40种蕨类植物matK基因的系统分类及分子进化研究

采用“放松分子钟”模型、氨基酸位点正选择模型和分子内共进化网络估算方法,对蕨类植物Ⅱ型内含子成熟酶蛋白K(Maturase K,MATK)编码基因matK的进化趋势进行研究。结果显示:matK基因在蕨类植物系统学研究中具有一定的应用价值,与rbcL基因和psaA基因联合后能显著提升系统发育树的可信度;蕨类植物MATK蛋白中存在少数曾经历正选择的位点;MATK蛋白内部有多对氨基酸位点共同构成共进化网络。在被子植物兴起环境改变后,MATK蛋白部分位点发生适应性进化,通过位点间共进化网络协同作用方式提升蕨类植物对新光合环境的适应能力。     

Genomes of 12 fig wasps provide insights into the adaptation of pollinators to fig syconia

Figs and fig pollinators are one of the few classic textbook examples of obligate pollination mutualism. The specific dependence of fig pollinators on the relatively safe living environment with sufficient food sources in the enclosed fig syconia implies that they are vulnerable to habitat changes. However, there is still no extensive genomic evidence to reveal the evolutionary footprint of this long-term mutually beneficial symbiosis in fig pollinators. In fig syconia, there are also non-pollinator species. The non-pollinator species differ in their evolutionary and life histories from pollinators. We conducted comparative analyses on 11 newly sequenced fig wasp genomes and one previously published genome. The pollinators colonized the figs approximately 66.9 million years ago, consistent with the origin of host figs. Compared with nonpollinators, many more genes in pollinators were subject to relaxed selection. Seven genes were absent in pollinators in response to environmental stress and immune activation. Pollinators had more streamlined gene repertoires in the innate immune system, chemosensory toolbox, and detoxification system. Our results provide genomic evidence for the differentiation between pollinators and nonpollinators. The data suggest that owing to the long-term adaptation to the fig, some genes related to functions no longer required are absent in pollinators.     

Can indicator species predict restoration outcomes early in the monitoring process? a case study with peatlands

Success in ecological restoration is rarely assessed rigorously due to insufficient planning for post-restoration monitoring programs, limited funding and, especially, lack of scientifically validated evaluation criteria and protocols. In this article, we propose the use of the Indicator Value Index technique (IndVal), which statistically determines the association of species to one or several particular site types, to obtain indicators of success at the early stages of the recovery process in restoration projects. Peat bogs extracted by the vacuum method, subsequently restored by a moss-transfer technique and regularly monitored for ~10 years were used as a model system to test this approach. We first identified 34 restored sectors of ~10 ha from 4 to 11 years old in twelve eastern-Canadian bogs. These sectors were then classified according to their degree of success in recovering a typical sphagnum moss carpet (restoration goal). Then, we retrospectively reviewed vegetation communities recorded at the third year after restoration to identify indicator species of different categories of restoration success, using the IndVal methodology. By identifying early indicator species, our method provides a tool that guides intervention soon after restoration if a site is not on a desired successional trajectory. Typical bog species, namely the bryophytes S. rubellum and Mylia anomala and the tree Picea mariana, were indicative of successful restoration; while bare peat, lichens and one species of ericaceous shrubs (Empetrum nigrum), which cope better under drier conditions, indicated sites where restoration failed. A surprising finding was that the moss Polytrichum strictum, which is known to facilitate the colonization of sphagnum in disturbed peatlands, is an early indicator of unsuccessful restoration. This finding made us question the nursing role of P. strictum at a cover threshold above ca. 30%, when P. strictum could be outcompeting sphagnum and become dominant. We conclude that the IndVal method is an effective tool to identify early indicators of restoration success when combined with a thoughtful examination of species frequency and cover within each site type.     

A unified framework for diversity gradients: the adaptive trait continuum

Aim Adaptive trait continua are axes of covariation observed in multivariate trait data for a given taxonomic group. These continua quantify and summarize life‐history variation at the inter‐specific level in multi‐specific assemblages. Here we examine whether trait continua can provide a useful framework to link life‐history variation with demographic and evolutionary processes in species richness gradients. Taking an altitudinal species richness gradient for Mediterranean butterflies as a study case, we examined a suite of traits (larval diet breadth, adult phenology, dispersal capacity and wing length) and species‐specific habitat measures (temperature and aridity breadth). We tested whether traits and species‐specific habitat measures tend to co‐vary, whether they are phylogenetically conserved, and whether they are able to explain species distributions and spatial genetic variation in a large number of butterfly assemblages. Location Catalonia, Spain. Methods We formulated predictions associated with species richness gradients and adaptive trait continua. We applied principal components analyses (PCAs), structural equation modelling and phylogenetic generalized least squares models. Results We found that traits and species‐specific habitat measures covaried along a main PCA axis, ranging from multivoltine trophic generalists with high dispersal capacity to univoltine (i.e. one generation per year), trophic specialist species with low dispersal capacity. This trait continuum was closely associated with the observed distributions along the altitudinal gradient and predicted inter‐specific differences in patterns of spatial genetic variability (F_ST and genetic distances), population responses to the impacts of global change and local turnover dynamics. Main conclusions The adaptive trait continuum of Mediterranean butterflies provides an integrative and mechanistic framework to: (1) analyse geographical gradients in species richness, (2) explain inter‐specific differences in population abundances, spatial distributions and demographic trends, (3) explain inter‐specific differences in patterns of genetic variation (F_ST and genetic distances), and (4) study specialist–generalist life‐history transitions frequently involved in butterfly diversification processes.     

Approximation of bias and mean-squared error in two-sample Mendelian randomization analyses

Mendelian randomization (MR) is a type of instrumental variable (IV) analysis that uses genetic variants as IVs for a risk factor to study its causal effect on an outcome. Extensive investigations on the performance of IV analysis procedures, such as the one based on the two-stage least squares (2SLS) procedure, have been conducted under the one-sample scenario, where measures on IVs, the risk factor, and the outcome are assumed to be available for each study participant. Recent MR analysis usually is performed with data from two independent or partially overlapping genetic association studies (two-sample setting), with one providing information on the association between the IVs and the outcome, and the other on the association between the IVs and the risk factor. We investigate the performance of 2SLS in the two-sample–based MR when the IVs are weakly associated with the risk factor. We derive closed form formulas for the bias and mean squared error of the 2SLS estimate and verify them with numeric simulations under realistic circumstances. Using these analytic formulas, we can study the pros and cons of conducting MR analysis under one-sample and two-sample settings and assess the impact of having overlapping samples. We also propose and validate a bias-corrected estimator for the causal effect.     

Randomization inference with general interference and censoring

Interference occurs between individuals when the treatment (or exposure) of one individual affects the outcome of another individual. Previous work on causal inference methods in the presence of interference has focused on the setting where it is a priori assumed that there is “partial interference,” in the sense that individuals can be partitioned into groups wherein there is no interference between individuals in different groups. Bowers et al. (2012, Political Anal, 21, 97–124) and Bowers et al. (2016, Political Anal, 24, 395–403) consider randomization-based inferential methods that allow for more general interference structures in the context of randomized experiments. In this paper, extensions of Bowers et al. that allow for failure time outcomes subject to right censoring are proposed. Permitting right-censored outcomes is challenging because standard randomization-based tests of the null hypothesis of no treatment effect assume that whether an individual is censored does not depend on treatment. The proposed extension of Bowers et al. to allow for censoring entails adapting the method of Wang et al. (2010, Biostatistics, 11, 676–692) for two-sample survival comparisons in the presence of unequal censoring. The methods are examined via simulation studies and utilized to assess the effects of cholera vaccination in an individually randomized trial of 73 000 children and women in Matlab, Bangladesh.     

A Ruler Protein in a Complex for Antiviral Defense Determines the Length of Small Interfering CRISPR RNAs

Small RNAs undergo maturation events that precisely determine the length and structure required for their function. CRISPRs (clustered regularly interspaced short palindromic repeats) encode small RNAs (crRNAs) that together with CRISPR-associated (cas) genes constitute a sequence-specific prokaryotic immune system for anti-viral and anti-plasmid defense. crRNAs are subject to multiple processing events during their biogenesis, and little is known about the mechanism of the final maturation step. We show that in the Staphylococcus epidermidis type III CRISPR-Cas system, mature crRNAs are measured in a Cas10·Csm ribonucleoprotein complex to yield discrete lengths that differ by 6-nucleotide increments. We looked for mutants that impact this crRNA size pattern and found that an alanine substitution of a conserved aspartate residue of Csm3 eliminates the 6-nucleotide increments in the length of crRNAs. In vitro, recombinant Csm3 binds RNA molecules at multiple sites, producing gel-shift patterns that suggest that each protein binds 6 nucleotides of substrate. In vivo, changes in the levels of Csm3 modulate the crRNA size distribution without disrupting the 6-nucleotide periodicity. Our data support a model in which multiple Csm3 molecules within the Cas10·Csm complex bind the crRNA with a 6-nucleotide periodicity to function as a ruler that measures the extent of crRNA maturation.     

A PARAMETRIC METHOD FOR ASSESSING DIVERSIFICATION‐RATE VARIATION IN PHYLOGENETIC TREES

Phylogenetic hypotheses are frequently used to examine variation in rates of diversification across the history of a group. Patterns of diversification‐rate variation can be used to infer underlying ecological and evolutionary processes responsible for patterns of cladogenesis. Most existing methods examine rate variation through time. Methods for examining differences in diversification among groups are more limited. Here, we present a new method, parametric rate comparison (PRC), that explicitly compares diversification rates among lineages in a tree using a variety of standard statistical distributions. PRC can identify subclades of the tree where diversification rates are at variance with the remainder of the tree. A randomization test can be used to evaluate how often such variance would appear by chance alone. The method also allows for comparison of diversification rate among a priori defined groups. Further, the application of the PRC method is not restricted to monophyletic groups. We examined the performance of PRC using simulated data, which showed that PRC has acceptable false‐positive rates and statistical power to detect rate variation. We apply the PRC method to the well‐studied radiation of North American Plethodon salamanders, and support the inference that the large‐bodied Plethodon glutinosus clade has a higher historical rate of diversification compared to other Plethodon salamanders.     

EVOLUTIONARY INFERENCES FROM THE ANALYSIS OF EXCHANGEABILITY

Evolutionary inferences are usually based on statistical models that compare mean genotypes or phenotypes (or their frequencies) among populations. An alternative is to use the full distribution of genotypes and phenotypes to infer the “exchangeability” of individuals among populations. We illustrate this approach by using discriminant functions on principal components to classify individuals among paired lake and stream populations of threespine stickleback in each of six independent watersheds. Classification based on neutral and nonneutral microsatellite markers was highest to the population of origin and next highest to populations in the same watershed. These patterns are consistent with the influence of historical contingency (separate colonization of each watershed) and subsequent gene flow (within but not between watersheds). In comparison to this low genetic exchangeability, ecological (diet) and morphological (trophic and armor traits) exchangeability was relatively high—particularly among populations from similar habitats. These patterns reflect the role of natural selection in driving parallel adaptive changes when independent populations colonize similar habitats. Importantly, however, substantial nonparallelism was also evident. Our results show that analyses based on exchangeability can confirm inferences based on statistical analyses of means or frequencies, while also refining insights into the drivers of—and constraints on—evolutionary diversification.