Implementing Core Genes and an Omnigenic Model for Behaviour Traits Prediction in Genomics

A high number of genome variants are associated with complex traits, mainly due to genome-wide association studies (GWAS). Using polygenic risk scores (PRSs) is a widely accepted method for calculating an individual's complex trait prognosis using such data. Unlike monogenic traits, the practical implementation of complex traits by applying this method still falls behind. Calculating PRSs from all GWAS data has limited practical usability in behaviour traits due to statistical noise and the small effect size from a high number of genome variants involved. From a behaviour traits perspective, complex traits are explored using the concept of core genes from an omnigenic model, aiming to employ a simplified calculation version. Simplification may reduce the accuracy compared to a complete PRS encompassing all trait-associated variants. Integrating genome data with datasets from various disciplines, such as IT and psychology, could lead to better complex trait prediction. This review elucidates the significance of clear biological pathways in understanding behaviour traits. Specifically, it highlights the essential role of genes related to hormones, enzymes, and neurotransmitters as robust core genes in shaping these traits. Significant variations in core genes are prominently observed in behaviour traits such as stress response, impulsivity, and substance use.

Integrated Bioinformatics Analysis and Experimental Verification of Immune Cell Infiltration and the Related Core Genes in Ulcerative Colitis

Background

Ulcerative colitis is a recurrent autoimmune disease. At present, the pathogenesis of UC is not completely clear. Hence, the etiology and underlying molecular mechanism need to be further investigated.

Methods

Three sets of microarray datasets were included from the Gene Expression Omnibus database. The differentially expressed genes in two sets of datasets were analyzed using the R software, and the core genes of UC were screened using machine learning. The sensitivity and specificity of the core genes were evaluated with the receiver operating characteristic curve in another microarray dataset. Subsequently, the CIBERSORT tool was used to analyze the relationship between UC and its core genes and immune cell infiltration. To verify the relationship between UC and core genes and the relationship between core genes and immune cell infiltration in vivo.

Results

A total of 36 DEGs were identified. AQP8, HMGCS2, and VNN1 were determined to be the core genes of UC. These genes had high sensitivity and specificity in receiver operating characteristic curve analysis. According to the analysis of immune cell infiltration, neutrophils, monocytes, and macrophages were positively correlated with UC. AQP8, HMGCS2, and VNN1 were also correlated with immune cell infiltration to varying degrees. In vivo experiments verified that the expressions of neutrophils, monocytes, and macrophages increased in the UC colon. Furthermore, the expressions of AQP8 and HMGCS2 decreased, whereas that of VNN1 increased. Azathioprine treatment improved all the indicators to different degrees.

Conclusion

AQP8, HMGCS2, and VNN1 are the core genes of UC and exhibit different degrees of correlation with immune cells. These genes are expected to become new therapeutic targets for UC. Moreover, the occurrence and development of UC are influenced by immune cell infiltration.

Core genes in lung adenocarcinoma identified by integrated bioinformatic analysis

This study aims to identify potential core genes of lung adenocarcinoma (LUAD). Three datasets (GSE32863, GSE43458, and GSE116959) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between LUAD and normal tissues were filtrated by GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed via Metascape database. The protein-protein interaction (PPI) network was constructed and core genes were identified using STRING and Cytoscape. Core genes expressions and their relevant clinical characteristics were performed via Oncomine and UALCAN databases respectively. The correlation between core genes and immune infiltrates was investigated by TIMER database. Kaplan-Meier plotter was performed for survival analysis. The signal pathway network of core genes was mapped by KEGG Mapper analysis tool. In this study, ten core genes were significantly related to overall survival (OS) of LUAD patients, which can provide clues for prognosis of LUAD.

Exploring Core Genes by Comparative Transcriptomics Analysis for Early Diagnosis, Prognosis, and Therapies of Colorectal Cancer

Colorectal cancer (CRC) is one of the most common cancers with a high mortality rate. Early diagnosis and therapies for CRC may reduce the mortality rate. However, so far, no researchers have yet investigated core genes (CGs) rigorously for early diagnosis, prognosis, and therapies of CRC. Therefore, an attempt was made in this study to explore CRC-related CGs for early diagnosis, prognosis, and therapies. At first, we identified 252 common differentially expressed genes (cDEGs) between CRC and control samples based on three gene-expression datasets. Then, we identified ten cDEGs (AURKA, TOP2A, CDK1, PTTG1, CDKN3, CDC20, MAD2L1, CKS2, MELK, and TPX2) as the CGs, highlighting their mechanisms in CRC progression. The enrichment analysis of CGs with GO terms and KEGG pathways revealed some crucial biological processes, molecular functions, and signaling pathways that are associated with CRC progression. The survival probability curves and box-plot analyses with the expressions of CGs in different stages of CRC indicated their strong prognostic performance from the earlier stage of the disease. Then, we detected CGs-guided seven candidate drugs (Manzamine A, Cardidigin, Staurosporine, Sitosterol, Benzo[a]pyrene, Nocardiopsis sp., and Riccardin D) by molecular docking. Finally, the binding stability of four top-ranked complexes (TPX2 vs. Manzamine A, CDC20 vs. Cardidigin, MELK vs. Staurosporine, and CDK1 vs. Riccardin D) was investigated by using 100 ns molecular dynamics simulation studies, and their stable performance was observed. Therefore, the output of this study may play a vital role in developing a proper treatment plan at the earlier stages of CRC.

Cre/lox-Mediated CRISPRi Library Reveals Core Genome of a Type I Methanotroph Methylotuvimicrobium buryatense 5GB1C

Methanotrophs play key roles in global methane cycling and are promising platforms for methane bioconversion. However, major gaps existing in fundamental knowledge undermines understanding of these methane-consuming microorganisms. To associate genes with a phenotype at the genome-wide level, we developed a Cre/lox-mediated method for constructing a large-scale CRISPRi library in a model methanotroph Methylotuvimicrobium buryatense 5GB1C. The efficiency of this Cre mediated integration method was up to a level of 10⁵ CFU/μg DNA. Targeting 4,100 predicted protein-coding genes, our CRISPRi pooled screening uncovered 788 core genes for the growth of strain 5GB1C using methane. The core genes are highly consistent with the gene knockout results, indicating the reliability of the CRISPRi screen. Insights from the core genes include that annotated isozymes generally exist in metabolic pathways and many core genes are hypothetical genes. This work not only provides functional genomic data for both fundamental research and metabolic engineering of methanotrophs, but also offers a method for CRISPRi library construction. IMPORTANCE Due to their key role in methane cycling and their industrial potential, methanotrophs have drawn increasing attention. Genome-wide experimental approaches for gene-phenotype mapping accelerate our understanding and engineering of a bacterium. However, these approaches are still unavailable in methanotrophs. This work has two significant implications. First, the core genes identified here provide functional genetic basics for complete reconstruction of the metabolic network and afford more clues for knowledge gaps. Second, the Cre-mediated knock-in method developed in this work enables large-scale DNA library construction in methanotrophs; the CRISPRi library can be used to screen the genes associated with special culture conditions.

Horizontal transfer and evolution of wall teichoic acid gene cassettes in Bacillus subtilis

Background: Wall teichoic acid (WTA) genes are essential for production of cell walls in gram-positive bacteria and necessary for survival and variability in the cassette has led to recent antibiotic resistance acquisition in pathogenic bacteria. 

Methods: Using a pan-genome approach, we examined the evolutionary history of WTA genes in  Bacillus subtilis ssp.  subtilis. 

Results: Our analysis reveals an interesting pattern of evolution from the type-strain WTA gene cassette possibly resulting from horizontal acquisition from organisms with similar gene sequences. The WTA cassettes have a high level of variation which may be due to one or more independent horizontal transfer events during the evolution of  Bacillus subtilis ssp.  subtilis. This swapping of entire WTA cassettes and smaller regions within the WTA cassettes is an unusual feature in the evolution of the  Bacillus subtilis genome and highlights the importance of horizontal transfer of gene cassettes through homologous recombination within  B. subtilis or other bacterial species. 

Conclusions: Reduced sequence conservation of these WTA cassettes may indicate a modified function like the previously documented WTA ribitol/glycerol variation. An improved understanding of high-frequency recombination of gene cassettes has ramifications for synthetic biology and the use of  B. subtilis in industry.

A pan-genome method to determine core regions of the Bacillus subtilis and Escherichia coli genomes

Background: Synthetic engineering of bacteria to produce industrial products is a burgeoning field of research and application. In order to optimize genome design, designers need to understand which genes are essential, which are optimal for growth, and locations in the genome that will be tolerated by the organism when inserting engineered cassettes.

Methods: We present a pan-genome based method for the identification of core regions in a genome that are strongly conserved at the species level.

Results: We show that the core regions determined by our method contain all or almost all essential genes. This demonstrates the accuracy of our method as essential genes should be core genes. We show that we outperform previous methods by this measure. We also explain why there are exceptions to this rule for our method.

Conclusions: We assert that synthetic engineers should avoid deleting or inserting into these core regions unless they understand and are manipulating the function of the genes in that region. Similarly, if the designer wishes to streamline the genome, non-core regions and in particular low penetrance genes would be good targets for deletion. Care should be taken to remove entire cassettes with similar penetrance of the genes within cassettes as they may harbor toxin/antitoxin genes which need to be removed in tandem. The bioinformatic approach introduced here saves considerable time and effort relative to knockout studies on single isolates of a given species and captures a broad understanding of the conservation of genes that are core to a species.

Identification and Full Characterisation of Two Novel Crustacean Infecting Members of the Family Nudiviridae Provides Support for Two Subfamilies

Multiple enveloped viruses with rod-shaped nucleocapsids have been described, infecting the epithelial cell nuclei within the hepatopancreas tubules of crustaceans. These bacilliform viruses share the ultrastructural characteristics of nudiviruses, a specific clade of viruses infecting arthropods. Using histology, electron microscopy and high throughput sequencing, we characterise two further bacilliform viruses from aquatic hosts, the brown shrimp (Crangon crangon) and the European shore crab (Carcinus maenas). We assembled the full double stranded, circular DNA genome sequences of these viruses (~113 and 132 kbp, respectively). Comparative genomics and phylogenetic analyses confirm that both belong within the family Nudiviridae but in separate clades representing nudiviruses found in freshwater and marine environments. We show that the three thymidine kinase (tk) genes present in all sequenced nudivirus genomes, thus far, were absent in the Crangon crangon nudivirus, suggesting there are twenty-eight core genes shared by all nudiviruses. Furthermore, the phylogenetic data no longer support the subdivision of the family Nudiviridae into four genera (Alphanudivirus to Deltanudivirus), as recently adopted by the International Committee on Taxonomy of Viruses (ICTV), but rather shows two main branches of the family that are further subdivided. Our data support a recent proposal to create two subfamilies within the family Nudiviridae, each subdivided into several genera.

Identification of a Core Module for Bone Mineral Density through the Integration of a Co-expression Network and GWAS Data

The "omnigenic" model of the genetic architecture of complex traits proposed two categories of causal genes: core and peripheral. Core genes are hypothesized to directly regulate disease and may serve as therapeutic targets. Using a cell-type- and time-point-specific gene co-expression network for mineralizing osteoblasts, we identify a co-expression module enriched for genes implicated by bone mineral density (BMD) genome-wide association studies (GWASs), correlated with in vitro osteoblast mineralization and associated with skeletal phenotypes in human monogenic disease and mouse knockouts. Four genes from this module (B4GALNT3, CADM1, DOCK9, and GPR133) are located within the BMD GWAS loci with colocalizing expression quantitative trait loci (eQTL) and exhibit altered BMD in mouse knockouts, suggesting that they are causal genetic drivers of BMD in humans. Our network-based approach identifies a "core" module for BMD and provides a resource for expanding our understanding of the genetics of bone mass.

Bioinformatics-based analysis of the lncRNA-miRNA-mRNA and TF regulatory networks reveals functional genes in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a 5-year survival rate unsatisfied malignancies. The study aimed to identify the novel diagnostic and prognostic targets for ESCC. Expression profiling (GSE89102, GSE97051, and GSE59973) data were downloaded from the GEO database. Then, differentially expressed (DE) lncRNAs, DEmiRNAs, and genes (DEGs) with P-values < 0.05, and |log₂FC| ≥ 2, were identified using GEO2R. Functional enrichment analysis of miRNA-related mRNAs and lncRNA co-expressed mRNA was performed. LncRNA–miRNA–mRNA, protein–protein interaction of miRNA-related mRNAs and DEGs, co-expression, and transcription factors-hub genes network were constructed. The transcriptional data, the diagnostic and prognostic value of hub genes were estimated with ONCOMINE, receiver operating characteristic (ROC) analyses, and Kaplan–Meier plotter, respectively. Also, the expressions of hub genes were assessed through qPCR and Western blot assays. The CDK1, VEGFA, PRDM10, RUNX1, CDK6, HSP90AA1, MYC, EGR1, and SOX2 used as hub genes. And among them, PRDM10, RUNX1, and CDK6 predicted worse overall survival (OS) in ESCC patients. Our results showed that the hub genes were significantly up-regulated in ESCA primary tumor tissues and cell lines, and exhibited excellent diagnostic efficiency. These results suggest that the hub genes may server as potential targets for the diagnosis and treatment of ESCC.

Identification of key pathways and core genes involved in atherosclerotic plaque progression

Background

Atherosclerosis leads to the occurrence of cardiovascular diseases. However, the molecular mechanisms that contribute to atherosclerotic plaque rupture are incompletely characterized. We aimed to identify the genes related to atherosclerotic plaque progression that could serve as novel biomarkers and interventional targets for plaque progression.

Methods

The datasets of GSE28829 in early vs. advanced atherosclerotic plaques and those of GSE41571 in stable vs. ruptured plaques from Gene Expression Omnibus (GEO) were analyzed by using bioinformatics methods. In addition, we used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the expression level of core genes in a mouse atherosclerosis model.

Results

There were 29 common differentially expressed genes (DEGs) between the GSE28829 and GSE41571 datasets, and the DEGs were mainly enriched in the chemokine signaling pathway and the Staphylococcus aureus infection pathway (P<0.05). We identified 6 core genes (FPR3, CCL18, MS4A4A, CXCR4, CXCL2, and C1QB) in the protein-protein interaction (PPI) network, 3 of which (CXCR4, CXCL2, and CCL18) were markedly enriched in the chemokine signaling pathway. qRT-PCR analysis showed that the messenger RNA levels of two core genes (CXCR4 and CXCL2) increased significantly during plaque progression in the mouse atherosclerosis model.

Conclusions

In summary, bioinformatics techniques proved useful for the screening and identification of novel biomarkers of disease. A total of 29 DEGs and 6 core genes were linked to atherosclerotic plaque progression, in particular the CXCR4 and CXCL2 genes.

Screening and bioinformatical analysis of differentially expressed genes in nasopharyngeal carcinoma

Objective: To identify differentially expressed genes via bioinformatical analysis for nasopharyngeal carcinoma (NPC) and explore potential biomarkers for NPC.

Methods: We downloaded the NPC gene expression datasets (GSE40290, GSE53819) and obtained differentially expressed genes (DEGs) via GEO2R. Functional analysis of DEGs was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In order to explore the interaction of DEGs and screen the core genes, we established protein-protein interaction (PPI) network. Then the expression level, prognostic and diagnostic analysis of the core genes in NPC were performed to reveal their potential effects on NPC. Furthermore, we obtained the transcription factors (TF) and microRNAs of core genes to construct the coregulatory network.

Results: We obtained 124 up-regulated genes and 190 down-regulated genes in total. These genes were found to be related to signal transduction, extracellular matrix organization and cell adhesion based on GO analysis. KEGG analysis revealed that the NF-kappa B (NF-κB) signaling pathway, pathways in cancer were mainly enriched signaling pathways. 25 core genes were obtained by constructing PPI network. Then the high expression of 10 core genes in NPC were verified via GEPIA, Oncomine databases and laboratory experiments. The TF-microRNA coregulatory network of the 10 core genes was built. Survival and diagnostic analysis indicated that SPP1 had negative influence on the prognosis of NPC patients based on two datasets and nine up-regulated core genes (FN1, MMP1, MMP3, PLAU, PLAUR, SERPINE1, SPP1, COL8A1, COL10A1) might be diagnostic markers for NPC.

Conclusions: Core genes of NPC were screened out by bioinformatical analysis in the present study and these genes may serve as prognostic and diagnostic biomarkers for NPC.

Defining the Rhizobium leguminosarum Species Complex

Bacteria currently included in Rhizobium leguminosarum are too diverse to be considered a single species, so we can refer to this as a species complex (the Rlc). We have found 429 publicly available genome sequences that fall within the Rlc and these show that the Rlc is a distinct entity, well separated from other species in the genus. Its sister taxon is R. anhuiense. We constructed a phylogeny based on concatenated sequences of 120 universal (core) genes, and calculated pairwise average nucleotide identity (ANI) between all genomes. From these analyses, we concluded that the Rlc includes 18 distinct genospecies, plus 7 unique strains that are not placed in these genospecies. Each genospecies is separated by a distinct gap in ANI values, usually at approximately 96% ANI, implying that it is a 'natural' unit. Five of the genospecies include the type strains of named species: R. laguerreae, R. sophorae, R. ruizarguesonis, "R. indicum" and R. leguminosarum itself. The 16S ribosomal RNA sequence is remarkably diverse within the Rlc, but does not distinguish the genospecies. Partial sequences of housekeeping genes, which have frequently been used to characterize isolate collections, can mostly be assigned unambiguously to a genospecies, but alleles within a genospecies do not always form a clade, so single genes are not a reliable guide to the true phylogeny of the strains. We conclude that access to a large number of genome sequences is a powerful tool for characterizing the diversity of bacteria, and that taxonomic conclusions should be based on all available genome sequences, not just those of type strains.

Dual RNase and β-lactamase Activity of a Single Enzyme Encoded in Archaea

β-lactam antibiotics have a well-known activity which disturbs the bacterial cell wall biosynthesis and may be cleaved by β-lactamases. However, these drugs are not active on archaea microorganisms, which are naturally resistant because of the lack of β-lactam target in their cell wall. Here, we describe that annotation of genes as β-lactamases in Archaea on the basis of homologous genes is a remnant of identification of the original activities of this group of enzymes, which in fact have multiple functions, including nuclease, ribonuclease, β-lactamase, or glyoxalase, which may specialized over time. We expressed class B β-lactamase enzyme from Methanosarcina barkeri that digest penicillin G. Moreover, while weak glyoxalase activity was detected, a significant ribonuclease activity on bacterial and synthetic RNAs was demonstrated. The β-lactamase activity was inhibited by β-lactamase inhibitor (sulbactam), but its RNAse activity was not. This gene appears to have been transferred to the Flavobacteriaceae group especially the Elizabethkingia genus, in which the expressed gene shows a more specialized activity on thienamycin, but no glyoxalase activity. The expressed class C-like β-lactamase gene, from Methanosarcina sp., also shows hydrolysis activity on nitrocefin and is more closely related to DD-peptidase enzymes. Our findings highlight the need to redefine the nomenclature of β-lactamase enzymes and the specification of multipotent enzymes in different ways in Archaea and bacteria over time.

Estimating Pangenomes with Roary

A description of the genetic makeup of a species based on a single genome is often insufficient because it ignores the variability in gene repertoire among multiple strains. The estimation of the pangenome of a species is a solution to this issue as it provides an overview of genes that are shared by all strains and genes that are present in only some of the genomes. These different sets of genes can then be analyzed functionally to explore correlations with unique phenotypes and adaptations. This protocol presents the usage of Roary, a Linux-native pangenome application. Roary is a straightforward software that provides 1) an overview about core and accessory genes for those interested in general trends and, also, 2) detailed information on gene presence/absence in each genome for in-depth analyses. Results are provided both in text and graphic format.

Genomic analysis of Ranavirus and exploring alternative genes for phylogenetics

Ranaviruses can infect both captive and wild cold-blooded vertebrates, leading to significant economic and environmental losses. With the cases of ranavirus infection increasing, many ranavirus genomic sequences were published, but little is known about ranavirus taxonomy on a whole-genome level. In this study, 44 ranaviruses core genes were identified in 32 ranaviruses genome sequences by using PanX. The neighbour-joining phylogenetic trees (NJ-tree) based on 44 ranaviruses core genes and 24 iridoviridae core genes and composition vector phylogenetic tree (CV-Tree) based on whole genome were constructed. The three of phylogenetic trees showed that 32 ranavirus isolates can be divided into 4 different subgroups including SGIV-like, EHNV-like, FV3-like and CMTV-like, and subgroups taxonomic position of three phylogenetic trees were consistent. However, the phylogenetic position of ToRV could not be determined if it belongs to FV3-like or CMTV-like group. Subsequently, we carried out dot plot analysis and confirmed that ToRV should belong to CMTV-like group. Based on dot plot analysis and phylogenetic trees, the taxonomic classification of ranaviruses was confirmed. Finally, four genes which are suitable for the construction of phylogenetic tree were selected from ranavirus core genes by recombination analysis, substitution saturation analysis and single-gene phylogenetic analysis. Phylogenetic tree based on concatenated sequences of the four selected genes showed that the classification of subgroups was identical with three of the phylogenetic trees. Conclusion: Our results confirmed taxonomic identification of ranaviruses; the four selected genes used in phylogenetic analysis will make taxonomic identification more convenient and accurate.

Identification and validation of core genes for serous ovarian adenocarcinoma via bioinformatics analysis

Ovarian cancer is a fatal gynaecological malignancy in women worldwide, and serous ovarian cancer (SOC) is considered the most common histological subtype of this malignancy. Thus, the present study aimed to identify the core genes for SOC via bioinformatics analysis. The GSE18520 and GSE14407 datasets were downloaded from the Gene Expression Omnibus (GEO) database to screen for differentially expressed genes (DEGs) and perform gene set enrichment analysis (GSEA). A protein-protein interaction (PPI) network was constructed to identify the core genes, while The Cancer Genome Atlas (TCGA) database was used to screen for prognosis-associated DEGs. Furthermore, clinical samples were collected for further validation of kinesin family member 11 (KIF11) gene. In the GEO analysis, a total of 198 DEGs were identified, including 81 upregulated and 117 downregulated genes compared SOC to normal tissue. GSEA across the two datasets demonstrated that 16 gene sets, including those involved in the cell cycle and DNA replication, were notably associated with SOC. A PPI network of the DEGs was constructed with 130 nodes and 387 edges. Subsequently, 20 core genes involved in the same top-ranked module were filtered out by submodule analysis. Survival analysis identified three predictive genes for SOC prognosis, including KIF11, CLDN3 and FGF13. KIF11 was identified as a core and predictive gene and thus was further validated using clinical samples. The results demonstrated that KIF11 was upregulated in tumour tissues compared with adjacent normal tissues and was associated with aggressive factors, including tumour grade, TNM stage and lymph node invasion. In conclusions, the present study identified the core genes and gene sets for SOC, thus extending the understanding of SOC occurrence and progression. Furthermore, KIF11 was identified as a promising tumour-promoting gene and a potential target for the diagnosis and treatment of SOC.

Codon Usage Optimization in the Prokaryotic Tree of Life: How Synonymous Codons Are Differentially Selected in Sequence Domains with Different Expression Levels and Degrees of Conservation

The prokaryotic genomes—the current heritage of the most ancient life forms on earth—are comprised of diverse gene sets, all characterized by varied origins, ancestries, and spatial-temporal expression patterns. Such genetic diversity has for a long time raised the question of how cells shape their coding strategies to optimize protein demands (i.e., product abundance) and accuracy (i.e., translation fidelity) through the use of the same genetic code in genomes with GC contents that range from less than 20 to more than 80%. Here, we present evidence on how codon usage is adjusted in the prokaryotic tree of life and on how specific biases have operated to improve translation. Through the use of proteome data, we characterized conserved and variable sequence domains in genes of either high or low expression level and quantitated the relative weight of efficiency and accuracy—as well as their interaction—in shaping codon usage in prokaryotes.

Prokaryote genomes exhibit a wide range of GC contents and codon usages, both resulting from an interaction between mutational bias and natural selection. In order to investigate the basis underlying specific codon changes, we performed a comprehensive analysis of 29 different prokaryote families. The analysis of core gene sets with increasing ancestries in each family lineage revealed that the codon usages became progressively more adapted to the tRNA pools. While, as previously reported, highly expressed genes presented the most optimized codon usage, the singletons contained the less selectively favored codons. The results showed that usually codons with the highest translational adaptation were preferentially enriched. In agreement with previous reports, a C bias in 2- to 3-fold pyrimidine-ending codons, and a U bias in 4-fold codons occurred in all families, irrespective of the global genomic GC content. Furthermore, the U biases suggested that U₃-mRNA–U₃₄-tRNA interactions were responsible for a prominent codon optimization in both the most ancestral core and the highly expressed genes. A comparative analysis of sequences that encode conserved (cr) or variable (vr) translated products, with each one being under high (HEP) and low (LEP) expression levels, demonstrated that the efficiency was more relevant (by a factor of 2) than accuracy to modeling codon usage. Finally, analysis of the third position of codons (GC3) revealed that in genomes with global GC contents higher than 35 to 40%, selection favored a GC3 increase, whereas in genomes with very low GC contents, a decrease in GC3 occurred. A comprehensive final model is presented in which all patterns of codon usage variations are condensed in four distinct behavioral groups.

Pan-Genome-Based Analysis as a Framework for Demarcating Two Closely Related Methanotroph Genera Methylocystis and Methylosinus

The Methylocystis and Methylosinus are two of the five genera that were included in the first taxonomic framework of methanotrophic bacteria created half a century ago. Members of both genera are widely distributed in various environments and play a key role in reducing methane fluxes from soils and wetlands. The original separation of these methanotrophs in two distinct genera was based mainly on their differences in cell morphology. Further comparative studies that explored various single-gene-based phylogenies suggested the monophyletic nature of each of these genera. Current availability of genome sequences from members of the Methylocystis/Methylosinus clade opens the possibility for in-depth comparison of the genomic potentials of these methanotrophs. Here, we report the finished genome sequence of Methylocystis heyeri H2^T and compare it to 23 currently available genomes of Methylocystis and Methylosinus species. The phylogenomic analysis confirmed that members of these genera form two separate clades. The Methylocystis/Methylosinus pan-genome core comprised 1173 genes, with the accessory genome containing 4941 and 11,192 genes in the shell and the cloud, respectively. Major differences between the genome-encoded environmental traits of these methanotrophs include a variety of enzymes for methane oxidation and dinitrogen fixation as well as genomic determinants for cell motility and photosynthesis.

Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

Aim:

To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD).

Materials & methods:

We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID.

Results:

Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD.

Conclusion:

23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

Gene Expression Profiling Indicated Diverse Functions and Characteristics of Core Genes in Pea Aphid

The pea aphid is a global insect pest, and variable phenotypes can be produced by pea aphids in the same genotype in response to changes in external environmental factors. However, detailed dynamic gene regulation networks and the core markers involved in different biological processes of pea aphids have not yet been reported. In this study, we obtained the published genomic and transcriptomic data, and performed transcriptome profiling of five pea aphid morphs (winged asexual female, wingless asexual female, wingless sexual female, winged male and wingless male) from each of three pea aphid genotypes, i.e., the transcriptomes from a total of 15 types of pea aphids were analyzed and the type-specific expression of genes in five different morphs was identified. The expression profiling was verified by quantitative real-time PCR (qPCR) analysis. Moreover, we determined the expression features and co-expression networks of highly variable genes. We also used the ARACNe method to obtain 263 core genes related to different biological pathways. Additionally, eight of the identified genes were aligned with transcription factor families, indicating that they act as transcription factors and regulate downstream genes. Furthermore, we found reliable markers using random forest methodology to distinguish different morphs of pea aphids. Our study provides a systematic and comprehensive approach for analyzing the core genes that may play important roles in a multitude of biological processes from the insect transcriptomes.

Comparative genomic analysis reveals an 'open' pan-genome of African swine fever virus

The worldwide transmission of African swine fever virus (ASFV) drastically affects the pig industry and global trade. Development of vaccines is hindered by the lack of knowledge of the genomic characteristics of ASFV. In this study, we developed a pipeline for the de novo assembly of ASFV genome without virus isolation and purification. We then used a comparative genomics approach to systematically study 46 genomes of ASFVs to reveal the genomic characteristics. The analysis revealed that ASFV has an 'open' pan-genome based on both protein-coding genes and intergenic regions. Of the 151-174 genes found in the ASFV strains, only 86 were identified as core genes; the remainder were flexible accessory genes. Notably, 44 of the 86 core genes and 155 of the 324 accessory genes have been functionally annotated according to the known proteins. Interestingly, a dynamic number of taxis-related genes were identified in the accessory genes, and two potential virulence genes were identified in all ASFV isolates. The 'open' pan-genome of ASFV based on gene and intergenic regions reveals its pronounced natural diversity concerning genomic composition and regulation.

Genome Improvement and Core Gene Set Refinement of Fugacium kawagutii

Cataloging an accurate functional gene set for the Symbiodiniaceae species is crucial for addressing biological questions of dinoflagellate symbiosis with corals and other invertebrates. To improve the gene models of Fugacium kawagutii, we conducted high-throughput chromosome conformation capture (Hi-C) for the genome and Illumina combined with PacBio sequencing for the transcriptome to achieve a new genome assembly and gene prediction. A 0.937-Gbp assembly of F. kawagutii were obtained, with a N50 > 13 Mbp and the longest scaffold of 121 Mbp capped with telomere motif at both ends. Gene annotation produced 45,192 protein-coding genes, among which, 11,984 are new compared to previous versions of the genome. The newly identified genes are mainly enriched in 38 KEGG pathways including N-Glycan biosynthesis, mRNA surveillance pathway, cell cycle, autophagy, mitophagy, and fatty acid synthesis, which are important for symbiosis, nutrition, and reproduction. The newly identified genes also included those encoding O-methyltransferase (O-MT), 3-dehydroquinate synthase, homologous-pairing protein 2-like (HOP2) and meiosis protein 2 (MEI2), which function in mycosporine-like amino acids (MAAs) biosynthesis and sexual reproduction, respectively. The improved version of the gene set (Fugka_Geneset _V3) raised transcriptomic read mapping rate from 33% to 54% and BUSCO match from 29% to 55%. Further differential gene expression analysis yielded a set of stably expressed genes under variable trace metal conditions, of which 115 with annotated functions have recently been found to be stably expressed under three other conditions, thus further developing the "core gene set" of F. kawagutii. This improved genome will prove useful for future Symbiodiniaceae transcriptomic, gene structure, and gene expression studies, and the refined "core gene set" will be a valuable resource from which to develop reference genes for gene expression studies.

Transcriptomic Analysis of Aggregatibacter actinomycetemcomitans Core and Accessory Genes in Different Growth Conditions

Aggregatibacter actinomycetemcomitans genome can be divided into an accessory gene pool (found in some but not all strains) and a core gene pool (found in all strains). The functions of the accessory genes (genomic islands and non-island accessory genes) are largely unknown. We hypothesize that accessory genes confer critical functions for A. actinomycetemcomitans in vivo. This study examined the expression patterns of accessory and core genes of A. actinomycetemcomitans in distinct growth conditions. We found similar expression patterns of island and non-island accessory genes, which were generally lower than the core genes in all growth conditions. The median expression levels of genomic islands were 29%–37% of the core genes in enriched medium but elevated to as high as 63% of the core genes in nutrient-limited media. Several putative virulence genes, including the cytolethal distending toxin operon, were found to be activated in nutrient-limited conditions. In conclusion, genomic islands and non-island accessory genes exhibited distinct patterns of expression from the core genes and may play a role in the survival of A. actinomycetemcomitans in nutrient-limited environments.

Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis

Endometrial carcinoma (EC) is a common malignant neoplasm of the female reproductive tract. The malignant degree of type II EC is much greater than that of type I EC, usually presenting with a high recurrence rate and a poor prognosis. Therefore, the present study aimed to examine the principal genes associated with the degree of differentiation in type I and type II EC and reveal their potential mechanisms. Differentially expressed genes (DEGs) were selected from the gene expression profiles derived from The Cancer Genome Atlas. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. In the present study, the KEGG pathway enrichment analysis revealed that 5,962 upregulated DEGs were significantly enriched in the ‘p53 signaling pathway’ and involved in ‘lysine degradation’. In addition, 3,709 downregulated DEGs were enriched in ‘pathways in cancer’, as well as ‘tight junction regulation’, the ‘cell cycle’ and the ‘Wnt signaling pathway’. The 13 top hub genes MAPK1, PHLPP1, ESR1, MDM2, CDKN2A, CDKN1A, AURKA, BCL2L1, POLQ, PIK3R3, RHOQ, EIF4E and LATS2 were identified via the protein-protein interaction network. Furthermore, the OncoPrint algorithm from cBioPortal declared that 25% of EC cases carried genetic alterations. The altered DEGs (MAPK1, MDM2, AURKA, EIF4E and LATS2) may be involved in tumor differentiation and may be valuable diagnostic biomarkers. In conclusion, a number of principal genes were identified in the present study that may be determinants of poorly differentiated type II EC carcinogenesis, which may contribute to future research into potential molecular mechanisms. In addition, these genes may help identify candidate biomarkers and novel therapeutic targets for type II EC.

Trans Effects on Gene Expression Can Drive Omnigenic Inheritance

Early genome-wide association studies (GWASs) led to the surprising discovery that, for typical complex traits, most of the heritability is due to huge numbers of common variants with tiny effect sizes. Previously, we argued that new models are needed to understand these patterns. Here, we provide a formal model in which genetic contributions to complex traits are partitioned into direct effects from core genes and indirect effects from peripheral genes acting in trans. We propose that most heritability is driven by weak trans-eQTL SNPs, whose effects are mediated through peripheral genes to impact the expression of core genes. In particular, if the core genes for a trait tend to be co-regulated, then the effects of peripheral variation can be amplified such that nearly all of the genetic variance is driven by weak trans effects. Thus, our model proposes a framework for understanding key features of the architecture of complex traits.

Exploring and Exploiting Pan-genomics for Crop Improvement

Genetic variation ranging from single-nucleotide polymorphisms to large structural variants (SVs) can cause variation of gene content among individuals within the same species. There is an increasing appreciation that a single reference genome is insufficient to capture the full landscape of genetic diversity of a species. Pan-genome analysis offers a platform to evaluate the genetic diversity of a species via investigation of its entire genome repertoire. Although a recent wave of pan-genomic studies has shed new light on crop diversity and improvement using advanced sequencing technology, the potential applications of crop pan-genomics in crop improvement are yet to be fully exploited. In this review, we highlight the progress achieved in understanding crop pan-genomics, discuss biological activities that cause SVs, review important agronomical traits affected by SVs, and present our perspective on the application of pan-genomics in crop improvement.

Genetic and phenotypic diversity of rhizobia nodulating chickpea (Cicer arietinum L.) in soils from southern and central Ethiopia

Forty-two chickpea-nodulating rhizobia were isolated from soil samples collected from diverse agro-ecological locations of Ethiopia and were characterized on the basis of 76 phenotypic traits. Furthermore, 18 representative strains were selected and characterized using multilocus sequence analyses of core and symbiotic gene loci. Numerical analysis of the phenotypic characteristics grouped the 42 strains into 4 distinct clusters. The analysis of the 16S rRNA gene of the 18 strains showed that they belong to the Mesorhizobium genus. On the basis of the phylogenetic tree constructed from the combined genes sequences (recA, atpD, glnII, and gyrB), the test strains were distributed into 4 genospecies (designated as genospecies I-IV). Genospecies I, II, and III could be classified with Mesorhizobium ciceri, Mesorhizobium abyssinicae, and Mesorhizobium shonense, respectively, while genospecies IV might represent an unnamed Mesorhizobium genospecies. Phylogenetic reconstruction based on the symbiosis-related (nifH and nodA) genes supported a single cluster together with a previously described symbiont of chickpea (M. ciceri and Mesorhizobium mediterraneum). Overall, our results corroborate earlier findings that Ethiopian soils harbor phylogenetically diverse Mesorhizobium species, justifying further explorative studies. The observed differences in symbiotic effectiveness indicated the potential to select effective strains for use as inoculants and to improve the productivity of chickpea in the country.

Pangenome Evidence for Higher Codon Usage Bias and Stronger Translational Selection in Core Genes of Escherichia coli

Codon usage bias, as a combined interplay from mutation and selection, has been intensively studied in Escherichia coli. However, codon usage analysis in an E. coli pangenome remains unexplored and the relative importance of mutation and selection acting on core genes and strain-specific genes is unknown. Here we perform comprehensive codon usage analyses based on a collection of multiple complete genome sequences of E. coli. Our results show that core genes that are present in all strains have higher codon usage bias than strain-specific genes that are unique to single strains. We further explore the forces in influencing codon usage and investigate the difference of the major force between core and strain-specific genes. Our results demonstrate that although mutation may exert genome-wide influences on codon usage acting similarly in different gene sets, selection dominates as an important force to shape biased codon usage as genes are present in an increased number of strains. Together, our results provide important insights for better understanding genome plasticity and complexity as well as evolutionary mechanisms behind codon usage bias.

Molecular characterization influencing metal resistance in the Cupriavidus/Ralstonia genomes

Our environment is stressed with a load of heavy and toxic metals. Microbes, abundant in our environment, are found to adapt well to this metal-stressed condition. A comparative study among five Cupriavidus/Ralstonia genomes can offer a better perception of their evolutionary mechanisms to adapt to these conditions. We have studied codon usage among 1051 genes common to all these organisms and identified 15 optimal codons frequently used in highly expressed genes present within 1051 genes. We found the core genes of Cupriavidus metallidurans CH34 have a different optimal codon choice for arginine, glycine and alanine in comparison with the other four bacteria. We also found that the synonymous codon usage bias within these 1051 core genes is highly correlated with their gene expression. This supports that translational selection drives synonymous codon usage in the core genes of these genomes. Synonymous codon usage is highly conserved in the core genes of these five genomes. The only exception among them is C. metallidurans CH34. This genomewide shift in synonymous codon choice in C. metallidurans CH34 may have taken place due to the insertion of new genes in its genomes facilitating them to survive in heavy metal containing environment and the co-evolution of the other genes in its genome to achieve a balance in gene expression. Structural studies indicated the presence of a longer N-terminal region containing a copper-binding domain in the cupC proteins of C. metallidurans CH3 that helps it to attain higher binding efficacy with copper in comparison with its orthologs.

A genome-based identification approach for members of the genus Bifidobacterium

During recent years, the significant and increasing interest in novel bifidobacterial strains with health-promoting characteristics has catalyzed the development of methods for efficient and reliable identification of Bifidobacterium strains at (sub) species level. We developed an assay based on recently acquired bifidobacterial genomic data and involving 98 primer pairs, called the Bifidobacterium-ampliseq panel. This panel includes multiplex PCR primers that target both core and variable genes of the pangenome of this genus. Our results demonstrate that the employment of the Bifidobacterium-ampliseq panel allows rapid and specific identification of the so far recognized 48 (sub)species harboring the Bifidobacterium genus, and thus represents a cost- and time-effective bifidobacterial screening methodology.

TDAC: co-expressed gene pattern finding using attribute clustering

A number of clustering methods introduced for analysis of gene expression data for extracting potential relationships among the genes are studied and reported in this paper. An effective unsupervised method (TDAC) is proposed for simultaneous detection of outliers and biologically relevant co-expressed patterns. Effectiveness of TDAC is established in comparison to its other competing algorithms over six publicly available benchmark gene expression datasets in terms of both internal and external validity measures. Main attractions of TDAC are: (a) it does not require discretisation, (b) it is capable of identifying biologically relevant gene co-expressed patterns as well as outlier genes(s), (c) it is cost-effective in terms of time and space, (d) it does not require the number of clusters a priori, and (e) it is free from the restrictions of using any proximity measure.

Transfer of noncoding DNA drives regulatory rewiring in bacteria

Understanding the mechanisms that generate variation is a common pursuit unifying the life sciences. Bacteria represent an especially striking puzzle, because closely related strains possess radically different metabolic and ecological capabilities. Differences in protein repertoire arising from gene transfer are currently considered the primary mechanism underlying phenotypic plasticity in bacteria. Although bacterial coding plasticity has been extensively studied in previous decades, little is known about the role that regulatory plasticity plays in bacterial evolution. Here, we show that bacterial genes can rapidly shift between multiple regulatory modes by acquiring functionally divergent nonhomologous promoter regions. Through analysis of 270,000 regulatory regions across 247 genomes, we demonstrate that regulatory "switching" to nonhomologous alternatives is ubiquitous, occurring across the bacterial domain. Using comparative transcriptomics, we show that at least 16% of the expression divergence between Escherichia coli strains can be explained by this regulatory switching. Further, using an oligonucleotide regulatory library, we establish that switching affects bacterial promoter architecture. We provide evidence that regulatory switching can occur through horizontal regulatory transfer, which allows regulatory regions to move across strains, and even genera, independently from the genes they regulate. Finally, by experimentally characterizing the fitness effect of a regulatory transfer on a pathogenic E. coli strain, we demonstrate that regulatory switching elicits important phenotypic consequences. Taken together, our findings expose previously unappreciated regulatory plasticity in bacteria and provide a gateway for understanding bacterial phenotypic variation and adaptation.

Comparative genomics defines the core genome of the growing N4-like phage genus and identifies N4-like Roseophage specific genes

Two bacteriophages, RPP1 and RLP1, infecting members of the marine Roseobacter clade were isolated from seawater. Their linear genomes are 74.7 and 74.6 kb and encode 91 and 92 coding DNA sequences, respectively. Around 30% of these are homologous to genes found in Enterobacter phage N4. Comparative genomics of these two new Roseobacter phages and 23 other sequenced N4-like phages (three infecting members of the Roseobacter lineage and 20 infecting other Gammaproteobacteria) revealed that N4-like phages share a core genome of 14 genes responsible for control of gene expression, replication and virion proteins. Phylogenetic analysis of these genes placed the five N4-like roseophages (RN4) into a distinct subclade. Analysis of the RN4 phage genomes revealed they share a further 19 genes of which nine are found exclusively in RN4 phages and four appear to have been acquired from their bacterial hosts. Proteomic analysis of the RPP1 and RLP1 virions identified a second structural module present in the RN4 phages similar to that found in the Pseudomonas N4-like phage LIT1. Searches of various metagenomic databases, including the GOS database, using CDS sequences from RPP1 suggests these phages are widely distributed in marine environments in particular in the open ocean environment.

Pan-genome analyses identify lineage- and niche-specific markers of evolution and adaptation in Epsilonproteobacteria

The rapidly increasing availability of complete bacterial genomes has created new opportunities for reconstructing bacterial evolution, but it has also highlighted the difficulty to fully understand the genomic and functional variations occurring among different lineages. Using the class Epsilonproteobacteria as a case study, we investigated the composition, flexibility, and function of its pan-genomes. Models were constructed to extrapolate the expansion of pan-genomes at three different taxonomic levels. The results show that, for Epsilonproteobacteria the seemingly large genome variations among strains of the same species are less noticeable when compared with groups at higher taxonomic ranks, indicating that genome stability is imposed by the potential existence of taxonomic boundaries. The analyses of pan-genomes has also defined a set of universally conserved core genes, based on which a phylogenetic tree was constructed to confirm that thermophilic species from deep-sea hydrothermal vents represent the most ancient lineages of Epsilonproteobacteria. Moreover, by comparing the flexible genome of a chemoautotrophic deep-sea vent species to (1) genomes of species belonging to the same genus, but inhabiting different environments, and (2) genomes of other vent species, but belonging to different genera, we were able to delineate the relative importance of lineage-specific versus niche-specific genes. This result not only emphasizes the overall importance of phylogenetic proximity in shaping the variable part of the genome, but also highlights the adaptive functions of niche-specific genes. Overall, by modeling the expansion of pan-genomes and analyzing core and flexible genes, this study provides snapshots on how the complex processes of gene acquisition, conservation, and removal affect the evolution of different species, and contribute to the metabolic diversity and versatility of Epsilonproteobacteria.