The Mio-Pliocene European primate fossil record: dynamics and habitat tracking

We present here a study of European Neogene primate occurrences in the context of changing humidity. We studied the differences of primate localities versus non-primate localities by using the mammal communities and the ecomorphological data of the taxa present in the communities. The distribution of primates is influenced by humidity changes during the whole Neogene, and the results suggest that the primates track the changes in humidity through time. The exception to this is the Superfamily Cercopithecoidea which shows a wider range of choices in habitats. All primate localities seem to differ from non-primate localities in that the mammal community structure is more closed habitat oriented, while in non-primate localities the community structure changes towards open-habitat oriented in the late Neogene. The differences in primate and non-primate localities are stronger during the times of deep environmental change, when primates are found in their preferred habitats and non-primate localities have faunas better able to adapt to changing conditions.     

Glucagon signalling in the dorsal vagal complex is sufficient and necessary for high‐protein feeding to regulate glucose homeostasis in vivo

High‐protein feeding acutely lowers postprandial glucose concentration compared to low‐protein feeding, despite a dichotomous rise of circulating glucagon levels. The physiological role of this glucagon rise has been largely overlooked. We here first report that glucagon signalling in the dorsal vagal complex (DVC) of the brain is sufficient to lower glucose production by activating a Gcgr–PKA–ERK–K_ATP channel signalling cascade in the DVC of rats in vivo. We further demonstrate that direct blockade of DVC Gcgr signalling negates the acute ability of high‐ vs. low‐protein feeding to reduce plasma glucose concentration, indicating that the elevated circulating glucagon during high‐protein feeding acts in the brain to lower plasma glucose levels. These data revise the physiological role of glucagon and argue that brain glucagon signalling contributes to glucose homeostasis during dietary protein intake.     

THE IMPACT OF REGIONAL CLIMATE ON THE EVOLUTION OF MAMMALS: A CASE STUDY USING FOSSIL HORSES

One of the classic examples of faunal turnover in the fossil record is the Miocene transition from faunas dominated by anchitheriine horses with low-crowned molar teeth to faunas with hipparionine horses characterized by high-crowned teeth. The spread of hipparionine horses is associated with increased seasonality and the expansion of open habitats. It is generally accepted that anchitheriine horses did not display an evolutionary increase in tooth crown height prior to their extinction. Nevertheless, to test whether anchitheriines showed any changes interpretable as adaptation to local conditions, we analyzed molar teeth from multiple populations of Anchitherium in three dimensions. Our results show differences in tooth morphology that suggest incipient hypsodonty in Spain, the first region experiencing increasingly arid conditions in the early Miocene of Europe. Furthermore, analyses of tooth wear show that Spanish specimens cluster with present ungulates that eat foliage together with grasses and shrubs, whereas German specimens cluster with present-day ungulates that eat mostly foliage. Taken together, even a taxon such as Anchitherium , with a long and successful history of forest adaptation, did respond to regional environmental changes in an adaptive manner.     

Biomine: predicting links between biological entities using network models of heterogeneous databases

ABSTRACT: BACKGROUND: Biological databases contain large amounts of data concerning the functions and associationsof genes and proteins. Integration of data from several such databases into a single repositorycan aid the discovery of previously unknown connections spanning multiple types ofrelationships and databases. RESULTS: Biomine is a system that integrates cross-references from several biological databases into agraph model with multiple types of edges, such as protein interactions, gene-diseaseassociations and gene ontology annotations. Edges are weighted based on their type,reliability, and informativeness. We present Biomine and evaluate its performance in linkprediction, where the goal is to predict pairs of nodes that will be connected in the future,based on current data. In particular, we formulate protein interaction prediction and diseasegene prioritization tasks as instances of link prediction. The predictions are based on aproximity measure computed on the integrated graph. We consider and experiment withseveral such measures, and perform a parameter optimization procedure where different edgetypes are weighted to optimize link prediction accuracy. We also propose a novel method fordisease-gene prioritization, defined as finding a subset of candidate genes that cluster togetherin the graph. We experimentally evaluate Biomine by predicting future annotations in thesource databases and prioritizing lists of putative disease genes. CONCLUSIONS: The experimental results show that Biomine has strong potential for predicting links when aset of selected candidate links is available. The predictions obtained using the entire Biominedataset are shown to clearly outperform ones obtained using any single source of data alone,when different types of links are suitably weighted. In the gene prioritization task, anestablished reference set of disease-associated genes is useful, but the results show that underfavorable conditions, Biomine can also perform well when no such information is available.The Biomine system is a proof of concept. Its current version contains 1.1 million entities and8.1 million relations between them, with focus on human genetics. Some of its functionalitiesare available in a public query interface at http://biomine.cs.helsinki.fi, allowing searching forand visualizing connections between given biological entities.     

Clusterings should not be compared by visual inspection: response to Gagné & Proulx

In Heikinheimo et al . ( Journal of Biogeography , 2007, 34 , 1053–1064) we used clustering to analyse European land mammal fauna. Gagné & Proulx criticized our choice of the Euclidean distance measure in the analysis, and advocated the use of the Hellinger distance measure, claiming that this leads to very different clustering results. The criticism fails to take into account the probabilistic nature of the methods used and the fact that in this case the similarity measures correlate strongly. Gagné & Proulx used subjective inspection as the criterion of similarity between clusterings. We show that this is insufficient and misleading. Namely, owing to the local minimum problem, two clustering runs rarely give identical results. In the case of our study, the measured similarity (using the kappa statistic) between the Euclidean- and Hellinger-based clusterings is roughly equal to the similarity between two clusterings that both use the Hellinger distance but different random initialization points.     

Biogeography of European land mammals shows environmentally distinct and spatially coherent clusters

Aim  To produce a spatial clustering of Europe on the basis of species occurrence data for the land mammal fauna.
Location  Europe defined by the following boundaries: 11°W, 32°E, 71°N, 35°N.
Methods  Presence/absence records of mammal species collected by the Societas Europaea Mammalogica with a resolution of 50 × 50 km were used in the analysis. After pre-processing, the data provide information on 124 species in 2183 grid cells. The data were clustered using the k -means and probabilistic expectation maximization (EM) clustering algorithms. The resulting geographical pattern of clusters was compared against climate variables and against an environmental stratification of Europe based on climate, geomorphology and soil characteristics (EnS).
Results  The mammalian presence/absence data divide naturally into clusters, which are highly connected spatially and most strongly determined by the small mammals with the highest grid cell incidence. The clusters reflect major physiographic and environmental features and differ significantly in the values of basic climate variables. The geographical pattern is a fair match for the EnS stratification and is robust between non-overlapping subsets of the data, such as trophic groups.
Main conclusions  The pattern of clusters is regarded as reflecting the spatial expression of biologically distinct, metacommunity-like entities influenced by deterministic forces ultimately related to the physical environment. Small mammals give the most spatially coherent clusters of any subgroup, while large mammals show stronger relationships to climate variables. The spatial pattern is mainly due to small mammals with high grid cell incidence and is robust to noise from other subsets. The results support the use of spatially resolved environmental reconstructions based on fossil mammal data, especially when based on species with the highest incidence.     

Genome-Wide Scoring of Positive and Negative Epistasis through Decomposition of Quantitative Genetic Interaction Fitness Matrices

Recent technological developments in genetic screening approaches have offered the means to start exploring quantitative genotype-phenotype relationships on a large-scale. What remains unclear is the extent to which the quantitative genetic interaction datasets can distinguish the broad spectrum of interaction classes, as compared to existing information on mutation pairs associated with both positive and negative interactions, and whether the scoring of varying degrees of such epistatic effects could be improved by computational means. To address these questions, we introduce here a computational approach for improving the quantitative discrimination power encoded in the genetic interaction screening data. Our matrix approximation model decomposes the original double-mutant fitness matrix into separate components, representing variability across the array and query mutants, which can be utilized for estimating and correcting the single-mutant fitness effects, respectively. When applied to three large-scale quantitative interaction datasets in yeast, we could improve the accuracy of scoring various interaction classes beyond that obtained with the original fitness data, especially in synthetic genetic array (SGA) and in genetic interaction mapping (GIM) datasets. In addition to the known pairs of interactions used in the evaluation of the computational approach, a number of novel interaction pairs were also predicted, along with underlying biological mechanisms, which remained undetected by the original datasets. It was shown that the optimal choice of the scoring function depends heavily on the screening approach and on the interaction class under analysis. Moreover, a simple preprocessing of the fitness matrix could further enhance the discrimination power of the epistatic miniarray profiling (E-MAP) dataset. These systematic evaluation results provide in-depth information on the optimal analysis of the future, large-scale screening experiments. In general, the modeling framework, enabling accurate identification and classification of genetic interactions, provides a solid basis for completing and mining the genetic interaction networks in yeast and other organisms.     

Functional and anionic cellulose-interacting polymers by selective chemo-enzymatic carboxylation of galactose-containing polysaccharides

Carboxylated, anionic polysaccharides were selectively prepared using a combination of enzymatic and chemical reactions. The galactose-containing polysaccharides studied were spruce galactoglucomannan, guar galactomannan, and tamarind galactoxyloglucan. The galactosyl units of the polysaccharides were first oxidized with galactose oxidase (EC 1.1.3.9) and then selectively carboxylated, resulting in the galacturonic acid derivatives with good conversion and yield. The degrees of oxidation (DO) of the products were determined by gas chromatography-mass spectrometry (GC-MS). A novel feasible electrospray ionization-mass spectrometry (ESI-MS) method was also developed for the determination of DO. The solution properties and charge densities of the products were investigated. The interaction of the products with cellulose was studied by two methods, bulk sorption onto bleached birch kraft pulp and adsorption onto nanocellulose ultrathin films by quartz crystal microbalance with dissipation (QCM-D). To study the effect of the location of the carboxylic acid groups on the physicochemical properties, polysaccharides were also oxidized by 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-mediated reaction producing polyuronic acids. The chemo-enzymatically oxidized galacturonic polysaccharides with an unmodified backbone had a better ability to interact with cellulose than the TEMPO-oxidized products. The selectively carboxylated polysaccharides can be further exploited, as such, or in the targeted functionalization of cellulose surfaces.