PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data

Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http://dragon.bio.purdue.edu/pfp/.     

Universal Pattern and Diverse Strengths of Successive Synonymous Codon Bias in Three Domains of Life, Particularly Among Prokaryotic Genomes

There has been significant progress in understanding the process of protein translation in recent years. One of the best examples is the discovery of usage bias in successive synonymous codons and its role in eukaryotic translation efficiency. We observed here a similar type of bias in the other two life domains, bacteria and archaea, although the bias strength was much smaller than in eukaryotes. Among 136 prokaryotic genomes, 98 were found to have significant bias from random use of successive synonymous codons with Z scores larger than three. Furthermore, significantly different bias strengths were found between prokaryotes grouped by various genomic or biochemical characteristics. Interestingly, the bias strength measured by a general Z score could be fitted well (R = 0.83, P < 10⁻¹⁵) by three genomic variables: genome size, G + C content, and tRNA gene number based on multiple linear regression. A different distribution of synonymous codon pairs between protein-coding genes and intergenic sequences suggests that bias is caused by translation selection. The present results indicate that protein translation is tuned by codon (pair) usage, and the intensity of the regulation is associated with genome size, tRNA gene number, and G + C content.     

Accuracy of marker-assisted selection with auxiliary traits

Genetic information on molecular markers is increasingly being used in plant and animal improvement programmes particularly as indirect means to improve a metric trait by selection either on an individual basis or on the basis of an index incorporating such information. This paper examines the utility of an index of selection that not only combines phenotypic and molecular information on the trait under improvement but also combines similar information on one or more auxiliary traits. The accuracy of such a selection procedure has been theoretically studied for sufficiently large populations so that the effects of detected quantitative trait loci can be perfectly estimated. The theory is illustrated numerically by considering one auxiliary trait. It is shown that the use of an auxiliary trait improves the selection accuracy; and, hence, the relative efficiency of index selection compared to individual selection which is based on the same intensity of selection. This is particularly so for higher magnitudes of residual genetic correlation and environmental correlation having opposite signs, lower values of the proportion of genetic variation in the main trait associated with the markers, negligible proportion of genetic variation in the auxiliary trait associated with the markers, and lower values of the heritability of the main trait but higher values of the heritability of the auxiliary trait.     

Thin-plate spline analysis of allometry and sexual dimorphism in the human craniofacial complex

The relationship between allometry and sexual dimorphism in the human craniofacial complex was analyzed using geometric morphometric methods. Thin-plate splines (TPS) analysis has been applied to investigate the lateral profile of complete adult skulls of known sex. Twenty-nine three-dimensional (3D) craniofacial and mandibular landmark coordinates were recorded from a sample of 52 adult females and 52 adult males of known age and sex. No difference in the influence of size on shape was detected between sexes. Both size and sex had significant influences on shape. As expected, the influence of centroid size on shape (allometry) revealed a shift in the proportions of the neurocranium and the viscerocranium, with a marked allometric variation of the lower face. Adjusted for centroid size, males presented a relatively larger size of the nasopharyngeal space than females. A mean-male TPS transformation revealed a larger piriform aperture, achieved by an increase of the angulation of the nasal bones and a downward rotation of the anterior nasal floor. Male pharynx expansion was also reflected by larger choanae and a more posteriorly inclined basilar part of the occipital clivus. Male muscle attachment sites appeared more pronounced. In contrast, the mean-female TPS transformation was characterized by a relatively small nasal aperture. The occipital clivus inclined anteriorly, and muscle insertion areas became smoothed. Besides these variations, both maxillary and mandibular alveolar regions became prognathic. The sex-specific TPS deformation patterns are hypothesized to be associated with sexual differences in body composition and energetic requirements.     

Association of CELSR2, APOB100, ABCG5/8, LDLR,and APOE polymorphisms and their genetic risks with lipids among the Thai subjects

BackgroundHypercholesterolemia is a common cardiovascular risk factor. The aim of this study was to investigate the association of CELSR2 (rs629301), APOB100 (rs1367117), ABCG5/8 (rs6544713), LDLR (rs6511720), and APOE (rs429358, rs7412) polymorphisms, and their genetic risk scores with lipids among Thai subjects.MethodsA total of 459 study subjects (184 males, and 275 females) were enrolled. Blood pressure, serum lipids, and fasting blood sugar were measured. CELSR2 (rs629301), APOB100 (rs1367117), ABCG5/8 (rs6544713), and LDLR (rs6511720) polymorphisms were analyzed using PCR-HRM. APOE (rs429358, rs7412) polymorphism was analyzed using PCR-RFLP.ResultsTotal cholesterol (TC) levels were significantly higher in APOB100 AA genotype compared with GG, or AA + AG genotypes in total subjects. In addition, significantly higher concentrations of TC and low density lipoprotein cholesterol (LDL-C) were observed in APOE4 carriers compared to APOE2 carriers in total subjects, males, and females. The significantly higher concentrations of TC were observed in APOE4 carriers compared to APOE3 carriers in females. Moreover, the concentrations of TC, and LDL-C were significantly increased with genetic risk scores of APOB100, and APOE polymorphisms in total subjects, and females. There was no association between CELSR2 (rs629301), ABCG5/8 (rs6544713), and LDLR (rs6511720) polymorphisms and serum lipids.ConclusionAPOB100 (rs1367117), and APOE (rs429358, rs7412) but not CELSR2 (rs629301), ABCG5/8 (rs6544713), and LDLR (rs6511720) polymorphisms were associated with serum lipids. The cumulative risk alleles of APOB100 (rs1367117), and APOE (rs429358, rs7412) polymorphisms could enhance the elevated concentrations of TC, and LDL-C, and they may be used to predict severity of hypercholesterolemia among Thai subjects.     

The collaborative study on the genetics of alcoholism: Genetics

This review describes the genetic approaches and results from the family-based Collaborative Study on the Genetics of Alcoholism (COGA). COGA was designed during the linkage era to identify genes affecting the risk for alcohol use disorder (AUD) and related problems, and was among the first AUD-focused studies to subsequently adopt a genome-wide association (GWAS) approach. COGA's family-based structure, multimodal assessment with gold-standard clinical and neurophysiological data, and the availability of prospective longitudinal phenotyping continues to provide insights into the etiology of AUD and related disorders. These include investigations of genetic risk and trajectories of substance use and use disorders, phenome-wide association studies of loci of interest, and investigations of pleiotropy, social genomics, genetic nurture, and within-family comparisons. COGA is one of the few AUD genetics projects that includes a substantial number of participants of African ancestry. The sharing of data and biospecimens has been a cornerstone of the COGA project, and COGA is a key contributor to large-scale GWAS consortia. COGA's wealth of publicly available genetic and extensive phenotyping data continues to provide a unique and adaptable resource for our understanding of the genetic etiology of AUD and related traits.     

Family studies of tooth size factors in the permanent dentition.

Correlations between dimensions of the permanent teeth in Australian Aboriginals were studied by factor analysis to disclose the main sources of shared variability. Findings indicated that in both males and females most of the common variability in the tooth dimensions could be accounted for by factors representing mesiodistal size of anterior teeth, buccolingual size of anterior teeth, generalized size of the premolars and generalized size of the molars. Factor scores derived from the analysis were used to calculate intraclass correlations among brothers and among sisters. These correlations tended to be higher for the factors contributing most to the common variability indicating that the factors might represent fields under direct genetic control. There was no trend for intraclass correlations among siblings derived from multivariate scores to be consistently higher than those based on observed tooth dimensions. The main advantage to the user of factor analysis is the ability to interpret associations between interrelated variables more objectively than is possible by conventional correlation methods.     

Synthesis and biological evaluation of cyclopeptide GG-8-6 and its analogues as anti-hepatocellular carcinoma agents

GG-8-6, cyclo-(Val-Leu-Pro-Ile-Leu-Leu-Leu-Val-Leu, compound 1), and its twelve analogues (compound 2–13) were synthesized based on the lead compound Grifficyclocin B, a cyclic peptide with anti-tumor activity which was isolated from the plants of Goniothalamus species (Annonaceae). The bioassay results showed that these synthetic cyclopeptides exhibited different extent of cytotoxicity against human hepatocellular carcinoma cell lines. Among them, GG-8-6 (1) was the most active compound with IC₅₀ values of 6.38?μM and 12.22?μM against SMMC-7721 and HepG2, respectively. Further studies on the mechanism demonstrated that GG-8-6 (1) could induce apoptosis and G2/M arrest of HCC cells, and the activation of caspase pathways was probably involved. In vivo anti-tumor experiments showed that GG-8-6 (1) could significantly inhibit the growth of tumor in the mouse xenograft tumor model. At the dose of 40?mg/kg, the inhibition ratio was 67.9% without weight loss. Our results suggested that GG-8-6 (1), a new cyclic peptide, might be a potential candidate for developing new anti-HCC drug in the coming future.     

SynAggreg: A Multifunctional High-Throughput Technology for Precision Study of Amyloid Aggregation and Systematic Discovery of Synergistic Inhibitor Compounds

Numerous proteins can coalesce into amyloid self-assemblies, which are responsible for a class of diseases called amyloidoses, but which can also fulfill important biological functions and are of great interest for biotechnology. Amyloid aggregation is a complex multi-step process, poorly prone to detailed structural studies. Therefore, small molecules interacting with amyloids are often used as tools to probe the amyloid aggregation pathway and in some cases to treat amyloidoses as they prevent pathogenic protein aggregation. Here, we report on SynAggreg, an in vitro high-throughput (HT) platform dedicated to the precision study of amyloid aggregation and the effect of modulator compounds. SynAggreg relies on an accurate bi-fluorescent amyloid-tracer readout that overcomes some limitations of existing HT methods. It allows addressing diverse aspects of aggregation modulation that are critical for pathomechanistic studies, such as the specificity of compounds toward various amyloids and their effects on aggregation kinetics, as well as the co-assembly propensity of distinct amyloids and the influence of prion-like seeding on self-assembly. Furthermore, SynAggreg is the first HT technology that integrates tailored methodology to systematically identify synergistic compound combinations—an emerging strategy to improve fatal amyloidoses by targeting multiple steps of the aggregation pathway. To this end, we apply analytical combinatorial scores to rank the inhibition efficiency of couples of compounds and to readily detect synergism. Finally, the SynAggreg platform should be suited for the characterization of a broad class of amyloids, whether of interest for drug development purposes, for fundamental research on amyloid functions, or for biotechnological applications.     

Predicting loneliness with polygenic scores of social,psychological and psychiatric traits

Loneliness is a heritable trait that accompanies multiple disorders. The association between loneliness and mental health indices may partly be due to inherited biological factors. We constructed polygenic scores for 27 traits related to behavior, cognition and mental health and tested their prediction for self‐reported loneliness in a population‐based sample of 8798 Dutch individuals. Polygenic scores for major depressive disorder (MDD), schizophrenia and bipolar disorder were significantly associated with loneliness. Of the Big Five personality dimensions, polygenic scores for neuroticism and conscientiousness also significantly predicted loneliness, as did the polygenic scores for subjective well‐being, tiredness and self‐rated health. When including all polygenic scores simultaneously into one model, only 2 major depression polygenic scores remained as significant predictors of loneliness. When controlling only for these 2 MDD polygenic scores, only neuroticism and schizophrenia remain significant. The total variation explained by all polygenic scores collectively was 1.7%. The association between the propensity to feel lonely and the susceptibility to psychiatric disorders thus pointed to a shared genetic etiology. The predictive power of polygenic scores will increase as the power of the genome‐wide association studies on which they are based increases and may lead to clinically useful polygenic scores that can inform on the genetic predisposition to loneliness and mental health.