水稻Trihelix转录因子家族全基因组分析及功能预测

Trihelix转录因子家族在植物生长发育以及响应逆境胁迫等方面发挥着重要作用,但目前基于水稻全基因组水平鉴定和分析该基因家族的研究尚未见相关报道。本文利用生物信息学方法在水稻基因组数据库中鉴定到Trihelix家族成员31个,序列聚类和功能结构域分析发现该家族均含有高度保守的、特征性的Trihelix结构域;根据亲缘关系远近和结构域特点,将其分为5个亚家族(Ⅰ~Ⅴ)。通过与拟南芥、二穗短炳草和高粱中Trihelix家族的聚类分析发现,这4个物种中Trihelix家族的分类相一致,但每个物种均含有不同亚家族的成员,表明该基因家族的分化早于物种的分化。基于MEME程序分析水稻Trihelix转录因子家族的保守基序与聚类分析结果具有较高的一致性。染色体区段复制分析表明,部分Trihelix家族成员在水稻以及水稻与其他物种之间存在种内和种间的染色体区段复制;生物芯片数据分析发现,Trihelix基因家族在水稻不同组织中、以及对6种不同植物激素的响应呈现多样化的表达谱。采用RiceFREND在线数据库分析发现,水稻Trihelix转录因子家族的20个成员与其他蛋白存在互作关系。本研究结果初步明确了水稻Trihelix转录因子家族的进化特点、染色体分布、染色体区段复制关系、组织表达、激素应答,以及该家族蛋白与其他蛋白质的互作情况,为进一步揭示Trihelix转录因子家族的分子进化规律和生物学功能奠定了基础。     

蛋白质结构域研究进展简述

蛋白质是由结构域组成的,结构域是蛋白质结构、功能和进化的单位。结构域通过复制和组合可以形成新的蛋白质,不同结构域间的组合分布并不符合随机模型,而是表现出有些结构域组合能力非常强,有些却很少与其他结构域组合的模式。为了研究结构域的这一组合特性,人们建立了结构域共出现网络。就结构域的定义、常用的结构域数据库以及杂凑性结构域进行了介绍,供感兴趣的初学者参考。     

基因组序列8-mer频次使用规律及与物种进化的关系

基因组序列k-mer的非随机使用规律及包含的生物学意义一直是人们关注的问题,目前还没有根本性进展。本文以七个物种的全部基因序列为样本,得到各物种基因组序列的8-mer频谱分布。发现狗和牛的频谱有三个峰,而斑马鱼、青鳉鱼、秀丽线虫和酿酒酵母的频谱只有一个峰,鸡的频谱分布形状介于两者之间。将8-mer集合按照XY二核苷含量分类,结果显示只有CG二核苷分类下0CG、1CG和2CG三类子集的频谱形成各自独立的单峰分布。对照随机序列,发现0CG模体是随机进化的,1CG和2CG模体是定向进化的,它们的使用频次远小于随机频次,且这种独立进化分离规律具有物种普适性。三个CG子集频谱之间的距离是产生单峰或多峰现象的根本原因。将七个物种基因组序列标准化到109bp,比较发现1CG和2CG子集频谱与物种进化显著相关,0CG子集频谱与物种进化无显著关系。可以认为三种CG模体各自执行着不同的生物学功能。基因组序列8-mer的独立分离规律为揭示基因组结构、基因组进化以及模体的生物功能提供了一种新的思维方式。     

放牧强度和地形对内蒙古典型草原物种多度分布的影响

为了更好地理解放牧对草原生态系统物种多度分布格局的影响, 以及常见种和稀有种对维持群落多样性的作用, 以内蒙古典型草原为研究对象, 基于长期放牧控制实验平台(包括7个载畜率水平(0、1.5、3.0、4.5、6.0、7.5、9.0 sheep·hm^-2)和两种地形系统(平地和坡地)), 研究了群落内全部物种、常见种和稀有种的丰富度和多度对放牧强度的响应规律, 并选取对数正态模型、对数级数模型和幂分割模型, 对物种多度数据进行拟合。结果表明: 1)平地系统中, 物种丰富度和多度在低放牧强度下(1.5、3.0 sheep·hm^-2)增加, 而在中、高度放牧强度下(4.5-9.0 sheep·hm^-2)降低, 全部物种的多度分布在大多数放牧强度下符合幂分割模型, 在高放牧强度下也符合对数正态模型; 坡地系统中, 物种丰富度和多度随着放牧强度增加而显著降低, 全部物种的多度分布在各个放牧强度下, 均符合幂分割模型和对数正态模型。2)随着放牧强度增加, 常见种的多度响应趋势与全部物种的响应趋势一致, 其多度分布均符合幂分割模型和对数正态模型; 稀有种的丰富度响应趋势与全部物种的响应趋势一致, 其多度分布符合幂分割模型, 同时也部分符合对数正态和对数级数模型。总之, 适宜的载畜率有利于生物多样性和初级生产力的提高, 平地系统中物种多度的响应在一定程度上支持放牧优化假说; 而坡地系统中不同物种多度的响应差异说明: 确定最佳载畜率时, 还需要考虑地形因素的影响。此外, 模型的拟合结果表明: 生态位分化机制对内蒙古典型草原物种多度分布起着主要作用, 常见种和稀有种通过不同的响应方式共同维持着草原生态系统的物种多样性。     

长白山阔叶红松林物种多度和空间分布格局的关系

应用随机分布多度模型和聚集分布多度模型,探讨不同研究尺度下物种多度和空间分布格局的关系.结果表明,预测的物种多度不仅受物种分布面积大小的影响,还受其聚集程度的影响.物种多度和空间分布格局的关系存在着明显的尺度效应,即随着研究尺度的增加,无论是随机分布多度模型还是聚集分布多度模型,通过物种空间分布格局来预测物种多度的准确度都在下降.聚集分布多度模型预测物种多度的结果要好于随机分布多度模型,这表明该区大多数物种是聚集分布的.由于物种的空间分布格局不同,不同物种多度的预测值和真实值之间的差异也不同.因此,为了进一步提高模型预测的准确性,进一步考虑不同物种的生活史特性是必要的.     

高等生物中基因组序列8-mer频谱分布模式及其在物种进化研究中的应用

基因组序列的8-mer频谱具有物种特异性,解读8-mer频谱内在规律,对于揭示基因组序列的结构组成和进化模式具有重要的意义。本研究统计了66个物种的8-mer频谱分布,发现高等哺乳动物8-mer频谱分布以三峰为主,鸟类和爬行类动物频谱分布以双峰为主,而鱼类和非脊椎类动物频谱分布以单峰为主。为了进一步研究基因组8-mer频谱的构成,使用16种XY二核苷分类方法。研究结果表明,只有在CG分类下具有以下两个特征：(1)CG0、 CG1和CG2子集的8-mer频谱呈现单峰分布,并且3个峰彼此分离;(2)相对随机中心位置,CG1和CG2子集频谱分布远离随机中心,CG0子集频谱分布在随机中心周围。为了进一步验证CG0、 CG1和CG2子集频谱分布与物种进化的关系,使用3个CG子集频谱的分离性指标构建了66个物种的系统发育树,该系统发育树将物种分为4个簇,分别为高等哺乳类、鸟类与爬行类、鱼类和非脊椎类。研究结果表明3个CG子集频谱分布与物种基因组进化信息密切相关。     

广西弄岗北热带喀斯特季节性雨林监测样地种群空间点格局分析

种群的空间分布格局是由多种机制的交互作用而形成,是探究生物多样性维持机制的基础。北热带喀斯特季节性雨林是我国北热带石灰岩山地具有地带性特征的植被,其生境的典型特征在于土层浅薄、岩石裸露率高、贮水能力低和周期性水淹,以及富钙强碱性环境等。本研究基于广西弄岗北热带喀斯特季节性雨林15 ha动态监测样地的第一次调查资料,采用双关联g(r)函数点格局方法,分析了雨林中出现个体数≥15株的160个种的种群空间分布格局以及不同类群间种群分布的差异。研究表明:160种木本植物中有146种在0–10 m的尺度上呈聚集分布,且随着空间尺度的增大,聚集度呈下降趋势;物种的种群聚集度与其物种多度、平均胸径和最大胸径成负相关;常绿物种的种群聚集度与落叶物种间差异不显著;不同生活型间的种群聚集度差异显著,总体表现为亚乔木层物种高于乔木层,灌木层物种显著高于亚乔木层;剔除生境异质性后大部分物种表现为随机分布,仅少部分物种的种群表现为聚集分布。这表明物种的功能属性如物种多度、生活型等可较好地预测物种的分布格局。此外,物种种群的分布格局还受生境异质性的影响,且不同物种受生境异质性影响的程度不同。     

物种丰富度垂直分布格局及影响机制

物种丰富度分布格局是一定地域内物种丰富度沿三维空间的立体分布,包括物种丰富度在经度、纬度和垂直梯度(海拔高度和海水深度)三个维度上的空间分异。近年来物种多样性的垂直分布格局与机制研究得到了生物地理学家和生态学家的重视。物种丰富度的垂直分布格局存在多种类型,但随海拔增加而物种数减少的单调递减模型和中海拔物种丰富度最高的单峰模型较为常见。目前在机制研究中验证较多的是气候稳定性、生物因子(种间相互作用)、能量、生境异质性、干扰、进化时间、物种分化速率、面积、中域效应(mid-domain effect)、生态位保守性(niche conservatism)等假说和机制。物种丰富度的分布格局是多方面因素综合作用的结果;由于地理、地形、气候、地质演化历史、物种库和进化历史、物种分化速率、干扰等差异,在不同地区存在着特别的物种丰富度空间分布格局和机制;处于同一地区的不同类群的物种也因进化扩散历史和生态适应能力不同而呈现多样化的分布格局。因此,对不同地区和类群的物种丰富度格局和机制进行研究应具体分析后才能得到可信结论。     

亚热带不同纬度森林群落物种空间分布格局

为探讨我国亚热带森林群落中物种空间分布格局特点及其成因,揭示其共性规律和个性差异,为相关区域的生物多样性保护和监测工作提供科学依据。选取我国亚热带不同纬度的6个1 hm²典型森林群落中所有胸径（DBH,Diameter at Breast Height）≥ 1 cm的物种为研究对象;采用L （t）方程统计所有监测物种的空间分布格局类型,为满足L （t）方程的统计精度,将各群落中多度≥10株的植物以物种为单位统计,多度<10株的低多度物种和单个体物种则以种组为单位进行空间点格局分析;并对物种多度、胸径与空间聚集程度的度量指标L₁₀进行相关性分析。结果表明：（1）亚热带不同纬度群落中多度≥10株物种的空间分布格局表现出相似的尺度依赖性规律：显著聚集分布比例随尺度增大而降低,不同纬度群落的变化幅度存在差异,纬度较低的群落稳定性更强。（2）各群落中低多度种组空间分布格局表现出小尺度显著聚集分布,大尺度随机分布的尺度效应,但尺度效应在不同纬度群落间存在差异;各群落的单个体种组空间分布格局均以随机分布为主。（3）不同纬度群落物种多度与空间聚集程度之间均存在负相关关系,物种多度对空间聚集程度的影响随纬度从高到低逐渐减弱。（4）较高纬度群落物种胸径与空间聚集程度之间存在负相关关系;随纬度从高到低,物种胸径对空间聚集程度影响水平逐渐降低。对亚热带不同纬度森林群落物种空间分布格局形成原因的进一步探讨,认为由纬度差异引起的生境异质性是影响群落物种空间分布格局产生过程的主要因素,此外,林型、扩散限制、密度制约和随机作用是影响各群落物种空间格局成因及多样性维持的次要因素。     

拟南芥DNA探针的比较基因组原位杂交揭示的拟南芥与远缘植物基因组间的同源性

采用生物素标记的拟南芥基因组DNA探针在75%杂交严谨度下对双子叶植物番茄、蚕豆和单子叶植物水稻、玉米、大麦的染色体进行了比较基因组荧光原位杂交（comparative genomic in situ hybridization,cGISH）分析,以揭示拟南芥与远缘植物基因组间的同源性.cGISH信号代表了拟南芥基因组DNA中的重复DNA与靶物种染色体上同源序列的杂交.探针DNA在所有靶物种的全部染色体上都产生了杂交信号.杂交信号为散在分布,并呈现随基因组增大,杂交信号增多,且分布更加分散的趋势.所有靶物种的核仁组织区（NOR）都显示了明显强于其他区域的杂交信号,表明拟南芥基因组DNA探针可用于植物NOR的物理定位.在所有的靶物种中,信号主要分布在染色体的臂中间区和末端,着丝粒或近着丝粒区有少数信号分布.大麦染色体显示了与C-和N-带不同的独特的cGISH信号带型,表明此探针可用于不同植物染色体的识别.这些结果表明,拟南芥基因组与远缘植物基因组之间,除rDNA和端粒重复序列外,还存在其它同源的重复DNA;一些重复DNA序列在被子植物分歧进化为单子叶和双子叶植物之前就已存在,虽经历了长期的进化过程,至今在远缘物种之间仍保持了较高的同源性.结果还提示,大基因组中古老而保守的重复DNA在进化过程中发生了明显的扩增.     

Eukaryotic signalling domain homologues in archaea and bacteria. Ancient ancestry and horizontal gene transfer.

Phyletic distributions of eukaryotic signalling domains were studied using recently developed sensitive methods for protein sequence analysis, with an emphasis on the detection and accurate enumeration of homologues in bacteria and archaea. A major difference was found between the distributions of enzyme families that are typically found in all three divisions of cellular life and non-enzymatic domain families that are usually eukaryote-specific. Previously undetected bacterial homologues were identified for# plant pathogenesis-related proteins, Pad1, von Willebrand factor type A, src homology 3 and YWTD repeat-containing domains. Comparisons of the domain distributions in eukaryotes and prokaryotes enabled distinctions to be made between the domains originating prior to the last common ancestor of all known life forms and those apparently originating as consequences of horizontal gene transfer events. A number of transfers of signalling domains from eukaryotes to bacteria were confidently identified, in contrast to only a single case of apparent transfer from eukaryotes to archaea.     

Prokaryotic Ancestry of Eukaryotic Protein Networks Mediating Innate Immunity and Apoptosis

Protein domains characteristic of eukaryotic innate immunity and apoptosis have many prokaryotic counterparts of unknown function. By reconstructing interactomes computationally, we found that bacterial proteins containing these domains are part of a network that also includes other domains not hitherto associated with immunity. This network is connected to the network of prokaryotic signal transduction proteins, such as histidine kinases and chemoreceptors. The network varies considerably in domain composition and degree of paralogy, even between strains of the same species, and its repetitive domains are often amplified recently, with individual repeats sharing up to 100% sequence identity. Both phenomena are evidence of considerable evolutionary pressure and thus compatible with a role in the “arms race” between host and pathogen. In order to investigate the relationship of this network to its eukaryotic counterparts, we performed a cluster analysis of organisms based on a census of its constituent domains across all fully sequenced genomes. We obtained a large central cluster of mainly unicellular organisms, from which multicellular organisms radiate out in two main directions. One is taken by multicellular bacteria, primarily cyanobacteria and actinomycetes, and plants form an extension of this direction, connected via the basal, unicellular cyanobacteria. The second main direction is taken by animals and fungi, which form separate branches with a common root in the α-proteobacteria of the central cluster. This analysis supports the notion that the innate immunity networks of eukaryotes originated from their endosymbionts and that increases in the complexity of these networks accompanied the emergence of multicellularity.     

Global Patterns of Protein Domain Gain and Loss in Superkingdoms

Domains are modules within proteins that can fold and function independently and are evolutionarily conserved. Here we compared the usage and distribution of protein domain families in the free-living proteomes of Archaea, Bacteria and Eukarya and reconstructed species phylogenies while tracing the history of domain emergence and loss in proteomes. We show that both gains and losses of domains occurred frequently during proteome evolution. The rate of domain discovery increased approximately linearly in evolutionary time. Remarkably, gains generally outnumbered losses and the gain-to-loss ratios were much higher in akaryotes compared to eukaryotes. Functional annotations of domain families revealed that both Archaea and Bacteria gained and lost metabolic capabilities during the course of evolution while Eukarya acquired a number of diverse molecular functions including those involved in extracellular processes, immunological mechanisms, and cell regulation. Results also highlighted significant contemporary sharing of informational enzymes between Archaea and Eukarya and metabolic enzymes between Bacteria and Eukarya. Finally, the analysis provided useful insights into the evolution of species. The archaeal superkingdom appeared first in evolution by gradual loss of ancestral domains, bacterial lineages were the first to gain superkingdom-specific domains, and eukaryotes (likely) originated when an expanding proto-eukaryotic stem lineage gained organelles through endosymbiosis of already diversified bacterial lineages. The evolutionary dynamics of domain families in proteomes and the increasing number of domain gains is predicted to redefine the persistence strategies of organisms in superkingdoms, influence the make up of molecular functions, and enhance organismal complexity by the generation of new domain architectures. This dynamics highlights ongoing secondary evolutionary adaptations in akaryotic microbes, especially Archaea.     

Expansion of protein domain repeats

Many proteins, especially in eukaryotes, contain tandem repeats of several domains from the same family. These repeats have a variety of binding properties and are involved in protein–protein interactions as well as binding to other ligands such as DNA and RNA. The rapid expansion of protein domain repeats is assumed to have evolved through internal tandem duplications. However, the exact mechanisms behind these tandem duplications are not well-understood. Here, we have studied the evolution, function, protein structure, gene structure, and phylogenetic distribution of domain repeats. For this purpose we have assigned Pfam-A domain families to 24 proteomes with more sensitive domain assignments in the repeat regions. These assignments confirmed previous findings that eukaryotes, and in particular vertebrates, contain a much higher fraction of proteins with repeats compared with prokaryotes. The internal sequence similarity in each protein revealed that the domain repeats are often expanded through duplications of several domains at a time, while the duplication of one domain is less common. Many of the repeats appear to have been duplicated in the middle of the repeat region. This is in strong contrast to the evolution of other proteins that mainly works through additions of single domains at either terminus. Further, we found that some domain families show distinct duplication patterns, e.g., nebulin domains have mainly been expanded with a unit of seven domains at a time, while duplications of other domain families involve varying numbers of domains. Finally, no common mechanism for the expansion of all repeats could be detected. We found that the duplication patterns show no dependence on the size of the domains. Further, repeat expansion in some families can possibly be explained by shuffling of exons. However, exon shuffling could not have created all repeats.     

Evolutionary connections between bacterial and eukaryotic signaling systems: a genomic perspective

Recent advances in microbial genomics suggest that several protein domains are common to bacterial and eukaryotic regulatory proteins. In particular, developmentally and morphologically complex prokaryotes appear to share several signaling modules with eukaryotes. New experimental studies and information from domain architectures point to several similar mechanistic themes in bacterial and eukaryotic signaling proteins. Laterally transferred protein domains, originally of bacterial provenance, appear to have contributed to the evolution of sensory pathways related to light, redox and nitric oxide signaling, and developmental pathways, such as Notch, cytokine and cytokinin signaling in eukaryotes.     

Nuclear organization: Uniting replication foci,chromatin domains and chromosome structure

In higher eukaryotes, ‘replication factories’ coordinate DNA synthesis within local clusters of chromatin domains. Recent experiments^(1,2) have confirmed the complexity of these clusters and established that the organization of sites labelled during S phase persists throughout the cell cycle. This implies that domain clusters are critical elements of an hierarchy that is fundamental to both nuclear and chromosome structure.     

Multi-domain proteins in the three kingdoms of life: orphan domains and other unassigned regions

Comparative studies of the proteomes from different organisms have provided valuable information about protein domain distribution in the kingdoms of life. Earlier studies have been limited by the fact that only about 50% of the proteomes could be matched to a domain. Here, we have extended these studies by including less well-defined domain definitions, Pfam-B and clustered domains, MAS, in addition to Pfam-A and SCOP domains. It was found that a significant fraction of these domain families are homologous to Pfam-A or SCOP domains. Further, we show that all regions that do not match a Pfam-A or SCOP domain contain a significantly higher fraction of disordered structure. These unstructured regions may be contained within orphan domains or function as linkers between structured domains. Using several different definitions we have re-estimated the number of multi-domain proteins in different organisms and found that several methods all predict that eukaryotes have approximately 65% multi-domain proteins, while the prokaryotes consist of approximately 40% multi-domain proteins. However, these numbers are strongly dependent on the exact choice of cut-off for domains in unassigned regions. In conclusion, all eukaryotes have similar fractions of multi-domain proteins and disorder, whereas a high fraction of repeating domain is distinguished only in multicellular eukaryotes. This implies a role for repeats in cell-cell contacts while the other two features are important for intracellular functions.     

Co-Inheritance Analysis within the Domains of Life Substantially Improves Network Inference by Phylogenetic Profiling

Phylogenetic profiling, a network inference method based on gene inheritance profiles, has been widely used to construct functional gene networks in microbes. However, its utility for network inference in higher eukaryotes has been limited. An improved algorithm with an in-depth understanding of pathway evolution may overcome this limitation. In this study, we investigated the effects of taxonomic structures on co-inheritance analysis using 2,144 reference species in four query species: Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, and Homo sapiens. We observed three clusters of reference species based on a principal component analysis of the phylogenetic profiles, which correspond to the three domains of life—Archaea, Bacteria, and Eukaryota—suggesting that pathways inherit primarily within specific domains or lower-ranked taxonomic groups during speciation. Hence, the co-inheritance pattern within a taxonomic group may be eroded by confounding inheritance patterns from irrelevant taxonomic groups. We demonstrated that co-inheritance analysis within domains substantially improved network inference not only in microbe species but also in the higher eukaryotes, including humans. Although we observed two sub-domain clusters of reference species within Eukaryota, co-inheritance analysis within these sub-domain taxonomic groups only marginally improved network inference. Therefore, we conclude that co-inheritance analysis within domains is the optimal approach to network inference with the given reference species. The construction of a series of human gene networks with increasing sample sizes of the reference species for each domain revealed that the size of the high-accuracy networks increased as additional reference species genomes were included, suggesting that within-domain co-inheritance analysis will continue to expand human gene networks as genomes of additional species are sequenced. Taken together, we propose that co-inheritance analysis within the domains of life will greatly potentiate the use of the expected onslaught of sequenced genomes in the study of molecular pathways in higher eukaryotes.     

Conserved domains and evolution of secreted phospholipases A(2)

Secreted phospholipases A(2) (sPLA(2) s) are lipolytic enzymes present in organisms ranging from prokaryotes to eukaryotes but their origin and emergence are poorly understood. We identified and compared the conserved domains of 333 sPLA(2) s and proposed a model for their evolution. The conserved domains were grouped into seven categories according to the in silico annotated conserved domain collections of 'cd00618: PLA(2) _like' and 'pfam00068: Phospholip_A2_1'. PLA(2) s containing the conserved domain cd04706 (plant-specific PLA(2) ) are present in bacteria and plants. Metazoan PLA(2) s of the group (G) I/II/V/X PLA(2) collection exclusively contain the conserved domain cd00125. GIII PLA(2) s of both vertebrates and invertebrates contain the conserved domain cd04704 (bee venom-like PLA(2) ), and mammalian GIII PLA(2) s also contain the conserved domain cd04705 (similar to human GIII PLA(2) ). The sPLA(2) s of bacteria, fungi and marine invertebrates contain the conserved domain pfam09056 (prokaryotic PLA(2) ) that is the only conserved domain identified in fungal sPLA(2) s. Pfam06951 (GXII PLA(2) ) is present in bacteria and is widely distributed in eukaryotes. All conserved domains were present across mammalian sPLA(2) s, with the exception of cd04706 and pfam09056. Notably, no sPLA(2) s were found in Archaea. Phylogenetic analysis of sPLA(2) conserved domains reveals that two main clades, the cd- and the pfam-collection, exist, and that they have evolved via gene-duplication and gene-deletion events. These observations are consistent with the hypothesis that sPLA(2) s in eukaryotes shared common origins with two types of bacterial sPLA(2) s, and their persistence during evolution may be related to their role in phospholipid metabolism, which is fundamental for survival.