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Sauce B, Wiedenhoeft J, Judd N, Klingberg T. Change by challenge: A common genetic basis behind childhood cognitive development and cognitive training. NPJ Sci Learn 2021; 6:16. [PMID: 34078902 PMCID: PMC8172838 DOI: 10.1038/s41539-021-00096-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 03/12/2021] [Indexed: 06/02/2023]
Abstract
The interplay of genetic and environmental factors behind cognitive development has preoccupied multiple fields of science and sparked heated debates over the decades. Here we tested the hypothesis that developmental genes rely heavily on cognitive challenges-as opposed to natural maturation. Starting with a polygenic score (cogPGS) that previously explained variation in cognitive performance in adults, we estimated its effect in 344 children and adolescents (mean age of 12 years old, ranging from 6 to 25) who showed changes in working memory (WM) in two distinct samples: (1) a developmental sample showing significant WM gains after 2 years of typical, age-related development, and (2) a training sample showing significant, experimentally-induced WM gains after 25 days of an intense WM training. We found that the same genetic factor, cogPGS, significantly explained the amount of WM gain in both samples. And there was no interaction of cogPGS with sample, suggesting that those genetic factors are neutral to whether the WM gains came from development or training. These results represent evidence that cognitive challenges are a central piece in the gene-environment interplay during cognitive development. We believe our study sheds new light on previous findings of interindividual differences in education (rich-get-richer and compensation effects), brain plasticity in children, and the heritability increase of intelligence across the lifespan.
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Affiliation(s)
- Bruno Sauce
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - John Wiedenhoeft
- Core Facility Medical Biometry and Statistical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany
| | - Nicholas Judd
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Torkel Klingberg
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden.
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2
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Judd N, Sauce B, Wiedenhoeft J, Tromp J, Chaarani B, Schliep A, van Noort B, Penttilä J, Grimmer Y, Insensee C, Becker A, Banaschewski T, Bokde ALW, Quinlan EB, Desrivières S, Flor H, Grigis A, Gowland P, Heinz A, Ittermann B, Martinot JL, Paillère Martinot ML, Artiges E, Nees F, Papadopoulos Orfanos D, Paus T, Poustka L, Hohmann S, Millenet S, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Garavan H, Klingberg T. Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment. Proc Natl Acad Sci U S A 2020; 117:12411-12418. [PMID: 32430323 PMCID: PMC7275733 DOI: 10.1073/pnas.2001228117] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Genetic factors and socioeconomic status (SES) inequalities play a large role in educational attainment, and both have been associated with variations in brain structure and cognition. However, genetics and SES are correlated, and no prior study has assessed their neural associations independently. Here we used a polygenic score for educational attainment (EduYears-PGS), as well as SES, in a longitudinal study of 551 adolescents to tease apart genetic and environmental associations with brain development and cognition. Subjects received a structural MRI scan at ages 14 and 19. At both time points, they performed three working memory (WM) tasks. SES and EduYears-PGS were correlated (r = 0.27) and had both common and independent associations with brain structure and cognition. Specifically, lower SES was related to less total cortical surface area and lower WM. EduYears-PGS was also related to total cortical surface area, but in addition had a regional association with surface area in the right parietal lobe, a region related to nonverbal cognitive functions, including mathematics, spatial cognition, and WM. SES, but not EduYears-PGS, was related to a change in total cortical surface area from age 14 to 19. This study demonstrates a regional association of EduYears-PGS and the independent prediction of SES with cognitive function and brain development. It suggests that the SES inequalities, in particular parental education, are related to global aspects of cortical development, and exert a persistent influence on brain development during adolescence.
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Affiliation(s)
- Nicholas Judd
- Department of Neuroscience, Karolinska Institute, Stockholm, 17165, Sweden
| | - Bruno Sauce
- Department of Neuroscience, Karolinska Institute, Stockholm, 17165, Sweden
| | - John Wiedenhoeft
- Department of Medical Statistics, University of Göttingen, Göttingen, 37073, Germany
| | - Jeshua Tromp
- Department of Cognitive Psychology, Leiden University, Leiden, 2311, The Netherlands
| | - Bader Chaarani
- Department of Psychiatry, University of Vermont, Burlington, VT 05405
- Department of Psychological Science, University of Vermont, Burlington, VT 05405
| | - Alexander Schliep
- Department of Computer Science and Engineering, University of Gothenburg, Gothenburg, 41756, Sweden
| | - Betteke van Noort
- Hochschule für Gesundheit und Medizin, Medical School Berlin, Berlin, 14197, Germany
| | - Jani Penttilä
- Department of Social and Health Care, Psychosocial Services Adolescent Outpatient Clinic, University of Tampere, Lahti, 33100, Finland
| | - Yvonne Grimmer
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, 69117, Germany
| | - Corinna Insensee
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center, Göttingen, 37075, Germany
| | - Andreas Becker
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center, Göttingen, 37075, Germany
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, 69117, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, D02 PN40, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, D02 PN40, Ireland
| | - Erin Burke Quinlan
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, United Kingdom
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, United Kingdom
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, 69117, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, 68131, Germany
| | - Antoine Grigis
- NeuroSpin, French Alternative Energies and Atomic Energy Commission (CEA), Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Berlin, 10117, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt, Berlin, 38116, Germany
| | - Jean-Luc Martinot
- INSERM Unit 1000 "Neuroimaging & Psychiatry," Institut National de la Santé et de la Recherche Médicale, University Paris Saclay, University Paris Descartes, Paris, 75006, France
| | - Marie-Laure Paillère Martinot
- INSERM Unit 1000 "Neuroimaging & Psychiatry," Institut National de la Santé et de la Recherche Médicale, University Paris Saclay, University Paris Descartes, Paris, 75006, France
- Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Sorbonne Université, Paris, 75006, France
| | - Eric Artiges
- INSERM Unit 1000 "Neuroimaging & Psychiatry," Institut National de la Santé et de la Recherche Médicale, University Paris Saclay, University Paris Descartes, Paris, 75006, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, 69117, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, 68131, Germany
| | - Dimitri Papadopoulos Orfanos
- NeuroSpin, French Alternative Energies and Atomic Energy Commission (CEA), Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Tomáš Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, University of Toronto, Toronto, ON M6A 2E1, Canada
- Department of Psychology, University of Toronto, Toronto, ON M6A 2E1, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M6A 2E1, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center, Göttingen, 37075, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, 69117, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, 69117, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, 01087, Germany
| | - Michael N Smolka
- Department of Psychiatry, Technische Universität Dresden, Dresden, 01062, Germany
- Neuroimaging Center, Technische Universität Dresden, Dresden, 01069, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Berlin, 10117, Germany
| | - Robert Whelan
- School of Psychology, Trinity College Dublin, Dublin, D02 PN40, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, D02 PN40, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, United Kingdom
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT 05405
- Department of Psychological Science, University of Vermont, Burlington, VT 05405
| | - Torkel Klingberg
- Department of Neuroscience, Karolinska Institute, Stockholm, 17165, Sweden;
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3
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Bakker FT, Antonelli A, Clarke JA, Cook JA, Edwards SV, Ericson PGP, Faurby S, Ferrand N, Gelang M, Gillespie RG, Irestedt M, Lundin K, Larsson E, Matos-Maraví P, Müller J, von Proschwitz T, Roderick GK, Schliep A, Wahlberg N, Wiedenhoeft J, Källersjö M. The Global Museum: natural history collections and the future of evolutionary science and public education. PeerJ 2020; 8:e8225. [PMID: 32025365 PMCID: PMC6993751 DOI: 10.7717/peerj.8225] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 11/15/2019] [Indexed: 12/27/2022] Open
Abstract
Natural history museums are unique spaces for interdisciplinary research and educational innovation. Through extensive exhibits and public programming and by hosting rich communities of amateurs, students, and researchers at all stages of their careers, they can provide a place-based window to focus on integration of science and discovery, as well as a locus for community engagement. At the same time, like a synthesis radio telescope, when joined together through emerging digital resources, the global community of museums (the ‘Global Museum’) is more than the sum of its parts, allowing insights and answers to diverse biological, environmental, and societal questions at the global scale, across eons of time, and spanning vast diversity across the Tree of Life. We argue that, whereas natural history collections and museums began with a focus on describing the diversity and peculiarities of species on Earth, they are now increasingly leveraged in new ways that significantly expand their impact and relevance. These new directions include the possibility to ask new, often interdisciplinary questions in basic and applied science, such as in biomimetic design, and by contributing to solutions to climate change, global health and food security challenges. As institutions, they have long been incubators for cutting-edge research in biology while simultaneously providing core infrastructure for research on present and future societal needs. Here we explore how the intersection between pressing issues in environmental and human health and rapid technological innovation have reinforced the relevance of museum collections. We do this by providing examples as food for thought for both the broader academic community and museum scientists on the evolving role of museums. We also identify challenges to the realization of the full potential of natural history collections and the Global Museum to science and society and discuss the critical need to grow these collections. We then focus on mapping and modelling of museum data (including place-based approaches and discovery), and explore the main projects, platforms and databases enabling this growth. Finally, we aim to improve relevant protocols for the long-term storage of specimens and tissues, ensuring proper connection with tomorrow’s technologies and hence further increasing the relevance of natural history museums.
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Affiliation(s)
- Freek T Bakker
- Biosystematics Group, Wageningen University & Research, Wageningen, The Netherlands
| | | | - Julia A Clarke
- Jackson School of Geosciences, University of Texas at Austin, Austin, TX, United States of America
| | - Joseph A Cook
- Museum of Southwestern Biology, Department of Biology, University of New Mexico, Albuquerque, NM, United States of America
| | - Scott V Edwards
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, United States of America.,Gothenburg Centre for Advanced Studies in Science and Technology, Chalmers University of Technology and University of Gothenburg, Göteborg, Sweden
| | - Per G P Ericson
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
| | - Søren Faurby
- Department of Biological and Environmental Sciences, Gothenburg Global Biodiversity Centre, University of Gothenburg, Göteborg, Sweden
| | - Nuno Ferrand
- Museu de História Natural e da Ciência, Universidade do Porto, Porto, Portugal
| | - Magnus Gelang
- Department of Zoology, Gothenburg Natural History Museum, Göteborg, Sweden.,Gothenburg Global Biodiversity Centre, University of Gothenburg, Göteborg, Sweden
| | - Rosemary G Gillespie
- Essig Museum of Entomology, Department of Environmental Science, Policy and Management, University of California, Berkeley, Berkeley, CA, United States of America
| | - Martin Irestedt
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
| | - Kennet Lundin
- Department of Zoology, Gothenburg Natural History Museum, Göteborg, Sweden.,Gothenburg Global Biodiversity Centre, University of Gothenburg, Göteborg, Sweden
| | - Ellen Larsson
- Department of Biological and Environmental Sciences, Gothenburg Global Biodiversity Centre, University of Gothenburg, Göteborg, Sweden.,Gothenburg Global Biodiversity Centre, University of Gothenburg, Göteborg, Sweden
| | - Pável Matos-Maraví
- Biology Centre of the Czech Academy of Sciences, Institute of Entomology, České Budějovice, Czechia
| | - Johannes Müller
- Leibniz-Institut für Evolutions- und Biodiversitätsforschung, Museum für Naturkunde, Berlin, Germany
| | - Ted von Proschwitz
- Department of Zoology, Gothenburg Natural History Museum, Göteborg, Sweden.,Gothenburg Global Biodiversity Centre, University of Gothenburg, Göteborg, Sweden
| | - George K Roderick
- Essig Museum of Entomology, Department of Environmental Science, Policy and Management, University of California, Berkeley, Berkeley, CA, United States of America
| | - Alexander Schliep
- Department of Computer Science and Engineering, University of Gothenburg, Göteborg, Sweden
| | | | - John Wiedenhoeft
- Department of Computer Science and Engineering, University of Gothenburg, Göteborg, Sweden
| | - Mari Källersjö
- Gothenburg Global Biodiversity Centre, University of Gothenburg, Göteborg, Sweden.,Gothenburg Botanical Garden, Göteborg, Sweden
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4
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Wiedenhoeft J, Cagan A, Kozhemyakina R, Gulevich R, Schliep A. Bayesian localization of CNV candidates in WGS data within minutes. Algorithms Mol Biol 2019; 14:20. [PMID: 31572486 PMCID: PMC6757390 DOI: 10.1186/s13015-019-0154-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 08/08/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Full Bayesian inference for detecting copy number variants (CNV) from whole-genome sequencing (WGS) data is still largely infeasible due to computational demands. A recently introduced approach to perform Forward-Backward Gibbs sampling using dynamic Haar wavelet compression has alleviated issues of convergence and, to some extent, speed. Yet, the problem remains challenging in practice. RESULTS In this paper, we propose an improved algorithmic framework for this approach. We provide new space-efficient data structures to query sufficient statistics in logarithmic time, based on a linear-time, in-place transform of the data, which also improves on the compression ratio. We also propose a new approach to efficiently store and update marginal state counts obtained from the Gibbs sampler. CONCLUSIONS Using this approach, we discover several CNV candidates in two rat populations divergently selected for tame and aggressive behavior, consistent with earlier results concerning the domestication syndrome as well as experimental observations. Computationally, we observe a 29.5-fold decrease in memory, an average 5.8-fold speedup, as well as a 191-fold decrease in minor page faults. We also observe that metrics varied greatly in the old implementation, but not the new one. We conjecture that this is due to the better compression scheme. The fully Bayesian segmentation of the entire WGS data set required 3.5 min and 1.24 GB of memory, and can hence be performed on a commodity laptop.
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5
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Bravo GA, Antonelli A, Bacon CD, Bartoszek K, Blom MPK, Huynh S, Jones G, Knowles LL, Lamichhaney S, Marcussen T, Morlon H, Nakhleh LK, Oxelman B, Pfeil B, Schliep A, Wahlberg N, Werneck FP, Wiedenhoeft J, Willows-Munro S, Edwards SV. Embracing heterogeneity: coalescing the Tree of Life and the future of phylogenomics. PeerJ 2019; 7:e6399. [PMID: 30783571 PMCID: PMC6378093 DOI: 10.7717/peerj.6399] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 01/07/2019] [Indexed: 12/23/2022] Open
Abstract
Building the Tree of Life (ToL) is a major challenge of modern biology, requiring advances in cyberinfrastructure, data collection, theory, and more. Here, we argue that phylogenomics stands to benefit by embracing the many heterogeneous genomic signals emerging from the first decade of large-scale phylogenetic analysis spawned by high-throughput sequencing (HTS). Such signals include those most commonly encountered in phylogenomic datasets, such as incomplete lineage sorting, but also those reticulate processes emerging with greater frequency, such as recombination and introgression. Here we focus specifically on how phylogenetic methods can accommodate the heterogeneity incurred by such population genetic processes; we do not discuss phylogenetic methods that ignore such processes, such as concatenation or supermatrix approaches or supertrees. We suggest that methods of data acquisition and the types of markers used in phylogenomics will remain restricted until a posteriori methods of marker choice are made possible with routine whole-genome sequencing of taxa of interest. We discuss limitations and potential extensions of a model supporting innovation in phylogenomics today, the multispecies coalescent model (MSC). Macroevolutionary models that use phylogenies, such as character mapping, often ignore the heterogeneity on which building phylogenies increasingly rely and suggest that assimilating such heterogeneity is an important goal moving forward. Finally, we argue that an integrative cyberinfrastructure linking all steps of the process of building the ToL, from specimen acquisition in the field to publication and tracking of phylogenomic data, as well as a culture that values contributors at each step, are essential for progress.
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Affiliation(s)
- Gustavo A. Bravo
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA
| | - Alexandre Antonelli
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA
- Gothenburg Global Biodiversity Centre, Göteborg, Sweden
- Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden
- Gothenburg Botanical Garden, Göteborg, Sweden
| | - Christine D. Bacon
- Gothenburg Global Biodiversity Centre, Göteborg, Sweden
- Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden
| | - Krzysztof Bartoszek
- Department of Computer and Information Science, Linköping University, Linköping, Sweden
| | - Mozes P. K. Blom
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
| | - Stella Huynh
- Institut de Biologie, Université de Neuchâtel, Neuchâtel, Switzerland
| | - Graham Jones
- Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden
| | - L. Lacey Knowles
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA
| | - Sangeet Lamichhaney
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA
| | - Thomas Marcussen
- Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway
| | - Hélène Morlon
- Institut de Biologie, Ecole Normale Supérieure de Paris, Paris, France
| | - Luay K. Nakhleh
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Bengt Oxelman
- Gothenburg Global Biodiversity Centre, Göteborg, Sweden
- Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden
| | - Bernard Pfeil
- Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden
| | - Alexander Schliep
- Department of Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg, Göteborg, Sweden
| | | | - Fernanda P. Werneck
- Coordenação de Biodiversidade, Programa de Coleções Científicas Biológicas, Instituto Nacional de Pesquisa da Amazônia, Manaus, AM, Brazil
| | - John Wiedenhoeft
- Department of Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg, Göteborg, Sweden
- Department of Computer Science, Rutgers University, Piscataway, NJ, USA
| | - Sandi Willows-Munro
- School of Life Sciences, University of Kwazulu-Natal, Pietermaritzburg, South Africa
| | - Scott V. Edwards
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA
- Gothenburg Centre for Advanced Studies in Science and Technology, Chalmers University of Technology and University of Gothenburg, Göteborg, Sweden
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Abstract
CNV detection requires a high-quality segmentation of genomic data. In many WGS experiments, sample and control are sequenced together in a multiplexed fashion using DNA barcoding for economic reasons. Using the differential read depth of these two conditions cancels out systematic additive errors. Due to this detrending, the resulting data is appropriate for inference using a hidden Markov model (HMM), arguably one of the principal models for labeled segmentation. However, while the usual frequentist approaches such as Baum-Welch are problematic for several reasons, they are often preferred to Bayesian HMM inference, which normally requires prohibitively long running times and exceeds a typical user's computational resources on a genome scale data. HaMMLET solves this problem using a dynamic wavelet compression scheme, which makes Bayesian segmentation of WGS data feasible on standard consumer hardware.
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Affiliation(s)
- John Wiedenhoeft
- Chalmers University of Technology, Gothenburg, Sweden.
- Rutgers University, New Brunswick, NJ, USA.
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7
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Abstract
Motivation: Mapping billions of reads from next generation sequencing experiments to reference genomes is a crucial task, which can require hundreds of hours of running time on a single CPU even for the fastest known implementations. Traditional approaches have difficulties dealing with matches of large edit distance, particularly in the presence of frequent or large insertions and deletions (indels). This is a serious obstacle both in determining the spectrum and abundance of genetic variations and in personal genomics. Results: For the first time, we adopt the approximate string matching paradigm of geometric embedding to read mapping, thus rephrasing it to nearest neighbor queries in a q-gram frequency vector space. Using the L1 distance between frequency vectors has the benefit of providing lower bounds for an edit distance with affine gap costs. Using a cache-oblivious kd-tree, we realize running times, which match the state-of-the-art. Additionally, running time and memory requirements are about constant for read lengths between 100 and 1000 bp. We provide a first proof-of-concept that geometric embedding is a promising paradigm for read mapping and that L1 distance might serve to detect structural variations. TreQ, our initial implementation of that concept, performs more accurate than many popular read mappers over a wide range of structural variants. Availability and implementation: TreQ will be released under the GNU Public License (GPL), and precomputed genome indices will be provided for download at http://treq.sf.net. Contact:pavelm@cs.rutgers.edu Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Md Pavel Mahmud
- Department of Computer Science, Rutgers University, New Jersey, USA.
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8
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Günzel D, Zakrzewski SS, Schmid T, Pangalos M, Wiedenhoeft J, Blasse C, Ozboda C, Krug SM. From TER to trans- and paracellular resistance: lessons from impedance spectroscopy. Ann N Y Acad Sci 2012; 1257:142-51. [DOI: 10.1111/j.1749-6632.2012.06540.x] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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Wiedenhoeft J, Krause R, Eulenstein O. The plexus model for the inference of ancestral multidomain proteins. IEEE/ACM Trans Comput Biol Bioinform 2011; 8:890-901. [PMID: 21282868 DOI: 10.1109/tcbb.2011.22] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Interactions of protein domains control essential cellular processes. Thus, inferring the evolutionary histories of multidomain proteins in the context of their families can provide rewarding insights into protein function. However, methods to infer these histories are challenged by the complexity of macroevolutionary events. Here, we address this challenge by describing an algorithm that computes a novel network-like structure, called plexus, which represents the evolution of domains and their combinations. Finally, we demonstrate the performance of this algorithm with empirical data sets.
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Affiliation(s)
- John Wiedenhoeft
- Max Planck Institute for Molecular Genetics, Department Vingron-Computational Molecular Biology, D-14195 Berlin.
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10
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Homilius M, Wiedenhoeft J, Thieme S, Standfuß C, Kel I, Krause R. Cocos: Constructing multi-domain protein phylogenies. PLoS Curr 2011; 3:RRN1240. [PMID: 21686311 PMCID: PMC3110499 DOI: 10.1371/currents.rrn1240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 06/08/2011] [Indexed: 12/05/2022]
Abstract
Phylogenies of multi-domain proteins have to incorporate macro-evolutionary events, which dramatically increases the complexity of their construction. We present an application to infer ancestral multi-domain proteins given a species tree and domain phylogenies. As the individual domain phylogenies are often incongruent, we provide diagnostics for the identification and reconciliation of implausible topologies. We implement and extend a suggested algorithmic approach by Behzadi and Vingron (2006).
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Affiliation(s)
- Max Homilius
- Dept. of Computer Science, Free University of Berlin, Germany; Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany and Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics Berlin, Free University of Berlin, Germany
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