Pushed to the edge: Spatial sorting can slow down invasions

Our ability to understand population spread dynamics is complicated by rapid evolution, which renders simple ecological models insufficient. If dispersal ability evolves, more highly dispersive individuals may arrive at the population edge than less dispersive individuals (spatial sorting), accelerating spread. If individuals at the low-density population edge benefit (escape competition), high dispersers have a selective advantage (spatial selection). These two processes are often described as forming a positive feedback loop; they reinforce each other, leading to faster spread. Although spatial sorting is close to universal, this form of spatial selection is not: low densities can be detrimental for organisms with Allee effects. Here, we present two conceptual models to explore the feedback loops that form between spatial sorting and spatial selection. We show that the presence of an Allee effect can reverse the positive feedback loop between spatial sorting and spatial selection, creating a negative feedback loop that slows population spread.     

烯效唑干拌种对小麦氮素积累和运转及籽粒蛋白质品质的影响

通过田间试验,研究了不同烯效唑干拌种剂量对3个不同筋力小麦品种植株氮素积累、运转和籽粒蛋白质品质的影响,结果表明,基因型、环境及烯效唑处理对小麦品质的影响效应依次减小,且均达到了极显著水平,但三者的互作效应较小。烯效唑处理后提高了不同生态点下不同小麦品种籽粒蛋白质含量和产量,处理后的面筋含量和沉淀值增加,面团形成时间和稳定时间延长;干拌种增加了开花期各营养器官中的氮素含量和单株氮素积累量,花后氮素总转移量、总转移率及其对籽粒氮的贡献率极显著提高,且处理后旗叶中可溶性蛋白质含量在花后15 d内均显著高于对照;对籽粒中氮含量而言,烯效唑处理后提高了灌浆初期籽粒中的非蛋白氮含量,花后5—20 d内均高于对照,灌浆期间籽粒蛋白氮含量均高于对照,因而处理后的粗蛋白质含量变化动态特点为谷底高、回升快。研究认为,烯效唑处理如同基因、环境一样独立影响小麦籽粒品质,而烯效唑处理后提高了开花初期旗叶中的可溶性蛋白质含量和花前营养器官中氮素含量及花后氮素转运量,可能是其提高籽粒非蛋白氮含量、促进籽粒蛋白质含量增加和蛋白质质量提高的重要原因之一,烯效唑干拌种对小麦籽粒蛋白质品质的改善具有广适性。     

宽窄行栽植模式下三倍体毛白杨根系分布特征及其与根系吸水的关系

采用剖面法对宽窄行栽植模式下三倍体毛白杨(triploid Populus tomentosa)的根系分布特征进行了研究;采用管式TDR系统对土壤剖面含水率变化动态进行了连续观测,并据此计算林木根系吸水速率,以探讨土壤含水率、根系分布和根系吸水分布之间的相关关系。研究结果表明:毛白杨的总平均根长密度在林带两侧和不同径向距离处非常接近(P>0.05);但在不同土层间变化很大(P<0.01),其中0-20和60-150 cm土层为根系主要分布区域,其根系所占比例共达86%;不同径阶间的根长密度差异显著(P<0.01),且其比例关系会随空间位置的改变而发生变化。不同栽植方位下,林带东侧毛白杨根系分布的浅层化程度高于西侧,且在径向240-280 cm内其0-0.5 mm的极细根显著多于西侧(P<0.05)。因此,宽窄行栽植模式下,深度和径阶是毛白杨根系分布的主要影响因子,而栽植方位会对其形态构型产生影响。毛白杨根系吸水模式受细根分布的影响,但会随土壤剖面水分有效性分布的变化而变化:当表土层水分有效性增加时,根系吸水主要集中在表土层;当表土层水分有效性降低时,深层土壤根系的吸水贡献率会逐渐增加;当土壤剖面水分条件异质性较高时,根系吸水主要集中在根系密度与水分有效性均较高的区域;当土壤剖面水分分布均匀且不存在水分胁迫时,根系吸水分布与细根分布最为一致。     

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。     

Genomic prediction in CIMMYT maize and wheat breeding programs

Genomic selection (GS) has been implemented in animal and plant species, and is regarded as a useful tool for accelerating genetic gains. Varying levels of genomic prediction accuracy have been obtained in plants, depending on the prediction problem assessed and on several other factors, such as trait heritability, the relationship between the individuals to be predicted and those used to train the models for prediction, number of markers, sample size and genotype × environment interaction (GE). The main objective of this article is to describe the results of genomic prediction in International Maize and Wheat Improvement Center''s (CIMMYT''s) maize and wheat breeding programs, from the initial assessment of the predictive ability of different models using pedigree and marker information to the present, when methods for implementing GS in practical global maize and wheat breeding programs are being studied and investigated. Results show that pedigree (population structure) accounts for a sizeable proportion of the prediction accuracy when a global population is the prediction problem to be assessed. However, when the prediction uses unrelated populations to train the prediction equations, prediction accuracy becomes negligible. When genomic prediction includes modeling GE, an increase in prediction accuracy can be achieved by borrowing information from correlated environments. Several questions on how to incorporate GS into CIMMYT''s maize and wheat programs remain unanswered and subject to further investigation, for example, prediction within and between related bi-parental crosses. Further research on the quantification of breeding value components for GS in plant breeding populations is required.     

Morphological variation associated with dispersal capacity in a tree‐killing bark beetle Dendroctonus ponderosae Hopkins

相似文献   

Fibrous long spacing type collagen fibrils have a hierarchical internal structure

Nanodissection of single fibrous long spacing (FLS) type collagen fibrils by atomic force microscopy (AFM) reveals hierarchical internal structure: Fibrillar subcomponents with diameters of approximately 10 to 20 nm were observed to be running parallel to the long axis of the fibril in which they are found. The fibrillar subcomponent displayed protrusions with characteristic approximately 270 nm periodicity, such that protrusions on neighboring subfibrils were aligned in register. Hence, the banding pattern of mature FLS-type collagen fibrils arises from the in-register alignment of these fibrillar subcomponents. This hierarchical organization observed in FLS-type collagen fibrils is different from that previously reported for native-type collagen fibrils, displaying no supercoiling at the level of organization observed.     

Associating somatic mutation with clinical outcomes through kernel regression and optimal transport

Somatic mutations in cancer patients are inherently sparse and potentially high dimensional. Cancer patients may share the same set of deregulated biological processes perturbed by different sets of somatically mutated genes. Therefore, when assessing the associations between somatic mutations and clinical outcomes, gene-by-gene analysis is often under-powered because it does not capture the complex disease mechanisms shared across cancer patients. Rather than testing genes one by one, an intuitive approach is to aggregate somatic mutation data of multiple genes to assess their joint association with clinical outcomes. The challenge is how to aggregate such information. Building on the optimal transport method, we propose a principled approach to estimate the similarity of somatic mutation profiles of multiple genes between tumor samples, while accounting for gene–gene similarities defined by gene annotations or empirical mutational patterns. Using such similarities, we can assess the associations between somatic mutations and clinical outcomes by kernel regression. We have applied our method to analyze somatic mutation data of 17 cancer types and identified at least five cancer types, where somatic mutations are associated with overall survival, progression-free interval, or cytolytic activity.     

Integrating multi-platform genomic data using hierarchical Bayesian relevance vector machines

Background

Recent advances in genome technologies and the subsequent collection of genomic information at various molecular resolutions hold promise to accelerate the discovery of new therapeutic targets. A critical step in achieving these goals is to develop efficient clinical prediction models that integrate these diverse sources of high-throughput data. This step is challenging due to the presence of high-dimensionality and complex interactions in the data. For predicting relevant clinical outcomes, we propose a flexible statistical machine learning approach that acknowledges and models the interaction between platform-specific measurements through nonlinear kernel machines and borrows information within and between platforms through a hierarchical Bayesian framework. Our model has parameters with direct interpretations in terms of the effects of platforms and data interactions within and across platforms. The parameter estimation algorithm in our model uses a computationally efficient variational Bayes approach that scales well to large high-throughput datasets.

Results

We apply our methods of integrating gene/mRNA expression and microRNA profiles for predicting patient survival times to The Cancer Genome Atlas (TCGA) based glioblastoma multiforme (GBM) dataset. In terms of prediction accuracy, we show that our non-linear and interaction-based integrative methods perform better than linear alternatives and non-integrative methods that do not account for interactions between the platforms. We also find several prognostic mRNAs and microRNAs that are related to tumor invasion and are known to drive tumor metastasis and severe inflammatory response in GBM. In addition, our analysis reveals several interesting mRNA and microRNA interactions that have known implications in the etiology of GBM.

Conclusions

Our approach gains its flexibility and power by modeling the non-linear interaction structures between and within the platforms. Our framework is a useful tool for biomedical researchers, since clinical prediction using multi-platform genomic information is an important step towards personalized treatment of many cancers. We have a freely available software at: http://odin.mdacc.tmc.edu/~vbaladan.

     

Formation of spacing pattern and morphogenesis of chick feather buds is regulated by cytoskeletal structures

Chick feather buds develop sequentially in a hexagonal array. Each feather bud develops with anterior posterior polarity, which is thought to develop in response to signals derived from specialized regions of mesenchymal condensation and epithelial thickening. These developmental processes are performed by cellular mechanisms, such as cell proliferation and migration, which occur during chick feather bud development. In order to understand the mechanisms regulating the formation of mesenchymal condensation and their role in feather bud development, we explanted chick dorsal skin at stage HH29+ with cytochalasin D, which inhibits cytoskeletal formation. We show that the aggregation of mesenchymal cells can be prevented by cytochalasin D treatment in a concentration-dependent manner. Subsequently, cytochalasin D disrupts the spacing pattern and inhibits feather bud axis formation as well. In addition, expression patterns of Bmp-4 and Msx-2, key molecules for early feather bud development, were disturbed by cytochalasin D treatment. Our results fully indicate that both the cytoskeletal structure and cell activity via gene regulation are of fundamental importance in mesenchymal condensation leading to proper morphogenesis of feather bud and spacing pattern formation.