In order to model protein networks we must extend our knowledge of the protein associations occurring in molecular systems and their functional relationships. We have significantly increased the ...accuracy of protein association predictions by the meta-statistical integration of three computational methods specifically designed for eukaryotic proteomes. From this former work it was discovered that high-throughput experimental assays seem to perform biased screenings of the real protein networks and leave important areas poorly characterized. This finding supports the convenience to combine computational prediction approaches to model protein interaction networks. We address in this work the challenge of integrating context information, present in predicted and known protein network models, to functionally characterize novel proteins. We applied a random walk-with-restart kernel to our models aiming at fixing some poorly described or unknown proteins involve in angiogenesis. This approach reveals some novel key angiogenic components within the human interactome.
The recent assembly and annotation of the 26 maize nested association mapping population founder inbreds have enabled large-scale pan-genomic comparative studies. These studies have expanded our ...understanding of agronomically important traits by integrating pan-transcriptomic data with trait-specific gene candidates from previous association mapping results. In contrast to the availability of pan-transcriptomic data, obtaining reliable protein-protein interaction (PPI) data has remained a challenge due to its high cost and complexity. We generated predicted PPI networks for each of the 26 genomes using the established STRING database. The individual genome-interactomes were then integrated to generate core- and pan-interactomes. We deployed the PPI clustering algorithm ClusterONE to identify numerous PPI clusters that were functionally annotated using gene ontology (GO) functional enrichment, demonstrating a diverse range of enriched GO terms across different clusters. Additional cluster annotations were generated by integrating gene coexpression data and gene description annotations, providing additional useful information. We show that the functionally annotated PPI clusters establish a useful framework for protein function prediction and prioritization of candidate genes of interest. Our study not only provides a comprehensive resource of predicted PPI networks for 26 maize genomes but also offers annotated interactome clusters for predicting protein functions and prioritizing gene candidates. The source code for the Python implementation of the analysis workflow and a standalone web application for accessing the analysis results are available at https://github.com/eporetsky/PanPPI.
The main roles of adipose tissue include triglycerides storage and adipokine secretion, which regulate energy balance and inflammation status. In obesity, adipocyte dysfunction leads to ...proinflammatory cytokine production and insulin resistance. Bariatric surgery is the most effective treatment for obesity, the gold-standard technique being Roux-en-Y gastric bypass (RYGB). Since metabolic improvements after RYGB are clear, a better understanding of adipose tissue molecular modifications could be derived from this study. Thus, the aim of this systematic review was to find differentially expressed genes in subcutaneous adipose tissue of lean, obese and post-RYGB (distinct timepoints). To address this objective, publications from 2015-2022 reporting gene expression (candidate genes or transcriptomic approach) of subcutaneous adipose tissue from lean and obese individuals before and after RGYB were searched in PubMed, Elsevier, and Springer Link. Excluded publications were reviews, studies analyzing serum, other types of tissues, or bariatric procedures. A risk-of-bias summary was created for each paper using Robvis, to finally include 17 studies. Differentially expressed genes in post-RYGB vs. obese and lean vs. obese were obtained and the intersection among these groups was used for analysis and gene classification by metabolic pathway. Results showed that the lean state as well as the post-RYGB is similar in terms of increased expression of insulin-sensitizing molecules, inducing lipogenesis over lipolysis and downregulating leukocyte activation, cytokine production and other factors that promote inflammation. Thus, massive weight loss and metabolic improvements after RYGB are accompanied by gene expression modifications reverting the "adipocyte dysfunction" phenomenon observed in obesity conditions.
Tomato belongs to the Solanaceae family of plants. It is a diploid plant with 12 chromosomes. Previous studies have reported that its genome size is 950 MB with 35,000 protein-coding genes. Micro-Tom ...Tomato is a miniature dwarf determinate tomato cultivar. It has a small-sized genome, a short lifecycle, and a short seed-setting under fluorescent light. These features are similar to those of Arabidopsis. Consequently, Micro-Tom Tomato is considered as a model cultivar of tomato (Solanum lycopersicum) suitable for research. We sequenced its transcriptomes to identify tissue-specific gene candidate profiles in different plant tissues (petals, sepals, pistils, and stamens) at developmental stages.
Disagreements over genetic signatures associated with disease have been particularly prominent in the field of psychiatric genetics, creating a sharp divide between disease burdens attributed to ...common and rare variation, with study designs independently targeting each. Meta-analysis within each of these study designs is routine, whether using raw data or summary statistics, but combining results across study designs is atypical. However, tests of functional convergence are used across all study designs, where candidate gene sets are assessed for overlaps with previously known properties. This suggests one possible avenue for combining not study data, but the functional conclusions that they reach.
In this work, we test for functional convergence in autism spectrum disorder (ASD) across different study types, and specifically whether the degree to which a gene is implicated in autism is correlated with the degree to which it drives functional convergence. Because different study designs are distinguishable by their differences in effect size, this also provides a unified means of incorporating the impact of study design into the analysis of convergence.
We detected remarkably significant positive trends in aggregate (p < 2.2e-16) with 14 individually significant properties (false discovery rate <0.01), many in areas researchers have targeted based on different reasoning, such as the fragile X mental retardation protein (FMRP) interactor enrichment (false discovery rate 0.003). We are also able to detect novel technical effects and we see that network enrichment from protein-protein interaction data is heavily confounded with study design, arising readily in control data.
We see a convergent functional signal for a subset of known and novel functions in ASD from all sources of genetic variation. Meta-analytic approaches explicitly accounting for different study designs can be adapted to other diseases to discover novel functional associations and increase statistical power.
Mapping disease-associated genetic variants to complex disease pathophysiology is a major challenge in translating findings from genome-wide association studies into novel therapeutic opportunities. ...The difficulty lies in our limited understanding of how phenotypic traits arise from non-coding genetic variants in highly organized biological systems with heterogeneous gene expression across cells and tissues.
We present a novel strategy, called GWAS component analysis, for transferring disease associations from single-nucleotide polymorphisms to co-expression modules by stacking models trained using reference genome and tissue-specific gene expression data. Application of this method to genome-wide association studies of blood cell counts confirmed that it could detect gene sets enriched in expected cell types. In addition, coupling of our method with Bayesian networks enables GWAS components to be used to discover drug targets.
We tested genome-wide associations of four disease phenotypes, including age-related macular degeneration, Crohn's disease, ulcerative colitis and rheumatoid arthritis, and demonstrated the proposed method could select more functional genes than S-PrediXcan, the previous single-step model for predicting gene-level associations from SNP-level associations.
The relationship between suffering and spiritual growth is foundational to the treatment literature on spiritually oriented psychotherapy. A common developmental path between suffering and increased ...spirituality may point to a unified psychological process, which has in turn a common underlying physiology with a genetic foundation. Possible genetic correlates of spirituality and depression have been identified in community samples. We investigate some of the previously identified candidates in a sample of families at both high and low risk for depression. Offspring and grandchildren of individuals at high and low risk for depression, participating in a multiwave 30-year longitudinal study, were assessed for 7 SNPs (single nucleotide polymorphisms) drawn from 4 single gene candidates associated with systems implicated in both depression and spirituality: Serotonin (5-HT1B and 5-HT2A), Dopamine (DRD2), Oxytocin (OT), and Monoamine Vesicular Transporter (VMAT1). Dopamine (DRD2) Serotonin (5-HT1B), their Transporter (VMAT1), and Oxytocin (OXTR) were positively associated with a high level of importance of spirituality or religion (S/R) in the group at low familial risk for depression. DRD2 minor allele was associated with both lifetime major depressive disorder (MDD) and spirituality in the low-risk group for depression. No SNPs were related to S/R in the group at high familial risk for depression. OXTR was associated with lifetime MDD in the full sample. Genes for dopamine, serotonin, their vesicular transporter, and oxytocin may be associated with S/R in people at low familial risk for depression. Genes for dopamine may be associated both with S/R and increased risk for depression in people at low-risk for depression, suggesting a common pathway or physiology to mild to moderate depression. MDD is associated with oxytocin across risk groups. In the high-risk group, phenotypic expression of S/R may be suppressed. The shared association of DRD2 by S/R and depression, generally found to be inversely related, calls for further research on their common physiological pathways, and the phenotypic expression of these pathways based upon use and environment. The findings may be interpreted to offer biological evidence in support of engaging suffering as an opportunity for spiritual growth in treatment, as is foundational to many existing spiritually oriented psychotherapies.
Population stratification of functional gene polymorphisms is a potential confounding factor in genetic association studies. The Val66Met (rs6265) single-nucleotide polymorphism in the brain-derived ...neurotrophic factor gene (
) exhibits one of the highest variabilities in terms of allelic distribution between populations. The present study reports the distribution of BDNF Val66Met alleles in a sample of healthy volunteers (N = 1124) selected from the Romanian population. Frequencies were 80.74% for the Val allele and 19.26% for the Met allele. The data from this study extends efforts to map the allelic distribution of BDNF Val66Met in populations around the world and emphasizes that population stratification should be controlled for in future studies that report phenotypic associations in samples from different populations.
► Eighty-four resistance gene candidate sequences cloned from gerbera. ► Sequences were similar to the NB–LRR class R-genes and belong to nine subfamilies. ► One SCAR, 11 CAPS, and 242 TRAP markers ...developed from these sequences. ► These markers were polymorphic between the parents of two mapping populations. ► These markers expected to help locate gerbera genes or QTLs for disease resistance.
Improving disease resistance has become an important breeding objective in gerbera, one of the most important floricultural crops in the world. Development and application of molecular markers are expected to assist selection of gerberas with improved disease resistance. The availability of resistance gene candidate (RGC) sequences has accelerated the development of molecular markers for disease resistance traits in numerous plants. In this study, 84 gerbera RGC sequences (GhRGCs) were identified from cloned PCR products amplified from powdery mildew (PM)-resistant gerberas with degenerate oligonucleotide primers from two conserved motifs of plant disease resistance genes (R-genes). Nineteen GhRGC sequences could be translated into polypeptides with ≤90% amino acid identity. Multiple sequence alignment analysis of the 19 representative polypeptide sequences suggests two major clusters of gerbera RGCs. Twelve GhRGCs in cluster 1 contain the typical motifs of the toll and interleukin receptor–nucleotide binding site–leucine-rich repeat (TIR–NB–LRR) class R-genes within the nucleotide-binding site (NB) domain, and the seven GhRGCs in cluster 2 possess the typical motifs of the coiled coil–nucleotide binding site–leucine-rich repeat (CC–NB–LRR) class R-genes in the NB domain. The 19 GhRGCs were further divided into nine sub-families that share 15–50% amino acid identity. Thirty specific oligonucleotide primers were designed from 15 GhRGCs and tested on gerbera breeding line UFGE 4033 and ‘Sunburst Snow White’ that are PM-resistant and PM-susceptible, respectively, and are parents of two mapping populations for developing molecular markers for PM resistance. One sequence characterized amplified polymorphism (SCAR) and 11 cleaved amplified polymorphic site (CAPS) markers were developed and were polymorphic between the two parents. When used with the target region amplification polymorphism (TRAP) marker system, the 30 GhRGC-derived primers detected 242 additional DNA bands that were polymorphic between UFGE 4033 and ‘Sunburst Snow White’. This study represents the first effort to sample and characterize R-gene candidate sequences in gerbera. The obtained sequences may provide a valuable entry point to obtain full-length or additional sequences of gerbera NB–LRR genes. The SCAR, CAPS and TRAP markers developed may be valuable for mapping of genes or quantitative trait loci responsible for disease resistance in gerbera.
Asthma is a complex multifactorial disease that is not yet fully understood. Oxidative stress due to an imbalance between the oxidative forces and the antioxidant defense systems has been implicated ...in asthma pathogenesis. However, much debate still surrounds the key genetic factors involved in the development of this disease. Candidate genes include the glutathione S-transferases (GSTs). In particular, mu, pi, and theta classes of GSTs play an important role in regulating inflammatory responses. However, few and contradictory data are available on the association between asthma development and GST gene polymorphisms (GSTM1, GSTP1, and GST1).
To investigate whether GSTM1, GSTT1, and GSTP1 polymorphisms are associated with asthma development.
We recruited 200 unrelated healthy individuals and 199 asthmatic patients from Rome in Central Italy. Genotyping of GSTMI and GSTT1 genes was performed by a multiplex polymerase chain reaction (PCR) while the GSTP1 polymorphism (rs1695) was determined using PCR-restriction fragment length polymorphism analysis.
Our results suggest that the GST polymorphisms analyzed are not associated with asthma, confirming the uncertain role of GST genes in the development of asthma.
Oxidative stress is certainly involved in the development of asthma, and GSTs may therefore influence asthma risk, although, as our results show, their role in pathogenesis remains to be elucidated. Future studies should focus on the interactions of GST genes with the environment and other antioxidant genes to shed light on the role of GSTs in asthma.
PDF
