet, Tomas, Meyer, Wynn K., Nweela, Martin, Sabeti, Pardis C., Shapiro, Beth, Smit, Arian F. A., Springer, Mark S., Teeling, Emma C., Weng, Zhiping, Hiller, Michael, Levesque, Danielle L., Lewin, Harris A., Murphy, William J., Navarro, Arcadi, Paten, Benedict, Pollard, Katherine S., Ray, David A., Ruf, Irina, Ryder, Oliver A., Pfenning, Andreas R., Lindblad-Toh, Kerstin, and Karlsson, Elinor K.

Abstract

Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (similar to 10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.

Published
2023
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16. The contribution of historical processes to contemporary extinction risk in placental mammals

Author

Wilder, Aryn P., Supple, Megan A., Subramanian, Ayshwarya, Mudide, Anish, Swofford, Ross, Serres-Armero, Aitor, Steiner, Cynthia, Koepfli, Klaus -Peter, Genereux, Diane P., Karlsson, Elinor K., Lindblad-Toh, Kerstin, Marques-Bonet, Tomas, Fuentes, Violeta Munoz, Foley, Kathleen, Meyer, Wynn K., Ryder, Oliver A., Shapiro, Beth, Wilder, Aryn P., Supple, Megan A., Subramanian, Ayshwarya, Mudide, Anish, Swofford, Ross, Serres-Armero, Aitor, Steiner, Cynthia, Koepfli, Klaus -Peter, Genereux, Diane P., Karlsson, Elinor K., Lindblad-Toh, Kerstin, Marques-Bonet, Tomas, Fuentes, Violeta Munoz, Foley, Kathleen, Meyer, Wynn K., Ryder, Oliver A., and Shapiro, Beth

Abstract

Species persistence can be influenced by the amount, type, and distribution of diversity across the genome, suggesting a potential relationship between historical demography and resilience. In this study, we surveyed genetic variation across single genomes of 240 mammals that compose the Zoonomia alignment to evaluate how historical effective population size (Ne) affects heterozygosity and deleterious genetic load and how these factors may contribute to extinction risk. We find that species with smaller historical Ne carry a proportionally larger burden of deleterious alleles owing to long-term accumulation and fixation of genetic load and have a higher risk of extinction. This suggests that historical demography can inform contemporary resilience. Models that included genomic data were predictive of species' conservation status, suggesting that, in the absence of adequate census or ecological data, genomic information may provide an initial risk assessment.

Published
2023
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17. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

Author

National Science Foundation (US), Carnegie Mellon University, Alfred P. Sloan Foundation, Swedish Research Council, Juan, David [0000-0003-1912-9667], Marqués-Bonet, Tomàs [0000-0002-5597-3075], Muntané, Gerard [0000-0003-1541-8365], Navarro, Arcadi [0000-0003-2162-8246], Valenzuela, Alejandro [0000-0001-6120-6246], Kaplow, Irene M., Lawler, Alyssa J., Schäffer, Daniel E., Srinivasan, Chaitanya, Sestili, Heather H., Wirthlin, Morgan E., Phan, BaDoi N., Prasad, Kavya, Brown, Ashley R., Zhang, Xiaomeng, Foley, Kathleen, Genereux, Diane P., Zoonomia Consortium, Juan, David, Marqués-Bonet, Tomàs, Muntané, Gerard, Navarro, Arcadi, Serres-Armero, Aitor, Valenzuela, Alejandro, Karlsson, Elinor K., Lindblad-Toh, Kerstin, Meyer, Wynn K., Pfenning, Andreas R., National Science Foundation (US), Carnegie Mellon University, Alfred P. Sloan Foundation, Swedish Research Council, Juan, David [0000-0003-1912-9667], Marqués-Bonet, Tomàs [0000-0002-5597-3075], Muntané, Gerard [0000-0003-1541-8365], Navarro, Arcadi [0000-0003-2162-8246], Valenzuela, Alejandro [0000-0001-6120-6246], Kaplow, Irene M., Lawler, Alyssa J., Schäffer, Daniel E., Srinivasan, Chaitanya, Sestili, Heather H., Wirthlin, Morgan E., Phan, BaDoi N., Prasad, Kavya, Brown, Ashley R., Zhang, Xiaomeng, Foley, Kathleen, Genereux, Diane P., Zoonomia Consortium, Juan, David, Marqués-Bonet, Tomàs, Muntané, Gerard, Navarro, Arcadi, Serres-Armero, Aitor, Valenzuela, Alejandro, Karlsson, Elinor K., Lindblad-Toh, Kerstin, Meyer, Wynn K., and Pfenning, Andreas R.

Abstract

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

Published
2023

18. The contribution of historical processes to contemporary extinction risk in placental mammals

Author

National Institutes of Health (US), Swedish Research Council, European Research Council, European Commission, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Howard Hughes Medical Institute, Generalitat de Catalunya, Marqués-Bonet, Tomàs [0000-0002-5597-3075], Juan, David [0000-0003-1912-9667], Muntané, Gerard [0000-0003-1541-8365], Navarro, Arcadi [0000-0003-2162-8246], Valenzuela, Alejandro [0000-0001-6120-6246], Wilder, Aryn P., Supple, Megan A., Subramanian, Ayshwarya, Mudide, Anish, Swofford, Ross, Serres-Armero, Aitor, Steiner, Cynthia, Koepfli, Klaus-Peter, Genereux, Diane P., Karlsson, Elinor K., Lindblad-Toh, Kerstin, Marqués-Bonet, Tomàs, Muñoz-Fuentes, Violeta, Foley, Kathleen, Meyer, Wynn K., Zoonomia Consortium, Juan, David, Muntané, Gerard, Navarro, Arcadi, Valenzuela, Alejandro, Ryder, Oliver A., Shapiro, Beth, National Institutes of Health (US), Swedish Research Council, European Research Council, European Commission, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Howard Hughes Medical Institute, Generalitat de Catalunya, Marqués-Bonet, Tomàs [0000-0002-5597-3075], Juan, David [0000-0003-1912-9667], Muntané, Gerard [0000-0003-1541-8365], Navarro, Arcadi [0000-0003-2162-8246], Valenzuela, Alejandro [0000-0001-6120-6246], Wilder, Aryn P., Supple, Megan A., Subramanian, Ayshwarya, Mudide, Anish, Swofford, Ross, Serres-Armero, Aitor, Steiner, Cynthia, Koepfli, Klaus-Peter, Genereux, Diane P., Karlsson, Elinor K., Lindblad-Toh, Kerstin, Marqués-Bonet, Tomàs, Muñoz-Fuentes, Violeta, Foley, Kathleen, Meyer, Wynn K., Zoonomia Consortium, Juan, David, Muntané, Gerard, Navarro, Arcadi, Valenzuela, Alejandro, Ryder, Oliver A., and Shapiro, Beth

Abstract

[INTRODUCTION] The Anthropocene is marked by an accelerated loss of biodiversity, widespread population declines, and a global conservation crisis. Given limited resources for conservation intervention, an approach is needed to identify threatened species from among the thousands lacking adequate information for status assessments. Such prioritization for intervention could come from genome sequence data, as genomes contain information about demography, diversity, fitness, and adaptive potential. However, the relevance of genomic data for identifying at-risk species is uncertain, in part because genetic variation may reflect past events and life histories better than contemporary conservation status., [RATIONALE] The Zoonomia multispecies alignment presents an opportunity to systematically compare neutral and functional genomic diversity and their relationships to contemporary extinction risk across a large sample of diverse mammalian taxa. We surveyed 240 species spanning from the “Least Concern” to “Critically Endangered” categories, as published in the International Union for Conservation of Nature’s Red List of Threatened Species. Using a single genome for each species, we estimated historical effective population sizes (Ne) and distributions of genome-wide heterozygosity. To estimate genetic load, we identified substitutions relative to reconstructed ancestral sequences, assuming that mutations at evolutionarily conserved sites and in protein-coding sequences, especially in genes essential for viability in mice, are predominantly deleterious. We examined relationships between the conservation status of species and metrics of heterozygosity, demography, and genetic load and used these data to train and test models to distinguish threatened from nonthreatened species., [RESULTS] Species with smaller historical Ne are more likely to be categorized as at risk of extinction, suggesting that demography, even from periods more than 10,000 years in the past, may be informative of contemporary resilience. Species with smaller historical Ne also carry proportionally higher burdens of weakly and moderately deleterious alleles, consistent with theoretical expectations of the long-term accumulation and fixation of genetic load under strong genetic drift. We found weak support for a causative link between fixed drift load and extinction risk; however, other types of genetic load not captured in our data, such as rare, highly deleterious alleles, may also play a role. Although ecological (e.g., physiological, life-history, and behavioral) variables were the best predictors of extinction risk, genomic variables nonrandomly distinguished threatened from nonthreatened species in regression and machine learning models. These results suggest that information encoded within even a single genome can provide a risk assessment in the absence of adequate ecological or population census data., [CONCLUSION] Our analysis highlights the potential for genomic data to rapidly and inexpensively gauge extinction risk by leveraging relationships between contemporary conservation status and genetic variation shaped by the long-term demographic history of species. As more resequencing data and additional reference genomes become available, estimates of genetic load, estimates of recent demographic history, and accuracy of predictive models will improve. We therefore echo calls for including genomic information in assessments of the conservation status of species.

Published
2023

19. Evolutionary constraint and innovation across hundreds of placental mammals

Author

National Institutes of Health (US), National Science Foundation (US), European Research Council, European Commission, Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Science Foundation Ireland, Irish Research Council, Swedish Research Council, Carnegie Mellon University, Roddenberry Foundation, Gladstone Institutes, LOEWE Center for Insect Biotechnology & Bioresources, Robert and Rosabel Osborne Endowment, SFI Research Centre in Applied Geosciences (Ireland), Alfred P. Sloan Foundation, UMaine Institute of Medicine, University College Dublin, Knut and Alice Wallenberg Foundation, Lehigh University, Valenzuela, Alejandro [0000-0001-6120-6246], Marqués-Bonet, Tomàs [0000-0002-5597-3075], Navarro, Arcadi [0000-0003-2162-8246], Christmas, Matthew J., Kaplow, Irene M., Genereux, Diane P., Dong, Michael X., Hughes, Graham M., Li, Xue, Sullivan, Patrick F., Hindle, Allyson G., Andrews,Gregory, Armstrong, Joel C., Bianchi, Matteo, Breit, Ana M., Diekhans, Mark, Fanter, Cornelia, Foley, Nicole M., Goodman, Daniel B., Goodman, Linda, Keough, Kathleen C., Kirilenko, Bogdan, Kowalczyk, Amanda, Lawless, Colleen, Lind, Abigail L., Meadows, Jennifer R. S., Moreira, Lucas R., Redlich, Ruby W., Ryan, Louise, Swofford, Ross, Valenzuela, Alejandro, Wagner, Franziska, Wallerman, Ola, Brown, Ashley R., Damas, Joana, Fan, Kaili, Gatesy, John, Grimshaw, Jenna, Johnson, Jeremy, Kozyrev, Sergey V., Lawler, Alyssa J., Marinescu, Voichita D., Morrill, Kathleen M., Osmanski, Austin, Paulat, Nicole S., Phan, BaDoi N., Reilly, Steven K., Schäffer, Daniel E., Steiner, Cynthia, Supple, Megan A., Wilder, Aryn P., Wirthlin, Morgan E., Xue, James R., Zoonomia Consortium, Birren, Bruce W., Gazal, Steven, Hubley, Robert M., Koepfli, Klaus-Peter, Marqués-Bonet, Tomàs, Meyer, Wynn K., Nweeia, Martin, Sabeti, Pardis C., Shapiro, Beth, Smit, Arian F. A., Springer, Mark S., Teeling, Emma C., Weng, Zhiping, Hiller, Michael, Levesque, Danielle L., Lewin, Harris A., Murphy, William J., Navarro, Arcadi, Paten, Benedict, Pollard, Katherine S., Ray, David A., Ruf, Irina, Ryder, Oliver A., Pfenning , Andreas R., Lindblad-Toh, Kerstin, Karlsson, Elinor K., National Institutes of Health (US), National Science Foundation (US), European Research Council, European Commission, Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Science Foundation Ireland, Irish Research Council, Swedish Research Council, Carnegie Mellon University, Roddenberry Foundation, Gladstone Institutes, LOEWE Center for Insect Biotechnology & Bioresources, Robert and Rosabel Osborne Endowment, SFI Research Centre in Applied Geosciences (Ireland), Alfred P. Sloan Foundation, UMaine Institute of Medicine, University College Dublin, Knut and Alice Wallenberg Foundation, Lehigh University, Valenzuela, Alejandro [0000-0001-6120-6246], Marqués-Bonet, Tomàs [0000-0002-5597-3075], Navarro, Arcadi [0000-0003-2162-8246], Christmas, Matthew J., Kaplow, Irene M., Genereux, Diane P., Dong, Michael X., Hughes, Graham M., Li, Xue, Sullivan, Patrick F., Hindle, Allyson G., Andrews,Gregory, Armstrong, Joel C., Bianchi, Matteo, Breit, Ana M., Diekhans, Mark, Fanter, Cornelia, Foley, Nicole M., Goodman, Daniel B., Goodman, Linda, Keough, Kathleen C., Kirilenko, Bogdan, Kowalczyk, Amanda, Lawless, Colleen, Lind, Abigail L., Meadows, Jennifer R. S., Moreira, Lucas R., Redlich, Ruby W., Ryan, Louise, Swofford, Ross, Valenzuela, Alejandro, Wagner, Franziska, Wallerman, Ola, Brown, Ashley R., Damas, Joana, Fan, Kaili, Gatesy, John, Grimshaw, Jenna, Johnson, Jeremy, Kozyrev, Sergey V., Lawler, Alyssa J., Marinescu, Voichita D., Morrill, Kathleen M., Osmanski, Austin, Paulat, Nicole S., Phan, BaDoi N., Reilly, Steven K., Schäffer, Daniel E., Steiner, Cynthia, Supple, Megan A., Wilder, Aryn P., Wirthlin, Morgan E., Xue, James R., Zoonomia Consortium, Birren, Bruce W., Gazal, Steven, Hubley, Robert M., Koepfli, Klaus-Peter, Marqués-Bonet, Tomàs, Meyer, Wynn K., Nweeia, Martin, Sabeti, Pardis C., Shapiro, Beth, Smit, Arian F. A., Springer, Mark S., Teeling, Emma C., Weng, Zhiping, Hiller, Michael, Levesque, Danielle L., Lewin, Harris A., Murphy, William J., Navarro, Arcadi, Paten, Benedict, Pollard, Katherine S., Ray, David A., Ruf, Irina, Ryder, Oliver A., Pfenning , Andreas R., Lindblad-Toh, Kerstin, and Karlsson, Elinor K.

Abstract

[INTRODUCTION] A major challenge in genomics is discerning which bases among billions alter organismal phenotypes and affect health and disease risk. Evidence of past selective pressure on a base, whether highly conserved or fast evolving, is a marker of functional importance. Bases that are unchanged in all mammals may shape phenotypes that are essential for organismal health. Bases that are evolving quickly in some species, or changed only in species that share an adaptive trait, may shape phenotypes that support survival in specific niches. Identifying bases associated with exceptional capacity for cellular recovery, such as in species that hibernate, could inform therapeutic discovery., [RATIONALE] The power and resolution of evolutionary analyses scale with the number and diversity of species compared. By analyzing genomes for hundreds of placental mammals, we can detect which individual bases in the genome are exceptionally conserved (constrained) and likely to be functionally important in both coding and noncoding regions. By including species that represent all orders of placental mammals and aligning genomes using a method that does not require designating humans as the reference species, we explore unusual traits in other species., [RESULTS] Zoonomia’s mammalian comparative genomics resources are the most comprehensive and statistically well-powered produced to date, with a protein-coding alignment of 427 mammals and a whole-genome alignment of 240 placental mammals representing all orders. We estimate that at least 10.7% of the human genome is evolutionarily conserved relative to neutrally evolving repeats and identify about 101 million significantly constrained single bases (false discovery rate < 0.05). We cataloged 4552 ultraconserved elements at least 20 bases long that are identical in more than 98% of the 240 placental mammals. Many constrained bases have no known function, illustrating the potential for discovery using evolutionary measures. Eighty percent are outside protein-coding exons, and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Constrained bases tend to vary less within human populations, which is consistent with purifying selection. Species threatened with extinction have few substitutions at constrained sites, possibly because severely deleterious alleles have been purged from their small populations. By pairing Zoonomia’s genomic resources with phenotype annotations, we find genomic elements associated with phenotypes that differ between species, including olfaction, hibernation, brain size, and vocal learning. We associate genomic traits, such as the number of olfactory receptor genes, with physical phenotypes, such as the number of olfactory turbinals. By comparing hibernators and nonhibernators, we implicate genes involved in mitochondrial disorders, protection against heat stress, and longevity in this physiologically intriguing phenotype. Using a machine learning–based approach that predicts tissue-specific cis-regulatory activity in hundreds of species using data from just a few, we associate changes in noncoding sequence with traits for which humans are exceptional: brain size and vocal learning., [CONCLUSION] Large-scale comparative genomics opens new opportunities to explore how genomes evolved as mammals adapted to a wide range of ecological niches and to discover what is shared across species and what is distinctively human. High-quality data for consistently defined phenotypes are necessary to realize this potential. Through partnerships with researchers in other fields, comparative genomics can address questions in human health and basic biology while guiding efforts to protect the biodiversity that is essential to these discoveries.

Published
2023

20. Evolutionary constraint and innovation across hundreds of placental mammals

Author

Christmas, Matthew J., Kaplow, Irene M., Genereux, Diane P., Dong, Michael X., Hughes, Graham M., Li, Xue, Sullivan, Patrick F., Hindle, Allyson G., Andrews, Gregory, Armstrong, Joel C., Bianchi, Matteo, Breit, Ana M., Diekhans, Mark, Fanter, Cornelia, Foley, Nicole M., Goodman, Daniel B., Goodman, Linda, Keough, Kathleen C., Kirilenko, Bogdan, Kowalczyk, Amanda, Lawless, Colleen, Lind, Abigail L., Meadows, Jennifer R. S., Moreira, Lucas R., Redlich, Ruby W., Ryan, Louise, Swofford, Ross, Valenzuela, Alejandro, Wagner, Franziska, Wallerman, Ola, Brown, Ashley R., Damas, Joana, Fan, Kaili, Gatesy, John, Grimshaw, Jenna, Johnson, Jeremy, Kozyrev, Sergey V., Lawler, Alyssa J., Marinescu, Voichita D., Morrill, Kathleen M., Osmanski, Austin, Paulat, Nicole S., Phan, BaDoi N., Reilly, Steven K., Schäffer, Daniel E., Steiner, Cynthia, Supple, Megan A., Wilder, Aryn P., Wirthlin, Morgan E., Xue, James R., Birren, Bruce W., Gazal, Steven, Hubley, Robert M., Koepfli, Klaus-Peter, Marques-Bonet, Tomas, Meyer, Wynn K., Nweeia, Martin, Sabeti, Pardis C., Shapiro, Beth, Smit, Arian F. A., Springer, Mark S., Teeling, Emma C., Weng, Zhiping, Hiller, Michael, Levesque, Danielle L., Lewin, Harris A., Murphy, William J., Navarro, Arcadi, Paten, Benedict, Pollard, Katherine S., Ray, David A., Ruf, Irina, Ryder, Oliver A., Pfenning, Andreas R., Lindblad-Toh, Kerstin, and Karlsson, Elinor K.

Subjects
Article
Abstract

Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth’s vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.

Published
2023

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

Author

Kaplow, Irene M., Lawler, Alyssa J., Schäffer, Daniel E., Srinivasan, Chaitanya, Sestili, Heather H., Wirthlin, Morgan E., Phan, BaDoi N., Prasad, Kavya, Brown, Ashley R., Zhang, Xiaomeng, Foley, Kathleen, Genereux, Diane P., Karlsson, Elinor K., Lindblad-Toh, Kerstin, Meyer, Wynn K., and Pfenning, Andreas R.

Subjects
Article
Abstract

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

Published
2023

22. Reduction of Paraoxonase expression followed by inactivation across independent semiaquatic mammals suggests stepwise path to pseudogenization

Author

Graham, Allie M, primary, Jamison, Jerrica M, additional, Bustos, Marisol, additional, Cournoyer, Charlotte, additional, Michaels, Alexa, additional, Presnell, Jason S, additional, Richter, Rebecca, additional, Crocker, Daniel E, additional, Fustukjian, Ari, additional, Hunter, Margaret E, additional, Rea, Lorrie D, additional, Furlong, Clement E, additional, Meyer, Wynn K, additional, and Clark, Nathan L, additional

Published
2022
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24. Diving mammals lose Paraoxonase 1 function in multiple different ways

Author

Meyer, Wynn K., Jamison, Jerrica, Cournoyer, Charlotte, Kaplow, Irene, Michaels, Alexis, Jiaxuan Yang, Richter, Rebecca J., Furlong, Clement E., and Clark, Nathaniel L

Subjects
ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, ComputingMethodologies_GENERAL
Abstract

Presentation of poster 1212C at TAGC 2020 Online. Files include a PDF of the poster (WMeyer_TAGC2020.PDF) and a 9m17s video walkthrough of the poster material (WMeyer_TAGCWalkthrough.mp4).

Published
2020
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31. NCBI's Virus Discovery Codeathon: Building "FIVE" —The Federated Index of Viral Experiments API Index.

Author

Martí-Carreras, Joan, Gener, Alejandro Rafael, Miller, Sierra D., Brito, Anderson F., Camacho, Christiam E., Connor, Ryan, Deboutte, Ward, Glickman, Cody, Kristensen, David M., Meyer, Wynn K., Modha, Sejal, Norris, Alexis L., Saha, Surya, Belford, Anna K., Biederstedt, Evan, Brister, James Rodney, Buchmann, Jan P., Cooley, Nicholas P., Edwards, Robert A., and Javkar, Kiran

Subjects
VIRAL genomes, VIRAL variation, GENOME size, VIRUSES, ACCESS to information
Abstract

Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus–host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE. [ABSTRACT FROM AUTHOR]

Published
2020
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32. Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements.

Author

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, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, and Zhang X

Subjects
Animals, Chiroptera genetics, Chiroptera physiology, Chromatin metabolism, Larynx physiology, Epigenesis, Genetic, Genome, Amino Acid Sequence, Machine Learning, Vocalization, Animal physiology, Motor Cortex cytology, Motor Cortex physiology, Enhancer Elements, Genetic, Motor Neurons physiology, Gene Expression Regulation, Evolution, Molecular, Proteins genetics, Proteins metabolism, Eutheria genetics, Eutheria physiology
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.

Published
2024
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33. RERconverge Expansion: Using Relative Evolutionary Rates to Study Complex Categorical Trait Evolution.

Author

Redlich R, Kowalczyk A, Tene M, Sestili HH, Foley K, Saputra E, Clark N, Chikina M, Meyer WK, and Pfenning A

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.

Published
2023
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