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Accurate strain identification is essential for economically significant fungi, as it aids in understanding their diverse agronomic traits, pathogenicity, and other important characteristics. However, traditional methods often face challenges related to limited accuracy, high workloads, and reproducibility issues. Recently, multiple nucleotide polymorphism (MNP) markers have been employed in mushroom strain identification, demonstrating significantly improved accuracy and reproducibility. Nevertheless, the identification of strains across different species still heavily depends on specific and often overly complex MNP markers. In this study, we address these challenges by developing a novel method for constructing high‐resolution phylogenomic topologies using core gene‐associated multiple nucleotide polymorphism (cgMNP) markers, focusing on Agaricus bisporus (button mushroom). Utilising resequencing data from 213 cultivated and wild strains of A. bisporus, we identified 84 cgMNP markers within 83 core genes from 1011 MNP markers. Phylogenetic analysis based on cgMNP sequences and the genetic distance between strain pairs allowed for precise identification of all strains. Moreover, the successful transferability of these cgMNP markers to an additional 385 A. bisporus strains and other fungal species, including Flammulina filiformis (enoki mushroom) and Saccharomyces cerevisiae (yeast), highlights their cross‐species applicability. The high resolution and strong congruence of cgMNP markers with whole‐genome data provide a robust and reliable method for strain‐level discrimination in fungi. The success of this approach in A. bisporus sets a promising precedent for its application to a broader range of fungal taxa. This study introduces a novel method for strain‐level identification in Agaricus bisporus using core gene‐associated multiple nucleotide polymorphism (cgMNP) markers. The approach offers enhanced resolution, accuracy, and transferability across fungal species, facilitating improved phylogenomic analysis, strain discrimination, and applications in breeding and conservation.

Genome-based phylogeny plays a central role in the future taxonomy and phylogenetics of Bacteria and Archaea by replacing 16S rRNA gene phylogeny. The concatenated core gene alignments are frequently used for such a purpose. The bacterial core genes are defined as single-copy, homologous genes that are present in most of the known bacterial species. There have been several studies describing such a gene set, but the number of species considered was rather small. Here we present the up-to-date bacterial core gene set, named UBCG, and software suites to accommodate necessary steps to generate and evaluate phylogenetic trees. The method was successfully used to infer phylogenomic relationship of Escherichia and related taxa and can be used for the set of genomes at any taxonomic ranks of Bacteria . The UBCG pipeline and file viewer are freely available at https://www.ezbiocloud.net/tools/ubcg and https://www.ezbiocloud.net/tools/ubcg_viewer , respectively.

African Swine Fever Virus (ASFV) is a highly contagious pathogen responsible for substantial economic losses in swine populations worldwide. Despite extensive research, the mechanisms underlying the genomic evolution of ASFV remain poorly understood. In this study, we conducted a comprehensive analysis of ASFV evolutionary strategies by examining 252 complete ASFV genomes. Our pan-genome analysis categorizes ASFV genes into core and non-core categories, with core genes predominantly locate in the central region of the genome, while non-core genes are primarily situated at the variable genomic termini, exhibiting higher rates of genetic loss and diversification. Gene synteny analysis revealed that ASFV inherited a portion of its core gene repertoire from the common ancestor of the Asfarviridae family, establishing its central genomic framework, and acquired virus-specific genes that contributed to its distinct genetic identity during divergence. Homologous recombination analysis identified 76 genes exhibiting strong recombination signals, emphasizing the critical role of recombination in ASFV evolution. Additionally, 9 genes were found to be under positive selection, highlighting the influence of the host-virus evolutionary arms race in shaping ASFV genome, particularly in terms of immune evasion and host interaction. These findings underscore the dynamic evolutionary forces driving ASFV adaptive evolution and provide important implications for understanding the virus global spread and the development of effective control measures.

Gene expression analyses of microglia, the tissue-resident macrophages of the central nervous system (CNS), led to the identification of homeostatic as well as neurological disease-specific gene signatures of microglial phenotypes. Upon alterations in the neural microenvironment, either caused by local insults from within the CNS (during neurodegenerative diseases) or by macroenvironmental incidents, such as social stress, microglia can switch phenotypes-generally referred to as \"microglial activation.\" The interplay between the microenvironment and its influence on microglial phenotypes, regulated by (epi)genetic mechanisms, can be imagined as the different colorful crystal formations (microglial phenotypes) that change upon rotation (microenvironmental changes) of a kaleidoscope. In this review, we will discuss microglial phenotypes in relation to neurodevelopment, homeostasis, conditions, aging, and neurodegenerative diseases based on transcriptome studies. By overlaying these disease-specific microglial signatures, recent publications have identified a specific set of genes that is differentially expressed in all investigated diseases, called a microglial core gene signature with multiple diseases. We will conclude this review with a discussion about the complexity of this microglial core gene signature associated with multiple diseases.

Background Genome-scale phylogenetic analysis based on core gene sets is routinely used in microbiological research. However, the techniques are still not approachable for individuals with little bioinformatics experience. Here, we present EasyCGTree, a user-friendly and cross-platform pipeline to reconstruct genome-scale maximum-likehood (ML) phylogenetic tree using supermatrix (SM) and supertree (ST) approaches. Results EasyCGTree was implemented in Perl programming languages and was built using a collection of published reputable programs. All the programs were precompiled as standalone executable files and contained in the EasyCGTree package. It can run after installing Perl language environment. Several profile hidden Markov models (HMMs) of core gene sets were prepared in advance to construct a profile HMM database (PHD) that was enclosed in the package and available for homolog searching. Customized gene sets can also be used to build profile HMM and added to the PHD via EasyCGTree. Taking 43 genomes of the genus Paracoccus as the testing data set, consensus (a variant of the typical SM), SM, and ST trees were inferred via EasyCGTree successfully, and the SM trees were compared with those inferred via the pipelines UBCG and bcgTree, using the metrics of cophenetic correlation coefficients (CCC) and Robinson–Foulds distance (topological distance). The results suggested that EasyCGTree can infer SM trees with nearly identical topology (distance < 0.1) and accuracy (CCC > 0.99) to those of trees inferred with the two pipelines. Conclusions EasyCGTree is an all-in-one automatic pipeline from input data to phylogenomic tree with guaranteed accuracy, and is much easier to install and use than the reference pipelines. In addition, ST is implemented in EasyCGTree conveniently and can be used to explore prokaryotic evolutionary signals from a different perspective. The EasyCGTree version 4 is freely available for Linux and Windows users at Github ( https://github.com/zdf1987/EasyCGTree4 ).

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.

Large dsDNA viruses are involved in the population control of many globally distributed species of eukaryotic phytoplankton and have a prominent role in bloom termination. The genus Phaeocystis (Haptophyta , Prymnesiophyceae) includes several high-biomass-forming phytoplankton species, such as Phaeocystis globosa , the blooms of which occur mostly in the coastal zone of the North Atlantic and the North Sea. Here, we report the 459,984-bp-long genome sequence of P. globosa virus strain PgV-16T, encoding 434 proteins and eight tRNAs and, thus, the largest fully sequenced genome to date among viruses infecting algae. Surprisingly, PgV-16T exhibits no phylogenetic affinity with other viruses infecting microalgae (e.g., phycodnaviruses), including those infecting Emiliania huxleyi , another ubiquitous bloom-forming haptophyte. Rather, PgV-16T belongs to an emerging clade (the Megaviridae) clustering the viruses endowed with the largest known genomes, including Megavirus, Mimivirus (both infecting acanthamoeba), and a virus infecting the marine microflagellate grazer Cafeteria roenbergensis . Seventy-five percent of the best matches of PgV-16T–predicted proteins correspond to two viruses [Organic Lake phycodnavirus (OLPV)1 and OLPV2] from a hypersaline lake in Antarctica (Organic Lake), the hosts of which are unknown. As for OLPVs and other Megaviridae, the PgV-16T sequence data revealed the presence of a virophage-like genome. However, no virophage particle was detected in infected P. globosa cultures. The presence of many genes found only in Megaviridae in its genome and the presence of an associated virophage strongly suggest that PgV-16T shares a common ancestry with the largest known dsDNA viruses, the host range of which already encompasses the earliest diverging branches of domain Eukarya.

Background A key step for comparative genomics is to group open reading frames into functionally and evolutionarily meaningful gene clusters. Gene clustering is complicated by intraspecific duplications and horizontal gene transfers that are frequent in prokaryotes. In consequence, gene clustering methods must deal with a trade-off between identifying vertically transmitted representatives of multicopy gene families, which are recognizable by synteny conservation, and retrieving complete sets of species-level orthologs. We studied the implications of adopting homology, orthology, or synteny conservation as formal criteria for gene clustering by performing comparative analyses of 125 prokaryotic pangenomes. Results Clustering criteria affect pangenome functional characterization, core genome inference, and reconstruction of ancestral gene content to different extents. Species-wise estimates of pangenome and core genome sizes change by the same factor when using different clustering criteria, allowing robust cross-species comparisons regardless of the clustering criterion. However, cross-species comparisons of genome plasticity and functional profiles are substantially affected by inconsistencies among clustering criteria. Such inconsistencies are driven not only by mobile genetic elements, but also by genes involved in defense, secondary metabolism, and other accessory functions. In some pangenome features, the variability attributed to methodological inconsistencies can even exceed the effect sizes of ecological and phylogenetic variables. Conclusions Choosing an appropriate criterion for gene clustering is critical to conduct unbiased pangenome analyses. We provide practical guidelines to choose the right method depending on the research goals and the quality of genome assemblies, and a benchmarking dataset to assess the robustness and reproducibility of future comparative studies.

The association between anal fistula patients and colorectal cancer, as well as the potential pathophysiological mechanisms, remains unclear. To explore the relationship between anal fistula and colorectal cancer and its potential mechanisms. Analysis of GEO and TCGA databases. Disease‐related genes were also referenced from Coremine Medical, GeneCard and OMIM. Core hub genes were identified through protein–protein interaction analysis by intersecting differentially expressed genes from the datasets with disease data. On one hand, a prognostic model was developed using genes and its prognostic role was validated. On the other hand, the optimal diagnostic genes were selected through machine learning. Mendelian randomization (MR) analysis was conducted to explore the potential causal link between anal fistula and colorectal cancer. Thirteen core genes were identified (TMEM121B, PDGFRA, MID2, WNT10B, HOXD13, BARX1, SIX2, MMP1, SNAL1, CDKN2A, ITGB3, TIMP1, CALB2). Functional enrichment analysis revealed that the intersecting genes between anal fistula and colorectal cancer were associated with extracellular matrix components, signalling pathways, cell growth, protein modification, as well as important roles in cellular activities, tissue and organ development, and biological function maintenance. These genes were also involved in pathways related to Wnt signalling and colorectal cancer development. Prognostic analysis and immune infiltration analysis indicated a close relationship between core hub genes and the prognosis and immune infiltration in colorectal cancer. Machine learning showed that core genes played an essential role in the diagnostic differentiation of colorectal cancer. MR results suggested no causal relationship between anal fistula and colorectal cancer. This study identified shared core genes between anal fistula and colorectal cancer, involved in various pathways related to tumour development. These genes play crucial roles in prognosis and diagnosis.

Background Diazotrophs carry out biological nitrogen fixation (BNF) using the nitrogenase enzyme complex (NEC), which relies on nitrogenase encoded by nif genes. Horizontal gene transfer (HGT) and gene duplications have created significant diversity among these genes, making it challenging to identify potential diazotrophs. Previous studies have established a minimal set of Nif proteins, known as the Nif core, which includes NifH, NifD, NifK, NifE, NifN, and NifB. This study aimed to identify potential diazotroph groups based on the Nif core and to analyze the inheritance patterns of accessory Nif proteins related to Mo-nitrogenase, along with their impact on N2 fixation maintenance. Results In a systematic study, 118 diazotrophs were identified, resulting in a database of 2,156 Nif protein sequences obtained with RAFTS³G. Using this Nif database and a data mining strategy, we extended our analysis to 711 species and found that 544 contain the Nif core. A partial Nif core set was observed in eight species in this study. Finally, we cataloged 662 species with Nif core, of which 52 were novel. Our analysis generated 10,076 Nif proteins from these species and revealed some Nif core duplications. Additionally, we determined the optimal cluster value (k  = 10) for analyzing diazotrophic diversity. Combining synteny and phylogenetic analyses revealed distinct syntenies in the nif gene composition across ten groups. Conclusions This study advances our understanding of the distribution of nif genes, aiding in the prediction and classification of N₂-fixing organisms. Furthermore, we present a comprehensive overview of the diversity, distribution, and evolutionary relationships among diazotrophic organisms associated with the Nif core. The analysis revealed the phylogenetic and functional organization of different groups, identifying synteny patterns and new nif gene arrangements across various bacterial and archaeal species.The identified groups serve as a valuable framework for further exploration of the molecular mechanisms underlying biological nitrogen fixation and its evolutionary significance across different bacterial lineages.