No evidence that mRNAs have lower folding free energies than random sequences with the same dinucleotide distribution

This work investigates whether mRNA has a lower estimated folding free energy than random sequences. The free energy estimates are calculated by the mfold program for prediction of RNA secondary structures. For a set of 46 mRNAs it is shown that the predicted free energy is not significantly different from random sequences with the same dinucleotide distribution. For random sequences with the same mononucleotide distribution it has previously been shown that the native mRNA sequences have a lower predicted free energy, which indicates a more stable structure than random sequences. However, dinucleotide content is important when assessing the significance of predicted free energy as the physical stability of RNA secondary structure is known to depend on dinucleotide base stacking energies. Even known RNA secondary structures, like tRNAs, can be shown to have predicted free energies indistinguishable from randomized sequences. This suggests that the predicted free energy is not always a good determinant for RNA folding.     

Algorithms for prediction of alpha-helical and beta-structural regions in globular proteins

Algorithms are suggested for identifying α-helical and β-structural regions in native globular proteins. α-Helical and β-structural regions are predicted, with accuracy of ~80 and ~85% respectively, for 25 proteins, the three-dimensional structures of which have been determined by X-ray diffraction crystallography. Secondary structure is predicted in 25 proteins with unknown three-dimensional structure.     

Age-structured effects and disease interference in childhood infections

Recent studies have demonstrated that ecological interference among some childhood diseases may have important dynamic consequences. An interesting question is, when would we expect the interference effect to be pronounced? To address the issue, here we develop a seasonally forced two-disease age-structured model, using empirically derived age-specific force of infection (ASFOI) for numerous infections of childhood. Our comparative numerical analysis shows that when the ASFOIs for the two diseases largely overlap, the dynamics predicted by the two-disease model are generally different from those predicted by the analogous single-disease model, suggesting strong fingerprints of disease interference. When the ASFOIs overlap less, on the other hand, both diseases behave as predicted by the single-disease model, suggesting weak interference. We conclude that age structure is an important factor that should be taken into account in order to explore the underlying mechanisms of disease interference.     

Single nucleotide polymorphism-based validation of exonic splicing enhancers

Because deleterious alleles arising from mutation are filtered by natural selection, mutations that create such alleles will be underrepresented in the set of common genetic variation existing in a population at any given time. Here, we describe an approach based on this idea called VERIFY (variant elimination reinforces functionality), which can be used to assess the extent of natural selection acting on an oligonucleotide motif or set of motifs predicted to have biological activity. As an application of this approach, we analyzed a set of 238 hexanucleotides previously predicted to have exonic splicing enhancer (ESE) activity in human exons using the relative enhancer and silencer classification by unanimous enrichment (RESCUE)-ESE method. Aligning the single nucleotide polymorphisms (SNPs) from the public human SNP database to the chimpanzee genome allowed inference of the direction of the mutations that created present-day SNPs. Analyzing the set of SNPs that overlap RESCUE-ESE hexamers, we conclude that nearly one-fifth of the mutations that disrupt predicted ESEs have been eliminated by natural selection (odds ratio = 0.82 +/- 0.05). This selection is strongest for the predicted ESEs that are located near splice sites. Our results demonstrate a novel approach for quantifying the extent of natural selection acting on candidate functional motifs and also suggest certain features of mutations/SNPs, such as proximity to the splice site and disruption or alteration of predicted ESEs, that should be useful in identifying variants that might cause a biological phenotype.     

Human demography and reserve size predict wildlife extinction in West Africa.

Species-area models have become the primary tool used to predict baseline extinction rates for species in isolated habitats, and have influenced conservation and land-use planning worldwide. In particular, these models have been used to predict extinction rates following the loss or fragmentation of natural habitats in the absence of direct human influence on species persistence. Thus, where direct human influences, such as hunting, put added pressure on species in remnant habitat patches, we should expect to observe extinction rates higher than those predicted by simple species-area models. Here, we show that extinction rates for 41 species of large mammals in six nature reserves in West Africa are 14-307 times higher than those predicted by models based on reserve size alone. Human population and reserve size accounted for 98% of the observed variation in extinction rates between reserves. Extinction occurred at higher rates than predicted by species-area models for carnivores, primates and ungulates, and at the highest rates overall near reserve borders. Our results indicate that, where the harvest of wildlife is common, conservation plans should focus on increasing the size of reserves and reducing the rate of hunting.     

Climate change and plant distribution: local models predict high-elevation persistence

Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted by species distribution models (SDMs). Depending on the geographic extent, elevation range, and spatial resolution of data used in making these models, different rates of habitat loss have been predicted, with associated risk of species extinction. Few coordinated across-scale comparisons have been made using data of different resolutions and geographic extents. Here, we assess whether climate change-induced habitat losses predicted at the European scale (10 × 10' grid cells) are also predicted from local-scale data and modeling (25 m × 25 m grid cells) in two regions of the Swiss Alps. We show that local-scale models predict persistence of suitable habitats in up to 100% of species that were predicted by a European-scale model to lose all their suitable habitats in the area. Proportion of habitat loss depends on climate change scenario and study area. We find good agreement between the mismatch in predictions between scales and the fine-grain elevation range within 10 × 10' cells. The greatest prediction discrepancy for alpine species occurs in the area with the largest nival zone. Our results suggest elevation range as the main driver for the observed prediction discrepancies. Local-scale projections may better reflect the possibility for species to track their climatic requirement toward higher elevations.     

Rat heart fatty acid-binding protein. Evidence that supports the amino acid sequence predicted from the cDNA.

The amino acid sequence of rat heart fatty acid-binding protein was re-examined by analysing the tryptic and the chymotryptic peptides, since some discrepancies have been reported between the sequences determined by protein analyses and that deduced from the cDNA analyses. Our result completely agreed with the amino acid sequence predicted from the cDNA analyses, providing evidence for the actual existence of the molecular species predicted from the cDNA.     

WorfDB: the Caenorhabditis elegans ORFeome Database

WorfDB (Worm ORFeome DataBase; http://worfdb.dfci.harvard.edu) was created to integrate and disseminate the data from the cloning of complete set of approximately 19 000 predicted protein-encoding Open Reading Frames (ORFs) of Caenorhabditis elegans (also referred to as the 'worm ORFeome'). WorfDB serves as a central data repository enabling the scientific community to search for availability and quality of cloned ORFs. So far, ORF sequence tags (OSTs) obtained for all individual clones have allowed exon structure corrections for approximately 3400 ORFs originally predicted by the C. elegans sequencing consortium. In addition, we now have OSTs for approximately 4300 predicted genes for which no ESTs were available. The database contains this OST information along with data pertinent to the cloning process. WorfDB could serve as a model database for other metazoan ORFeome cloning projects.     

Construction of disease-specific cytokine profiles by associating disease genes with immune responses

The pathogenesis of many inflammatory diseases is a coordinated process involving metabolic dysfunctions and immune response—usually modulated by the production of cytokines and associated inflammatory molecules. In this work, we seek to understand how genes involved in pathogenesis which are often not associated with the immune system in an obvious way communicate with the immune system. We have embedded a network of human protein-protein interactions (PPI) from the STRING database with 14,707 human genes using feature learning that captures high confidence edges. We have found that our predicted Association Scores derived from the features extracted from STRING’s high confidence edges are useful for predicting novel connections between genes, thus enabling the construction of a full map of predicted associations for all possible pairs between 14,707 human genes. In particular, we analyzed the pattern of associations for 126 cytokines and found that the six patterns of cytokine interaction with human genes are consistent with their functional classifications. To define the disease-specific roles of cytokines we have collected gene sets for 11,944 diseases from DisGeNET. We used these gene sets to predict disease-specific gene associations with cytokines by calculating the normalized average Association Scores between disease-associated gene sets and the 126 cytokines; this creates a unique profile of inflammatory genes (both known and predicted) for each disease. We validated our predicted cytokine associations by comparing them to known associations for 171 diseases. The predicted cytokine profiles correlate (p-value<0.0003) with the known ones in 95 diseases. We further characterized the profiles of each disease by calculating an “Inflammation Score” that summarizes different modes of immune responses. Finally, by analyzing subnetworks formed between disease-specific pathogenesis genes, hormones, receptors, and cytokines, we identified the key genes responsible for interactions between pathogenesis and inflammatory responses. These genes and the corresponding cytokines used by different immune disorders suggest unique targets for drug discovery.     

气候变暖情境下松材线虫在我国的适生区范围

基于历史气象数据(1971—2000),利用CLIMEX软件对松材线虫Bursaphelenchus xylophilus在我国的潜在适生区进行了预测,结果显示:松材线虫在我国的适生范围广、适生程度高,全国除黑龙江、吉林省无适生区外,其余各省市区均有适生区域,其中约2/3的适生区为高度适生区,覆盖整个南方地区,分布北界达内蒙古通辽地区,西至西藏的日喀则地区;进一步结合英国气候变化研究中心提供的气候变暖情境下未来气候模拟数据TYNSC2.0,利用CLIMEX软件预测出未来30年内(2010-2039)松材线虫在我国的潜在适生区,结果发现同历史气候条件下相比,未来30年内松材线虫在我国的适生分布区将呈现范围增加、适生程度增加、向北扩散的趋势,其中分布北界将到达吉林省西部,分布西界则与历史气候条件下预测结果相差无几。     

Visualization of alpha-helices in a 6-angstrom resolution cryoelectron microscopy structure of adenovirus allows refinement of capsid protein assignments

The structure of adenovirus was determined to a resolution of 6 A by cryoelectron microscopy (cryoEM) single-particle image reconstruction. Docking of the hexon and penton base crystal structures into the cryoEM density established that alpha-helices of 10 or more residues are resolved as rods. A difference map was calculated by subtracting a pseudoatomic capsid from the cryoEM reconstruction. The resulting density was analyzed in terms of observed alpha-helices and secondary structure predictions for the additional capsid proteins that currently lack atomic resolution structures (proteins IIIa, VI, VIII, and IX). Protein IIIa, which is predicted to be highly alpha-helical, is assigned to a cluster of helices observed below the penton base on the inner capsid surface. Protein VI is present in approximately 1.5 copies per hexon trimer and is predicted to have two long alpha-helices, one of which appears to lie inside the hexon cavity. Protein VIII is cleaved by the adenovirus protease into two fragments of 7.6 and 12.1 kDa, and the larger fragment is predicted to have one long alpha-helix, in agreement with the observed density for protein VIII on the inner capsid surface. Protein IX is predicted to have one long alpha-helix, which also has a strongly indicated propensity for coiled-coil formation. A region of density near the facet edge is now resolved as a four-helix bundle and is assigned to four copies of the C-terminal alpha-helix from protein IX.     

多肽的α螺旋结构对多肽与钙调蛋白亲合力的影响

本文设计并采用固相法合成了4种钙调蛋白可结合多肽,这些多肽分成两组,每一组中两个多肽的碱性和疏水性相近,但形成α螺旋结构的倾向(预测)不同。研究了这些多肽与钙调蛋白的相互作用,在Ca~(2+)存在下,这些多肽与丹磺酰钙调蛋白结合,使丹磺酰钙调蛋白的荧光光谱发生显著变化,测定了多肽与钙调蛋白所形成的复合物的解离常数。结果表明,预测形成α螺旋结构倾向较大的多肽与钙调蛋白的亲合力也较大。     

Predicted residue–residue contacts can help the scoring of 3D models

During the 7th Critical Assessment of Protein Structure Prediction (CASP7) experiment, it was suggested that the real value of predicted residue–residue contacts might lie in the scoring of 3D model structures. Here, we have carried out a detailed reassessment of the contact predictions made during the recent CASP8 experiment to determine whether predicted contacts might aid in the selection of close‐to‐native structures or be a useful tool for scoring 3D structural models. We used the contacts predicted by the CASP8 residue–residue contact prediction groups to select models for each target domain submitted to the experiment. We found that the information contained in the predicted residue–residue contacts would probably have helped in the selection of 3D models in the free modeling regime and over the harder comparative modeling targets. Indeed, in many cases, the models selected using just the predicted contacts had better GDT‐TS scores than all but the best 3D prediction groups. Despite the well‐known low accuracy of residue–residue contact predictions, it is clear that the predictive power of contacts can be useful in 3D model prediction strategies. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

结构模型中预报方法的研究及其应用

本文对结构模型中未知真值在两种不同条件下的最佳预报方法进行了研究.其次,对因子模型预报方法进行了探讨.最后,分别举例说明了这些方法的应用.     

Components of error in predictions of species compositional change

Abstract. A method is given for measuring two components of error (rate and direction) in predictions of compositional change through time. Observed compositional change between two times can be represented as a vector between two points in multidimensional species space. The point at the tail of this vector is the species composition at one particular time. A vector of predicted compositional change will diverge from the vector of observed change to some degree. The error in the predicted rate of change is measured by the difference between the lengths of the two vectors. The error in the predicted direction of change is measured by the angle between the vectors. The cosine of this angle is a non-standardized correlation coefficient (r_n) between the predicted and observed species compositions. The quantity 1 - r_n² measures the error in direction of the predicted dynamics without being influenced by the overall rate of change. These measures in Euclidean space have useful counterparts in city-block space. The method is illustrated by comparing actual long-term changes in Midwestern old-growth forests with the changes predicted by a growth and yield model, TWIGS.     

Predicted microbial biomass in the rhizosphere of barley in the field

Summary Laboratory data for the loss of root material by barley and field data for the growth of barley plants in Syria and in England have been combined to predict the amount of material lost by barley roots during a season, and to predict the resulting microbial biomass in the rhizosphere. The predicted microbial biomass C in the rhizosphere ranged from 10–34% of the total plant biomass C depending mainly upon the value used for rate of loss of root material. Total loss of root material predicted during a season in England constituted 7.7–25.4 percent of C fixed by photosynthesis. The major assumptions made in these calculations are considered, and the predicted values discussed in relation to reported values for soil microbial biomass, CO₂ fluxes from soil and associative nitrogen fixation.     

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein–protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.     

Male-killing in the Coccinellidae: testing the predictions

Male-killing endosymbionts have been widely reported in the invertebrates and are highly prevalent in the Coccinellidae. The presence of male-killers can lead to extreme bias in host population sex ratios and may have important and far-reaching consequences for the life-history and evolution of their hosts. Male-killers may have direct and indirect effects on host fitness and reproductive behaviour, as well as affecting the host genome, either via strong selection pressure imposed by highly female-biased population sex ratios or by selective sweeps caused as a male-killer conferring an advantage to infected individuals spreads through a population. Criteria used to predict which species are liable to male-killer invasion, based on a variety of ecological factors, have been produced. In summary male-killers are predicted to occur in aphidophageous species, that lay eggs in clutches, show sibling egg consumption and are liable to neonatal larval mortality due to starvation. We assayed 30 species of Coccinellid for the presence of such male-killers to assess the predictive accuracy of the criteria. Male-killers were identified in 8 species in which they were predicted to occur and were absent from all 10 species predicted not to harbor them. Analysis of the remaining 12 species, where male-killers were predicted by the original criteria, but where they were not found, allowed us to identify areas where the criteria can be refined and improved. We conclude that whilst the original criteria give a reasonably accurate prediction, there are refinements and improvements, concerning details of host diet and life-history, which make them more robust, especially in the light of discoveries of male-killing suppressors and when incorporated give a better fit to our findings from field samples.