蓖麻毒蛋白A链基因RNAi转化研究

通过基因沉默技术调控蓖麻毒蛋白A链基因的表达,以期获得低毒蓖麻新材料.利用基因克隆技术获得蓖麻毒蛋白A链基因762 bp片段,命名为RTA基因.进一步利用该基因构建了植物RNAi表达载体pBI-RTA-S-AS,通过农杆菌介导法转化蓖麻子叶节,用卡那抗性筛选转化再生植株,PCR进一步鉴定转基因植株.结果表明:克隆得到目的基因长762 bp,与预期结果一致;卡那抗性筛选和PCR鉴定结果显示,获得了3株转基因阳性植株.     

不同类群水生昆虫群落间的一致性以及空间和环境因子的相对作用

生物多样性监测和保护过程中通常用到指示类群,然而对于这些指示类群有效性的测度仍然十分欠缺.为探讨不同类群水生昆虫群落的一致性及空间因子、环境变量的相对影响,作者于2010年4月对东苕溪流域源头溪流21个采样点进行了调查.共记录水生昆虫7目44科92属130种.我们将水生昆虫群落划分成鞘翅目(C)、蜉蝣目+襀翅目+毛翅目(EPT)和双翅目+广翅目+蜻蜒目(DMO)3个类群.一致性分析结果表明:3个类群的群落一致性(r)较高,分别为C对EPTr=0.65 (P＜0.001)、C对DMO r=0.67 (P＜0.001)、EPT对DMO r=0.82 (P＜0.001).方差分解表明环境变量是影响不同类群水生昆虫群落结构的主要因素,空间因子的影响相对较小.环境因子中影响不同类群水生昆虫群落的关键变量大体相似,其中海拔、pH、平均流速和化学需氧量是最主要的驱动因子.我们的结果表明该研究区域不同类群的水生昆虫群落一致性很高,且对环境变量的响应也相似;因此,在水生昆虫生物多样性保护中可考虑利用其中的某一类群,如蜉蝣目+襀翅目+毛翅目(EPT)类群,作为有效的指示类群.     

Increased Activity of Liver Xanthine Oxidase in Rats from Increasing Dietary Calcium

A new binary vector, pZT4B, containing the UDP-N-acetylglucosamine: dolichol phosphate N-acetylglucosamine-1-P transferase (GPT) gene as a selection marker, was constructed. The green fluorescent protein (GFP) gene was inserted into pZT4B, and the resulting plasmid was used in the transformation of Arabidopsis. All of six independent transformants obtained after selection with 0.3 mg/l tunicamycin contained the transgene and showed GFP fluorescence.     

Development of R4 Gateway Binary Vectors (R4pGWB) Enabling High-Throughput Promoter Swapping for Plant Research

We developed a new series of Gateway binary vectors, R4pGWBs, that are plant transformation vectors designed for one-step construction of chimeric genes between any promoter and any cDNA. The structure of R4pGWBs is almost the same as the promoterless type of improved pGWBs (ImpGWBs), except that the attR1 site is replaced with attR4, which enables tripartite recombination of these vectors with promoter- and cDNA-entry clones. While ImpGWBs are suitable for promoter analysis and constitutive expression of cDNAs in higher plants, R4pGWBs have a great advantage in expressing a cDNA under the regulation of desired promoters.     

Comparison of boosted regression tree and random forest models for mapping topsoil organic carbon concentration in an alpine ecosystem

Soil organic carbon (SOC) plays an important role in soil fertility and carbon sequestration, and a better understanding of the spatial patterns of SOC is essential for soil resource management. In this study, we used boosted regression tree (BRT) and random forest (RF) models to map the distribution of topsoil organic carbon content at the northeastern edge of the Tibetan Plateau in China. A set of 105 soil samples and 12 environmental variables (including topography, climate and vegetation) were analyzed. The performance of the models was evaluated using a 10-fold cross-validation procedure. Maps of the mean values and standard deviations of SOC were generated to illustrate model variability and uncertainty. The results indicate that the BRT and RF models exhibited very similar performance and yielded similar predicted distributions of SOC. The two models explained approximately 70% of the total SOC variability. The BRT and RF models robustly predicted the SOC at low observed SOC values, whereas they underestimated high observed SOC values. This underestimation may have been caused by biased distributions of soil samples in the SOC space. Vegetation-related variables were assigned the highest importance in both models, followed by climate and topography. Both models produced spatial distribution maps of SOC that were closely related to vegetation cover. The SOC content predicted by the BRT model was clearly higher than that of the RF model in areas with greater vegetation cover because the contributions of vegetation-related variables in the two models (65% and 43%, respectively) differed significantly. The predicted SOC content increased from the northwestern to the southeastern part of the study area, average values produced by the BRT and RF models were 27.3 g kg⁻¹ and 26.6 g kg⁻¹, respectively. We conclude that the BRT and RF methods should be calibrated and compared to obtain the best prediction of SOC spatial distribution in similar regions. In addition, vegetation variables, including those obtained from remote sensing imagery, should be taken as the main environmental indicators and explicitly included when generating SOC maps in Alpine environments.     

Climatic effects on the distribution of ant- and bat fly-associated fungal ectoparasites (Ascomycota,Laboulbeniales)

Laboulbeniales (Ascomycota: Laboulbeniomycetes) are obligate ectoparasitic fungi of arthropods with a worldwide distribution. Their effects on host physiology and behaviour as well as their ecology have recently gained wider attention. One aspect that is virtually unknown regarding Laboulbeniales and arthropod-associated fungi in general, is how abiotic factors shape the distribution of these parasites. We used ant- and bat fly-associated Laboulbeniales to study whether climatic elements play a role in the distribution of fungal species. We collected uninfected and Laboulbeniales-infected insects belonging to three species: bat flies Nycteribia schmidlii and Penicillidia conspicua (Diptera: Nycteribiidae) and the ant Myrmica scabrinodis (Hymenoptera: Formicidae). We used climatic variables and performed statistical analyses to explain the distribution of Laboulbeniales infection. Our results show a higher likelihood of Laboulbeniales presence in habitats with low annual mean temperature and humidity, suggesting that climatic elements can considerably shape the distribution of Laboulbeniales species.     

Spatial variation in the ongoing and widespread decline of a keystone plant species

Extensive dieback in dominant plant species in response to climate change is increasingly common. Climatic conditions and related variables, such as evapotranspiration, vary in response to topographical complexity. This complexity plays an important role in the provision of climate refugia. In 2008/2009, an island‐wide dieback event of the keystone cushion plant Azorella macquariensis Orchard (Apiaceae) occurred on sub‐Antarctic Macquarie Island. This signalled the start of a potential regime shift, suggested to be driven by increasing vapour pressure deficit. Eight years later, we quantified cover and dieback across the range of putative microclimates to which the species is exposed, with the aim of explaining dieback patterns. We test for the influence of evapotranspiration using a suite of topographic proxies and other variables as proposed drivers of change. We found higher cover and lower dieback towards the south of the island. The high spatial variation in A. macquariensis populations was best explained by latitude, likely a proxy for macroscale climate gradients and geology. Dieback was best explained by A. macquariensis cover and latitude, increasing with cover and towards the north of the island. The effect sizes of terrain variables that influence evapotranspiration rates were small. Island‐wide dieback remains conspicuous. Comparison between a subset of sites and historical data revealed a reduction of cover in the north and central regions of the island, and a shift south in the most active areas of dieback. Dieback remained comparatively low in the south. The presence of seedlings was independent of dieback. This study provides an empirical baseline for spatial variation in the cover and condition of A. macquariensis, both key variables for monitoring condition and ‘cover‐debt’ in this critically endangered endemic plant species. These findings have broader implications for understanding the responses of fellfield ecosystems and other Azorella species across the sub‐Antarctic under future climates.     

Red panda fine‐scale habitat selection along a Central Himalayan longitudinal gradient

Red panda Ailurus fulgens, an endangered habitat specialist, inhabits a narrow distribution range in bamboo abundance forests along mountain slopes in the Himalaya and Hengduan Mountains. However, their habitat use may be different in places with different longitudinal environmental gradients, climatic regimes, and microclimate. This study aimed to determine the habitat variables affecting red panda distribution across different longitudinal gradients through a multivariate analysis. We studied habitat selection patterns along the longitudinal gradient in Nepal's Himalaya which is grouped into the eastern, central, and western complexes. We collected data on red panda presence and habitat variables (e.g., tree richness, canopy cover, bamboo abundance, water availability, tree diameter, tree height) by surveys along transects throughout the species’ potential range. We used a multimodal inference approach with a generalized linear model to test the relative importance of environmental variables. Although the study showed that bamboo abundance had a major influence, habitat selection was different across longitudinal zones. Both canopy cover and species richness were unimportant in eastern Nepal, but their influence increased progressively toward the west. Conversely, tree height showed a decreasing influence on habitat selection from Eastern to Western Nepal. Red panda's habitat selection revealed in this study corresponds to the uneven distribution of vegetation assemblages and the dry climatic gradient along the eastern‐western Himalayas which could be related to a need to conserve energy and thermoregulate. This study has further highlighted the need of importance of bamboo conservation and site‐specific conservation planning to ensure long‐term red panda conservation.