Comparative Analysis Of Completely Sequenced Genomes

完全测序的基因组的比较分析

• 批准号: 9160910
• 负责人: Eugene V Koonin
• 金额: $ 30.47万
• 依托单位: NATIONAL LIBRARY OF MEDICINE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9160910
• 关键词: Accounting; Adopted; Affect; Animals; Archaea; Bacteria; Bacteriophages; Beryllium; Clustered Regularly Interspaced Short Palindromic Repeats; Collection; Computing Methodologies; Data; Databases; Double Stranded DNA Virus; Double Stranded RNA Virus; Double-Stranded RNA; Elements; Eukaryota; Evolution; Family; Gene Frequency; Genes; Genetic Variation; Genome; Genome engineering; Genomics; Goals; Horizontal Gene Transfer; Immune system; Immunoglobulin Genes; Individual; Life; Methods; Minority; Mobile Genetic Elements; Modeling; Modification; Nature; Organism; Orthologous Gene; Phylogenetic Analysis; Phylogeny; Plant Roots; Plasmids; Probability; Process; Prokaryotic Cells; RNA Viruses; Recording of previous events; Relative (related person); Research; Retroelements; Role; Sampling; Single Stranded DNA Virus; Source; Surveys; System; Technology; Tectiviruses; Theoretical Studies; Trees; V(D)J Recombination; Vertebrates; Viral; Virion; Virus; adaptive immunity; comparative; ds-DNA; experience; fusion gene; genetic element; genome editing; genome sequencing; genome-wide; insight; long term memory; mathematical methods; mathematical model; paralogous gene; plasmid DNA; recombinase; tool; trend; virome

The rapidly growing database of completely and nearly completely sequenced genomes of bacteria, archaea, eukaryotes and viruses (several thousand genomes already available and many more in progress) creates both new opportunities and new challenges for genome research. During the last year, we performed a variety of studies that took advantage of the genomic information to establish fundamental principles of genome evolution. A comprehensive phylogenomic analysis of viruses infecting eukaryotic hosts and the related mobile elements was performed. Viruses and other selfish genetic elements are dominant entities in the biosphere, with respect to both physical abundance and genetic diversity. Various selfish elements parasitize on all cellular life forms. The relative abundances of different classes of viruses are dramatically different between prokaryotes and eukaryotes. In prokaryotes, the great majority of viruses possess double-stranded (ds) DNA genomes, with a substantial minority of single-stranded (ss) DNA viruses and only limited presence of RNA viruses. In contrast, in eukaryotes, RNA viruses account for the majority of the virome diversity although ssDNA and dsDNA viruses are common as well. Phylogenomic analysis yields tangible clues for the origins of major classes of eukaryotic viruses and in particular their likely roots in prokaryotes. Specifically, the ancestral genome of positive-strand RNA viruses of eukaryotes might have been assembled de novo from genes derived from prokaryotic retroelements and bacteria although a primordial origin of this class of viruses cannot be ruled out. Different groups of double-stranded RNA viruses derive either from dsRNA bacteriophages or from positive-strand RNA viruses. The eukaryotic ssDNA viruses apparently evolved via a fusion of genes from prokaryotic rolling circle-replicating plasmids and positive-strand RNA viruses. Different families of eukaryotic dsDNA viruses appear to have originated from specific groups of bacteriophages on at least two independent occasions. Polintons, the largest known eukaryotic transposons, predicted to also form virus particles, most likely, were the evolutionary intermediates between bacterial tectiviruses and several groups of eukaryotic dsDNA viruses including the proposed order "Megavirales" that unites diverse families of large and giant viruses. Strikingly, evolution of all classes of eukaryotic viruses appears to have involved fusion between structural and replicative gene modules derived from different sources along with additional acquisitions of diverse genes. We developed a general scenario of evolution of adaptive immunity systems and possibly other genome manipulation machineries from mobile genetic elements. Adaptive immune systems in prokaryotes and animals give rise to long-term memory through modification of specific genomic loci, such as by insertion of foreign (viral or plasmid) DNA fragments into clustered regularly interspaced short palindromic repeat (CRISPR) loci in prokaryotes and by V(D)J recombination of immunoglobulin genes in vertebrates. Strikingly, recombinases derived from unrelated mobile genetic elements have essential roles in both prokaryotic and vertebrate adaptive immune systems. Mobile elements, which are ubiquitous in cellular life forms, provide the only known, naturally evolved tools for genome engineering that are successfully adopted by both innate immune systems and genome-editing technologies. We performed a theoretical study of the evolution of bacterial and archaeal supergenomes. Because prokaryotic genomes experience a rapid flux of genes, selection may act at a higher level than an individual genome. We explore a quantitative model of the distributed genome whereby groups of genomes evolve by acquiring genes from a fixed reservoir which we denote as supergenome. Previous attempts to understand the nature of the supergenome treated genomes as random, independent collections of genes and assumed that the supergenome consists of a small number of homogeneous sub-reservoirs. Here we explore the consequences of relaxing both assumptions. We surveyed several methods for estimating the size and composition of the supergenome. The methods assumed that genomes were either random, independent samples of the supergenome or that they evolved from a common ancestor along a known tree via stochastic sampling from the reservoir. The reservoir was assumed to be either a collection of homogeneous sub-reservoirs or alternatively composed of genes with Gamma distributed gain probabilities. Empirical gene frequencies were used to either compute the likelihood of the data directly or first to reconstruct the history of gene gains and then compute the likelihood of the reconstructed numbers of gains. Supergenome size estimates using the empirical gene frequencies directly are not robust with respect to the choice of the model. By contrast, using the gene frequencies and the phylogenetic tree to reconstruct multiple gene gains produces reliable estimates of the supergenome size and indicates that a homogeneous supergenome is more consistent with the data than a supergenome with Gamma distributed gain probabilities. Taken together, these studies advance the existing understanding of the genome evolution in diverse life forms, in particular viruses and mobile elements, and provide new insights into general principles of genome evolution.

细菌、古细菌、真核生物和病毒的完全和几乎完全测序的基因组数据库的快速增长（已有数千个基因组，还有更多基因组正在开发中）为基因组研究创造了新的机遇和新的挑战。去年，我们进行了各种研究，利用基因组信息来建立基因组进化的基本原理。 对感染真核宿主的病毒和相关的移动元件进行了全面的系统发育分析。就物理丰度和遗传多样性而言，病毒和其他自私的遗传元素是生物圈中的主导实体。各种自私的元素寄生在所有的细胞生命体上。不同类别病毒的相对丰度在原核生物和真核生物之间存在显着差异。在原核生物中，绝大多数病毒具有双链 (ds) DNA 基因组，少数具有单链 (ss) DNA 病毒，仅存在有限的 RNA 病毒。相比之下，在真核生物中，尽管 ssDNA 和 dsDNA 病毒也很常见，但 RNA 病毒占病毒组多样性的大部分。系统基因组分析为主要真核病毒类别的起源，特别是它们可能起源于原核生物提供了切实的线索。具体来说，真核生物正链RNA病毒的祖先基因组可能是由原核逆转录因子和细菌的基因从头组装而成，尽管不能排除此类病毒的原始起源。不同组的双链RNA病毒源自dsRNA噬菌体或正链RNA病毒。真核单链DNA病毒显然是通过原核滚环复制质粒和正链RNA病毒的基因融合进化而来。不同的真核双链 DNA 病毒家族似乎至少在两次独立的情况下起源于特定的噬菌体群体。波林顿（Polintons）是已知最大的真核转座子，预计也能形成病毒颗粒，很可能是细菌四层病毒和几组真核双链DNA病毒之间的进化中间体，其中包括联合不同大型和巨型病毒家族的拟议目“Megavirales”。引人注目的是，所有类别的真核病毒的进化似乎都涉及来自不同来源的结构和复制基因模块之间的融合以及不同基因的额外获得。 我们从移动遗传元件中开发了适应性免疫系统和可能的其他基因组操纵机制进化的一般情景。原核生物和动物的适应性免疫系统通过修改特定基因组位点来产生长期记忆，例如通过将外源（病毒或质粒）DNA片段插入原核生物中成簇的规则间隔的短回文重复（CRISPR）位点，以及通过脊椎动物中免疫球蛋白基因的V（D）J重组。引人注目的是，源自不相关的移动遗传元件的重组酶在原核和脊椎动物适应性免疫系统中都具有重要作用。移动元件在细胞生命形式中普遍存在，为基因组工程提供了唯一已知的、自然进化的工具，并已被先天免疫系统和基因组编辑技术成功采用。 我们对细菌和古细菌超基因组的进化进行了理论研究。由于原核基因组经历基因的快速流动，选择可能在比个体基因组更高的水平上发挥作用。我们探索了分布式基因组的定量模型，通过该模型，基因组组通过从固定库（我们将其称为超基因组）获取基因来进化。之前理解超基因组本质的尝试将基因组视为随机、独立的基因集合，并假设超基因组由少量同质子库组成。在这里，我们探讨放松这两个假设的后果。 我们调查了几种估计超基因组大小和组成的方法。这些方法假设基因组要么是超基因组的随机、独立样本，要么是通过从水库随机采样沿已知树从共同祖先进化而来。假设储层是同质子储层的集合，或者由具有伽玛分布增益概率的基因组成。经验基因频率用于直接计算数据的可能性，或者首先重建基因增益的历史，然后计算重建的增益数量的可能性。直接使用经验基因频率估计的超基因组大小对于模型的选择来说并不稳健。相比之下，使用基因频率和系统发育树来重建多个基因增益可以产生对超基因组大小的可靠估计，并表明同质超基因组比具有 Gamma 分布增益概率的超基因组与数据更一致。 总而言之，这些研究推进了对不同生命形式（特别是病毒和移动元件）中基因组进化的现有理解，并为基因组进化的一般原理提供了新的见解。