基因流存在条件下的物种形成研究述评:生殖隔离机制进化

物种形成过程是生物多样性形成的基础, 长期以来一直是进化生物学的中心议题之一。传统的异域物种形成理论认为, 地理隔离是物种分化的主要决定因子, 物种形成只有在种群之间存在地理隔离的情况下才能发生。近年来, 随着种群基因组学的发展和溯祖理论分析方法的完善, 种群间存在基因流情况下的物种形成成为进化生物学领域新的研究焦点。物种形成过程中是否有基因流的发生?基因流如何影响物种的形成与分化?基因流存在条件下物种形成的生殖隔离机制是什么?根据已发表的相关文献资料, 作者综述了当前物种形成研究中基因流的时间和空间分布模式、基因流对物种分化的影响以及生殖隔离机制形成等问题, 指出基因流存在条件下的物种形成可能是自然界普遍发生的一种模式。     

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。     

海洋岛屿生物多样性保育研究进展

海洋岛屿生态系统因具有明显的海域地理隔离而区别于陆地生态系统,被誉为生物地理与进化生态学研究的"天然实验室".陆地或其它邻近岛屿的种源物种迁移到新的岛屿后,经历地理隔离、特征置换或适应辐射等一系列的岛屿进化过程,形成与种源物种具有显著遗传差异的岛屿特有种.岛屿在小面积范围内分化形成大量的特有种,是岛屿生物多样性最为重要的特点之一.但是,岛屿种群由于分布范围局限、生境脆弱且种群规模较小,岛屿种群较陆地种群具有更高的灭绝风险.本文通过对海洋岛屿物种的起源与演化、遗传结构以及岛屿物种的濒危与保护3个热点问题的讨论,阐述岛屿生物多样性的形成机制、濒危肇因以及岛屿生物多样性保育的重要性.     

区域生命之树及其在植物区系研究中的应用

区域生命之树是对一个区域内的所有物种进行生命之树重建,在最近10年已成为生命科学领域的研究热点。生命之树反映了物种间的亲缘关系和进化信息,可以将生物区系形成与发展过程中的进化和生态因素联系起来,是揭示区系来源和演化规律的有效手段。本文从3个方面总结了区域生命之树在植物区系研究中的应用:(1)在时间维度上,通过生命之树类群分化时间和进化速率估算,反映区系演化历史,揭示区系的时间分化格局;(2)在空间维度上,结合系统发育信息与物种分布数据,揭示区系内生物多样性的空间格局,并在此基础上进行区系分区;(3)整合生物地理信息和气候环境数据,分析区系中生物类群对古地理事件以及气候变化的响应机制,以揭示形成现存生物多样性格局的生态、地理和历史因素。此外,我们阐述了区域生命之树与全球生命之树之间的关系;指出由于类群取样不全而造成的时间估算偏差是区域生命之树研究中需要注意的问题;建议对生物多样性热点地区从不同尺度进行大数据的整合分析。     

植物细胞核型的进化

生命从诞生开始,在经历了复杂的进化历程之后,才形成了现在丰富多彩的生物世界。在这一进化过程中,作为遗传物质的载体──染色体也发生了相应的进化。并且,核型的进化反映了生物的进化过程及各物种的亲缘关系。因此,对植物的核型进行分析将有助于对植物系统进化的认识。 在生物的进化过程中,物种形成是非常关键的一步。现代达尔文主义认为：生物进化的方式有两种,一是渐进式物种形成,即原来的种经过突变与选择,逐渐积累变异,首先形成地理族和生态族,然后分化成独立的新种。而还有少数学者认为种间进化不同于种内进化,新种形成…     

适合度的相对性与路径依赖的自然选择

自然选择理论认为生物个体或者种群在进化的过程中, 其基因或者性状、行为策略的选择一定是能够提高其适合度或者达到某个可期的“目标”。然而, 随着某个突变基因或者性状特征、行为策略在种群中扩散, 其期望收益将随着其在种群中分布的密度变化或环境改变而发生改变, 这就是适合度景观的悖论, 即静态的、固定可期望的收益可能因此而不存在。基于动态而非静态适合度景观的概念, 我们提出路径依赖的自然选择概念。路径依赖的自然选择过程中, 一个突变的基因或表型在某种环境下随机产生, 但是该基因或表型在某些特定环境下会产生正反馈。尤其是在正反馈与随机漂变的共同作用下, 多条路径的演化就可能发生, 并且其路径的形成将同时受到其种群进化历史过程和空间特征分布等因素的强烈影响。而在不同路径下, 由于观测维度、角度和尺度的不同, 适合度意义将因此而存在不同。在此意义下, 自然选择更可能选择路径频率而不是适合度大小。基于上述概念, 我们借鉴现代物理学中复函数的方法, 来描述多重动力对物种形成或者生物特征、种群进化等路径依赖的演化过程, 以期为同域物种、隐存种形成以及生物多样性演化提供解释机制。     

物种分布模型理论研究进展

利用物种分布模型估计物种的真实和潜在分布区,已成为区域生态学与生物地理学中非常活跃的研究领域。然而,到目前为止,这项技术的理论基础仍然存在不足之处,一些关键的生态过程未能被有效纳入到物种分布模型的理论框架中,从而为解释物种分布模型预测的结果带来了诸多困惑。鉴于此,总结了物种分布模型的理论基础;系统探讨了物种分布模型与物种分布区的关系;特别指出了物种分布模型研究中存在的理论问题;重点阐述了物种分布模型未来的发展方向。研究认为,物种分布模型与生态位理论、源-库理论、种群动态理论、集合种群理论、进化理论等具有重要的联系;正确理解物种分布模型的预测结果与物种分布区的关系,有赖于对影响物种分布的3个主要因素(环境条件、物种相互作用与物种迁移能力)做出定量的分离;目前物种分布模型主要存在的问题是未能将物种的相互作用和物种的迁移能力有效纳入到模型的构建过程中;未来物种分布模型的发展应该加强模型背后理论框架的研究,并进一步加强整合物种相互作用过程、种群动态过程、迁移过程和物种进化过程等内容。研究还认为,从更高的理论层次模拟功能群和群落结构将是未来物种分布模型的重要发展方向。     

生态位分化与森林群落物种多样性维持研究展望

一直以来,生态学家和进化生物学家对森林群落物种多样格局及其形成机制持有不同的观点。虽然Robert Ricklefs将进化和生态过程整合的观点已经被群落生态学家广泛接受,但是区域物种进化历史以及局域群落微进化过程是否能够影响群落生态学过程以及这些过程如何影响群落结构和动态还有待商榷。经典的生态位理论同时强调了种间和种内生态位分化对群落多样性维持的影响。但是生态学家普遍认为种间差异足以代表群落内个体间的相互作用关系,并且由于进化过程导致的种内分化往往涉及较长的时间尺度,因此,虽然种内差异是自然选择的重要材料,物种对环境的适应性进化过程所导致的种内分化对群落构建的影响往往被生态学家所忽视。为此,通过回顾种间和个体生态位分化的研究历史,对两类研究分别进行简要阐述,强调在今后的群落生态学研究中需要考虑个体分化对局域群落构建的影响。     

分子绝对进化速率与物种分歧时间之间的定量关系

通过对美国国家生物技术信息中心数据库Gen Bank提供的一些蛋白质和核苷酸序列进行比对和分析,发现生物分子绝对进化速率k与进化时间或物种分歧时间t之间存在下列定量关系:lnk=-Ea/Rt+lnK0,式中Ea为位点突变活化能,k0为分子极限绝对进化速率,R为常数,并对其生物学意义进行了初步的探讨;数据分析还揭示出物种的分子极限绝对进化速率与进化时间或物种分歧时间之间也服从相似的定量公式,也就是说生物分子进化过程可能同时受到序列位点突变和控制物种分子极限绝对进化速率进化的两个"分子钟"作用,即存在"双重分子钟"现象。     

路径依赖下的物种形成机制

生物科学几乎所有研究都需要物种概念作为基础, 生物多样性研究亦需要可操作的物种概念, 但现有物种概念存在不同程度的人为因素或难操作性, 对物种划分造成不利影响。本文引入“进化路径”这一概念, 说明适合度景观时刻变化着, 物种在每个进化时间点上依据瞬时适合度选择下一时刻的进化状态, 且总是沿着动态适合度景观中适合度增加的方向进化。基于演化博弈的方法, 以随机过程为例模拟物种的进化过程。进而提出路径依赖下的物种形成机制, 并在此基础上给出可操作的物种定义, 即: 针对基因、性状、生态过程等任一状态下两个群体内个体的多个变量做统计分析, 若群体之间同时在两个或多个维度状态下呈现出的不连续性d大于群体内变量呈现出的差异性σ_k, 则拥有相应变量的个体属于不同物种。     

The uniqueness of biological self-organization: challenging the Darwinian paradigm

Here we discuss the challenge posed by self-organization to the Darwinian conception of evolution. As we point out, natural selection can only be the major creative agency in evolution if all or most of the adaptive complexity manifest in living organisms is built up over many generations by the cumulative selection of naturally occurring small, random mutations or variants, i.e., additive, incremental steps over an extended period of time. Biological self-organization—witnessed classically in the folding of a protein, or in the formation of the cell membrane—is a fundamentally different means of generating complexity. We agree that self-organizing systems may be fine-tuned by selection and that self-organization may be therefore considered a complementary mechanism to natural selection as a causal agency in the evolution of life. But we argue that if self-organization proves to be a common mechanism for the generation of adaptive order from the molecular to the organismic level, then this will greatly undermine the Darwinian claim that natural selection is the major creative agency in evolution. We also point out that although complex self-organizing systems are easy to create in the electronic realm of cellular automata, to date translating in silico simulations into real material structures that self-organize into complex forms from local interactions between their constituents has not proved easy. This suggests that self-organizing systems analogous to those utilized by biological systems are at least rare and may indeed represent, as pre-Darwinists believed, a unique ascending hierarchy of natural forms. Such a unique adaptive hierarchy would pose another major challenge to the current Darwinian view of evolution, as it would mean the basic forms of life are necessary features of the order of nature and that the major pathways of evolution are determined by physical law, or more specifically by the self-organizing properties of biomatter, rather than natural selection.     

Structural complexity analysis for industrial ecosystems: A case study on LuBei industrial ecosystem in China

Natural ecosystems and human societies have evolved in many diverse ways and they are both complex systems. Our learning from the structure complexity of natural ecosystems can help us to redesign the structure of industrial system. Thus the materials and energy efficiency of industrial systems can be improved well to achieve the sustainable goals. In this paper, Structural Analysis Method for Industrial Ecosystems (SAMIE) is introduced and applied in the analysis of the structure complexity and efficiency of the industrial ecosystems. The industrial ecosystem is analyzed based on the industrial species’ classification, which is analogous to the natural ecosystem. A set of indicators are developed to evaluate the industrial system, in order to explore the problems of structural complexity, identify the limiting factors of industrial ecosystem evolution, and strengthen the capacity of adaptation and self-organization. A case study on LuBei industrial ecosystem in China has been selected to apply the SAMIE approach.     

Conservation and coevolution in the scale-free human gene coexpression network

The role of natural selection in biology is well appreciated. Recently, however, a critical role for physical principles of network self-organization in biological systems has been revealed. Here, we employ a systems level view of genome-scale sequence and expression data to examine the interplay between these two sources of order, natural selection and physical self-organization, in the evolution of human gene regulation. The topology of a human gene coexpression network, derived from tissue-specific expression profiles, shows scale-free properties that imply evolutionary self-organization via preferential node attachment. Genes with numerous coexpressed partners (the hubs of the coexpression network) evolve more slowly on average than genes with fewer coexpressed partners, and genes that are coexpressed show similar rates of evolution. Thus, the strength of selective constraints on gene sequences is affected by the topology of the gene coexpression network. This connection is strong for the coding regions and 3' untranslated regions (UTRs), but the 5' UTRs appear to evolve under a different regime. Surprisingly, we found no connection between the rate of gene sequence divergence and the extent of gene expression profile divergence between human and mouse. This suggests that distinct modes of natural selection might govern sequence versus expression divergence, and we propose a model, based on rapid, adaptation-driven divergence and convergent evolution of gene expression patterns, for how natural selection could influence gene expression divergence.     

Life history predicts risk of species decline in a stochastic world

Understanding what traits determine the extinction risk of species has been a long-standing challenge. Natural populations increasingly experience reductions in habitat and population size concurrent with increasing novel environmental variation owing to anthropogenic disturbance and climate change. Recent studies show that a species risk of decline towards extinction is often non-random across species with different life histories. We propose that species with life histories in which all stage-specific vital rates are more evenly important to population growth rate may be less likely to decline towards extinction under these pressures. To test our prediction, we modelled declines in population growth rates under simulated stochastic disturbance to the vital rates of 105 species taken from the literature. Populations with more equally important vital rates, determined using elasticity analysis, declined more slowly across a gradient of increasing simulated environmental variation. Furthermore, higher evenness of elasticity was significantly correlated with a reduced chance of listing as Threatened on the International Union for Conservation of Nature Red List. The relative importance of life-history traits of diverse species can help us infer how natural assemblages will be affected by novel anthropogenic and climatic disturbances.     

Insights into population genetics and evolution of polyploids and their ancestors

We have developed the first comprehensive simulator for polyploid genomes (PolySim) and demonstrated its value by performing large‐scale simulations to examine the effect of different population parameters on the evolution of polyploids. PolySim is unlimited in terms of ploidy, population size or number of simulated loci. Our process considered the evolution of polyploids from diploid ancestors, polysomic inheritance, inbreeding, recombination rate change in polyploids and gene flow from lower to higher ploidies. We compared the number of segregating single nucleotide polymorphisms, minor allele frequency, heterozygosity, R² and average kinship relatedness between different simulated scenarios, and to real data from polyploid species. As expected, allotetraploid populations showed no difference from their ancestral diploids when population size remained constant and there was no gene flow or multivalent (MV) pairing between subgenomes. Autotetraploid populations showed significant differences from their ancestors for most parameters and diverged from their ancestral populations faster than allotetraploids. Autotetraploids can have significantly higher heterozygosity, relatedness and extended linkage disequilibrium compared with allotetraploids. Interestingly, autotetraploids were more sensitive to increasing selfing rate and decreasing population size. MV formation can homogenize allotetraploid subgenomes, but this homogenization requires a higher MV rate than previously proposed. Our results can be considered as the first building block to understand polyploid population evolutionary dynamics. PolySim can be used to simulate a wide variety of polyploid organisms that mimic empirical populations, which, in combination with quantitative genetics tools, can be used to investigate the power of genomewide association, genomic selection or breeding programme designs in these species.     

遗传负荷理论的一种普适框架

遗传负荷表示种群由于遗传变异能力的存在而在平均适宜度上的损失,定量讨论各种遗传负荷,对研究现实发生水平上的物种进化具有重要意义,以往的遗传负荷理论从种群平衡出发,探讨现实发生水平上的物种进化,可是,进化是种群平衡的位移;这便构成了理论与现实之间的矛盾,为拓展以往的遗传负荷理论,给出了一个描述各种遗传负荷的普适理论框架,利用这个理论框架既能探讨平衡种群的遗传负荷,又能模写非平衡种群的遗传负荷及其变化,从而克服了以往的遗传负荷理论不能描述非平衡种群和不时与生物进化现实相悖的不足之处,为研究物种的进化提供了一种可靠的模拟方法。     

Evolution in plant populations as a driver of ecological changes in arthropod communities

Heritable variation in traits can have wide-ranging impacts on species interactions, but the effects that ongoing evolution has on the temporal ecological dynamics of communities are not well understood. Here, we identify three conditions that, if experimentally satisfied, support the hypothesis that evolution by natural selection can drive ecological changes in communities. These conditions are: (i) a focal population exhibits genetic variation in a trait(s), (ii) there is measurable directional selection on the trait(s), and (iii) the trait(s) under selection affects variation in a community variable(s). When these conditions are met, we expect evolution by natural selection to cause ecological changes in the community. We tested these conditions in a field experiment examining the interactions between a native plant (Oenothera biennis) and its associated arthropod community (more than 90 spp.). Oenothera biennis exhibited genetic variation in several plant traits and there was directional selection on plant biomass, life-history strategy (annual versus biennial reproduction) and herbivore resistance. Genetically based variation in biomass and life-history strategy consistently affected the abundance of common arthropod species, total arthropod abundance and arthropod species richness. Using two modelling approaches, we show that evolution by natural selection in large O. biennis populations is predicted to cause changes in the abundance of individual arthropod species, increases in the total abundance of arthropods and a decline in the number of arthropod species. In small O. biennis populations, genetic drift is predicted to swamp out the effects of selection, making the evolution of plant populations unpredictable. In short, evolution by natural selection can play an important role in affecting the dynamics of communities, but these effects depend on several ecological factors. The framework presented here is general and can be applied to other systems to examine the community-level effects of ongoing evolution.     

The sociobiology of biofilms

Biofilms are densely packed communities of microbial cells that grow on surfaces and surround themselves with secreted polymers. Many bacterial species form biofilms, and their study has revealed them to be complex and diverse. The structural and physiological complexity of biofilms has led to the idea that they are coordinated and cooperative groups, analogous to multicellular organisms. We evaluate this idea by addressing the findings of microbiologists from the perspective of sociobiology, including theories of collective behavior (self-organization) and social evolution. This yields two main conclusions. First, the appearance of organization in biofilms can emerge without active coordination. That is, biofilm properties such as phenotypic differentiation, species stratification and channel formation do not necessarily require that cells communicate with one another using specialized signaling molecules. Second, while local cooperation among bacteria may often occur, the evolution of cooperation among all cells is unlikely for most biofilms. Strong conflict can arise among multiple species and strains in a biofilm, and spontaneous mutation can generate conflict even within biofilms initiated by genetically identical cells. Biofilms will typically result from a balance between competition and cooperation, and we argue that understanding this balance is central to building a complete and predictive model of biofilm formation.     

Effects of micro-nutrients and major nutrients on natural phytoplankton populations

Six experiments were carried out with natural phytoplanktonpopulations grown under simulated natural conditions, in anattempt to assess the gross effects of major nutrient and micronutrientperturbations upon the growth and species composition of thesepopulations. Water was collected from Yaquina Bay, Oregon, andfiltered into twenty-litre growth containers. Some of this waterwas treated with activated carbon to remove a portion of thetrace metals and trace organics. Various combinations of majornutrients, micro-nutrients, and chelators were added to thesecultures. Inoculation was with unfiltered bay water, at a ratioof 1:1000. Incubation was in outdoor tanks of water circulatingfrom the bay, under natural sunlight. The major nutrients andmicro-nutrients appeared to have fundamentally different effectson the growth and species composition of phytoplankton. Themicro-nutrients had marked effects on the species compositionof the phytoplankton populations, while major nutrients hadminimal effects on species composition. The micro-nutrientsalso had substantial effects on population growth rates, lagperiods, and final yields. The major nutrients had a substantialeffect only on final yields.     

抗马拉硫磷淡色库蚊不同基因型的自然内禀增长率及其对抗性演化的影响

本文涉及淡色库蚊(Culex pipiens pallens)抗马拉硫磷纯合子(RR)、杂合子(RS)和敏感纯合子(SS)的自然内禀增长率及其对马拉硫磷抗性演化的影响。RR、RS和SS的内禀增长率分别为0.1118、0.1171和0.1339。RR和RS基因型在无杀虫剂时呈现出繁殖不利性,RR和RS的相对适合度分别是SS的0.65和0.68。 影响淡色库蚊对马拉硫磷进化的某些因子在计算机上进行了模拟。模拟的因子包括R等位基因的起始频率(P_o)、所用马拉硫磷的剂量和迁入率(m)。模拟结果表明(I)不用药时R等位基因衰减是由于RR和RS基因型的繁殖不利性;(2)在起始种群N_o=200,P_o=0.1,使用杀死全部SS和RS的剂量(8ppm)处理,使R等位基因为有效隐性,并且m≥0.15时可阻止马拉硫磷抗性的发生。