1
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Jeong H, Dishuck PC, Yoo D, Harvey WT, Munson KM, Lewis AP, Kordosky J, Garcia GH, Yilmaz F, Hallast P, Lee C, Pastinen T, Eichler EE. Structural polymorphism and diversity of human segmental duplications. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.04.597452. [PMID: 38895457 PMCID: PMC11185583 DOI: 10.1101/2024.06.04.597452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Segmental duplications (SDs) contribute significantly to human disease, evolution, and diversity yet have been difficult to resolve at the sequence level. We present a population genetics survey of SDs by analyzing 170 human genome assemblies where the majority of SDs are fully resolved using long-read sequence assembly. Excluding the acrocentric short arms, we identify 173.2 Mbp of duplicated sequence (47.4 Mbp not present in the telomere-to-telomere reference) distinguishing fixed from structurally polymorphic events. We find that intrachromosomal SDs are among the most variable with rare events mapping near their progenitor sequences. African genomes harbor significantly more intrachromosomal SDs and are more likely to have recently duplicated gene families with higher copy number when compared to non-African samples. A comparison to a resource of 563 million full-length Iso-Seq reads identifies 201 novel, potentially protein-coding genes corresponding to these copy number polymorphic SDs.
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Affiliation(s)
- Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Altos Labs, San Diego, CA, USA
| | - Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William T. Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M. Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P. Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jennifer Kordosky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Gage H. Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Tomi Pastinen
- Children’s Mercy Hospital and University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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2
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Neale N, Lona-Durazo F, Ryten M, Gagliano Taliun SA. Leveraging sex-genetic interactions to understand brain disorders: recent advances and current gaps. Brain Commun 2024; 6:fcae192. [PMID: 38894947 PMCID: PMC11184352 DOI: 10.1093/braincomms/fcae192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 04/11/2024] [Accepted: 05/30/2024] [Indexed: 06/21/2024] Open
Abstract
It is established that there are sex differences in terms of prevalence, age of onset, clinical manifestations, and response to treatment for a variety of brain disorders, including neurodevelopmental, psychiatric, and neurodegenerative disorders. Cohorts of increasing sample sizes with diverse data types collected, including genetic, transcriptomic and/or phenotypic data, are providing the building blocks to permit analytical designs to test for sex-biased genetic variant-trait associations, and for sex-biased transcriptional regulation. Such molecular assessments can contribute to our understanding of the manifested phenotypic differences between the sexes for brain disorders, offering the future possibility of delivering personalized therapy for females and males. With the intention of raising the profile of this field as a research priority, this review aims to shed light on the importance of investigating sex-genetic interactions for brain disorders, focusing on two areas: (i) variant-trait associations and (ii) transcriptomics (i.e. gene expression, transcript usage and regulation). We specifically discuss recent advances in the field, current gaps and provide considerations for future studies.
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Affiliation(s)
- Nikita Neale
- Faculty of Medicine, Université de Montréal, Québec, H3C 3J7 Canada
| | - Frida Lona-Durazo
- Faculty of Medicine, Université de Montréal, Québec, H3C 3J7 Canada
- Research Centre, Montreal Heart Institute, Québec, H1T 1C8 Canada
| | - Mina Ryten
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, WC1N 1EH London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, 20815 MD, USA
- NIHR Great Ormond Street Hospital Biomedical Research Centre, Great Ormond Street Institute of Child Health, Bloomsbury, WC1N 1EH London, UK
| | - Sarah A Gagliano Taliun
- Research Centre, Montreal Heart Institute, Québec, H1T 1C8 Canada
- Department of Medicine & Department of Neurosciences, Faculty of Medicine, Université de Montréal, Québec, H3C 3J7 Canada
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3
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Liu X, Koyama S, Tomizuka K, Takata S, Ishikawa Y, Ito S, Kosugi S, Suzuki K, Hikino K, Koido M, Koike Y, Horikoshi M, Gakuhari T, Ikegawa S, Matsuda K, Momozawa Y, Ito K, Kamatani Y, Terao C. Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing. SCIENCE ADVANCES 2024; 10:eadi8419. [PMID: 38630824 PMCID: PMC11023554 DOI: 10.1126/sciadv.adi8419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 03/07/2024] [Indexed: 04/19/2024]
Abstract
We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.
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Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Sadaaki Takata
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Faculty of Medicine, Shimane University, Izumo, Japan
| | - Shunichi Kosugi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masaru Koido
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinao Koike
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Takashi Gakuhari
- Institute for the Study of Ancient Civilizations and Cultural Resources, College of Human and Social Sciences, Kanazawa University, Kanazawa, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
| | - Kochi Matsuda
- Laboratory of Genome Technology, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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4
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Lawrence ES, Gu W, Bohlender RJ, Anza-Ramirez C, Cole AM, Yu JJ, Hu H, Heinrich EC, O’Brien KA, Vasquez CA, Cowan QT, Bruck PT, Mercader K, Alotaibi M, Long T, Hall JE, Moya EA, Bauk MA, Reeves JJ, Kong MC, Salem RM, Vizcardo-Galindo G, Macarlupu JL, Figueroa-Mujíca R, Bermudez D, Corante N, Gaio E, Fox KP, Salomaa V, Havulinna AS, Murray AJ, Malhotra A, Powel FL, Jain M, Komor AC, Cavalleri GL, Huff CD, Villafuerte FC, Simonson TS. Functional EPAS1/ HIF2A missense variant is associated with hematocrit in Andean highlanders. SCIENCE ADVANCES 2024; 10:eadj5661. [PMID: 38335297 PMCID: PMC10857371 DOI: 10.1126/sciadv.adj5661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 01/10/2024] [Indexed: 02/12/2024]
Abstract
Hypoxia-inducible factor pathway genes are linked to adaptation in both human and nonhuman highland species. EPAS1, a notable target of hypoxia adaptation, is associated with relatively lower hemoglobin concentration in Tibetans. We provide evidence for an association between an adaptive EPAS1 variant (rs570553380) and the same phenotype of relatively low hematocrit in Andean highlanders. This Andean-specific missense variant is present at a modest frequency in Andeans and absent in other human populations and vertebrate species except the coelacanth. CRISPR-base-edited human cells with this variant exhibit shifts in hypoxia-regulated gene expression, while metabolomic analyses reveal both genotype and phenotype associations and validation in a lowland population. Although this genocopy of relatively lower hematocrit in Andean highlanders parallels well-replicated findings in Tibetans, it likely involves distinct pathway responses based on a protein-coding versus noncoding variants, respectively. These findings illuminate how unique variants at EPAS1 contribute to the same phenotype in Tibetans and a subset of Andean highlanders despite distinct evolutionary trajectories.
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Affiliation(s)
- Elijah S. Lawrence
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Wanjun Gu
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Ryan J. Bohlender
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Cecilia Anza-Ramirez
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Amy M. Cole
- School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - James J. Yu
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Hao Hu
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Erica C. Heinrich
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
- Division of Biomedical Sciences, School of Medicine, University of California, Riverside, Riverside, CA, USA
| | - Katie A. O’Brien
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EG, UK
| | - Carlos A. Vasquez
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA
| | - Quinn T. Cowan
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA
| | - Patrick T. Bruck
- Department of Anthropology and Global Health, University of California, San Diego, La Jolla, CA, USA
| | - Kysha Mercader
- Department of Medicine and Pharmacology, University of California, San Diego, La Jolla, CA, USA
| | - Mona Alotaibi
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Medicine and Pharmacology, University of California, San Diego, La Jolla, CA, USA
| | - Tao Long
- Department of Medicine and Pharmacology, University of California, San Diego, La Jolla, CA, USA
- Sapient Bioanalytics, LLC, San Diego, CA, USA
| | - James E. Hall
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Esteban A. Moya
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Marco A. Bauk
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jennifer J. Reeves
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Mitchell C. Kong
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Rany M. Salem
- Herbert Wertheim School of Public Health and Longevity Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Gustavo Vizcardo-Galindo
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Jose-Luis Macarlupu
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Rómulo Figueroa-Mujíca
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Daniela Bermudez
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Noemi Corante
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Eduardo Gaio
- Laboratório de Fisiologia Respiratória, Faculdade de Medicina, Universidade de Brasília, Brasília, Brazil
| | - Keolu P. Fox
- Department of Anthropology and Global Health, University of California, San Diego, La Jolla, CA, USA
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Aki S. Havulinna
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM-HiLIFE), Helsinki, Finland
| | - Andrew J. Murray
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EG, UK
| | - Atul Malhotra
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Frank L. Powel
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Mohit Jain
- Department of Medicine and Pharmacology, University of California, San Diego, La Jolla, CA, USA
- Sapient Bioanalytics, LLC, San Diego, CA, USA
| | - Alexis C. Komor
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA
| | - Gianpiero L. Cavalleri
- School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Chad D. Huff
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Francisco C. Villafuerte
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Tatum S. Simonson
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
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5
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Hayeck TJ, Li Y, Mosbruger TL, Bradfield JP, Gleason AG, Damianos G, Shaw GTW, Duke JL, Conlin LK, Turner TN, Fernández-Viña MA, Sarmady M, Monos DS. The Impact of Patterns in Linkage Disequilibrium and Sequencing Quality on the Imprint of Balancing Selection. Genome Biol Evol 2024; 16:evae009. [PMID: 38302106 PMCID: PMC10853003 DOI: 10.1093/gbe/evae009] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 01/08/2024] [Accepted: 01/12/2024] [Indexed: 02/03/2024] Open
Abstract
Regions under balancing selection are characterized by dense polymorphisms and multiple persistent haplotypes, along with other sequence complexities. Successful identification of these patterns depends on both the statistical approach and the quality of sequencing. To address this challenge, at first, a new statistical method called LD-ABF was developed, employing efficient Bayesian techniques to effectively test for balancing selection. LD-ABF demonstrated the most robust detection of selection in a variety of simulation scenarios, compared against a range of existing tests/tools (Tajima's D, HKA, Dng, BetaScan, and BalLerMix). Furthermore, the impact of the quality of sequencing on detection of balancing selection was explored, as well, using: (i) SNP genotyping and exome data, (ii) targeted high-resolution HLA genotyping (IHIW), and (iii) whole-genome long-read sequencing data (Pangenome). In the analysis of SNP genotyping and exome data, we identified known targets and 38 new selection signatures in genes not previously linked to balancing selection. To further investigate the impact of sequencing quality on detection of balancing selection, a detailed investigation of the MHC was performed with high-resolution HLA typing data. Higher quality sequencing revealed the HLA-DQ genes consistently demonstrated strong selection signatures otherwise not observed from the sparser SNP array and exome data. The HLA-DQ selection signature was also replicated in the Pangenome samples using considerably less samples but, with high-quality long-read sequence data. The improved statistical method, coupled with higher quality sequencing, leads to more consistent identification of selection and enhanced localization of variants under selection, particularly in complex regions.
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Affiliation(s)
- Tristan J Hayeck
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yang Li
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy L Mosbruger
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Adam G Gleason
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - George Damianos
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Grace Tzun-Wen Shaw
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jamie L Duke
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Laura K Conlin
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Tychele N Turner
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Marcelo A Fernández-Viña
- Department of Pathology, Stanford University School of Medicine, Palo Alto, CA, USA
- Histocompatibility and Immunogenetics Laboratory, Stanford Blood Center, Palo Alto, CA, USA
| | - Mahdi Sarmady
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dimitri S Monos
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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6
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Pettie KP, Mumbach M, Lea AJ, Ayroles J, Chang HY, Kasowski M, Fraser HB. Chromatin activity identifies differential gene regulation across human ancestries. Genome Biol 2024; 25:21. [PMID: 38225662 PMCID: PMC10789071 DOI: 10.1186/s13059-024-03165-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 01/04/2024] [Indexed: 01/17/2024] Open
Abstract
BACKGROUND Current evidence suggests that cis-regulatory elements controlling gene expression may be the predominant target of natural selection in humans and other species. Detecting selection acting on these elements is critical to understanding evolution but remains challenging because we do not know which mutations will affect gene regulation. RESULTS To address this, we devise an approach to search for lineage-specific selection on three critical steps in transcriptional regulation: chromatin activity, transcription factor binding, and chromosomal looping. Applying this approach to lymphoblastoid cells from 831 individuals of either European or African descent, we find strong signals of differential chromatin activity linked to gene expression differences between ancestries in numerous contexts, but no evidence of functional differences in chromosomal looping. Moreover, we show that enhancers rather than promoters display the strongest signs of selection associated with sites of differential transcription factor binding. CONCLUSIONS Overall, our study indicates that some cis-regulatory adaptation may be more easily detected at the level of chromatin than DNA sequence. This work provides a vast resource of genomic interaction data from diverse human populations and establishes a novel selection test that will benefit future study of regulatory evolution in humans and other species.
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Affiliation(s)
- Kade P Pettie
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Maxwell Mumbach
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Amanda J Lea
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
| | - Julien Ayroles
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Maya Kasowski
- Sean N. Parker Center for Allergy and Asthma Research, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Hunter B Fraser
- Department of Biology, Stanford University, Stanford, CA, USA.
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7
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Janivara R, Hazra U, Pfennig A, Harlemon M, Kim MS, Eaaswarkhanth M, Chen WC, Ogunbiyi A, Kachambwa P, Petersen LN, Jalloh M, Mensah JE, Adjei AA, Adusei B, Joffe M, Gueye SM, Aisuodionoe-Shadrach OI, Fernandez PW, Rohan TE, Andrews C, Rebbeck TR, Adebiyi AO, Agalliu I, Lachance J. Uncovering the genetic architecture and evolutionary roots of androgenetic alopecia in African men. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.12.575396. [PMID: 38293167 PMCID: PMC10827056 DOI: 10.1101/2024.01.12.575396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Androgenetic alopecia is a highly heritable trait. However, much of our understanding about the genetics of male pattern baldness comes from individuals of European descent. Here, we examined a novel dataset comprising 2,136 men from Ghana, Nigeria, Senegal, and South Africa that were genotyped using a custom array. We first tested how genetic predictions of baldness generalize from Europe to Africa, finding that polygenic scores from European GWAS yielded AUC statistics that ranged from 0.513 to 0.546, indicating that genetic predictions of baldness in African populations performed notably worse than in European populations. Subsequently, we conducted the first African GWAS of androgenetic alopecia, focusing on self-reported baldness patterns at age 45. After correcting for present age, population structure, and study site, we identified 266 moderately significant associations, 51 of which were independent (p-value < 10-5, r2 < 0.2). Most baldness associations were autosomal, and the X chromosomes does not appear to have a large impact on baldness in African men. Finally, we examined the evolutionary causes of continental differences in genetic architecture. Although Neanderthal alleles have previously been associated with skin and hair phenotypes, we did not find evidence that European-ascertained baldness hits were enriched for signatures of ancient introgression. Most loci that are associated with androgenetic alopecia are evolving neutrally. However, multiple baldness-associated SNPs near the EDA2R and AR genes have large allele frequency differences between continents. Collectively, our findings illustrate how evolutionary history contributes to the limited portability of genetic predictions across ancestries.
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Affiliation(s)
- Rohini Janivara
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Ujani Hazra
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Aaron Pfennig
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Maxine Harlemon
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
- Department of Biology, Morgan State University, Baltimore, Maryland, USA
| | - Michelle S Kim
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
- Department of Human Genetics University of Michigan, Ann Arbor, Michigan, USA
| | | | - Wenlong C Chen
- Strengthening Oncology Services Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- National Cancer Registry, National Institute for Communicable Diseases a Division of the National Health Laboratory Service, Johannesburg, South Africa
| | | | - Paidamoyo Kachambwa
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
- Mediclinic Precise Southern Africa, Cape Town, South Africa
| | - Lindsay N Petersen
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
- Mediclinic Precise Southern Africa, Cape Town, South Africa
| | - Mohamed Jalloh
- Université Cheikh Anta Diop de Dakar, Dakar, Senegal
- Université Iba Der Thiam de Thiès, Thiès, Senegal
| | - James E Mensah
- Korle-Bu Teaching Hospital and University of Ghana Medical School, Accra, Ghana
| | - Andrew A Adjei
- Department of Pathology, University of Ghana Medical School, Accra, Ghana
| | | | - Maureen Joffe
- Strengthening Oncology Services Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Oseremen I Aisuodionoe-Shadrach
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Centre, Abuja, Nigeria
| | - Pedro W Fernandez
- Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Thomas E Rohan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | | | - Timothy R Rebbeck
- Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | | | - Ilir Agalliu
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
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8
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Bai X, Bao Y, Bei S, Bu C, Cao R, Cao Y, Cen H, Chao J, Chen F, Chen H, Chen K, Chen M, Chen M, Chen M, Chen Q, Chen R, Chen S, Chen T, Chen X, Chen X, Cheng Y, Chu Y, Cui Q, Dong L, Du Z, Duan G, Fan S, Fan Z, Fang X, Fang Z, Feng Z, Fu S, Gao F, Gao G, Gao H, Gao W, Gao X, Gao X, Gao X, Gong J, Gong J, Gou Y, Gu S, Guo AY, Guo G, Guo X, Han C, Hao D, Hao L, He Q, He S, He S, Hu W, Huang K, Huang T, Huang X, Huang Y, Jia P, Jia Y, Jiang C, Jiang M, Jiang S, Jiang T, Jiang X, Jin E, Jin W, Kang H, Kang H, Kong D, Lan L, Lei W, Li CY, Li C, Li C, Li H, Li J, Li J, Li L, Li P, Li R, Li X, Li Y, Li Y, Li Z, Liao X, Lin S, Lin Y, Ling Y, Liu B, Liu CJ, Liu D, Liu GH, Liu L, Liu S, Liu W, Liu X, Liu X, Liu Y, Liu Y, Lu M, Lu T, Luo H, Luo H, Luo M, Luo S, Luo X, Ma L, Ma Y, Mai J, Meng J, Meng X, Meng Y, Meng Y, Miao W, Miao YR, Ni L, Nie Z, Niu G, Niu X, Niu Y, Pan R, Pan S, Peng D, Peng J, Qi J, Qi Y, Qian Q, Qin Y, Qu H, Ren J, Ren J, Sang Z, Shang K, Shen WK, Shen Y, Shi Y, Song S, Song T, Su T, Sun J, Sun Y, Sun Y, Sun Y, Tang B, Tang D, Tang Q, Tang Z, Tian D, Tian F, Tian W, Tian Z, Wang A, Wang G, Wang G, Wang J, Wang J, Wang P, Wang P, Wang W, Wang Y, Wang Y, Wang Y, Wang Y, Wang Z, Wei H, Wei Y, Wei Z, Wu D, Wu G, Wu S, Wu S, Wu W, Wu W, Wu Z, Xia Z, Xiao J, Xiao L, Xiao Y, Xie G, Xie GY, Xie J, Xie Y, Xiong J, Xiong Z, Xu D, Xu S, Xu T, Xu T, Xue Y, Xue Y, Yan C, Yang D, Yang F, Yang F, Yang H, Yang J, Yang K, Yang N, Yang QY, Yang S, Yang X, Yang X, Yang X, Yang YG, Ye W, Yu C, Yu F, Yu S, Yuan C, Yuan H, Zeng J, Zhai S, Zhang C, Zhang F, Zhang G, Zhang M, Zhang P, Zhang Q, Zhang R, Zhang S, Zhang W, Zhang W, Zhang W, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang YE, Zhang Y, Zhang Z, Zhang Z, Zhao D, Zhao F, Zhao G, Zhao M, Zhao W, Zhao W, Zhao X, Zhao Y, Zhao Y, Zhao Z, Zheng X, Zheng Y, Zhou C, Zhou H, Zhou X, Zhou X, Zhou Y, Zhou Y, Zhu J, Zhu L, Zhu R, Zhu T, Zong W, Zou D, Zuo Z. Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2024. Nucleic Acids Res 2024; 52:D18-D32. [PMID: 38018256 PMCID: PMC10767964 DOI: 10.1093/nar/gkad1078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/12/2023] [Accepted: 10/27/2023] [Indexed: 11/30/2023] Open
Abstract
The National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support the global academic and industrial communities. With the rapid accumulation of multi-omics data at an unprecedented pace, CNCB-NGDC continuously expands and updates core database resources through big data archiving, integrative analysis and value-added curation. Importantly, NGDC collaborates closely with major international databases and initiatives to ensure seamless data exchange and interoperability. Over the past year, significant efforts have been dedicated to integrating diverse omics data, synthesizing expanding knowledge, developing new resources, and upgrading major existing resources. Particularly, several database resources are newly developed for the biodiversity of protists (P10K), bacteria (NTM-DB, MPA) as well as plant (PPGR, SoyOmics, PlantPan) and disease/trait association (CROST, HervD Atlas, HALL, MACdb, BioKA, BioKA, RePoS, PGG.SV, NAFLDkb). All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.
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9
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Benjelloun B, Leempoel K, Boyer F, Stucki S, Streeter I, Orozco-terWengel P, Alberto FJ, Servin B, Biscarini F, Alberti A, Engelen S, Stella A, Colli L, Coissac E, Bruford MW, Ajmone-Marsan P, Negrini R, Clarke L, Flicek P, Chikhi A, Joost S, Taberlet P, Pompanon F. Multiple genomic solutions for local adaptation in two closely related species (sheep and goats) facing the same climatic constraints. Mol Ecol 2023:e17257. [PMID: 38149334 DOI: 10.1111/mec.17257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 08/18/2023] [Accepted: 12/05/2023] [Indexed: 12/28/2023]
Abstract
The question of how local adaptation takes place remains a fundamental question in evolutionary biology. The variation of allele frequencies in genes under selection over environmental gradients remains mainly theoretical and its empirical assessment would help understanding how adaptation happens over environmental clines. To bring new insights to this issue we set up a broad framework which aimed to compare the adaptive trajectories over environmental clines in two domesticated mammal species co-distributed in diversified landscapes. We sequenced the genomes of 160 sheep and 161 goats extensively managed along environmental gradients, including temperature, rainfall, seasonality and altitude, to identify genes and biological processes shaping local adaptation. Allele frequencies at putatively adaptive loci were rarely found to vary gradually along environmental gradients, but rather displayed a discontinuous shift at the extremities of environmental clines. Of the 430 candidate adaptive genes identified, only 6 were orthologous between sheep and goats and those responded differently to environmental pressures, suggesting different putative mechanisms involved in local adaptation in these two closely related species. Interestingly, the genomes of the 2 species were impacted differently by the environment, genes related to signatures of selection were most related to altitude, slope and rainfall seasonality for sheep, and summer temperature and spring rainfall for goats. The diversity of candidate adaptive pathways may result from a high number of biological functions involved in the adaptations to multiple eco-climatic gradients, and a differential role of climatic drivers on the two species, despite their co-distribution along the same environmental gradients. This study describes empirical examples of clinal variation in putatively adaptive alleles with different patterns in allele frequency distributions over continuous environmental gradients, thus showing the diversity of genetic responses in adaptive landscapes and opening new horizons for understanding genomics of adaptation in mammalian species and beyond.
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Affiliation(s)
- Badr Benjelloun
- Livestock Genomics Laboratory, Regional Center of Agricultural Research Tadla, National Institute of Agricultural Research INRA, Rabat, Morocco
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Kevin Leempoel
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Frédéric Boyer
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Sylvie Stucki
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Ian Streeter
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Pablo Orozco-terWengel
- School of Biosciences, Cardiff University, Wales, UK
- Sustainable Places Research Institute, Cardiff University, Cardiff, UK
| | - Florian J Alberto
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Bertrand Servin
- GenPhySE, Université de Toulouse, INRAE, INPT, ENVT, Castanet-Tolosan, France
| | - Filippo Biscarini
- Institute of Agricultural Biology and Biotechnology, Consiglio Nazionale delle Ricerche (CNR), Milan, Italy
| | - Adriana Alberti
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ. Evry, Université Paris-Saclay, Evry, France
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-Yvette, France
| | - Stefan Engelen
- Genoscope, Institut de biologie François-Jacob, Commissariat à l'Energie Atomique CEA, Université Paris-Saclay, Evry, France
| | - Alessandra Stella
- Institute of Agricultural Biology and Biotechnology, Consiglio Nazionale delle Ricerche (CNR), Milan, Italy
| | - Licia Colli
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, Piacenza, Italy
- BioDNA - Centro di Ricerca sulla Biodiversità e sul DNA Antico, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Eric Coissac
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Michael W Bruford
- School of Biosciences, Cardiff University, Wales, UK
- Sustainable Places Research Institute, Cardiff University, Cardiff, UK
| | - Paolo Ajmone-Marsan
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, Piacenza, Italy
- BioDNA - Centro di Ricerca sulla Biodiversità e sul DNA Antico, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Riccardo Negrini
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, Piacenza, Italy
- AIA Associazione Italiana Allevatori, Roma, Italy
| | - Laura Clarke
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Abdelkader Chikhi
- Livestock Genomics Laboratory, Regional Center of Agricultural Research Tadla, National Institute of Agricultural Research INRA, Rabat, Morocco
| | - Stéphane Joost
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Pierre Taberlet
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - François Pompanon
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
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10
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Liu X, Li Y. Genetic correlation for alcohol consumption between Europeans and East Asians. BMC Genomics 2023; 24:652. [PMID: 37904118 PMCID: PMC10614326 DOI: 10.1186/s12864-023-09766-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 10/25/2023] [Indexed: 11/01/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified many genetic variants associated with alcohol consumption in Europeans and East Asians, as well as other populations. However, the genetic homogeneity and heterogeneity between these populations have not been thoroughly investigated, despite evidence of varying effect sizes of variants between ethnicities and the presence of population-specific strong signals of selection on loci associated with alcohol consumption. In order to better understand the relationship between Europeans and East Asians in the genetic architecture of alcohol consumption, we compared their heritability and evaluated their genetic correlation using GWAS results from UK Biobank (UKB) and Biobank Japan (BBJ). We found that these two populations have low genetic correlation due to the large difference on chromosome 12. After excluding this chromosome, the genetic correlation was moderately high ([Formula: see text] = 0.544, p = 1.12e-4) and 44.31% of the genome-wide causal variants were inferred to be shared between Europeans and East Asians. Given those observations, we conducted a meta-analysis on UKB and BBJ and identified new signals, including the CADM2 gene on chromosome 3, which has been associated with various behavioral and metabolic traits. Overall, our findings suggest that the genetic architecture of alcohol consumption is largely shared between Europeans and East Asians, but there are exceptions such as the enrichment of heritability on chromosome 12 in East Asians.
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Affiliation(s)
- Xuan Liu
- Department of Neurology, The First People's Hospital of Wenling, Taizhou, China
| | - Yongang Li
- Department of Neurology, The First People's Hospital of Wenling, Taizhou, China.
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11
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Luo H, Zhang P, Zhang W, Zheng Y, Hao D, Shi Y, Niu Y, Song T, Li Y, Zhao S, Chen H, Xu T, He S. Recent positive selection signatures reveal phenotypic evolution in the Han Chinese population. Sci Bull (Beijing) 2023; 68:2391-2404. [PMID: 37661541 DOI: 10.1016/j.scib.2023.08.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/08/2023] [Accepted: 08/10/2023] [Indexed: 09/05/2023]
Abstract
Characterizing natural selection signatures and relationships with phenotype spectra is important for understanding human evolution and both biological and pathological mechanisms. Here, we identified 24 genetic loci under recent selection by analyzing rare singletons in 3946 high-depth whole-genome sequencing data of Han Chinese. The loci include immune-related gene regions (MHC cluster, IGH cluster, STING1, and PSG), alcohol metabolism-related gene regions (ADH1B, ALDH2, and ALDH3B2), and the olfactory perception gene OR4C16, in which the MHC cluster, ADH1B, and ALDH2 were also identified by TOPMed and WestLake Biobank. Among the signals, the IGH cluster is particularly interesting, in which the favored allele of variant 14_105737776_C_T (rs117518546, IgG1-G396R) promotes immune response, but also increases the risk of an autoimmune disease systemic lupus erythematosus (SLE). It is also surprising that our newly discovered ALDH3B2 evolved in the opposite direction to ALDH2 for alcohol metabolism. Besides monogenic traits, we found that multiple complex traits experienced polygenic adaptation. Particularly, multi-methods consistently revealed that lower blood pressure was favored in natural selection. Finally, we built a database named RePoS (recent positive selection, http://bigdata.ibp.ac.cn/RePoS/) to integrate and display multi-population selection signals. Our study extended our understanding of natural evolution and phenotype adaptation in Han Chinese as well as other populations.
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Affiliation(s)
- Huaxia Luo
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; Department of Pediatrics, Peking University First Hospital, Beijing 100034, China
| | - Peng Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Wanyu Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yu Zheng
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Di Hao
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yirong Shi
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiwei Niu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tingrui Song
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yanyan Li
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Shilei Zhao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; China National Center for Bioinformation, Beijing 100101, China
| | - Hua Chen
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; China National Center for Bioinformation, Beijing 100101, China.
| | - Tao Xu
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; Shandong First Medical University & Shandong Academy of Medical Sciences, Taian 271016, China.
| | - Shunmin He
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
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12
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Rebbeck T, Janivara R, Chen W, Hazra U, Baichoo S, Agalliu I, Kachambwa P, Simonti C, Brown L, Tambe S, Kim M, Harlemon M, Jalloh M, Muzondiwa D, Naidoo D, Ajayi O, Snyper N, Niang L, Diop H, Ndoye M, Mensah J, Darkwa-Abrahams A, Biritwum R, Adjei A, Adebiyi A, Shittu O, Ogunbiyi O, Adebayo S, Nwegbu M, Ajibola H, Oluwole O, Jamda M, Pentz A, Haiman C, Spies P, Van der Merwe A, Cook M, Chanock SJ, Berndt SI, Watya S, Lubwama A, Muchengeti M, Doherty S, Smyth N, Lounsbury D, Fortier B, Rohan T, Jacobson J, Neugut A, Hsing A, Gusev A, Aisuodionoe-Shadrach O, Joffe M, Adusei B, Gueye S, Fernandez P, McBride J, Andrews C, Petersen L, Lachance J. Heterogeneous genetic architectures and evolutionary genomics of prostate cancer in Sub-Saharan Africa. RESEARCH SQUARE 2023:rs.3.rs-3378303. [PMID: 37886553 PMCID: PMC10602179 DOI: 10.21203/rs.3.rs-3378303/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Men of African descent have the highest prostate cancer (CaP) incidence and mortality rates, yet the genetic basis of CaP in African men has been understudied. We used genomic data from 3,963 CaP cases and 3,509 controls recruited in Ghana, Nigeria, Senegal, South Africa, and Uganda, to infer ancestry-specific genetic architectures and fine-mapped disease associations. Fifteen independent associations at 8q24.21, 6q22.1, and 11q13.3 reached genome-wide significance, including four novel associations. Intriguingly, multiple lead SNPs are private alleles, a pattern arising from recent mutations and the out-of-Africa bottleneck. These African-specific alleles contribute to haplotypes with odds ratios above 2.4. We found that the genetic architecture of CaP differs across Africa, with effect size differences contributing more to this heterogeneity than allele frequency differences. Population genetic analyses reveal that African CaP associations are largely governed by neutral evolution. Collectively, our findings emphasize the utility of conducting genetic studies that use diverse populations.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Maxwell Nwegbu
- University of Abuja Teaching Hospital and Cancer Science Center
| | - Hafees Ajibola
- University of Abuja Teaching Hospital and Cancer Science Center
| | - Olabode Oluwole
- University of Abuja and University of Abuja Teaching Hospital
| | - Mustapha Jamda
- University of Abuja Teaching Hospital and Cancer Science Center
| | | | | | | | | | | | | | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda
| | | | | | - Mazvita Muchengeti
- National Institute for Communicable Diseases a Division of the National Health Laboratory Service
| | | | | | | | | | | | | | | | - Ann Hsing
- Stanford University School of Medicine
| | | | | | | | | | | | | | - Jo McBride
- Centre for Proteomic and Genomic Research
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13
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Salazar-Tortosa DF, Huang YF, Enard D. Assessing the Presence of Recent Adaptation in the Human Genome With Mixture Density Regression. Genome Biol Evol 2023; 15:evad170. [PMID: 37713622 PMCID: PMC10563788 DOI: 10.1093/gbe/evad170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 08/30/2023] [Accepted: 09/04/2023] [Indexed: 09/17/2023] Open
Abstract
How much genome differences between species reflect neutral or adaptive evolution is a central question in evolutionary genomics. In humans and other mammals, the presence of adaptive versus neutral genomic evolution has proven particularly difficult to quantify. The difficulty notably stems from the highly heterogeneous organization of mammalian genomes at multiple levels (functional sequence density, recombination, etc.) which complicates the interpretation and distinction of adaptive versus neutral evolution signals. In this study, we introduce mixture density regressions (MDRs) for the study of the determinants of recent adaptation in the human genome. MDRs provide a flexible regression model based on multiple Gaussian distributions. We use MDRs to model the association between recent selection signals and multiple genomic factors likely to affect the occurrence/detection of positive selection, if the latter was present in the first place to generate these associations. We find that an MDR model with two Gaussian distributions provides an excellent fit to the genome-wide distribution of a common sweep summary statistic (integrated haplotype score), with one of the two distributions likely enriched in positive selection. We further find several factors associated with signals of recent adaptation, including the recombination rate, the density of regulatory elements in immune cells, GC content, gene expression in immune cells, the density of mammal-wide conserved elements, and the distance to the nearest virus-interacting gene. These results support the presence of strong positive selection in recent human evolution and highlight MDRs as a powerful tool to make sense of signals of recent genomic adaptation.
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Affiliation(s)
- Diego F Salazar-Tortosa
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, USA
- Department of Ecology, University of Granada, Granada, Spain
| | - Yi-Fei Huang
- Department of Biology, Pennsylvania State University, University Park, State College, Pennsylvania, PA 16801, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, State College, Pennsylvania, PA 16801, USA
| | - David Enard
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, USA
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14
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Liu X, Matsunami M, Horikoshi M, Ito S, Ishikawa Y, Suzuki K, Momozawa Y, Niida S, Kimura R, Ozaki K, Maeda S, Imamura M, Terao C. Natural Selection Signatures in the Hondo and Ryukyu Japanese Subpopulations. Mol Biol Evol 2023; 40:msad231. [PMID: 37903429 PMCID: PMC10615566 DOI: 10.1093/molbev/msad231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 09/20/2023] [Accepted: 10/06/2023] [Indexed: 11/01/2023] Open
Abstract
Natural selection signatures across Japanese subpopulations are under-explored. Here we conducted genome-wide selection scans with 622,926 single nucleotide polymorphisms for 20,366 Japanese individuals, who were recruited from the main-islands of Japanese Archipelago (Hondo) and the Ryukyu Archipelago (Ryukyu), representing two major Japanese subpopulations. The integrated haplotype score (iHS) analysis identified several signals in one or both subpopulations. We found a novel candidate locus at IKZF2, especially in Ryukyu. Significant signals were observed in the major histocompatibility complex region in both subpopulations. The lead variants differed and demonstrated substantial allele frequency differences between Hondo and Ryukyu. The lead variant in Hondo tags HLA-A*33:03-C*14:03-B*44:03-DRB1*13:02-DQB1*06:04-DPB1*04:01, a haplotype specific to Japanese and Korean. While in Ryukyu, the lead variant tags DRB1*15:01-DQB1*06:02, which had been recognized as a genetic risk factor for narcolepsy. In contrast, it is reported to confer protective effects against type 1 diabetes and human T lymphotropic virus type 1-associated myelopathy/tropical spastic paraparesis. The FastSMC analysis identified 8 loci potentially affected by selection within the past 20-150 generations, including 2 novel candidate loci. The analysis also showed differences in selection patterns of ALDH2 between Hondo and Ryukyu, a gene recognized to be specifically targeted by selection in East Asian. In summary, our study provided insights into the selection signatures within the Japanese and nominated potential sources of selection pressure.
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Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Masatoshi Matsunami
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shumpei Niida
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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15
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Zhao H, Souilljee M, Pavlidis P, Alachiotis N. Genome-wide scans for selective sweeps using convolutional neural networks. Bioinformatics 2023; 39:i194-i203. [PMID: 37387128 DOI: 10.1093/bioinformatics/btad265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2023] Open
Abstract
MOTIVATION Recent methods for selective sweep detection cast the problem as a classification task and use summary statistics as features to capture region characteristics that are indicative of a selective sweep, thereby being sensitive to confounding factors. Furthermore, they are not designed to perform whole-genome scans or to estimate the extent of the genomic region that was affected by positive selection; both are required for identifying candidate genes and the time and strength of selection. RESULTS We present ASDEC (https://github.com/pephco/ASDEC), a neural-network-based framework that can scan whole genomes for selective sweeps. ASDEC achieves similar classification performance to other convolutional neural network-based classifiers that rely on summary statistics, but it is trained 10× faster and classifies genomic regions 5× faster by inferring region characteristics from the raw sequence data directly. Deploying ASDEC for genomic scans achieved up to 15.2× higher sensitivity, 19.4× higher success rates, and 4× higher detection accuracy than state-of-the-art methods. We used ASDEC to scan human chromosome 1 of the Yoruba population (1000Genomes project), identifying nine known candidate genes.
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Affiliation(s)
- Hanqing Zhao
- Faculty of EEMCS, University of Twente, Enschede, The Netherlands
| | | | - Pavlos Pavlidis
- Institute of Computer Science, Foundation for Research and Technology-Hellas, Heraklion, Greece
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16
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Souilmi Y, Tobler R, Johar A, Williams M, Grey ST, Schmidt J, Teixeira JC, Rohrlach A, Tuke J, Johnson O, Gower G, Turney C, Cox M, Cooper A, Huber CD. Admixture has obscured signals of historical hard sweeps in humans. Nat Ecol Evol 2022; 6:2003-2015. [PMID: 36316412 PMCID: PMC9715430 DOI: 10.1038/s41559-022-01914-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 09/16/2022] [Indexed: 11/06/2022]
Abstract
The role of natural selection in shaping biological diversity is an area of intense interest in modern biology. To date, studies of positive selection have primarily relied on genomic datasets from contemporary populations, which are susceptible to confounding factors associated with complex and often unknown aspects of population history. In particular, admixture between diverged populations can distort or hide prior selection events in modern genomes, though this process is not explicitly accounted for in most selection studies despite its apparent ubiquity in humans and other species. Through analyses of ancient and modern human genomes, we show that previously reported Holocene-era admixture has masked more than 50 historic hard sweeps in modern European genomes. Our results imply that this canonical mode of selection has probably been underappreciated in the evolutionary history of humans and suggest that our current understanding of the tempo and mode of selection in natural populations may be inaccurate.
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Affiliation(s)
- Yassine Souilmi
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
| | - Raymond Tobler
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Evolution of Cultural Diversity Initiative, Australian National University, Canberra, Australian Capital Territory, Australia.
| | - Angad Johar
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA.
| | - Matthew Williams
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Shane T Grey
- Transplantation Immunology Group, Immunology Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- St Vincent's Clinical School, Faculty of Medicine, UNSW, Darlinghurst, New South Wales, Australia
| | - Joshua Schmidt
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - João C Teixeira
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Adam Rohrlach
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, South Australia, Australia
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany
| | - Jonathan Tuke
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, South Australia, Australia
- School of Mathematical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Olivia Johnson
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Graham Gower
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Chris Turney
- Chronos 14Carbon-Cycle Facility and Earth and Sustainability Science Research Centre, University of New South Wales, Sydney, New South Wales, Australia
| | - Murray Cox
- Statistics and Bioinformatics Group, School of Fundamental Sciences, Massey University, Palmerston North, New Zealand
| | - Alan Cooper
- South Australian Museum, Adelaide, South Australia, Australia.
- BlueSky Genetics, Ashton, South Australia, Australia.
| | - Christian D Huber
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Department of Biology, Penn State University, University Park, PA, USA.
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17
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Mouterde M, Daali Y, Rollason V, Čížková M, Mulugeta A, Al Balushi KA, Fakis G, Constantinidis TC, Al-Thihli K, Černá M, Makonnen E, Boukouvala S, Al-Yahyaee S, Yimer G, Černý V, Desmeules J, Poloni ES. Joint Analysis of Phenotypic and Genomic Diversity Sheds Light on the Evolution of Xenobiotic Metabolism in Humans. Genome Biol Evol 2022; 14:6852765. [PMID: 36445690 PMCID: PMC9750130 DOI: 10.1093/gbe/evac167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 11/03/2022] [Accepted: 11/22/2022] [Indexed: 11/30/2022] Open
Abstract
Variation in genes involved in the absorption, distribution, metabolism, and excretion of drugs (ADME) can influence individual response to a therapeutic treatment. The study of ADME genetic diversity in human populations has led to evolutionary hypotheses of adaptation to distinct chemical environments. Population differentiation in measured drug metabolism phenotypes is, however, scarcely documented, often indirectly estimated via genotype-predicted phenotypes. We administered seven probe compounds devised to target six cytochrome P450 enzymes and the P-glycoprotein (P-gp) activity to assess phenotypic variation in four populations along a latitudinal transect spanning over Africa, the Middle East, and Europe (349 healthy Ethiopian, Omani, Greek, and Czech volunteers). We demonstrate significant population differentiation for all phenotypes except the one measuring CYP2D6 activity. Genome-wide association studies (GWAS) evidenced that the variability of phenotypes measuring CYP2B6, CYP2C9, CYP2C19, and CYP2D6 activity was associated with genetic variants linked to the corresponding encoding genes, and additional genes for the latter three. Instead, GWAS did not indicate any association between genetic diversity and the phenotypes measuring CYP1A2, CYP3A4, and P-gp activity. Genome scans of selection highlighted multiple candidate regions, a few of which included ADME genes, but none overlapped with the GWAS candidates. Our results suggest that different mechanisms have been shaping the evolution of these phenotypes, including phenotypic plasticity, and possibly some form of balancing selection. We discuss how these contrasting results highlight the diverse evolutionary trajectories of ADME genes and proteins, consistent with the wide spectrum of both endogenous and exogenous molecules that are their substrates.
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Affiliation(s)
| | - Youssef Daali
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Victoria Rollason
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Martina Čížková
- Institute of Archaeology of the Academy of Sciences of the Czech Republic, Prague, Czech Republic
| | - Anwar Mulugeta
- Department of Pharmacology and Clinical Pharmacy, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Khalid A Al Balushi
- College of Pharmacy, National University of Science and Technology, Muscat, Sultanate of Oman
| | - Giannoulis Fakis
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece
| | | | - Khalid Al-Thihli
- Department of Genetics, Sultan Qaboos University Hospital, Muscat, Sultanate of Oman
| | - Marie Černá
- Department of Medical Genetics, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Eyasu Makonnen
- Department of Pharmacology and Clinical Pharmacy, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia,Center for Innovative Drug Development and Therapeutic Trials for Africa, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Sotiria Boukouvala
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece
| | - Said Al-Yahyaee
- Department of Genetics, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Sultanate of Oman
| | - Getnet Yimer
- Center for Global Genomics & Health Equity, Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Viktor Černý
- Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Prague, Czech Republic
| | - Jules Desmeules
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
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18
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Genetic variation of glycophorins and infectious disease. Immunogenetics 2022; 75:201-206. [DOI: 10.1007/s00251-022-01280-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 09/30/2022] [Indexed: 11/26/2022]
Abstract
Abstract
Glycophorins are transmembrane proteins of red blood cells (RBCs), heavily glycosylated on their external-facing surface. In humans, there are four glycophorin proteins, glycophorins A, B, C and D. Glycophorins A and B are encoded by two similar genes GYPA and GYPB, and glycophorin C and glycophorin D are encoded by a single gene, GYPC. The exact function of glycophorins remains unclear. However, given their abundance on the surface of RBCs, it is likely that they serve as a substrate for glycosylation, giving the RBC a negatively charged, complex glycan “coat”. GYPB and GYPE (a closely related pseudogene) were generated from GYPA by two duplication events involving a 120-kb genomic segment between 10 and 15 million years ago. Non-allelic homologous recombination between these 120-kb repeats generates a variety of duplication alleles and deletion alleles, which have been systematically catalogued from genomic sequence data. One allele, called DUP4, encodes the Dantu NE blood type and is strongly protective against malaria as it alters the surface tension of the RBC membrane. Glycophorins interact with other infectious pathogens, including viruses, as well as the malarial parasite Plasmodium falciparum, but the role of glycophorin variation in mediating the effects of these pathogens remains underexplored.
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19
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Lea AJ, Peng J, Ayroles JF. Diverse environmental perturbations reveal the evolution and context-dependency of genetic effects on gene expression levels. Genome Res 2022; 32:1826-1839. [PMID: 36229124 PMCID: PMC9712631 DOI: 10.1101/gr.276430.121] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 09/07/2022] [Indexed: 01/18/2023]
Abstract
There is increasing appreciation that, in addition to being shaped by an individual's genotype and environment, most complex traits are also determined by poorly understood interactions between these two factors. So-called "genotype × environment" (G×E) interactions remain difficult to map at the organismal level but can be uncovered using molecular phenotypes. To do so at large scale, we used TM3'seq to profile transcriptomes across 12 cellular environments in 544 immortalized B cell lines from the 1000 Genomes Project. We mapped the genetic basis of gene expression levels across environments and revealed a context-dependent genetic architecture: The average heritability of gene expression levels increased in treatment relative to control conditions, and on average, each treatment revealed new expression quantitative trait loci (eQTLs) at 11% of genes. Across our experiments, 22% of all identified eQTLs were context-dependent, and this group was enriched for trait- and disease-associated loci. Further, evolutionary analyses suggested that positive selection has shaped G×E loci involved in responding to immune challenges and hormones but not to man-made chemicals. We hypothesize that this reflects a reduced opportunity for selection to act on responses to molecules recently introduced into human environments. Together, our work highlights the importance of considering an exposure's evolutionary history when studying and interpreting G×E interactions, and provides new insight into the evolutionary mechanisms that maintain G×E loci in human populations.
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Affiliation(s)
- Amanda J. Lea
- Department of Ecology and Evolution, Princeton University, Princeton, New Jersey 08544, USA;,Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA
| | - Julie Peng
- Department of Ecology and Evolution, Princeton University, Princeton, New Jersey 08544, USA;,Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA
| | - Julien F. Ayroles
- Department of Ecology and Evolution, Princeton University, Princeton, New Jersey 08544, USA;,Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA
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20
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McQuillan MA, Ranciaro A, Hansen MEB, Fan S, Beggs W, Belay G, Woldemeskel D, Tishkoff SA. Signatures of Convergent Evolution and Natural Selection at the Alcohol Dehydrogenase Gene Region are Correlated with Agriculture in Ethnically Diverse Africans. Mol Biol Evol 2022; 39:6677382. [PMID: 36026493 PMCID: PMC9547508 DOI: 10.1093/molbev/msac183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
The alcohol dehydrogenase (ADH) family of genes encodes enzymes that catalyze the metabolism of ethanol into acetaldehyde. Nucleotide variation in ADH genes can affect the catalytic properties of these enzymes and is associated with a variety of traits, including alcoholism and cancer. Some ADH variants, including the ADH1B*48His (rs1229984) mutation in the ADH1B gene, reduce the risk of alcoholism and are under positive selection in multiple human populations. The advent of Neolithic agriculture and associated increase in fermented foods and beverages is hypothesized to have been a selective force acting on such variants. However, this hypothesis has not been tested in populations outside of Asia. Here, we use genome-wide selection scans to show that the ADH gene region is enriched for variants showing strong signals of positive selection in multiple Afroasiatic-speaking, agriculturalist populations from Ethiopia, and that this signal is unique among sub-Saharan Africans. We also observe strong selection signals at putatively functional variants in nearby lipid metabolism genes, which may influence evolutionary dynamics at the ADH region. Finally, we show that haplotypes carrying these selected variants were introduced into Northeast Africa from a West-Eurasian source within the last ∼2,000 years and experienced positive selection following admixture. These selection signals are not evident in nearby, genetically similar populations that practice hunting/gathering or pastoralist subsistence lifestyles, supporting the hypothesis that the emergence of agriculture shapes patterns of selection at ADH genes. Together, these results enhance our understanding of how adaptations to diverse environments and diets have influenced the African genomic landscape.
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Affiliation(s)
| | - Alessia Ranciaro
- Current address: Department of Biological Sciences, Human and Evolutionary Biology Section, University of Southern California, Los Angeles, CA
| | | | - Shaohua Fan
- Human Phenome Institute, School of Life Sciences, Fudan University, Shanghai, China
| | - William Beggs
- Department of Genetics, University of Pennsylvania, Philadelphia, PA
| | - Gurja Belay
- Department of Microbial Cellular and Molecular Biology, Addis Ababa University, Addis Ababa, Ethiopia
| | - Dawit Woldemeskel
- Department of Biology, Addis Ababa University, Addis Ababa, Ethiopia
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21
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Padró J, De Panis DN, Luisi P, Dopazo H, Szajnman S, Hasson E, Soto IM. Ortholog genes from cactophilic Drosophila provide insight into human adaptation to hallucinogenic cacti. Sci Rep 2022; 12:13180. [PMID: 35915153 PMCID: PMC9343604 DOI: 10.1038/s41598-022-17118-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 07/20/2022] [Indexed: 11/18/2022] Open
Abstract
Cultural transformations of lifestyles and dietary practices have been key drivers of human evolution. However, while most of the evidence of genomic adaptations is related to the hunter-gatherer transition to agricultural societies, little is known on the influence of other major cultural manifestations. Shamanism is considered the oldest religion that predominated throughout most of human prehistory and still prevails in many indigenous populations. Several lines of evidence from ethno-archeological studies have demonstrated the continuity and importance of psychoactive plants in South American cultures. However, despite the well-known importance of secondary metabolites in human health, little is known about its role in the evolution of ethnic differences. Herein, we identified candidate genes of adaptation to hallucinogenic cactus in Native Andean populations with a long history of shamanic practices. We used genome-wide expression data from the cactophilic fly Drosophila buzzatii exposed to a hallucinogenic columnar cactus, also consumed by humans, to identify ortholog genes exhibiting adaptive footprints of alkaloid tolerance. Genomic analyses in human populations revealed a suite of ortholog genes evolving under recent positive selection in indigenous populations of the Central Andes. Our results provide evidence of selection in genetic variants related to alkaloids toxicity, xenobiotic metabolism, and neuronal plasticity in Aymara and Quechua populations, suggesting a possible process of gene-culture coevolution driven by religious practices.
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Affiliation(s)
- Julian Padró
- INIBIOMA-CONICET, Universidad Nacional del Comahue, Quintral 1250, R8400FRF, San Carlos de Bariloche, Argentina.
| | - Diego N De Panis
- IEGEBA-CONICET, Departamento de Ecología, Genética y Evolución, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Intendente Güiraldes 2160, C1428EHA, Buenos Aires, Argentina
| | - Pierre Luisi
- Facultad de Filosofía y Humanidades, Universidad Nacional de Córdoba (FFyH-UNC), Córdoba, Argentina.,Microbial Paleogenomics Unit, Institut Pasteur, 25-28 Rue du Dr Roux, 75015, Paris, France
| | - Hernan Dopazo
- IEGEBA-CONICET, Departamento de Ecología, Genética y Evolución, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Intendente Güiraldes 2160, C1428EHA, Buenos Aires, Argentina
| | - Sergio Szajnman
- Departamento de Química Orgánica and UMYMFOR (CONICET-FCEyN), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Intendente Güiraldes 2160, C1428EHA, Buenos Aires, Argentina
| | - Esteban Hasson
- IEGEBA-CONICET, Departamento de Ecología, Genética y Evolución, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Intendente Güiraldes 2160, C1428EHA, Buenos Aires, Argentina
| | - Ignacio M Soto
- IEGEBA-CONICET, Departamento de Ecología, Genética y Evolución, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Intendente Güiraldes 2160, C1428EHA, Buenos Aires, Argentina
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22
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Pellegrina D, Bahcheli AT, Krassowski M, Reimand J. Human phospho-signaling networks of SARS-CoV-2 infection are rewired by population genetic variants. Mol Syst Biol 2022; 18:e10823. [PMID: 35579274 PMCID: PMC9112486 DOI: 10.15252/msb.202110823] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 04/26/2022] [Accepted: 04/27/2022] [Indexed: 11/23/2022] Open
Abstract
SARS-CoV-2 infection hijacks signaling pathways and induces protein-protein interactions between human and viral proteins. Human genetic variation may impact SARS-CoV-2 infection and COVID-19 pathology; however, the genetic variation in these signaling networks remains uncharacterized. Here, we studied human missense single nucleotide variants (SNVs) altering phosphorylation sites modulated by SARS-CoV-2 infection, using machine learning to identify amino acid substitutions altering kinase-bound sequence motifs. We found 2,033 infrequent phosphorylation-associated SNVs (pSNVs) that are enriched in sequence motif alterations, potentially reflecting the evolution of signaling networks regulating host defenses. Proteins with pSNVs are involved in viral life cycle and host responses, including RNA splicing, interferon response (TRIM28), and glucose homeostasis (TBC1D4) with potential associations with COVID-19 comorbidities. pSNVs disrupt CDK and MAPK substrate motifs and replace these with motifs of Tank Binding Kinase 1 (TBK1) involved in innate immune responses, indicating consistent rewiring of signaling networks. Several pSNVs associate with severe COVID-19 and hospitalization (STARD13, ARFGEF2). Our analysis highlights potential genetic factors contributing to inter-individual variation of SARS-CoV-2 infection and COVID-19 and suggests leads for mechanistic and translational studies.
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Affiliation(s)
- Diogo Pellegrina
- Computational Biology ProgramOntario Institute for Cancer ResearchTorontoONCanada
| | - Alexander T Bahcheli
- Computational Biology ProgramOntario Institute for Cancer ResearchTorontoONCanada
- Department of Molecular GeneticsUniversity of TorontoTorontoONCanada
| | - Michal Krassowski
- Medical Sciences DivisionNuffield Department of Women's and Reproductive HealthUniversity of OxfordOxfordUK
| | - Jüri Reimand
- Computational Biology ProgramOntario Institute for Cancer ResearchTorontoONCanada
- Department of Molecular GeneticsUniversity of TorontoTorontoONCanada
- Department of Medical BiophysicsUniversity of TorontoTorontoONCanada
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23
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Schaschl H, Göllner T, Morris DL. Positive selection acts on regulatory genetic variants in populations of European ancestry that affect ALDH2 gene expression. Sci Rep 2022; 12:4563. [PMID: 35296751 PMCID: PMC8927298 DOI: 10.1038/s41598-022-08588-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 03/09/2022] [Indexed: 11/09/2022] Open
Abstract
ALDH2 is a key enzyme in alcohol metabolism that protects cells from acetaldehyde toxicity. Using iHS, iSAFE and FST statistics, we identified regulatory acting variants affecting ALDH2 gene expression under positive selection in populations of European ancestry. Several SNPs (rs3184504, rs4766578, rs10774625, rs597808, rs653178, rs847892, rs2013002) that function as eQTLs for ALDH2 in various tissues showed evidence of strong positive selection. Very large pairwise FST values indicated high genetic differentiation at these loci between populations of European ancestry and populations of other global ancestries. Estimating the timing of positive selection on the beneficial alleles suggests that these variants were recently adapted approximately 3000-3700 years ago. The derived beneficial alleles are in complete linkage disequilibrium with the derived ALDH2 promoter variant rs886205, which is associated with higher transcriptional activity. The SNPs rs4766578 and rs847892 are located in binding sequences for the transcription factor HNF4A, which is an important regulatory element of ALDH2 gene expression. In contrast to the missense variant ALDH2 rs671 (ALDH2*2), which is common only in East Asian populations and is associated with greatly reduced enzyme activity and alcohol intolerance, the beneficial alleles of the regulatory variants identified in this study are associated with increased expression of ALDH2. This suggests adaptation of Europeans to higher alcohol consumption.
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Affiliation(s)
- Helmut Schaschl
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, 1030, Vienna, Austria.
| | - Tobias Göllner
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, 1030, Vienna, Austria
| | - David L Morris
- Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King's College London, Great Maze Pond, London, SE1 9RT, UK
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24
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Quiver MH, Lachance J. Adaptive eQTLs reveal the evolutionary impacts of pleiotropy and tissue-specificity while contributing to health and disease. HGG ADVANCES 2022; 3:100083. [PMID: 35047867 PMCID: PMC8756519 DOI: 10.1016/j.xhgg.2021.100083] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 12/21/2021] [Indexed: 11/24/2022] Open
Abstract
Large numbers of expression quantitative trait loci (eQTLs) have recently been identified in humans, and many of these regulatory variants have large allele frequency differences between populations. Here, we conducted genome-wide scans of selection to identify adaptive eQTLs (i.e., eQTLs with large population branch statistics). We then tested if tissue pleiotropy affects whether eQTLs are more or less likely to be adaptive and identified tissues that have been key targets of positive selection during the last 100,000 years. Top adaptive eQTL outliers include rs1043809, rs66899053, and rs2814778 (a SNP that is associated with malaria resistance). We found that effect sizes of eQTLs were negatively correlated with population branch statistics and that adaptive eQTLs affect two-thirds as many tissues as do non-adaptive eQTLs. Because the tissue breadth of an eQTL can be viewed as a measure of pleiotropy, these results imply that pleiotropy inhibits adaptation. The proportion of eQTLs that are adaptive varies by tissue, and we found that eQTLs that regulate expression in testis, thyroid, blood, or sun-exposed skin are enriched for signatures of positive selection. By contrast, eQTLs that regulate expression in the cerebrum or female-specific tissues have a relative lack of adaptive outliers. Scans of selections also reveal that many adaptive eQTLs are closely linked to disease-associated loci. Taken together, our results indicate that eQTLs have played an important role in recent human evolution.
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Affiliation(s)
- Melanie H Quiver
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
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25
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Colomer-Vilaplana A, Murga-Moreno J, Canalda-Baltrons A, Inserte C, Soto D, Coronado-Zamora M, Barbadilla A, Casillas S. PopHumanVar: an interactive application for the functional characterization and prioritization of adaptive genomic variants in humans. Nucleic Acids Res 2022; 50:D1069-D1076. [PMID: 34664660 PMCID: PMC8728255 DOI: 10.1093/nar/gkab925] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 09/17/2021] [Accepted: 09/28/2021] [Indexed: 12/22/2022] Open
Abstract
Adaptive challenges that humans faced as they expanded across the globe left specific molecular footprints that can be decoded in our today's genomes. Different sets of metrics are used to identify genomic regions that have undergone selection. However, there are fewer methods capable of pinpointing the allele ultimately responsible for this selection. Here, we present PopHumanVar, an interactive online application that is designed to facilitate the exploration and thorough analysis of candidate genomic regions by integrating both functional and population genomics data currently available. PopHumanVar generates useful summary reports of prioritized variants that are putatively causal of recent selective sweeps. It compiles data and graphically represents different layers of information, including natural selection statistics, as well as functional annotations and genealogical estimations of variant age, for biallelic single nucleotide variants (SNVs) of the 1000 Genomes Project phase 3. Specifically, PopHumanVar amasses SNV-based information from GEVA, SnpEFF, GWAS Catalog, ClinVar, RegulomeDB and DisGeNET databases, as well as accurate estimations of iHS, nSL and iSAFE statistics. Notably, PopHumanVar can successfully identify known causal variants of frequently reported candidate selection regions, including EDAR in East-Asians, ACKR1 (DARC) in Africans and LCT/MCM6 in Europeans. PopHumanVar is open and freely available at https://pophumanvar.uab.cat.
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Affiliation(s)
- Aina Colomer-Vilaplana
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Jesús Murga-Moreno
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Aleix Canalda-Baltrons
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Clara Inserte
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Daniel Soto
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Marta Coronado-Zamora
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Antonio Barbadilla
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Sònia Casillas
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
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26
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Ebel ER, Uricchio LH, Petrov DA, Egan ES. Revisiting the malaria hypothesis: accounting for polygenicity and pleiotropy. Trends Parasitol 2022; 38:290-301. [PMID: 35065882 PMCID: PMC8916997 DOI: 10.1016/j.pt.2021.12.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 12/20/2021] [Accepted: 12/21/2021] [Indexed: 10/19/2022]
Abstract
The malaria hypothesis predicts local, balancing selection of deleterious alleles that confer strong protection from malaria. Three protective variants, recently discovered in red cell genes, are indeed more common in African than European populations. Still, up to 89% of the heritability of severe malaria is attributed to many genome-wide loci with individually small effects. Recent analyses of hundreds of genome-wide association studies (GWAS) in humans suggest that most functional, polygenic variation is pleiotropic for multiple traits. Interestingly, GWAS alleles and red cell traits associated with small reductions in malaria risk are not enriched in African populations. We propose that other selective and neutral forces, in addition to malaria prevalence, explain the global distribution of most genetic variation impacting malaria risk.
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27
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Villegas-Mirón P, Acosta S, Nye J, Bertranpetit J, Laayouni H. Chromosome X-wide Analysis of Positive Selection in Human Populations: Common and Private Signals of Selection and its Impact on Inactivated Genes and Enhancers. Front Genet 2021; 12:714491. [PMID: 34646300 PMCID: PMC8502928 DOI: 10.3389/fgene.2021.714491] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 09/08/2021] [Indexed: 01/22/2023] Open
Abstract
The ability of detecting adaptive (positive) selection in the genome has opened the possibility of understanding the genetic basis of population-specific adaptations genome-wide. Here, we present the analysis of recent selective sweeps, specifically in the X chromosome, in human populations from the third phase of the 1,000 Genomes Project using three different haplotype-based statistics. We describe instances of recent positive selection that fit the criteria of hard or soft sweeps, and detect a higher number of events among sub-Saharan Africans than non-Africans (Europe and East Asia). A global enrichment of neural-related processes is observed and numerous genes related to fertility appear among the top candidates, reflecting the importance of reproduction in human evolution. Commonalities with previously reported genes under positive selection are found, while particularly strong new signals are reported in specific populations or shared across different continental groups. We report an enrichment of signals in genes that escape X chromosome inactivation, which may contribute to the differentiation between sexes. We also provide evidence of a widespread presence of soft-sweep-like signatures across the chromosome and a global enrichment of highly scoring regions that overlap potential regulatory elements. Among these, enhancers-like signatures seem to present putative signals of positive selection which might be in concordance with selection in their target genes. Also, particularly strong signals appear in regulatory regions that show differential activities, which might point to population-specific regulatory adaptations.
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Affiliation(s)
- Pablo Villegas-Mirón
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
| | - Sandra Acosta
- Department Pathology and Experimental Therapeutics, Medical School, University of Barcelona, Barcelona, Spain
| | - Jessica Nye
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
| | - Jaume Bertranpetit
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
| | - Hafid Laayouni
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain.,Bioinformatics Studies, ESCI-UPF, Barcelona, Spain
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28
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Cádiz MI, López ME, Díaz-Domínguez D, Cáceres G, Marin-Nahuelpi R, Gomez-Uchida D, Canales-Aguirre CB, Orozco-terWengel P, Yáñez JM. Detection of selection signatures in the genome of a farmed population of anadromous rainbow trout (Oncorhynchus mykiss). Genomics 2021; 113:3395-3404. [PMID: 34339816 DOI: 10.1016/j.ygeno.2021.07.027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 07/06/2021] [Accepted: 07/28/2021] [Indexed: 11/26/2022]
Abstract
Domestication processes and artificial selection are likely to leave signatures that can be detected at a molecular level in farmed rainbow trout (Oncorhynchus mykiss). These signatures of selection are genomic regions that contain functional genetic variants conferring a higher fitness to their bearers. We genotyped 749 rainbow trout from a commercial population using a rainbow trout Axiom 57 K SNP array panel and identified putative genomic regions under selection using the pcadapt, Composite Likelihood Ratio (CLR) and Integrated Haplotype Score (iHS) methods. After applying quality-control pipelines and statistical analyses, we detected 12, 96 and 16 SNPs putatively under selection, associated with 96, 781 and 115 candidate genes, respectively. Several of these candidate genes were associated with growth, early development, reproduction, behavior and immune system traits. In addition, some of the SNPs were found in interesting regions located in autosomal inversions on Omy05 and Omy20. These findings could represent a genome-wide map of selection signatures in farmed rainbow trout and could be important in explaining domestication and selection for genetic traits of commercial interest.
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Affiliation(s)
- María I Cádiz
- Programa de Doctorado en Ciencias Silvoagropecuarias y Veterinarias, Campus Sur, Universidad de Chile, Santa Rosa 11315, La Pintana, Santiago 8820808, Chile; Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Avenida Santa Rosa 11735, La Pintana, 8820808 Santiago, Chile; Núcleo Milenio de Salmónidos Invasores (INVASAL), Concepción, Chile
| | - María E López
- Department of Aquatic Resources, Swedish University of Agricultural Sciences, Drottningholm, Sweden
| | | | - Giovanna Cáceres
- Programa de Doctorado en Ciencias Silvoagropecuarias y Veterinarias, Campus Sur, Universidad de Chile, Santa Rosa 11315, La Pintana, Santiago 8820808, Chile; Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Avenida Santa Rosa 11735, La Pintana, 8820808 Santiago, Chile
| | - Rodrigo Marin-Nahuelpi
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Avenida Santa Rosa 11735, La Pintana, 8820808 Santiago, Chile; Núcleo Milenio de Salmónidos Invasores (INVASAL), Concepción, Chile
| | - Daniel Gomez-Uchida
- Departamento de Zoología, Facultad de Ciencias Naturales y Oceanográficas, Universidad de Concepción, Chile; Núcleo Milenio de Salmónidos Invasores (INVASAL), Concepción, Chile
| | - Cristian B Canales-Aguirre
- Centro i~Mar, Universidad de Los Lagos, Camino Chinquihue 6 km, Puerto Montt, Chile; Núcleo Milenio de Salmónidos Invasores (INVASAL), Concepción, Chile
| | | | - José M Yáñez
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Avenida Santa Rosa 11735, La Pintana, 8820808 Santiago, Chile; Núcleo Milenio de Salmónidos Invasores (INVASAL), Concepción, Chile.
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29
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Otte KA, Nolte V, Mallard F, Schlötterer C. The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime. Genome Biol 2021; 22:211. [PMID: 34271951 PMCID: PMC8285869 DOI: 10.1186/s13059-021-02425-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 06/29/2021] [Indexed: 12/28/2022] Open
Abstract
Background Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures—either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates. Results Here, we expose the founder population from Portugal to a cold temperature regime. Although almost no selection targets are shared between the hot and cold selection regime, the adaptive architecture was similar. We identify a moderate number of targets under strong selection (19 selection targets, mean selection coefficient = 0.072) and parallel responses in the cold evolved replicates. This similarity across different environments indicates that the adaptive architecture depends more on the ancestry of the founder population than the specific selection regime. Conclusions These observations will have broad implications for the correct interpretation of the genomic responses to a changing climate in natural populations. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-021-02425-9.
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Affiliation(s)
- Kathrin A Otte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.,Present address: Institute for Zoology, University of Cologne, Cologne, Germany
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - François Mallard
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.,Present address: Institut de Biologie de l'École Normale Supérieure, CNRS UMR 8197, Inserm U1024, PSL Research University, F-75005, Paris, France
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30
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Arner AM, Grogan KE, Grabowski M, Reyes-Centeno H, Perry GH. Patterns of recent natural selection on genetic loci associated with sexually differentiated human body size and shape phenotypes. PLoS Genet 2021; 17:e1009562. [PMID: 34081690 PMCID: PMC8174730 DOI: 10.1371/journal.pgen.1009562] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 04/20/2021] [Indexed: 01/21/2023] Open
Abstract
Levels of sex differences for human body size and shape phenotypes are hypothesized to have adaptively reduced following the agricultural transition as part of an evolutionary response to relatively more equal divisions of labor and new technology adoption. In this study, we tested this hypothesis by studying genetic variants associated with five sexually differentiated human phenotypes: height, body mass, hip circumference, body fat percentage, and waist circumference. We first analyzed genome-wide association (GWAS) results for UK Biobank individuals (~194,000 females and ~167,000 males) to identify a total of 114,199 single nucleotide polymorphisms (SNPs) significantly associated with at least one of the studied phenotypes in females, males, or both sexes (P<5x10-8). From these loci we then identified 3,016 SNPs (2.6%) with significant differences in the strength of association between the female- and male-specific GWAS results at a low false-discovery rate (FDR<0.001). Genes with known roles in sexual differentiation are significantly enriched for co-localization with one or more of these SNPs versus SNPs associated with the phenotypes generally but not with sex differences (2.73-fold enrichment; permutation test; P = 0.0041). We also confirmed that the identified variants are disproportionately associated with greater phenotype effect sizes in the sex with the stronger association value. We then used the singleton density score statistic, which quantifies recent (within the last ~3,000 years; post-agriculture adoption in Britain) changes in the frequencies of alleles underlying polygenic traits, to identify a signature of recent positive selection on alleles associated with greater body fat percentage in females (permutation test; P = 0.0038; FDR = 0.0380), directionally opposite to that predicted by the sex differences reduction hypothesis. Otherwise, we found no evidence of positive selection for sex difference-associated alleles for any other trait. Overall, our results challenge the longstanding hypothesis that sex differences adaptively decreased following subsistence transitions from hunting and gathering to agriculture. There is uncertainty regarding the evolutionary history of human sex differences for quantitative body size and shape phenotypes. In this study we identified thousands of genetic loci that differentially impact body size and shape trait variation between females and males using a large sample of UK Biobank individuals. After confirming the biological plausibility of these loci, we used a population genomics approach to study the recent (over the past ~3,000 years) evolutionary histories of these loci in this population. We observed significant increases in the frequencies of alleles associated with greater body fat percentage in females. This result is contradictory to longstanding hypotheses that sex differences have adaptively decreased following subsistence transitions from hunting and gathering to agriculture.
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Affiliation(s)
- Audrey M. Arner
- Departments of Anthropology and Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America
- * E-mail: (AMA); (GHP)
| | - Kathleen E. Grogan
- Departments of Anthropology and Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Departments of Anthropology and Biology, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Mark Grabowski
- DFG Center for Advanced Studies, University of Tübingen, Tübingen, Germany
- Research Centre in Evolutionary Anthropology and Palaeoecology, Liverpool John Moores University, Liverpool, United Kingdom
| | - Hugo Reyes-Centeno
- DFG Center for Advanced Studies, University of Tübingen, Tübingen, Germany
- Department of Anthropology & William S. Webb Museum of Anthropology, University of Kentucky, Lexington, Kentucky, United States of America
| | - George H. Perry
- Departments of Anthropology and Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America
- DFG Center for Advanced Studies, University of Tübingen, Tübingen, Germany
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
- * E-mail: (AMA); (GHP)
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31
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Yasumizu Y, Sakaue S, Konuma T, Suzuki K, Matsuda K, Murakami Y, Kubo M, Palamara PF, Kamatani Y, Okada Y. Genome-Wide Natural Selection Signatures Are Linked to Genetic Risk of Modern Phenotypes in the Japanese Population. Mol Biol Evol 2021; 37:1306-1316. [PMID: 31957793 PMCID: PMC7182208 DOI: 10.1093/molbev/msaa005] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Elucidation of natural selection signatures and relationships with phenotype spectra is important to understand adaptive evolution of modern humans. Here, we conducted a genome-wide scan of selection signatures of the Japanese population by estimating locus-specific time to the most recent common ancestor using the ascertained sequentially Markovian coalescent (ASMC), from the biobank-based large-scale genome-wide association study data of 170,882 subjects. We identified 29 genetic loci with selection signatures satisfying the genome-wide significance. The signatures were most evident at the alcohol dehydrogenase (ADH) gene cluster locus at 4q23 (PASMC = 2.2 × 10−36), followed by relatively strong selection at the FAM96A (15q22), MYOF (10q23), 13q21, GRIA2 (4q32), and ASAP2 (2p25) loci (PASMC < 1.0 × 10−10). The additional analysis interrogating extended haplotypes (integrated haplotype score) showed robust concordance of the detected signatures, contributing to fine-mapping of the genes, and provided allelic directional insights into selection pressure (e.g., positive selection for ADH1B-Arg48His and HLA-DPB1*04:01). The phenome-wide selection enrichment analysis with the trait-associated variants identified a variety of the modern human phenotypes involved in the adaptation of Japanese. We observed population-specific evidence of enrichment with the alcohol-related phenotypes, anthropometric and biochemical clinical measurements, and immune-related diseases, differently from the findings in Europeans using the UK Biobank resource. Our study demonstrated population-specific features of the selection signatures in Japanese, highlighting a value of the natural selection study using the nation-wide biobank-scale genome and phenotype data.
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Affiliation(s)
| | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.,Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.,Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Takahiro Konuma
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Ken Suzuki
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Koichi Matsuda
- Department of Computational Biology and Medical Science, Graduate school of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinori Murakami
- Division of Molecular Pathology, The Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.,Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.,Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan.,Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
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32
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Lindo J, DeGiorgio M. Understanding the Adaptive Evolutionary Histories of South American Ancient and Present-Day Populations via Genomics. Genes (Basel) 2021; 12:360. [PMID: 33801556 PMCID: PMC8001801 DOI: 10.3390/genes12030360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 02/18/2021] [Accepted: 02/22/2021] [Indexed: 12/03/2022] Open
Abstract
The South American continent is remarkably diverse in its ecological zones, spanning the Amazon rainforest, the high-altitude Andes, and Tierra del Fuego. Yet the original human populations of the continent successfully inhabited all these zones, well before the buffering effects of modern technology. Therefore, it is likely that the various cultures were successful, in part, due to positive natural selection that allowed them to successfully establish populations for thousands of years. Detecting positive selection in these populations is still in its infancy, as the ongoing effects of European contact have decimated many of these populations and introduced gene flow from outside of the continent. In this review, we explore hypotheses of possible human biological adaptation, methods to identify positive selection, the utilization of ancient DNA, and the integration of modern genomes through the identification of genomic tracts that reflect the ancestry of the first populations of the Americas.
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Affiliation(s)
- John Lindo
- Department of Anthropology, Emory University, Atlanta, GA 30322, USA
| | - Michael DeGiorgio
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
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33
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Shi H, Gazal S, Kanai M, Koch EM, Schoech AP, Siewert KM, Kim SS, Luo Y, Amariuta T, Huang H, Okada Y, Raychaudhuri S, Sunyaev SR, Price AL. Population-specific causal disease effect sizes in functionally important regions impacted by selection. Nat Commun 2021; 12:1098. [PMID: 33597505 PMCID: PMC7889654 DOI: 10.1038/s41467-021-21286-1] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 01/15/2021] [Indexed: 01/31/2023] Open
Abstract
Many diseases exhibit population-specific causal effect sizes with trans-ethnic genetic correlations significantly less than 1, limiting trans-ethnic polygenic risk prediction. We develop a new method, S-LDXR, for stratifying squared trans-ethnic genetic correlation across genomic annotations, and apply S-LDXR to genome-wide summary statistics for 31 diseases and complex traits in East Asians (average N = 90K) and Europeans (average N = 267K) with an average trans-ethnic genetic correlation of 0.85. We determine that squared trans-ethnic genetic correlation is 0.82× (s.e. 0.01) depleted in the top quintile of background selection statistic, implying more population-specific causal effect sizes. Accordingly, causal effect sizes are more population-specific in functionally important regions, including conserved and regulatory regions. In regions surrounding specifically expressed genes, causal effect sizes are most population-specific for skin and immune genes, and least population-specific for brain genes. Our results could potentially be explained by stronger gene-environment interaction at loci impacted by selection, particularly positive selection.
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Affiliation(s)
- Huwenbo Shi
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Steven Gazal
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Masahiro Kanai
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Evan M Koch
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Armin P Schoech
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Katherine M Siewert
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samuel S Kim
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yang Luo
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tiffany Amariuta
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Graduate School of Arts and Sciences, Harvard University, Cambridge, MA, USA
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
| | - Soumya Raychaudhuri
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Shamil R Sunyaev
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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34
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COVID-19 as a worldwide selective event and bitter taste receptor polymorphisms: An ecological correlational study. Int J Biol Macromol 2021; 177:204-210. [PMID: 33582215 PMCID: PMC8043766 DOI: 10.1016/j.ijbiomac.2021.02.070] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 01/18/2021] [Accepted: 02/08/2021] [Indexed: 12/17/2022]
Abstract
Background Given the observed olfactory and gustatory dysfunctions in patients with COVID-19 and recent findings on taste receptors possible important activities in the immune system, we elected to estimate the correlation between COVID-19 mortality and polymorphism of a particular type of bitter taste receptor gene called TAS2R38, in a worldwide epidemiological point of view. Methods Pooled rate of each of the rs713598, rs1726866, rs10246939, and PAV/AVI polymorphisms of the TAS2R38 gene was obtained in different countries using a systematic review methodology and its relationship with the mortality of COVID-19. Data were analyzed by the comprehensive meta-analysis software and SPSS. Results There was only a significant reverse Pearson correlation in death counts and PAV/AVI ratio, p = 0.047, r = −0.503. Also, a significant reverse correlation of PAV/AVI ratio and death rate was seen, r = −0.572 p = 0.021. rs10246939 ratio had a significant positive correlation with death rate, r = 0.851 p = 0.031. Further analysis was not significant. Our results showed that the higher presence of PAV allele than AVI, and a higher rate of G allele than A in rs10246939 polymorphism in a country, could be associated with lower COVID-19 mortality. While assessing all three polymorphisms showed a huge diversity worldwide. Conclusion Due to extraoral activities of bitter taste receptor genes, especially in mucosal immunity, this gene seems to be a good candidate for future studies on COVID-19 pathophysiology. Also, the high worldwide diversity of TAS2R38 genes polymorphism and its possible assassination with mortality raises concerns about the efficiency of vaccine projects in different ethnicities.
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35
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Wang YF, Zhang Y, Lin Z, Zhang H, Wang TY, Cao Y, Morris DL, Sheng Y, Yin X, Zhong SL, Gu X, Lei Y, He J, Wu Q, Shen JJ, Yang J, Lam TH, Lin JH, Mai ZM, Guo M, Tang Y, Chen Y, Song Q, Ban B, Mok CC, Cui Y, Lu L, Shen N, Sham PC, Lau CS, Smith DK, Vyse TJ, Zhang X, Lau YL, Yang W. Identification of 38 novel loci for systemic lupus erythematosus and genetic heterogeneity between ancestral groups. Nat Commun 2021; 12:772. [PMID: 33536424 PMCID: PMC7858632 DOI: 10.1038/s41467-021-21049-y] [Citation(s) in RCA: 125] [Impact Index Per Article: 41.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 01/11/2021] [Indexed: 02/07/2023] Open
Abstract
Systemic lupus erythematosus (SLE), a worldwide autoimmune disease with high heritability, shows differences in prevalence, severity and age of onset among different ancestral groups. Previous genetic studies have focused more on European populations, which appear to be the least affected. Consequently, the genetic variations that underlie the commonalities, differences and treatment options in SLE among ancestral groups have not been well elucidated. To address this, we undertake a genome-wide association study, increasing the sample size of Chinese populations to the level of existing European studies. Thirty-eight novel SLE-associated loci and incomplete sharing of genetic architecture are identified. In addition to the human leukocyte antigen (HLA) region, nine disease loci show clear ancestral differences and implicate antibody production as a potential mechanism for differences in disease manifestation. Polygenic risk scores perform significantly better when trained on ancestry-matched data sets. These analyses help to reveal the genetic basis for disparities in SLE among ancestral groups.
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Affiliation(s)
- Yong-Fei Wang
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong, China
| | - Yan Zhang
- Department of Pediatric Surgery, Guangzhou Institute of Pediatrics, Guangdong Provincial Key Laboratory of Research in Structural Birth Defect Disease, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Zhiming Lin
- Department of Rheumatology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Huoru Zhang
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong, China
| | - Ting-You Wang
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong, China
- The Hormel Institute, University of Minnesota, Austin, USA
| | - Yujie Cao
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong, China
| | - David L Morris
- Division of Genetics and Molecular Medicine, King's College London, London, UK
| | - Yujun Sheng
- Department of Dermatology, No.1 Hospital, Anhui Medical University, Hefei, China
| | - Xianyong Yin
- Department of Dermatology, No.1 Hospital, Anhui Medical University, Hefei, China
| | - Shi-Long Zhong
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangzhou, China
| | - Xiaoqiong Gu
- Department of Clinical Biological Resource Bank, Guangzhou Institute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou, China
| | - Yao Lei
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong, China
| | - Jing He
- Department of Pediatric Surgery, Guangzhou Institute of Pediatrics, Guangdong Provincial Key Laboratory of Research in Structural Birth Defect Disease, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Qi Wu
- Department of Pediatric Surgery, Guangzhou Institute of Pediatrics, Guangdong Provincial Key Laboratory of Research in Structural Birth Defect Disease, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Jiangshan Jane Shen
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong, China
| | - Jing Yang
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong, China
| | - Tai-Hing Lam
- School of Public Health, The University of Hong Kong, Hong Kong, China
| | - Jia-Huang Lin
- School of Public Health, The University of Hong Kong, Hong Kong, China
| | - Zhi-Ming Mai
- School of Public Health, The University of Hong Kong, Hong Kong, China
- Radiation Epidemiology Branch, Division of Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - Mengbiao Guo
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong, China
| | - Yuanjia Tang
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yanhui Chen
- Department of Pediatrics, Union Hospital Affiliated to Fujian Medical University, Fuzhou, China
| | - Qin Song
- Department of Rheumatology, Affiliated Hospital of Jining Medical University, Jining, China
| | - Bo Ban
- Department of Endocrinology, Affiliated Hospital of Jining Medical University, Jining, China
| | - Chi Chiu Mok
- Department of Medicine, Tuen Mun Hospital, Hong Kong, China
| | - Yong Cui
- Department of Dermatology, China-Japan Friendship Hospital, Chaoyang, China
| | - Liangjing Lu
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Nan Shen
- Shanghai Institute of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Pak C Sham
- Department of Psychiatry, The University of Hong Kong, Hong Kong, China
| | - Chak Sing Lau
- Department of Medicine, The University of Hong Kong, Hong Kong, China
| | - David K Smith
- School of Public Health, The University of Hong Kong, Hong Kong, China
| | - Timothy J Vyse
- Division of Genetics and Molecular Medicine, King's College London, London, UK
| | - Xuejun Zhang
- Department of Dermatology, No.1 Hospital, Anhui Medical University, Hefei, China
| | - Yu Lung Lau
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong, China.
| | - Wanling Yang
- Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong, China.
- Shenzhen Institute of Research and Innovation, The University of Hong Kong, Hong Kong, China.
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36
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Enard D, Petrov DA. Ancient RNA virus epidemics through the lens of recent adaptation in human genomes. Philos Trans R Soc Lond B Biol Sci 2020; 375:20190575. [PMID: 33012231 PMCID: PMC7702803 DOI: 10.1098/rstb.2019.0575] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Over the course of the last several million years of evolution, humans probably have been plagued by hundreds or perhaps thousands of epidemics. Little is known about such ancient epidemics and a deep evolutionary perspective on current pathogenic threats is lacking. The study of past epidemics has typically been limited in temporal scope to recorded history, and in physical scope to pathogens that left sufficient DNA behind, such as Yersinia pestis during the Great Plague. Host genomes, however, offer an indirect way to detect ancient epidemics beyond the current temporal and physical limits. Arms races with pathogens have shaped the genomes of the hosts by driving a large number of adaptations at many genes, and these signals can be used to detect and further characterize ancient epidemics. Here, we detect the genomic footprints left by ancient viral epidemics that took place in the past approximately 50 000 years in the 26 human populations represented in the 1000 Genomes Project. By using the enrichment in signals of adaptation at approximately 4500 host loci that interact with specific types of viruses, we provide evidence that RNA viruses have driven a particularly large number of adaptive events across diverse human populations. These results suggest that different types of viruses may have exerted different selective pressures during human evolution. Knowledge of these past selective pressures will provide a deeper evolutionary perspective on current pathogenic threats. This article is part of the theme issue ‘Insights into health and disease from ancient biomolecules’.
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Affiliation(s)
- David Enard
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA
| | - Dmitri A Petrov
- Department of Biology, Stanford University, Stanford, CA, USA
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37
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Chen MH, Raffield LM, Mousas A, Sakaue S, Huffman JE, Moscati A, Trivedi B, Jiang T, Akbari P, Vuckovic D, Bao EL, Zhong X, Manansala R, Laplante V, Chen M, Lo KS, Qian H, Lareau CA, Beaudoin M, Hunt KA, Akiyama M, Bartz TM, Ben-Shlomo Y, Beswick A, Bork-Jensen J, Bottinger EP, Brody JA, van Rooij FJA, Chitrala K, Cho K, Choquet H, Correa A, Danesh J, Di Angelantonio E, Dimou N, Ding J, Elliott P, Esko T, Evans MK, Floyd JS, Broer L, Grarup N, Guo MH, Greinacher A, Haessler J, Hansen T, Howson JMM, Huang QQ, Huang W, Jorgenson E, Kacprowski T, Kähönen M, Kamatani Y, Kanai M, Karthikeyan S, Koskeridis F, Lange LA, Lehtimäki T, Lerch MM, Linneberg A, Liu Y, Lyytikäinen LP, Manichaikul A, Martin HC, Matsuda K, Mohlke KL, Mononen N, Murakami Y, Nadkarni GN, Nauck M, Nikus K, Ouwehand WH, Pankratz N, Pedersen O, Preuss M, Psaty BM, Raitakari OT, Roberts DJ, Rich SS, Rodriguez BAT, Rosen JD, Rotter JI, Schubert P, Spracklen CN, Surendran P, Tang H, Tardif JC, Trembath RC, Ghanbari M, Völker U, Völzke H, Watkins NA, Zonderman AB, Wilson PWF, Li Y, Butterworth AS, Gauchat JF, Chiang CWK, Li B, Loos RJF, Astle WJ, Evangelou E, van Heel DA, Sankaran VG, Okada Y, Soranzo N, Johnson AD, Reiner AP, Auer PL, Lettre G. Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations. Cell 2020; 182:1198-1213.e14. [PMID: 32888493 PMCID: PMC7480402 DOI: 10.1016/j.cell.2020.06.045] [Citation(s) in RCA: 308] [Impact Index Per Article: 77.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 04/16/2020] [Accepted: 06/29/2020] [Indexed: 12/14/2022]
Abstract
Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.
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Affiliation(s)
- Ming-Huei Chen
- The Framingham Heart Study, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Abdou Mousas
- Montreal Heart Institute, Montreal, QC H1T 1C8, Canada
| | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Bhavi Trivedi
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Tao Jiang
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Parsa Akbari
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK; Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK
| | | | - Erik L Bao
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02446, USA
| | - Xue Zhong
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA
| | - Regina Manansala
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA
| | - Véronique Laplante
- Département de Pharmacologie et Physiologie, Faculty of Medicine, Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Minhui Chen
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
| | - Ken Sin Lo
- Montreal Heart Institute, Montreal, QC H1T 1C8, Canada
| | - Huijun Qian
- Department of Statistics and Operation Research, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Caleb A Lareau
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02446, USA
| | | | - Karen A Hunt
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan; Department of Ocular Pathology and Imaging Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8581, Japan
| | - Traci M Bartz
- Department of Biostatistics, University of Washington, Seattle, WA 98101, USA
| | - Yoav Ben-Shlomo
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PS, UK
| | - Andrew Beswick
- Translational Health Sciences, Musculoskeletal Research Unit, Bristol Medical School, University of Bristol, Bristol BS10 5NB, UK
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Hasso-Plattner-Institut, Universität Potsdam, Potsdam 14469, Germany
| | - Jennifer A Brody
- Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | - Frank J A van Rooij
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam 3015, the Netherlands
| | - Kumaraswamynaidu Chitrala
- Laboratory of Epidemiology and Population Science, National Institute on Aging/NIH, Baltimore, MD 21224, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA; Department of Medicine, Division on Aging, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Hélène Choquet
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - John Danesh
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB10 1SA, UK; National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge University Hospitals, Cambridge CB2 0QQ, UK; British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Emanuele Di Angelantonio
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB10 1SA, UK; National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge University Hospitals, Cambridge CB2 0QQ, UK; British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Niki Dimou
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon 69008, France; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece
| | - Jingzhong Ding
- Department of Internal Medicine, Section of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK; Imperial Biomedical Research Centre, Imperial College London and Imperial College NHS Healthcare Trust, London SW7 2AZ, UK; Medical Research Council-Public Health England Centre for Environment, Imperial College London, London SW7 2AZ, UK; UK Dementia Research Institute, Imperial College London, London SW7 2AZ, UK; Health Data Research UK - London, London SW7 2AZ, UK
| | - Tõnu Esko
- Broad Institute of Harvard and MIT, Cambridge, MA 02446, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Science, National Institute on Aging/NIH, Baltimore, MD 21224, USA
| | - James S Floyd
- Department of Medicine, University of Washington, Seattle, WA 98101, USA; Department of Epidemiology, University of Washington, Seattle, WA 98101, USA
| | - Linda Broer
- Department of Internal Medicine, Erasmus University Medical Center Rotterdam, Rotterdam 3015, the Netherlands
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Michael H Guo
- Broad Institute of Harvard and MIT, Cambridge, MA 02446, USA; Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andreas Greinacher
- Institute for Immunology and Transfusion Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Jeff Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Joanna M M Howson
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Novo Nordisk Research Centre Oxford, Innovation Building, Old Road Campus, Oxford OX3 7FZ, UK
| | - Qin Qin Huang
- Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK
| | - Wei Huang
- Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute (SITI), Shanghai 201203, China
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Tim Kacprowski
- Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17475, Germany; Chair of Experimental Bioinformatics, Research Group Computational Systems Medicine, Technical University of Munich, Freising-Weihenstephan 85354, Germany; German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere 33521, Finland; Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan; Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan
| | - Masahiro Kanai
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Savita Karthikeyan
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Fotis Koskeridis
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece
| | - Leslie A Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Markus M Lerch
- Department of Internal Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg 2000, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Yongmei Liu
- Duke Molecular Physiology Institute, Department of Medicine, Division of Cardiology, Duke University Medical Center, Durham, NC 27701, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903, USA
| | - Hilary C Martin
- Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Yoshinori Murakami
- Division of Molecular Pathology, The Institute of Medical Sciences, The University of Tokyo, Tokyo 108-8639, Japan
| | - Girish N Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Matthias Nauck
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany; Institue of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere 33521, Finland; Department of Cardiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Willem H Ouwehand
- Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK; British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK; Department of Hematology, University of Cambridge, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Michael Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Bruce M Psaty
- Department of Medicine, University of Washington, Seattle, WA 98101, USA; Department of Epidemiology, University of Washington, Seattle, WA 98101, USA; Department of Health Services, University of Washington, Seattle, WA 98101, USA; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, USA
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku 20521, Finland; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20521, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20521, Finland
| | - David J Roberts
- The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK; Radcliffe Department of Medicine, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK; Department of Haematology, Churchill Hospital, Oxford OX3 7LE, UK; NHS Blood and Transplant - Oxford Centre, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903, USA
| | - Benjamin A T Rodriguez
- The Framingham Heart Study, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA
| | - Jonathan D Rosen
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Petra Schubert
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Cassandra N Spracklen
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA 01002, USA
| | - Praveen Surendran
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Rutherford Fund Fellow, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jean-Claude Tardif
- Montreal Heart Institute, Montreal, QC H1T 1C8, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Richard C Trembath
- School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King's College London, London SE1 1UL, UK
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam 3015, the Netherlands; Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad 9177948564, Iran
| | - Uwe Völker
- Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17475, Germany; German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany
| | - Henry Völzke
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany; Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Nicholas A Watkins
- National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Science, National Institute on Aging/NIH, Baltimore, MD 21224, USA
| | | | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Adam S Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB10 1SA, UK
| | - Jean-François Gauchat
- Département de Pharmacologie et Physiologie, Faculty of Medicine, Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA; Quantitative and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Bingshan Li
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - William J Astle
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge CB2 0QQ, UK; NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Strangeways Laboratory, Cambridge CB1 8RN, UK
| | - Evangelos Evangelou
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece; Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK
| | - David A van Heel
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Vijay G Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02446, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; Laboratory of Statistical Immunology, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan
| | - Nicole Soranzo
- Human Genetics, Wellcome Sanger Institute, Hinxton CB10 1SA, UK; Department of Hematology, University of Cambridge, Cambridge CB2 0PT, UK
| | - Andrew D Johnson
- The Framingham Heart Study, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98109, USA
| | - Paul L Auer
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA.
| | - Guillaume Lettre
- Montreal Heart Institute, Montreal, QC H1T 1C8, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, QC H3T 1J4, Canada.
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38
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Cádiz MI, López ME, Díaz-Domínguez D, Cáceres G, Yoshida GM, Gomez-Uchida D, Yáñez JM. Whole genome re-sequencing reveals recent signatures of selection in three strains of farmed Nile tilapia (Oreochromis niloticus). Sci Rep 2020; 10:11514. [PMID: 32661317 PMCID: PMC7359307 DOI: 10.1038/s41598-020-68064-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 06/16/2020] [Indexed: 01/24/2023] Open
Abstract
Nile tilapia belongs to the second most cultivated group of fish in the world, mainly because of its favorable characteristics for production. Genetic improvement programs and domestication process of Nile tilapia may have modified the genome through selective pressure, leaving signals that can be detected at the molecular level. In this work, signatures of selection were identified using genome-wide SNP data, by two haplotype-based (iHS and Rsb) and one FST based method. Whole-genome re-sequencing of 326 individuals from three strains (A, B and C) of farmed tilapia maintained in Brazil and Costa Rica was carried out using Illumina HiSeq 2500 technology. After applying conventional SNP-calling and quality-control filters, ~ 1.3 M high-quality SNPs were inferred and used as input for the iHS, Rsb and FST based methods. We detected several candidate genes putatively subjected to selection in each strain. A considerable number of these genes are associated with growth (e.g. NCAPG, KLF3, TBC1D1, TTN), early development (e.g. FGFR3, PFKFB3), and immunity traits (e.g. NLRC3, PIGR, MAP1S). These candidate genes represent putative genomic landmarks that could be associated to traits of biological and commercial interest in farmed Nile tilapia.
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Affiliation(s)
- María I Cádiz
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Avenida Santa Rosa 11735, 8820808, La Pintana, Santiago, Chile.,Programa de Doctorado en Ciencias Silvoagropecuarias y Veterinarias, Campus Sur, Universidad de Chile, Santa Rosa 11315, 8820808, La Pintana, Santiago, Chile
| | - María E López
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Avenida Santa Rosa 11735, 8820808, La Pintana, Santiago, Chile.,Department of Animal Breeding and Genetics, Swedish University of Agriculturall Sciences, Uppsala, Sweden
| | - Diego Díaz-Domínguez
- Departamento de Ciencias de la Computación, Universidad de Chile, Santiago, Chile
| | - Giovanna Cáceres
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Avenida Santa Rosa 11735, 8820808, La Pintana, Santiago, Chile.,Programa de Doctorado en Ciencias Silvoagropecuarias y Veterinarias, Campus Sur, Universidad de Chile, Santa Rosa 11315, 8820808, La Pintana, Santiago, Chile
| | - Grazyella M Yoshida
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Avenida Santa Rosa 11735, 8820808, La Pintana, Santiago, Chile
| | - Daniel Gomez-Uchida
- Facultad de Ciencias Naturales y Oceanográficas, Universidad de Concepción, Concepción, Chile.,Núcleo Milenio INVASAL, Concepción, Chile
| | - José M Yáñez
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Avenida Santa Rosa 11735, 8820808, La Pintana, Santiago, Chile. .,Núcleo Milenio INVASAL, Concepción, Chile.
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39
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A positively selected FBN1 missense variant reduces height in Peruvian individuals. Nature 2020; 582:234-239. [PMID: 32499652 PMCID: PMC7410362 DOI: 10.1038/s41586-020-2302-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 03/10/2020] [Indexed: 01/21/2023]
Abstract
On average, Peruvian individuals are among the shortest in the world1. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru.
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40
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Mathieson I. Human adaptation over the past 40,000 years. Curr Opin Genet Dev 2020; 62:97-104. [PMID: 32745952 PMCID: PMC7484260 DOI: 10.1016/j.gde.2020.06.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 05/10/2020] [Accepted: 06/01/2020] [Indexed: 02/07/2023]
Abstract
Over the past few years several methodological and data-driven advances have greatly improved our ability to robustly detect genomic signatures of selection in humans. New methods applied to large samples of present-day genomes provide increased power, while ancient DNA allows precise estimation of timing and tempo. However, despite these advances, we are still limited in our ability to translate these signatures into understanding about which traits were actually under selection, and why. Combining information from different populations and timescales may allow interpretation of selective sweeps. Other modes of selection have proved more difficult to detect. In particular, despite strong evidence of the polygenicity of most human traits, evidence for polygenic selection is weak, and its importance in recent human evolution remains unclear. Balancing selection and archaic introgression seem important for the maintenance of potentially adaptive immune diversity, but perhaps less so for other traits.
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Affiliation(s)
- Iain Mathieson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, United States.
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41
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Murga-Moreno J, Coronado-Zamora M, Bodelón A, Barbadilla A, Casillas S. PopHumanScan: the online catalog of human genome adaptation. Nucleic Acids Res 2020; 47:D1080-D1089. [PMID: 30335169 PMCID: PMC6323894 DOI: 10.1093/nar/gky959] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Accepted: 10/04/2018] [Indexed: 12/20/2022] Open
Abstract
Since the migrations that led humans to colonize Earth, our species has faced frequent adaptive challenges that have left signatures in the landscape of genetic variation and that we can identify in our today’s genomes. Here, we (i) perform an outlier approach on eight different population genetic statistics for 22 non-admixed human populations of the Phase III of the 1000 Genomes Project to detect selective sweeps at different historical ages, as well as events of recurrent positive selection in the human lineage; and (ii) create PopHumanScan, an online catalog that compiles and annotates all candidate regions under selection to facilitate their validation and thoroughly analysis. Well-known examples of human genetic adaptation published elsewhere are included in the catalog, as well as hundreds of other attractive candidates that will require further investigation. Designed as a collaborative database, PopHumanScan aims to become a central repository to share information, guide future studies and help advance our understanding of how selection has modeled our genomes as a response to changes in the environment or lifestyle of human populations. PopHumanScan is open and freely available at https://pophumanscan.uab.cat.
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Affiliation(s)
- Jesús Murga-Moreno
- Institut de Biotecnologia i de Biomedicina and Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
| | - Marta Coronado-Zamora
- Institut de Biotecnologia i de Biomedicina and Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
| | - Alejandra Bodelón
- Institut de Biotecnologia i de Biomedicina and Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
| | - Antonio Barbadilla
- Institut de Biotecnologia i de Biomedicina and Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
| | - Sònia Casillas
- Institut de Biotecnologia i de Biomedicina and Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
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42
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Harris AM, DeGiorgio M. Identifying and Classifying Shared Selective Sweeps from Multilocus Data. Genetics 2020; 215:143-171. [PMID: 32152048 PMCID: PMC7198270 DOI: 10.1534/genetics.120.303137] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 02/29/2020] [Indexed: 11/18/2022] Open
Abstract
Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term [Formula: see text] and [Formula: see text] to further classify identified shared sweeps as hard or soft. Finally, we identified both previously reported and novel shared sweep candidates from human whole-genome sequences. Previously reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.
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Affiliation(s)
- Alexandre M Harris
- Department of Biology, Pennsylvania State University, University Park, Pennsylvania 16802
- Molecular, Cellular, and Integrative Biosciences at the Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802
| | - Michael DeGiorgio
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida 33431
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43
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Terekhanova NV, Barmintseva AE, Kondrashov AS, Bazykin GA, Mugue NS. Architecture of Parallel Adaptation in Ten Lacustrine Threespine Stickleback Populations from the White Sea Area. Genome Biol Evol 2020; 11:2605-2618. [PMID: 31406984 PMCID: PMC6761963 DOI: 10.1093/gbe/evz175] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/10/2019] [Indexed: 12/20/2022] Open
Abstract
Adaptation of threespine stickleback to freshwater involves parallel recruitment of freshwater alleles in clusters of closely linked sites, or divergence islands (DIs). However, it remains unclear to what extent the DIs and the alleles that constitute them coincide between populations that underwent adaptation to freshwater independently. We examine threespine sticklebacks from ten freshwater lakes that emerged 500–1500 years ago in the White Sea basin, with the emphasis on repeatability of genomic patterns of adaptation among the lake populations and the role of local recombination rate in the distribution and structure of DIs. The 65 detected DIs are clustered in the genome, forming 12 aggregations, and this clustering cannot be explained by the variation of the recombination rate. Only 21 of the DIs are present in all the freshwater populations, likely being indispensable for successful colonization of freshwater environment by the ancestral marine population. Within most DIs, the same set of single nucleotide polymorphisms (SNPs) distinguish marine and freshwater haplotypes in all the lake populations; however, in some DIs, freshwater alleles differ between populations, suggesting that they could have been established by recruitment of different haplotypes in different populations.
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Affiliation(s)
- Nadezhda V Terekhanova
- Skolkovo Institute of Science and Technology, Skolkovo, Russia.,Sector for Molecular Evolution, Institute for Information Transmission Problems of the RAS (Kharkevich Institute), Moscow, Russia
| | - Anna E Barmintseva
- Laboratory of Molecular Genetics, Russian Federal Research Institute of Fisheries and Oceanography, Moscow, Russia
| | - Alexey S Kondrashov
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan.,M. V. Lomonosov Moscow State University, Moscow, Russia
| | - Georgii A Bazykin
- Skolkovo Institute of Science and Technology, Skolkovo, Russia.,Sector for Molecular Evolution, Institute for Information Transmission Problems of the RAS (Kharkevich Institute), Moscow, Russia
| | - Nikolai S Mugue
- Laboratory of Molecular Genetics, Russian Federal Research Institute of Fisheries and Oceanography, Moscow, Russia.,N. K. Koltzov Institute of Developmental Biology RAS, Moscow, Russia
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44
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Matoba N, Akiyama M, Ishigaki K, Kanai M, Takahashi A, Momozawa Y, Ikegawa S, Ikeda M, Iwata N, Hirata M, Matsuda K, Murakami Y, Kubo M, Kamatani Y, Okada Y. GWAS of 165,084 Japanese individuals identified nine loci associated with dietary habits. Nat Hum Behav 2020; 4:308-316. [PMID: 31959922 DOI: 10.1038/s41562-019-0805-1] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 12/03/2019] [Indexed: 01/02/2023]
Abstract
Dietary habits are important factors in our lifestyle, and confer both susceptibility to and protection from a variety of human diseases. We performed genome-wide association studies for 13 dietary habits including consumption of alcohol (ever versus never drinkers and drinks per week), beverages (coffee, green tea and milk) and foods (yoghurt, cheese, natto, tofu, fish, small whole fish, vegetables and meat) in Japanese individuals (n = 58,610-165,084) collected by BioBank Japan, the nationwide hospital-based genome cohort. Significant associations were found in nine genetic loci (MCL1-ENSA, GCKR, AGR3-AHR, ADH1B, ALDH1B1, ALDH1A1, ALDH2, CYP1A2-CSK and ADORA2A-AS1) for 13 dietary traits (P < 3.8 × 10-9). Of these, ten associations between five loci and eight traits were new findings. Furthermore, a phenome-wide association study revealed that five of the dietary trait-associated loci have pleiotropic effects on multiple human complex diseases and clinical measurements. Our findings provide new insight into the genetics of habitual consumption.
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Affiliation(s)
- Nana Matoba
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.,Department of Genetics, UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.,Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masahiro Kanai
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Atsushi Takahashi
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.,Department of Genomic Medicine, Research Institute, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Integrative Medical Sciences, Tokyo, Japan
| | - Masashi Ikeda
- Department of Psychiatry, Fujita Health University School of Medicine, Toyotake, Japan
| | - Nakao Iwata
- Department of Psychiatry, Fujita Health University School of Medicine, Toyotake, Japan
| | - Makoto Hirata
- Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Koichi Matsuda
- Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinori Murakami
- Division of Molecular Pathology, the Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan. .,Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan. .,Laboratory of Statistical Immunology, Immunology Frontier Research Center, Osaka University, Suita, Japan. .,Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan.
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45
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Chavez DE, Gronau I, Hains T, Kliver S, Koepfli KP, Wayne RK. Comparative genomics provides new insights into the remarkable adaptations of the African wild dog (Lycaon pictus). Sci Rep 2019; 9:8329. [PMID: 31171819 PMCID: PMC6554312 DOI: 10.1038/s41598-019-44772-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 05/22/2019] [Indexed: 12/02/2022] Open
Abstract
Within the Canidae, the African wild dog (Lycaon pictus) is the most specialized with regards to cursorial adaptations (specialized for running), having only four digits on their forefeet. In addition, this species is one of the few canids considered to be an obligate meat-eater, possessing a robust dentition for taking down large prey, and displays one of the most variable coat colorations amongst mammals. Here, we used comparative genomic analysis to investigate the evolutionary history and genetic basis for adaptations associated with cursoriality, hypercanivory, and coat color variation in African wild dogs. Genome-wide scans revealed unique amino acid deletions that suggest a mode of evolutionary digit loss through expanded apoptosis in the developing first digit. African wild dog-specific signals of positive selection also uncovered a putative mechanism of molar cusp modification through changes in genes associated with the sonic hedgehog (SHH) signaling pathway, required for spatial patterning of teeth, and three genes associated with pigmentation. Divergence time analyses suggest the suite of genomic changes we identified evolved ~1.7 Mya, coinciding with the diversification of large-bodied ungulates. Our results show that comparative genomics is a powerful tool for identifying the genetic basis of evolutionary changes in Canidae.
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Affiliation(s)
- Daniel E Chavez
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, 90095, USA.
| | - Ilan Gronau
- Efi Arazi School of Computer Science, Herzliya Interdisciplinary Center (IDC), Herzliya, 46150, Israel
| | - Taylor Hains
- Environmental Science and Policy, Johns Hopkins University, Washington, D.C., 20036, USA
| | - Sergei Kliver
- Institute of Molecular and Cellular Biology, Novosibirsk, 630090, Russian Federation
| | - Klaus-Peter Koepfli
- Smithsonian Conservation Biology Institute, National Zoological Park, Washington, D.C., 20008, USA
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, Saint Petersburg, 199034, Russian Federation
| | - Robert K Wayne
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, 90095, USA
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46
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James WPT, Johnson RJ, Speakman JR, Wallace DC, Frühbeck G, Iversen PO, Stover PJ. Nutrition and its role in human evolution. J Intern Med 2019; 285:533-549. [PMID: 30772945 DOI: 10.1111/joim.12878] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Our understanding of human evolution has improved rapidly over recent decades, facilitated by large-scale cataloguing of genomic variability amongst both modern and archaic humans. It seems clear that the evolution of the ancestors of chimpanzees and hominins separated 7-9 million years ago with some migration out of Africa by the earlier hominins; Homo sapiens slowly emerged as climate change resulted in drier, less forested African conditions. The African populations expanded and evolved in many different conditions with slow mutation and selection rates in the human genome, but with much more rapid mutation occurring in mitochondrial DNA. We now have evidence stretching back 300 000 years of humans in their current form, but there are clearly four very different large African language groups that correlate with population DNA differences. Then, about 50 000-100 000 years ago a small subset of modern humans also migrated out of Africa resulting in a persistent signature of more limited genetic diversity amongst non-African populations. Hybridization with archaic hominins occurred around this time such that all non-African modern humans possess some Neanderthal ancestry and Melanesian populations additionally possess some Denisovan ancestry. Human populations both within and outside Africa also adapted to diverse aspects of their local environment including altitude, climate, UV exposure, diet and pathogens, in some cases leaving clear signatures of patterns of genetic variation. Notable examples include haemoglobin changes conferring resistance to malaria, other immune changes and the skin adaptations favouring the synthesis of vitamin D. As humans migrated across Eurasia, further major mitochondrial changes occurred with some interbreeding with ancient hominins and the development of alcohol intolerance. More recently, an ability to retain lactase persistence into adulthood has evolved rapidly under the environmental stimulus of pastoralism with the ability to husband lactating ruminants. Increased amylase copy numbers seem to relate to the availability of starchy foods, whereas the capacity to desaturase and elongate monounsaturated fatty acids in different societies seems to be influenced by whether there is a lack of supply of readily available dietary sources of long-chain polyunsaturated fatty acids. The process of human evolution includes genetic drift and adaptation to local environments, in part through changes in mitochondrial and nuclear DNA. These genetic changes may underlie susceptibilities to some modern human pathologies including folate-responsive neural tube defects, diabetes, other age-related pathologies and mental health disorders.
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Affiliation(s)
- W P T James
- London School of Hygiene and Tropical Medicine, London, UK
| | - R J Johnson
- Division of Renal Diseases and Hypertension, University of Colorado, Denver, CO, USA
| | - J R Speakman
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - D C Wallace
- Mitochondrial and Epigenomic Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA, USA
| | - G Frühbeck
- Endocrinology and Nutrition, Clinica Universidad de Navarra, Pamplona, Spain
| | - P O Iversen
- Department of Nutrition, University of Oslo, Oslo, Norway
| | - P J Stover
- Vice Chancellor and Dean for Agriculture and Life Sciences, Texas A&M AgriLife, College Station, TX, USA
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47
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Algady W, Louzada S, Carpenter D, Brajer P, Färnert A, Rooth I, Ngasala B, Yang F, Shaw MA, Hollox EJ. The Malaria-Protective Human Glycophorin Structural Variant DUP4 Shows Somatic Mosaicism and Association with Hemoglobin Levels. Am J Hum Genet 2018; 103:769-776. [PMID: 30388403 PMCID: PMC6218809 DOI: 10.1016/j.ajhg.2018.10.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Accepted: 10/04/2018] [Indexed: 01/23/2023] Open
Abstract
Glycophorin A and glycophorin B are red blood cell surface proteins and are both receptors for the parasite Plasmodium falciparum, which is the principal cause of malaria in sub-Saharan Africa. DUP4 is a complex structural genomic variant that carries extra copies of a glycophorin A-glycophorin B fusion gene and has a dramatic effect on malaria risk by reducing the risk of severe malaria by up to 40%. Using fiber-FISH and Illumina sequencing, we validate the structural arrangement of the glycophorin locus in the DUP4 variant and reveal somatic variation in copy number of the glycophorin B-glycophorin A fusion gene. By developing a simple, specific, PCR-based assay for DUP4, we show that the DUP4 variant reaches a frequency of 13% in the population of a malaria-endemic village in south-eastern Tanzania. We genotype a substantial proportion of that village and demonstrate an association of DUP4 genotype with hemoglobin levels, a phenotype related to malaria, using a family-based association test. Taken together, we show that DUP4 is a complex structural variant that may be susceptible to somatic variation and show that DUP4 is associated with a malarial-related phenotype in a longitudinally followed population.
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Affiliation(s)
- Walid Algady
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, UK
| | - Sandra Louzada
- Wellcome Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Danielle Carpenter
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, UK
| | - Paulina Brajer
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, UK
| | - Anna Färnert
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, 17176 Stockholm, Sweden; Department of Infectious Diseases, Karolinska University Hospital, Stockholm 17176, Sweden
| | - Ingegerd Rooth
- Nyamisati Malaria Research, Rufiji, National Institute for Medical Research, Dar-es-Salaam, Tanzania
| | - Billy Ngasala
- Department of Parasitology and Medical Entomology, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania; Department of Women's and Children's Health, International Maternal and Child Health (IMCH), Uppsala Universitet, 75185 Uppsala, Sweden
| | - Fengtang Yang
- Wellcome Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Marie-Anne Shaw
- Leeds Institute of Medical Research at St James's, University of Leeds, Leeds LS9 7TF, UK
| | - Edward J Hollox
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, UK.
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Gu S, Li H, Pakstis AJ, Speed WC, Gurwitz D, Kidd JR, Kidd KK. Recent Selection on a Class I ADH Locus Distinguishes Southwest Asian Populations Including Ashkenazi Jews. Genes (Basel) 2018; 9:genes9090452. [PMID: 30205534 PMCID: PMC6162407 DOI: 10.3390/genes9090452] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 08/21/2018] [Accepted: 08/21/2018] [Indexed: 12/29/2022] Open
Abstract
The derived human alcohol dehydrogenase (ADH)1B*48His allele of the ADH1B Arg48His polymorphism (rs1229984) has been identified as one component of an East Asian specific core haplotype that underwent recent positive selection. Our study has been extended to Southwest Asia and additional markers in East Asia. Fst values (Sewall Wright’s fixation index) and long-range haplotype analyses identify a strong signature of selection not only in East Asian but also in Southwest Asian populations. However, except for the ADH2B*48His allele, different core haplotypes occur in Southwest Asia compared to East Asia and the extended haplotypes also differ. Thus, the ADH1B*48His allele, as part of a core haplotype of 10 kb, has undergone recent rapid increases in frequency independently in the two regions after divergence of the respective populations. Emergence of agriculture may be the common factor underlying the evident selection.
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Affiliation(s)
- Sheng Gu
- Department of Genetics, School of Medicine, Yale University, New Haven, CT 06520, USA.
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200433, China.
| | - Hui Li
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200433, China.
| | - Andrew J Pakstis
- Department of Genetics, School of Medicine, Yale University, New Haven, CT 06520, USA.
| | - William C Speed
- Department of Genetics, School of Medicine, Yale University, New Haven, CT 06520, USA.
| | - David Gurwitz
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
| | - Judith R Kidd
- Department of Genetics, School of Medicine, Yale University, New Haven, CT 06520, USA.
| | - Kenneth K Kidd
- Department of Genetics, School of Medicine, Yale University, New Haven, CT 06520, USA.
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49
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Leveraging GWAS for complex traits to detect signatures of natural selection in humans. Curr Opin Genet Dev 2018; 53:9-14. [PMID: 29913353 DOI: 10.1016/j.gde.2018.05.012] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 05/29/2018] [Accepted: 05/31/2018] [Indexed: 02/08/2023]
Abstract
Natural selection can shape the genetic architecture of complex traits. In human populations, signals of positive selection at genetic loci have been detected through a variety of genome-wide scanning approaches without the knowledge of how genes affect traits or fitness. In the past decade, genome-wide association studies (GWAS) have provided unprecedented insights into the genetic basis of quantitative variation in complex traits. Summary statistics generated from these GWAS have been shown to be an extraordinary data source that can be utilized to detect and quantify natural selection in the genetic architecture of complex traits. In this review, we focus on recent discoveries about selection on genetic variants associated with human complex traits based on GWAS-facilitated methods.
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