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      The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area

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          Abstract

          Structural brain changes along the lineage leading to modern Homo sapiens contributed to our distinctive cognitive and social abilities. However, the evolutionarily relevant molecular variants impacting key aspects of neuroanatomy are largely unknown. Here, we integrate evolutionary annotations of the genome at diverse timescales with common variant associations from large-scale neuroimaging genetic screens. We find that alleles with evidence of recent positive polygenic selection over the past 2000–3000 years are associated with increased surface area (SA) of the entire cortex, as well as specific regions, including those involved in spoken language and visual processing. Therefore, polygenic selective pressures impact the structure of specific cortical areas even over relatively recent timescales. Moreover, common sequence variation within human gained enhancers active in the prenatal cortex is associated with postnatal global SA. We show that such variation modulates the function of a regulatory element of the developmentally relevant transcription factor HEY2 in human neural progenitor cells and is associated with structural changes in the inferior frontal cortex. These results indicate that non-coding genomic regions active during prenatal cortical development are involved in the evolution of human brain structure and identify novel regulatory elements and genes impacting modern human brain structure.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            A global reference for human genetic variation

            The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
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              Second-generation PLINK: rising to the challenge of larger and richer datasets

              PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for even faster and more scalable implementations of key functions. In addition, GWAS and population-genetic data now frequently contain probabilistic calls, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1's primary data format. To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, O(sqrt(n))-time/constant-space Hardy-Weinberg equilibrium and Fisher's exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. This will be followed by PLINK 2.0, which will introduce (a) a new data format capable of efficiently representing probabilities, phase, and multiallelic variants, and (b) extensions of many functions to account for the new types of information. The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.
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                Author and article information

                Contributors
                Journal
                Cereb Cortex
                Cereb Cortex
                cercor
                Cerebral Cortex (New York, NY)
                Oxford University Press
                1047-3211
                1460-2199
                April 2021
                09 December 2020
                09 December 2020
                : 31
                : 4
                : 1873-1887
                Affiliations
                Language and Genetics Department , Max Planck Institute for Psycholinguistics , Nijmegen, 6500 AH, Netherlands
                Mark and Mary Stevens Neuroimaging and Informatics Institute , Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292, USA
                Department of Medicine , Section of Genetic Medicine & Institute for Genomics and Systems Biology , University of Chicago, Chicago, IL 60637, USA
                Computational Sciences , Janssen Pharmaceuticals , Spring House, PA 19477, USA
                Department of Genetics , University of North Carolina , Chapel Hill, NC 27599, USA
                UNC Neuroscience Center , University of North Carolina, Chapel Hill, NC 27599, USA
                Psychiatric Genetics , QIMR Berghofer Medical Research Institute , Brisbane, QLD 4006, Australia
                Mark and Mary Stevens Neuroimaging and Informatics Institute , Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292, USA
                Psychiatric Genetics , QIMR Berghofer Medical Research Institute , Brisbane, QLD 4006, Australia
                Psychiatric Genetics , QIMR Berghofer Medical Research Institute , Brisbane, QLD 4006, Australia
                Radboud University Medical Center , 6525 XZ Nijmegen, Netherlands
                Genentech, Inc. , South San Francisco, CA 94080, USA
                Psychiatric Genetics , QIMR Berghofer Medical Research Institute , Brisbane, QLD 4006, Australia
                Department of Genetics , University of North Carolina , Chapel Hill, NC 27599, USA
                UNC Neuroscience Center , University of North Carolina, Chapel Hill, NC 27599, USA
                Department of Genetics , University of North Carolina , Chapel Hill, NC 27599, USA
                UNC Neuroscience Center , University of North Carolina, Chapel Hill, NC 27599, USA
                Mark and Mary Stevens Neuroimaging and Informatics Institute , Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292, USA
                Psychiatric Genetics , QIMR Berghofer Medical Research Institute , Brisbane, QLD 4006, Australia
                Department of Psychiatry and Human Behavior , University of California , Irvine, CA 92697, USA
                Department of Medicine , Section of Genetic Medicine & Institute for Genomics and Systems Biology , University of Chicago, Chicago, IL 60637, USA
                Department of Pharmacology , Center for Genetic Medicine , Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
                Department of Medicine , Division of Medical Genetics, Vanderbilt University Medical Center , Nashville, TN 37232, USA
                Department of Psychiatry and Behavioral Sciences , Vanderbilt University Medical Center , Nashville, TN 37232, USA
                Vanderbilt University Medical Center , Vanderbilt Genetics Institute, Nashville, TN 37232, USA
                Language and Genetics Department , Max Planck Institute for Psycholinguistics , Nijmegen, 6500 AH, Netherlands
                Donders Institute for Brain , Cognition and Behaviour, Radboud University, Nijmegen, 6500 HB, Netherlands
                Department of Genetics , University of North Carolina , Chapel Hill, NC 27599, USA
                UNC Neuroscience Center , University of North Carolina, Chapel Hill, NC 27599, USA
                Author notes
                Address correspondence to Jason L. Stein, UNC Neuroscience Center, University of North Carolina, 7202A Mary Ellen Jones Bldg, Chapel Hill, NC 27599-7250, USA. Email: jason_stein@ 123456med.unc.edu ; Simon E. Fisher, Language and Genetics Department, Max Planck Institute for Psycholinguistics, P.O. Box 310, Nijmegen, 6500 AH, The Netherlands. Email: simon.fisher@ 123456mpi.nl .

                Joint senior authors

                Author information
                https://orcid.org/0000-0002-9107-8190
                https://orcid.org/0000-0002-9004-364X
                https://orcid.org/0000-0002-3132-1996
                https://orcid.org/0000-0003-4829-0513
                Article
                bhaa327
                10.1093/cercor/bhaa327
                7945014
                33290510
                d9080734-30f0-49b2-855b-88538980c29a
                © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 March 2020
                : 9 October 2020
                : 9 October 2020
                Page count
                Pages: 15
                Funding
                Funded by: Foundation of Hope;
                Funded by: Brain Research Foundation, DOI 10.13039/100000882;
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: R01 MH118349
                Award ID: R00 MH102357
                Award ID: U54 EB020403
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Award ID: ACI-16449916
                Funded by: Max Planck Society, DOI 10.13039/501100004189;
                Award ID: APP1173025
                Categories
                Original Article
                AcademicSubjects/MED00310
                AcademicSubjects/MED00385
                AcademicSubjects/SCI01870

                Neurology
                cortical surface area,genome-wide association study,human gained enhancers,polygenic selection

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