The Gene Ontology (GO) project: structured vocabularies for molecular biology and their application to genome and expression analysis

Computational tools for plant genomics and breeding

Plant genomics and crop breeding are at the intersection of biotechnology and information technology. Driven by a combination of high-throughput sequencing, molecular biology and data science, great advances have been made in omics technologies at every step along the central dogma, especially in genome assembling, genome annotation, epigenomic profiling, and transcriptome profiling. These advances further revolutionized three directions of development. One is genetic dissection of complex traits in crops, along with genomic prediction and selection. The second is comparative genomics and evolution, which open up new opportunities to depict the evolutionary constraints of biological sequences for deleterious variant discovery. The third direction is the development of deep learning approaches for the rational design of biological sequences, especially proteins, for synthetic biology. All three directions of development serve as the foundation for a new era of crop breeding where agronomic traits are enhanced by genome design.

TRIM5 as a promising diagnostic biomarker of hepatocellular carcinoma: integrated analysis and experimental validation

The TRIM family is associated with the membrane, and its involvement in the progression, growth, and development of various cancer types has been researched extensively. However, the role played by the TRIM5 gene within this family has yet to be explored to a great extent in terms of hepatocellular carcinoma (HCC). The data of patients relating to mRNA expression and the survival rate of individuals diagnosed with HCC were extracted from The Cancer Genome Atlas (TCGA) database. UALCAN was employed to examine the potential link between TRIM5 expression and clinicopathological characteristics. In addition, enrichment analysis of differentially expressed genes (DEGs) was conducted as a means of deciphering the function and mechanism of TRIM5 in HCC. The data in the TCGA and TIMER2.0 databases was utilized to explore the correlation between TRIM5 and immune infiltration in HCC. WGCNA was performed as a means of assessing TRIM5-related co-expressed genes. The "OncoPredict" R package was also used for investigating the association between TRIM5 and drug sensitivity. Finally, qRT-PCR, Western blotting (WB) and immunohistochemistry (IHC) were employed for exploring the differential expression of TRIM5 and its clinical relevance in HCC. According to the results that were obtained from the vitro experiments, mRNA and protein levels of TRIM5 demonstrated a significant upregulation in HCC tissues. It is notable that TRIM5 expression levels were found to have a strong association with the infiltration of diverse immune cells and displayed a positive correlation with several immune checkpoint inhibitors. The TRIM5 expression also displayed promising clinical prognostic value for HCC patients.

Senescence risk score: a multifaceted prognostic tool predicting outcomes, stemness, and immune responses in colorectal cancer

Colorectal cancer (CRC) remains a primary cause of cancer mortality globally, necessitating precise prognostic indicators for effective clinical management. Our study introduces the Senescence Risk Score (SRRS), based on several senescence-related genes (SRGs), a potent prognostic tool designed to measure cellular senescence in CRC. The higher SRRS predicts a poorer prognosis, providing a novel and efficient approach to patient stratification. Notably, we found that SRRS correlates with methylation and mutation variations, and increased immune infiltration in the tumor microenvironment, thus revealing potential therapeutic targets. We also discovered an inverse relationship between SRRS and cell stemness, which could have significant implications for cancer treatment strategies. Utilizing bioinformatics resources and machine learning, we identified LIMK1 and WRN as key genes associated with SRRS, further enhancing its prognostic value. Importantly, the modulation of these genes significantly impacts cellular senescence, proliferation, and stemness in CRC cells. In summary, our development of SRRS offers a powerful tool for CRC prognosis and paves the way for novel therapeutic strategies, underscoring its potential in transforming CRC patient management.

Assessing in silico the recruitment and functional spectrum of bacterial enzymes from secondary metabolism

BACKGROUND

Microbes, plants, and fungi synthesize an enormous number of metabolites exhibiting rich chemical diversity. For a high-level classification, metabolism is subdivided into primary (PM) and secondary (SM) metabolism. SM products are often not essential for survival of the organism and it is generally assumed that SM enzymes stem from PM homologs.

RESULTS

We wanted to assess evolutionary relationships and function of bona fide bacterial PM and SM enzymes. Thus, we analyzed the content of 1010 biosynthetic gene clusters (BGCs) from the MIBiG dataset; the encoded bacterial enzymes served as representatives of SM. The content of 15 bacterial genomes known not to harbor BGCs served as a representation of PM. Enzymes were categorized on their EC number and for these enzyme functions, frequencies were determined. The comparison of PM/SM frequencies indicates a certain preference for hydrolases (EC class 3) and ligases (EC class 6) in PM and of oxidoreductases (EC class 1) and lyases (EC class 4) in SM. Based on BLAST searches, we determined pairs of PM/SM homologs and their functional diversity. Oxidoreductases, transferases (EC class 2), lyases and isomerases (EC class 5) form a tightly interlinked network indicating that many protein folds can accommodate different functions in PM and SM. In contrast, the functional diversity of hydrolases and especially ligases is significantly limited in PM and SM. For the most direct comparison of PM/SM homologs, we restricted for each BGC the search to the content of the genome it comes from. For each homologous hit, the contribution of the genomic neighborhood to metabolic pathways was summarized in BGC-specific html-pages that are interlinked with KEGG; this dataset can be downloaded from https://www.bioinf.ur.de .

CONCLUSIONS

Only few reaction chemistries are overrepresented in bacterial SM and at least 55% of the enzymatic functions present in BGCs possess PM homologs. Many SM enzymes arose in PM and Nature utilized the evolvability of enzymes similarly to establish novel functions both in PM and SM. Future work aimed at the elucidation of evolutionary routes that have interconverted a PM enzyme into an SM homolog can profit from our BGC-specific annotations.

Systematic Analysis of Intracellular-targeting Antimicrobial Peptides, Bactenecin 7, Hybrid of Pleurocidin and Dermaseptin, Proline-Arginine-rich Peptide, and Lactoferricin B, by Using Escherichia coli Proteome Microarrays

Antimicrobial peptides (AMPs) act either through membrane lysis or by attacking intracellular targets. Intracellular targeting AMPs are a resource for antimicrobial agent development. Several AMPs have been identified as intracellular targeting peptides; however, the intracellular targets of many of these peptides remain unknown. In the present study, we used an Escherichia coli proteome microarray to systematically identify the protein targets of three intracellular targeting AMPs: bactenecin 7 (Bac7), a hybrid of pleurocidin and dermaseptin (P-Der), and proline-arginine-rich peptide (PR-39). In addition, we also included the data of lactoferricin B (LfcinB) from our previous study for a more comprehensive analysis. We analyzed the unique protein hits of each AMP in the Kyoto Encyclopedia of Genes and Genomes. The results indicated that Bac7 targets purine metabolism and histidine kinase, LfcinB attacks the transcription-related activities and several cellular carbohydrate biosynthetic processes, P-Der affects several catabolic processes of small molecules, and PR-39 preferentially recognizes proteins involved in RNA- and folate-metabolism-related cellular processes. Moreover, both Bac7 and LfcinB target purine metabolism, whereas LfcinB and PR-39 target lipopolysaccharide biosynthesis. This suggested that LfcinB and Bac7 as well as LfcinB and PR-39 have a synergistic effect on antimicrobial activity, which was validated through antimicrobial assays. Furthermore, common hits of all four AMPs indicated that all of them target arginine decarboxylase, which is a crucial enzyme for Escherichia coli survival in extremely acidic environments. Thus, these AMPs may display greater inhibition to bacterial growth in extremely acidic environments. We have also confirmed this finding in bacterial growth inhibition assays. In conclusion, this comprehensive identification and systematic analysis of intracellular targeting AMPs reveals crucial insights into the intracellular mechanisms of the action of AMPs.

A comparison of virus genome sequences with their host silkworm, Bombyx mori

With the recent availability of the genomes of many viruses and the silkworm, Bombyx mori, as well as a variety of Basic Local Alignment Search Tool (BLAST) programs, a new opportunity to gain insight into the interaction of viruses with the silkworm is possible. This study aims to determine the possible existence of sequence identities between the genomes of viruses and the silkworm and attempts to explain this phenomenon. BLAST searches of the genomes of viruses against the silkworm genome were performed using the resources of the National Center for Biotechnology Information. All studied viruses contained variable numbers of short regions with sequence identity to the genome of the silkworm. The short regions of sequence identity in the genome of the silkworm may be derived from the genomes of viruses in the long history of silkworm-virus interaction. This study is the first to compare these genomes, and may contribute to research on the interaction between viruses and the silkworm.

Genes with stable DNA methylation levels show higher evolutionary conservation than genes with fluctuant DNA methylation levels

Different human genes often exhibit different degrees of stability in their DNA methylation levels between tissues, samples or cell types. This may be related to the evolution of human genome. Thus, we compared the evolutionary conservation between two types of genes: genes with stable DNA methylation levels (SM genes) and genes with fluctuant DNA methylation levels (FM genes). For long-term evolutionary characteristics between species, we compared the percentage of the orthologous genes, evolutionary rate dn/ds and protein sequence identity. We found that the SM genes had greater percentages of the orthologous genes, lower dn/ds, and higher protein sequence identities in all the 21 species. These results indicated that the SM genes were more evolutionarily conserved than the FM genes. For short-term evolutionary characteristics among human populations, we compared the single nucleotide polymorphism (SNP) density, and the linkage disequilibrium (LD) degree in HapMap populations and 1000 genomes project populations. We observed that the SM genes had lower SNP densities, and higher degrees of LD in all the 11 HapMap populations and 13 1000 genomes project populations. These results mean that the SM genes had more stable chromosome genetic structures, and were more conserved than the FM genes.

Catecholamine-related gene expression in blood correlates with tic severity in tourette syndrome

Tourette syndrome (TS) is a heritable disorder characterized by tics that are decreased in some patients by treatment with alpha adrenergic agonists and dopamine receptor blockers. Thus, this study examines the relationship between catecholamine gene expression in blood and tic severity. TS diagnosis was confirmed using Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria and tic severity measured using the Yale Global Tic Severity Scale (YGTSS) for 26 un-medicated subjects with TS. Whole blood was collected and Ribonucleic acid (RNA) processed on Affymetrix Human Exon 1.0 ST arrays. An Analysis of Covariance (ANCOVA) identified 3627 genes correlated with tic severity (p<0.05). Searches of Medical Subject Headings, Gene Ontology, Allen Mouse Brain Atlas, and PubMed determined genes associated with catecholamines and located in the basal ganglia. Using GeneCards, PubMed, and manual curation, seven genes associated with TS were further examined: DRD2, HRH3, MAOB, BDNF, SNAP25, SLC6A4, and SLC22A3. These genes are highly associated with TS and have also been implicated in other movement disorders, Attention Deficit Hyperactivity Disorder (ADHD), and Obsessive-Compulsive Disorder (OCD). Correlation of gene expression in peripheral blood with tic severity may allow inferences about catecholamine pathway dysfunction in TS subjects. Findings built on previous work suggest that at least some genes expressed peripherally are relevant for central nervous system (CNS) pathology in the brain of individuals with TS.

Enrichment Disequilibrium: a novel approach for measuring the degree of enrichment after gene enrichment test

MOTIVATION

Commonly used gene enrichment analysis methods, such as Hypergeometric distribution, play an important role in the functional analysis of interesting gene lists. But the statistical significance obtained by these methods only represents the probability of error that is involved in accepting enrichment, and is not suitable to evaluate the degree of enrichment. Although there have been some methods to measure the enrichment degrees, such as relative enrichment factor, new methods are still needed to meet the requirements for comparing the degree of enrichment.

RESULTS

We developed a novel method, Enrichment Disequilibrium (ED), to measure the degree of enrichment. Enrichment equilibrium means that the interesting gene set and the known functional gene set (such as a KEGG pathway) are independent (i.e. random association). ED is defined as the degree of non-independence. Compared with the relative enrichment factor, ED has a clearer biological meaning, is a standardized indicator, and has a symmetrical interval (range from -1 to +1). It is more suitable to measure the enrichment degree. For an interesting gene set, researchers can obtain some significant functional gene sets by traditional enrichment test. Then using ED, they can compare the degree of enrichment among these significant gene sets, and prioritize them.

Multiscale modeling and data integration in the virtual physiological rat project

It has become increasingly evident that the descriptions of many complex diseases are only possible by taking into account multiple influences at different physiological scales. To do this with computational models often requires the integration of several models that have overlapping scales (genes to molecules, molecules to cells, cells to tissues). The Virtual Physiological Rat (VPR) Project, a National Institute of General Medical Sciences (NIGMS) funded National Center of Systems Biology, is tasked with mechanistically describing several complex diseases and is therefore identifying methods to facilitate the process of model integration across physiological scales. In addition, the VPR has a considerable experimental component and the resultant data must be integrated into these composite multiscale models and made available to the research community. A perspective of the current state of the art in model integration and sharing along with archiving of experimental data will be presented here in the context of multiscale physiological models. It was found that current ontological, model and data repository resources and integrative software tools are sufficient to create composite models from separate existing models and the example composite model developed here exhibits emergent behavior not predicted by the separate models.

Identifying highly conserved and highly differentiated gene ontology categories in human populations

Detecting and interpreting certain system-level characteristics associated with human population genetic differences is a challenge for human geneticists. In this study, we conducted a population genetic study using the HapMap genotype data to identify certain special Gene Ontology (GO) categories associated with high/low genetic difference among 11 Hapmap populations. Initially, the genetic differences in each gene region among these populations were measured using allele frequency, linkage disequilibrium (LD) pattern, and transferability of tagSNPs. The associations between each GO term and these genetic differences were then identified. The results showed that cellular process, catalytic activity, binding, and some of their sub-terms were associated with high levels of genetic difference, and genes involved in these functional categories displayed, on average, high genetic diversity among different populations. By contrast, multicellular organismal processes, molecular transducer activity, and some of their sub-terms were associated with low levels of genetic difference. In particular, the neurological system process under the multicellular organismal process category had low levels of genetic difference; the neurological function also showed high evolutionary conservation between species in some previous studies. These results may provide a new insight into the understanding of human evolutionary history at the system-level.

Chondrogenic differentiation of human bone marrow-derived mesenchymal stem cells in self-gelling alginate discs reveals novel chondrogenic signature gene clusters

We have used a disc-shaped self-gelling alginate hydrogel as a scaffold for in vitro chondrogenic differentiation of human bone marrow-derived mesenchymal stem cells. The comparison of monolayer cells and alginate embedded cells with or without differentiation medium allowed us to perform a detailed kinetic study of the expression of a range of genes and proteins known to be involved in chondrogenesis, using real-time polymerase chain reaction, fluorescence immunohistochemistry, and glycosaminoglycan measurement in the supernatant. mRNA encoding type II collagen (COL2), COL10, aggrecan, and SOX5, 6, and 9 were greatly elevated already at day 7, whereas COL1 and versican mRNA were gradually reduced. COL2 and aggrecan were dispersed throughout the extracellular matrix at day 21, whereas COL10 distribution was mainly intra/pericellular. COL1 seemed to be produced by only some of the cells. SOX proteins were predominantly localized in the nuclei. Then, using microarray analysis, we identified a signature cluster of extracellular matrix and transcription factor genes upregulated during chondrogenesis similar to COL2A1, and clusters of genes involved in immune responses, blood vessel development, and cell adhesion downregulated similar to the chemokine CXCL12. Analysis of the signature chondrogenic clusters, including novel potential marker genes identified here, may provide a better understanding of how the stem cell fate could be directed to produce perfect hyaline cartilage implants.

The distribution of GYR- and YLP-like motifs in Drosophila suggests a general role in cuticle assembly and other protein-protein interactions

Background

Arthropod cuticle is composed predominantly of a self-assembling matrix of chitin and protein. Genes encoding structural cuticular proteins are remarkably abundant in arthropod genomes, yet there has been no systematic survey of conserved motifs across cuticular protein families.

Methodology/Principal Findings

Two short sequence motifs with conserved tyrosines were identified in Drosophila cuticular proteins that were similar to the GYR and YLP Interpro domains. These motifs were found in members of the CPR, Tweedle, CPF/CPFL, and (in Anopheles gambiae) CPLCG cuticular protein families, and the Dusky/Miniature family of cuticle-associated proteins. Tweedle proteins have a characteristic motif architecture that is shared with the Drosophila protein GCR1 and its orthologs in other species, suggesting that GCR1 is also cuticular. A resilin repeat, which has been shown to confer elasticity, matched one of the motifs; a number of other Drosophila proteins of unknown function exhibit a motif architecture similar to that of resilin. The motifs were also present in some proteins of the peritrophic matrix and the eggshell, suggesting molecular convergence among distinct extracellular matrices. More surprisingly, gene regulation, development, and proteolysis were statistically over-represented ontology terms for all non-cuticular matches in Drosophila. Searches against other arthropod genomes indicate that the motifs are taxonomically widespread.

Conclusions

This survey suggests a more general definition for GYR and YLP motifs and reveals their contribution to several types of extracellular matrix. They may define sites of protein interaction with DNA or other proteins, based on ontology analysis. These results can help guide experimental studies on the biochemistry of cuticle assembly.

Tourette syndrome: gene expression as a tool to discover drug targets

Gene expression microarrays are a high-throughput, cost-effective method for measuring the expression of all genes in a sample. By comparing the expression patterns of healthy controls to diseased subjects, the genetic regulatory pathways underlying and affected by the disease can be elucidated. Furthermore, dysregulated genes are possible candidates for pharmaceutical therapy. Here, we consider the possibility of applying this approach to Tourette syndrome. We also review current theories of Tourette syndrome etiology and pharmacology.

Homozygous deletion mapping in myeloma samples identifies genes and an expression signature relevant to pathogenesis and outcome

PURPOSE

Myeloma is a clonal malignancy of plasma cells. Poor-prognosis risk is currently identified by clinical and cytogenetic features. However, these indicators do not capture all prognostic information. Gene expression analysis can be used to identify poor-prognosis patients and this can be improved by combination with information about DNA-level changes.

EXPERIMENTAL DESIGN

Using single nucleotide polymorphism-based gene mapping in combination with global gene expression analysis, we have identified homozygous deletions in genes and networks that are relevant to myeloma pathogenesis and outcome.

RESULTS

We identified 170 genes with homozygous deletions and corresponding loss of expression. Deletion within the "cell death" network was overrepresented and cases with these deletions had impaired overall survival. From further analysis of these events, we have generated an expression-based signature associated with shorter survival in 258 patients and confirmed this signature in data from two independent groups totaling 800 patients. We defined a gene expression signature of 97 cell death genes that reflects prognosis and confirmed this in two independent data sets.

CONCLUSIONS

We developed a simple 6-gene expression signature from the 97-gene signature that can be used to identify poor-prognosis myeloma in the clinical environment. This signature could form the basis of future trials aimed at improving the outcome of poor-prognosis myeloma.

Mechanism-anchored profiling derived from epigenetic networks predicts outcome in acute lymphoblastic leukemia

Background

Current outcome predictors based on "molecular profiling" rely on gene lists selected without consideration for their molecular mechanisms. This study was designed to demonstrate that we could learn about genes related to a specific mechanism and further use this knowledge to predict outcome in patients – a paradigm shift towards accurate "mechanism-anchored profiling". We propose a novel algorithm, PGnet, which predicts a tripartite mechanism-anchored network associated to epigenetic regulation consisting of phenotypes, genes and mechanisms. Genes termed as GEMs in this network meet all of the following criteria: (i) they are co-expressed with genes known to be involved in the biological mechanism of interest, (ii) they are also differentially expressed between distinct phenotypes relevant to the study, and (iii) as a biomodule, genes correlate with both the mechanism and the phenotype.

Results

This proof-of-concept study, which focuses on epigenetic mechanisms, was conducted in a well-studied set of 132 acute lymphoblastic leukemia (ALL) microarrays annotated with nine distinct phenotypes and three measures of response to therapy. We used established parametric and non parametric statistics to derive the PGnet tripartite network that consisted of 10 phenotypes and 33 significant clusters of GEMs comprising 535 distinct genes. The significance of PGnet was estimated from empirical p-values, and a robust subnetwork derived from ALL outcome data was produced by repeated random sampling. The evaluation of derived robust network to predict outcome (relapse of ALL) was significant (p = 3%), using one hundred three-fold cross-validations and the shrunken centroids classifier.

Conclusion

To our knowledge, this is the first method predicting co-expression networks of genes associated with epigenetic mechanisms and to demonstrate its inherent capability to predict therapeutic outcome. This PGnet approach can be applied to any regulatory mechanisms including transcriptional or microRNA regulation in order to derive predictive molecular profiles that are mechanistically anchored. The implementation of PGnet in R is freely available at .

Applying the Gene Ontology in microbial annotation

The ever-increasing number of microbial sequencing projects necessitates a standardized system for the capture of genomic data to ensure that the flood of information produced can be effectively utilized. The Gene Ontology (GO) provides the standard for gene product annotations in the areas of molecular function, biological process and cellular component. A recent effort by the Plant-Associated Microbe Gene Ontology (PAMGO) Consortium has produced more than 800 new GO terms specific for annotating interactions between microbes and their hosts and other symbiotic interactions. In addition, there have been changes and additions to the GO annotation format and evidence storage system to reflect the needs of the microbial annotation community. The capture of annotation information with systems like the GO is absolutely essential to enable the efficient mining of annotation information across diverse genomes and thus to further biological research in meaningful ways.

Computational biology methods and their application to the comparative genomics of endocellular symbiotic bacteria of insects

Comparative genomics has become a real tantalizing challenge in the postgenomic era. This fact has been mostly magnified by the plethora of new genomes becoming available in a daily bases. The overwhelming list of new genomes to compare has pushed the field of bioinformatics and computational biology forward toward the design and development of methods capable of identifying patterns in a sea of swamping data noise. Despite many advances made in such endeavor, the ever-lasting annoying exceptions to the general patterns remain to pose difficulties in generalizing methods for comparative genomics. In this review, we discuss the different tools devised to undertake the challenge of comparative genomics and some of the exceptions that compromise the generality of such methods. We focus on endosymbiotic bacteria of insects because of their genomic dynamics peculiarities when compared to free-living organisms.

The generation and properties of human macrophage populations from hemopoietic stem cells

Information about the development and function of human macrophage lineage populations, such as osteoclasts, is limited because of the lack of defined in vitro systems for their large-scale generation. Two M-CSF-containing cytokine cocktails were found under serum-free conditions to expand dramatically and to differentiate over time human CD34(+) hemopoietic stem cells into nonadherent and adherent macrophage populations. These populations exhibited increasing degrees of maturity over a 3-week period characterized by morphology, surface marker expression (CD11b, CD86, CD64, CD14, and c-Fms), phagocytic function, and gene-expression profiling using quantitative PCR and microarray analysis (principal component analysis, k-means clustering, and gene ontology classification). As assessed by the last criterion, the adherent population obtained at 3 weeks from the one protocol tested had high similarity to the well-studied peripheral blood monocyte-derived macrophages. The one population tested could be induced to differentiate into osteoclasts in the presence of M-CSF and receptor activator of NF-kappaB ligand, as judged by morphology, gene expression, and bone-resorbing ability. In addition to the large numbers of macrophage lineage cells able to be produced, this replicating system may be suitable for the molecular analysis of macrophage lineage commitment and progression and for gene targeting and delivery.

Modeling gene expression networks using fuzzy logic

Gene regulatory networks model regulation in living organisms. Fuzzy logic can effectively model gene regulation and interaction to accurately reflect the underlying biology. A new multiscale fuzzy clustering method allows genes to interact between regulatory pathways and across different conditions at different levels of detail. Fuzzy cluster centers can be used to quickly discover causal relationships between groups of coregulated genes. Fuzzy measures weight expert knowledge and help quantify uncertainty about the functions of genes using annotations and the gene ontology database to confirm some of the interactions. The method is illustrated using gene expression data from an experiment on carbohydrate metabolism in the model plant Arabidopsis thaliana. Key gene regulatory relationships were evaluated using information from the gene ontology database. A new regulatory relationship concerning trehalose regulation of carbohydrate metabolism was also discovered in the extracted network.