Genetics of dispersal

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.     

荞麦籽粒结构的观察与分析

从荞麦籽粒的和分析中可以看出,荞麦的果皮和种皮容易分开,种子中心巨大的“Ｓ”形胚芽、胚根以及糊粉层虹适量科贮藏蛋白质存在的主要场所。在“Ｓ”形胚芽和胚根两侧是荞麦的两片叶子,由淀粉贮藏细胞组成。该细胞呈长方多棱体,细胞壁极薄且透明,人淀粉粒呈多面球形,大小均匀整齐,淀粉粒间结合紧密、严实,具有一定的几何构形。在淀粉粒间未发现基质蛋白质。     

Application of neem seed kernel extracts result in mouthpart deformities and subsequent mortality in Nezara viridula (L.) (Hem: Pentatomidae)

Abstract:  The effect of topical application of neem seed kernel aqueous suspension (NSKAS) and neem seed kernel hexane extract (NSKHE) on 2-day-old fourth instar nymphs of Nezara viridula (L.) was studied under laboratory conditions. The applications resulted in loosening of the proboscis, along with separation and deformation of mouthparts, predominantly in the stylets in fifth instar nymphs, adults and in inter-stadial moults. This rendered the insects incapable of feeding and led them to death. Application of NSKAS at 2.5% concentration led to 100% mortality, of which 40% was due to mouthpart deformities. Application of NSKHE at 2.5% concentration led to only 70% mortality, of which 3.33% was due to mouthpart deformities. At 5% concentration, mortality was again 100% for NSKAS and reached close to 100% for the NSKHE application. Dose-dependent mortality was observed for both the applications. However, dose-dependent mouthpart deformities were observed only for NSKAS, the highest being 60% at the 5% concentration. Moreover, for both the applications, more than 50% of the total mortality was observed up to the fifth instar at almost all the concentrations. The LC₅₀ values for NSKAS and NSKHE applications, for mortality up to the fifth instar were 0.36% and 5.22%, and for mortality to the adult stage (10 days old) they were 0.23% and 1.32% respectively. The percentage of bugs showing mouthpart deformities and toxicity was higher for NSKAS than NSKHE, and indicated that NSKAS was more potent than NSKHE.     

Two-stage functional mixed models for evaluating the effect of longitudinal covariate profiles on a scalar outcome

The Daily Hormone Study, a substudy of the Study of Women's Health Across the Nation (SWAN) consisting of more than 600 pre- and perimenopausal women, includes a scalar measure of total hip bone mineral density (BMD) together with repeated measures of creatinine-adjusted follicle stimulating hormone (FSH) assayed from daily urine samples collected over one menstrual cycle. It is of scientific interest to investigate the effect of the FSH time profile during a menstrual cycle on total hip BMD, adjusting for age and body mass index. The statistical analysis is challenged by several features of the data: (1) the covariate FSH is measured longitudinally and its effect on the scalar outcome BMD may be complex; (2) due to varying menstrual cycle lengths, subjects have unbalanced longitudinal measures of FSH; and (3) the longitudinal measures of FSH are subject to considerable among- and within-subject variations and measurement errors. We propose a measurement error partial functional linear model, where repeated measures of FSH are modeled using a functional mixed effects model and the effect of the FSH time profile on BMD is modeled using a partial functional linear model by treating the unobserved true subject-specific FSH time profile as a functional covariate. We develop a two-stage nonparametric regression calibration method using period smoothing splines. Using the connection between smoothing splines and mixed models, we show that a key feature of our approach is that estimation at both stages can be conveniently cast into a unified mixed model framework. A simple testing procedure for constant functional covariate effect is also proposed. The proposed methods are evaluated using simulation studies and applied to the SWAN data.     

Fixed and random effects selection in linear and logistic models

We address the problem of selecting which variables should be included in the fixed and random components of logistic mixed effects models for correlated data. A fully Bayesian variable selection is implemented using a stochastic search Gibbs sampler to estimate the exact model-averaged posterior distribution. This approach automatically identifies subsets of predictors having nonzero fixed effect coefficients or nonzero random effects variance, while allowing uncertainty in the model selection process. Default priors are proposed for the variance components and an efficient parameter expansion Gibbs sampler is developed for posterior computation. The approach is illustrated using simulated data and an epidemiologic example.     

芒果核仁的化学成分及其抑菌活性

从杧果(Mangifera indica L.)果实核仁中分离得到6种化合物。经光谱分析及与文献对照,分别鉴定为没食子酸(1)、没食子酸甲酯(2)、没食子酸乙酯(3)、间-二没食子酸甲酯(4)、对羟基苯甲酸(5)和丁二酸单甲酯(6),它们均为首次从芒果核中获得。用琼脂平板稀释法测定了化合物1~5对7种细菌和4种真菌生长的抑制活性。结果表明,化合物1对金黄色葡萄球菌(Staphylococcus aureus)、表皮葡萄球菌(S. epidermidis)、干燥棒状杆菌(Corynebacterium xerosis)和藤黄微球菌(Micrococcus luteus)的最小抑制浓度(MIC)为50~100 µg mL-1,化合物4对绿脓杆菌(Pseudomonas aeruginosa)有抑制活性。     

响应面法优化微波辅助提取山苍子核仁油的研究

通过微波辅助提取技术结合响应面法优化山苍子核仁油提取条件,以期建立更高产率的提取方法。该研究在单因素设计基础上,选取液料比、微波功率、萃取时间、萃取温度4个主要因素,分析这4个因素对山苍子核仁油提取率的影响。结果表明:通过建立多元回归拟合分析,得出山苍子核仁油提取最佳工艺条件为液料比1∶16,萃取温度为69℃,微波功率为337 W,萃取时间为63 min,在此条件下山苍子核仁油提取率为37.42%,与环己烷溶剂回流法相比较提取率提高了30.11%。气质联用仪分析结果显示,山苍子核仁油主要成分有16种占总成分的88.21%,鉴定出10种脂肪酸占总成分的78.24%,饱和脂肪酸有4种占总成分的43.23%,不饱和脂肪酸有6种占总成分的35.01%,脂肪酸中含量最高的为月桂酸(31.36%)。该研究结果表明该方法严谨、可靠,采用微波辅助提取山苍子核仁油是可行的。