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Abstract
We developed dbCNS (http://yamasati.nig.ac.jp/dbcns), a new database for conserved noncoding sequences (CNSs). CNSs exist in many eukaryotes and are assumed to be involved in protein expression control. Version 1 of dbCNS, introduced here, includes a powerful and precise CNS identification pipeline for multiple vertebrate genomes. Mutations in CNSs may induce morphological changes and cause genetic diseases. For this reason, many vertebrate CNSs have been identified, with special reference to primate genomes. We integrated ∼6.9 million CNSs from many vertebrate genomes into dbCNS, which allows users to extract CNSs near genes of interest using keyword searches. In addition to CNSs, dbCNS contains published genome sequences of 161 species. With purposeful taxonomic sampling of genomes, users can employ CNSs as queries to reconstruct CNS alignments and phylogenetic trees, to evaluate CNS modifications, acquisitions, and losses, and to roughly identify species with CNSs having accelerated substitution rates. dbCNS also produces links to dbSNP for searching pathogenic single-nucleotide polymorphisms in human CNSs. Thus, dbCNS connects morphological changes with genetic diseases. A test analysis using 38 gnathostome genomes was accomplished within 30 s. dbCNS results can evaluate CNSs identified by other stand-alone programs using genome-scale data.
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Affiliation(s)
- Jun Inoue
- Population Genetics Laboratory, Department of Genomics and Evolutionary Biology, National Institute of Genetics, Mishima, Japan.,Center for Earth Surface System Dynamics, Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan
| | - Naruya Saitou
- Population Genetics Laboratory, Department of Genomics and Evolutionary Biology, National Institute of Genetics, Mishima, Japan.,Department of Okinawa Bioinformation Bank, Faculty of Medicine, University of the Ryukyus, Okinawa, Japan
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2
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Wang Y, Jiang T, Tang P, Wu Y, Jiang Z, Dai J, Gu Y, Xu J, Da M, Ma H, Jin G, Mo X, Li Q, Wang X, Hu Z. Family-based whole-genome sequencing identifies compound heterozygous protein-coding and noncoding mutations in tetralogy of Fallot. Gene 2020; 741:144555. [PMID: 32165302 DOI: 10.1016/j.gene.2020.144555] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 03/08/2020] [Indexed: 12/28/2022]
Abstract
Tetralogy of Fallot (TOF) is one of most serious cyanotic congenital heart disease (CHD) and the prevalence is estimated to be 1 in 3000 live births worldwide. Though multiple studies have found genetic variants as risk factors for TOF, they could only explain a small fraction of the pathogenesis. Here, we performed whole genome sequencing (WGS) for 6 individuals derived from 2 families to evaluate pathogenic mutations located in both coding and noncoding regions. We characterized the annotated deleterious coding mutations and impaired noncoding mutations in regulatory elements by various data analysis. Additionally, functional assays were conducted to validate function regulatory elements and noncoding mutations. Interestingly, a compound heterozygous pattern with pathogenic coding and noncoding mutations was identified in probands. In proband 1, biallelic mutations (g.139409115A > T, encoding p.Asn685Ile; g.139444949C > A) in NOTCH1 exon and its regulatory element were detected. In vitro experiments revealed that the regulatory element acted as a silencer and the noncoding mutation decreased the expression of NOTCH1. In proband 2, we also found compound heterozygous mutations (g. 216235029C > T, encoding p.Val2281Met; g. 216525154A > C) which potentially regulated the function of FN1 gene. In summary, our study firstly reported an instance of newly identified noncoding mutation in regulatory element within the compound heterozygous pattern in TOF. The results provided a deeper understanding of TOF genetic architectures.
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Affiliation(s)
- Yifeng Wang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 211166, China; Department of Epidemiology and Biostatistics, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Tao Jiang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 211166, China; Department of Epidemiology and Biostatistics, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Pushi Tang
- Department of Cardiovascular Center, The Second Affiliated Hospital of Nanjing Medical University, Nanjing 210000, China
| | - Yifei Wu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 211166, China; Department of Epidemiology and Biostatistics, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Zhu Jiang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 211166, China; Department of Epidemiology and Biostatistics, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Juncheng Dai
- Department of Epidemiology and Biostatistics, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Yayun Gu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 211166, China; Department of Epidemiology and Biostatistics, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Jing Xu
- Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Min Da
- Department of Cardiothoracic Surgery, Children's Hospital of Nanjing Medical University, Nanjing 210008, China
| | - Hongxia Ma
- Department of Epidemiology and Biostatistics, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Guangfu Jin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 211166, China; Department of Epidemiology and Biostatistics, Center for Global Health, Nanjing Medical University, Nanjing 211166, China
| | - Xuming Mo
- Department of Cardiothoracic Surgery, Children's Hospital of Nanjing Medical University, Nanjing 210008, China
| | - Qingguo Li
- Department of Cardiovascular Center, The Second Affiliated Hospital of Nanjing Medical University, Nanjing 210000, China.
| | - Xiaowei Wang
- Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 211166, China; Department of Epidemiology and Biostatistics, Center for Global Health, Nanjing Medical University, Nanjing 211166, China.
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Abstract
During the course of evolution the human brain has increased in size and complexity, ultimately these differences are the result of changes at the genetic level. Identifying and characterizing molecular evolution requires an understanding of both the genetic underpinning of the system as well as the comparative genetic tools to identify signatures of selection. This chapter aims to describe our current understanding of the genetics of human brain evolution. Primarily this is the story of the evolution of the human brain since our last common ape ancestor, but where relevant we will also discuss changes that are unique to the primate brain (compared to other mammals) or various other lineages in the evolution of humans more generally. It will focus on genetic changes that both directly affected the development and function of the brain as well as those that have indirectly influenced brain evolution through both prenatal and postnatal environment. This review is not meant to be exhaustive, but rather to begin to construct a general framework for understanding the full array of data being generated.
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Affiliation(s)
- Eric J Vallender
- University of Mississippi Medical Center, Jackson, MS, United States; Tulane National Primate Research Center, Covington, LA, United States.
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Saitou N. Neutral Evolution. INTRODUCTION TO EVOLUTIONARY GENOMICS 2018. [PMCID: PMC7121930 DOI: 10.1007/978-3-319-92642-1_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Neutral evolution is the default process of genomic changes. This is because our world is finite, and the randomness, indispensable for neutral evolution, is important when we consider the history of a finite world. The random nature of DNA propagation is discussed using branching process, coalescent process, Markov process, and diffusion process. Expected evolutionary patterns under neutrality are then discussed on fixation probability, rate of evolution, and amount of DNA variation kept in population. We then discuss various features of neutral evolution starting from evolutionary rates, synonymous and nonsynonymous substitutions, junk DNA, and pseudogenes.
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Affiliation(s)
- Naruya Saitou
- Division of Population Genetics, National Institute of Genetics (NIG), Mishima, Shizuoka Japan
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