Exploring structural features of the interaction between the scorpion toxinCnErg1 and ERG K+ channels

The gamma-KTx-type scorpion toxins specific for K+ channels were found to interact with ERG channels on the turret region, while alpha-KTx3.2 Agitoxin-2 binds to the pore region of the Shaker K+ channel, and alpha-KTx5.3 BmP05 binds to the intermediate region of the small-conductance calcium-activated K-channel (SK(Ca)). In order to explore the critical residues for gamma-KTx binding, we determined the NMR structure of native gamma-KTx1.1 (CnErg1), a 42 amino acid residues scorpion toxin isolated from the venom of the Mexican scorpion Centruro?des noxius Hoffmann, and we used computational evolutionary trace (ET) analysis to predict possible structural and functional features of interacting surfaces. The 1H-NMR three-dimensional solution structure of native ergtoxin (CnErg1) was solved using a total of 452 distance constraints, 13 3J(NH-Halpha) and 10 hydrogen bonds. The structure is characterized by 2 segments of alpha-helices and a triple-stranded antiparallel beta-sheet stabilized by 4 disulfide bridges. The ET and structural analysis provided indication of the presence of two important amino acid residue clusters, one hydrophobic and the other hydrophilic, that should be involved in the surface contact between the toxin and the channel. Some features of the proposed interacting surface are discussed.     

A stochastic metapopulation model accounting for habitat dynamics

A stochastic metapopulation model accounting for habitat dynamics is presented. This is the stochastic SIS logistic model with the novel aspect that it incorporates varying carrying capacity. We present results of Kurtz and Barbour, that provide deterministic and diffusion approximations for a wide class of stochastic models, in a form that most easily allows their direct application to population models. These results are used to show that a suitably scaled version of the metapopulation model converges, uniformly in probability over finite time intervals, to a deterministic model previously studied in the ecological literature. Additionally, they allow us to establish a bivariate normal approximation to the quasi-stationary distribution of the process. This allows us to consider the effects of habitat dynamics on metapopulation modelling through a comparison with the stochastic SIS logistic model and provides an effective means for modelling metapopulations inhabiting dynamic landscapes.     

Three-dimensional chromatin ensemble reconstruction via stochastic embedding

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Plant adaptation to climate change—Where are we?

Climate change poses critical challenges for population persistence in natural communities, for agriculture and environmental sustainability, and for food security. In this review, we discuss recent progress in climatic adaptation in plants. We evaluate whether climate change exerts novel selection and disrupts local adaptation, whether gene flow can facilitate adaptive responses to climate change, and whether adaptive phenotypic plasticity could sustain populations in the short term. Furthermore, we discuss how climate change influences species interactions. Through a more in‐depth understanding of these eco‐evolutionary dynamics, we will increase our capacity to predict the adaptive potential of plants under climate change. In addition, we review studies that dissect the genetic basis of plant adaptation to climate change. Finally, we highlight key research gaps, ranging from validating gene function to elucidating molecular mechanisms, expanding research systems from model species to other natural species, testing the fitness consequences of alleles in natural environments, and designing multifactorial studies that more closely reflect the complex and interactive effects of multiple climate change factors. By leveraging interdisciplinary tools (e.g., cutting‐edge omics toolkits, novel ecological strategies, newly developed genome editing technology), researchers can more accurately predict the probability that species can persist through this rapid and intense period of environmental change, as well as cultivate crops to withstand climate change, and conserve biodiversity in natural systems.     

Towards robust evolutionary inference with integral projection models

Integral projection models (IPMs) are extremely flexible tools for ecological and evolutionary inference. IPMs track the distribution of phenotype in populations through time, using functions describing phenotype‐dependent development, inheritance, survival and fecundity. For evolutionary inference, two important features of any model are the ability to (i) characterize relationships among traits (including values of the same traits across ages) within individuals, and (ii) characterize similarity between individuals and their descendants. In IPM analyses, the former depends on regressions of observed trait values at each age on values at the previous age (development functions), and the latter on regressions of offspring values at birth on parent values as adults (inheritance functions). We show analytically that development functions, characterized this way, will typically underestimate covariances of trait values across ages, due to compounding of regression to the mean across projection steps. Similarly, we show that inheritance, characterized this way, is inconsistent with a modern understanding of inheritance, and underestimates the degree to which relatives are phenotypically similar. Additionally, we show that the use of a constant biometric inheritance function, particularly with a constant intercept, is incompatible with evolution. Consequently, current implementations of IPMs will predict little or no phenotypic evolution, purely as artefacts of their construction. We present alternative approaches to constructing development and inheritance functions, based on a quantitative genetic approach, and show analytically and through an empirical example on a population of bighorn sheep how they can potentially recover patterns that are critical to evolutionary inference.     

Was it an explosion? Using population genetics to explore the dynamics of a recent radiation within Protea (Proteaceae L.)

Adaptive radiations likely underlie much of the world’s diversity, especially that of hyper‐diverse regions. They are usually characterized by a burst of speciation early in their evolutionary history, a pattern which can be detected using population genetic tools. The Cape Floristic Region (CFR) of southwestern South Africa is home to many spectacular plant radiations. Here, we investigate the white proteas (Protea section Exsertae), a typical CFR radiation, to determine if it demonstrates the burst of speciation associated with adaptive radiations in recent models. Inferences from individual assignment, tree‐based population relationships, and pairwise F‐statistics based on 10 microsatellite loci reveal that while the white proteas radiated recently they did not radiate explosively. In addition, we found evidence that there is little gene flow between sampled populations of most species. Taken together, these results demonstrate that within a small clade, the processes underlying the radiation are different from those envisioned by current models of adaptive radiation and suggest that geographical isolation could have played a role in the diversification of the group. Our study implicates both adaptive and non‐adaptive processes in the evolution of botanical diversity of the CFR.     

Data partitioning and correction for ascertainment bias reduce the uncertainty of placental mammal divergence times inferred from the morphological clock

Bayesian estimates of divergence times based on the molecular clock yield uncertainty of parameter estimates measured by the width of posterior distributions of node ages. For the relaxed molecular clock, previous works have reported that some of the uncertainty inherent to the variation of rates among lineages may be reduced by partitioning data. Here we test this effect for the purely morphological clock, using placental mammals as a case study. We applied the uncorrelated lognormal relaxed clock to morphological data of 40 extant mammalian taxa and 4,533 characters, taken from the largest published matrix of discrete phenotypic characters. The morphologically derived timescale was compared to divergence times inferred from molecular and combined data. We show that partitioning data into anatomical units significantly reduced the uncertainty of divergence time estimates for morphological data. For the first time, we demonstrate that ascertainment bias has an impact on the precision of morphological clock estimates. While analyses including molecular data suggested most divergences between placental orders occurred near the K‐Pg boundary, the partitioned morphological clock recovered older interordinal splits and some younger intraordinal ones, including significantly later dates for the radiation of bats and rodents, which accord to the short‐fuse hypothesis.     

细胞色素P450介导抗性的进化可塑性

细胞色素P450是超基因家族,由其介导的杀虫剂代谢解毒的增强是昆虫产生抗药性的普遍而主要的机制。近年的研究表明,细胞色素P450介导的代谢抗性表现出一定程度的进化可塑性:即使是同种昆虫的不同种群在相同种类杀虫剂的胁迫下,进化选择出的抗性相关的细胞色素P450也有所不同,抗性的产生也可以是几种不同细胞色素P450协同作用或控制P450表达的调控因子的不同。     

何首乌不同种质花粉形态及进化趋势研究

采用电镜扫描法,对48份何首乌种质的花粉形态进行了观察和分析。结果表明:何首乌花粉形状主要为椭球形,少量为长椭球形和近球形,部分种质花粉形状正处于椭球形向长椭球形进化的阶段;极面观主要为三裂圆形,部分种质的变异为半球状、四边形、凹陷状或平三角形;赤道面观主要为椭圆形,部分种质为三角形或四边形;萌发沟3条,狭长,几达两极,部分种质的1条或2条萌发沟中部或近极端处隆起,2条或3条萌发沟在极端处相交;表面纹饰为穴状,部分种质的穴中出现小孔。研究结果表明,何首乌物种正处于活跃进化阶段且因区域及生境的差异其进化速度不一致,低纬度地区的种质进化程度较高纬度地区的高,其最初的起源中心可能位于高纬度地区,在向低纬度地区迁移过程中其花粉形态发生了不同程度的变异。