CIC对高脂膳食大鼠肝脏氧化应激的影响

目的:研究慢性间断性冷暴露(mild chronic intermittent cold exposure,CIC)对高脂膳食大鼠肝脏氧化应激的影响。方法:轻度CIC已被广泛用于建立冷适应研究的动物模型。本研究通过将大鼠暴露于温和的CIC和/或高脂膳食4w,检测肛温、体重、肝脏重量、ATP和活性氧(ROS)的水平,Western blot检测冷诱导RNA结合蛋白(cold inducible RNA binding protein,Cirbp)和硫氧还蛋白(Thioredoxin,TRX)的蛋白表达。结果:同对照组相比,高脂膳食组体重显著增加,血清和肝脏ROS水平显著升高,ATP水平没有显著影响。同对照组相比,CIC暴露1w后大鼠肛温显著降低,而2w、3w和4w周肛温没有显著差异,ROS水平无显著差异,但ATP水平显著升高;Cirbp和TRX的表达显著升高。同常温高脂膳食组相比,CIC暴露4w后,大鼠体重显著降低,ROS水平无显著差异,而ATP水平显著升高;Cirbp和TRX的表达水平显著升高。这些结果均提示冷适应增强了高脂膳食大鼠肝脏的抗氧化水平,可能是由于冷适应后Cirbp表达升高,继而调控其下游的抗氧化蛋白TRX的表达增加,从而清除ROS的缘故。结论:CIC暴露诱导的冷适应可保护肝脏免于高脂膳食诱导的氧化应激。     

Female mate choice of male signals is unlikely to promote ecological adaptation in Enchenopa treehoppers (Hemiptera: Membracidae)

A key question in speciation research is how ecological and sexual divergence arise and interact. We tested the hypothesis that mate choice causes local adaptation and ecological divergence using the rationale that the performance~signal trait relationship should parallel the attractiveness~signal trait relationship. We used female fecundity as a measure of ecological performance. We used a species in the Enchenopa binotata treehopper complex, wherein speciation involves adaptation to novel environments and divergence in sexual communication. We used a full‐sibling, split‐family rearing design to estimate genetic correlations (r_G) between fecundity and signal traits, and compared those relationships against population‐level mate preferences for the signal traits. Animal model estimates for r_G between female fecundity and male signal traits overlapped zero—rejecting the hypothesis—but could reflect sample size limitations. The magnitude of r_G correlated with the strength of the mate preferences for the corresponding signal traits, especially for signal frequency, which has the strongest mate preference and the most divergence in the complex. However, signal frequencies favored by the population‐level mate preference are not associated with high fecundity. Therefore, mate preferences do not appear to have been selected to favor high‐performance genotypes. Our findings suggest that ecological and sexual divergence may arise separately, but reinforce each other, during speciation.     

Spatial analyses of two color polymorphisms in an alpine grasshopper reveal a role of small‐scale heterogeneity

Discrete color polymorphisms represent a fascinating aspect of intraspecific diversity. Color morph ratios often vary clinally, but in some cases, there are no marked clines and mixes of different morphs occur at appreciable frequencies in most populations. This poses the questions of how polymorphisms are maintained. We here study the spatial and temporal distribution of a very conspicuous color polymorphism in the club‐legged grasshopper Gomphocerus sibiricus. The species occurs in a green and a nongreen (predominately brown) morph, a green–brown polymorphism that is common among Orthopteran insects. We sampled color morph ratios at 42 sites across the alpine range of the species and related color morph ratios to local habitat parameters and climatic conditions. Green morphs occurred in both sexes, and their morph ratios were highly correlated among sites, suggesting shared control of the polymorphism in females and males. We found that in at least 40 of 42 sites green and brown morphs co‐occurred with proportions of green ranging from 0% to 70% with significant spatial heterogeneity. The proportion of green individuals tended to increase with decreasing summer and winter precipitations. Nongreen individuals can be further distinguished into brown and pied individuals, and again, this polymorphism is shared with other grasshopper species. We found pied individuals at all sites with proportions ranging from 3% to 75%, with slight, but significant variation between years. Pied morphs show a clinal increase in frequency from east to west and decreased with altitude and lower temperatures and were more common on grazed sites. The results suggest that both small‐scale and large‐scale spatial heterogeneity affects color morph ratios. The almost universal co‐occurrence of all three color morphs argues against strong effects of genetic drift. Instead, the data suggest that small‐scale migration–selection balance and/or local balancing selection maintain populations polymorphic.     

Characterizing the contribution of plasticity and genetic differentiation to community‐level trait responses to environmental change

The match between functional trait variation in communities and environmental gradients is maintained by three processes: phenotypic plasticity and genetic differentiation (intraspecific processes), and species turnover (interspecific). Recently, evidence has emerged suggesting that intraspecific variation might have a potentially large role in driving functional community composition and response to environmental change. However, empirical evidence quantifying the respective importance of phenotypic plasticity and genetic differentiation relative to species turnover is still lacking. We performed a reciprocal transplant experiment using a common herbaceous plant species (Oxalis montana) among low‐, mid‐, and high‐elevation sites to first quantify the contributions of plasticity and genetic differentiation in driving intraspecific variation in three traits: height, specific leaf area, and leaf area. We next compared the contributions of these intraspecific drivers of community trait–environment matching to that of species turnover, which had been previously assessed along the same elevational gradient. Plasticity was the dominant driver of intraspecific trait variation across elevation in all traits, with only a small contribution of genetic differentiation among populations. Local adaptation was not detected to a major extent along the gradient. Fitness components were greatest in O. montana plants with trait values closest to the local community‐weighted means, thus supporting the common assumption that community‐weighted mean trait values represent selective optima. Our results suggest that community‐level trait responses to ongoing climate change should be mostly mediated by species turnover, even at the small spatial scale of our study, with an especially small contribution of evolutionary adaptation within species.     

Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine‐scale models to evaluate environmental heterogeneity may help detecting adaptation to micro‐habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata. The two gene pools identified, experiencing limited gene flow along a 1‐km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine‐scale topography. Using a large panel of DEM‐derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high‐resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.     

Costs and benefits of admixture between foreign genotypes and local populations in the field

Admixture is the hybridization between populations within one species. It can increase plant fitness and population viability by alleviating inbreeding depression and increasing genetic diversity. However, populations are often adapted to their local environments and admixture with distant populations could break down local adaptation by diluting the locally adapted genomes. Thus, admixed genotypes might be selected against and be outcompeted by locally adapted genotypes in the local environments. To investigate the costs and benefits of admixture, we compared the performance of admixed and within‐population F1 and F2 generations of the European plant Lythrum salicaria in a reciprocal transplant experiment at three European field sites over a 2‐year period. Despite strong differences between site and plant populations for most of the measured traits, including herbivory, we found limited evidence for local adaptation. The effects of admixture depended on experimental site and plant population, and were positive for some traits. Plant growth and fruit production of some populations increased in admixed offspring and this was strongest with larger parental distances. These effects were only detected in two of our three sites. Our results show that, in the absence of local adaptation, admixture may boost plant performance, and that this is particularly apparent in stressful environments. We suggest that admixture between foreign and local genotypes can potentially be considered in nature conservation to restore populations and/or increase population viability, especially in small inbred or maladapted populations.     

石生南亚毛灰藓在不同温度和干旱条件下的生理生化特性

通过模拟高温和干旱处理,对喀斯特石漠化生境中南亚毛灰藓(Homomallium simlaense(Mitt.)Broth.Mitt)在胁迫条件下生理特征的变化进行了研究。结果表明,南亚毛灰藓在高温和干旱条件下,各项生理指标均与相对含水量呈显著正相关;丙二醛、渗透调节物质和叶绿素含量均随处理时间的增加和含水量的降低而减少,但植株仍保持较高的可溶性糖含量以维持渗透压的平衡。在极端干旱和高温的条件下,南亚毛灰藓可通过降低生理活性,保持一定的可溶性糖含量度过胁迫期,同时丙二醛含量保持最低状态。高温和干旱处理结束后,进行复水处理,植株的渗透调节物质和丙二醛含量显著升高,光合作用迅速恢复。研究结果表明,南亚毛灰藓适应干旱和高温的极端条件可能与丙二醛含量有关,但复水结束后丙二醛含量升高,胁迫反而增强,说明南亚毛灰藓对高温和干旱具有一定耐受性,原因可能与其长期生存于喀斯特的石生环境有关。     

Cas4 Facilitates PAM-Compatible Spacer Selection during CRISPR Adaptation

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A practical introduction to Random Forest for genetic association studies in ecology and evolution

Large genomic studies are becoming increasingly common with advances in sequencing technology, and our ability to understand how genomic variation influences phenotypic variation between individuals has never been greater. The exploration of such relationships first requires the identification of associations between molecular markers and phenotypes. Here, we explore the use of Random Forest (RF), a powerful machine‐learning algorithm, in genomic studies to discern loci underlying both discrete and quantitative traits, particularly when studying wild or nonmodel organisms. RF is becoming increasingly used in ecological and population genetics because, unlike traditional methods, it can efficiently analyse thousands of loci simultaneously and account for nonadditive interactions. However, understanding both the power and limitations of Random Forest is important for its proper implementation and the interpretation of results. We therefore provide a practical introduction to the algorithm and its use for identifying associations between molecular markers and phenotypes, discussing such topics as data limitations, algorithm initiation and optimization, as well as interpretation. We also provide short R tutorials as examples, with the aim of providing a guide to the implementation of the algorithm. Topics discussed here are intended to serve as an entry point for molecular ecologists interested in employing Random Forest to identify trait associations in genomic data sets.     

Effects of drought and phenology on GPP in Pinus sylvestris: a simulation study along a geographical gradient

1. A simple canopy model was developed for Scots Pine ( Pinus sylvestris L.) and applied to a transect of six meteorological stations in Europe. The model accounts for possible genetic adaptation of phenology of photosynthesis to the local climate and to decreases of gas exchange owing to drought.
2. Simulations accounting for adaptation of phenology to the local climate differed up to 20% from simulations using the same phenology parameter values for all locations.
3. A temperature increase of 3°C and a doubling of the CO₂ concentration, while adjusting the photosynthesis parameters to give approximately the observed changed photosynthesis of +30%, also increased the length of the growing season by 23–42%. Combination of increases in the rate of photosynthesis and the length of the growing season resulted in increases of yearly Gross Primary Productivity (GPP) from 72 to 101%. Increases in transpiration were smaller.
4. A decrease of the precipitation by 25% reduced this increase to 54–64%.
5. The relative magnitude of the simulated increases in GPP was similar for locations representing boreal, temperate and mediterranean climates.