HISTONE DEACETYLASE 15 and MOS4-associated complex subunits 3A/3B coregulate intron retention of ABA-responsive genes.

Histone deacetylases (HDAs) play an important role in transcriptional regulation of multiple biological processes. In this study, we investigated the function of HDA15 in abscisic acid (ABA) responses. We used immunopurification coupled with mass spectrometry-based proteomics to identify proteins interacting with HDA15 in Arabidopsis (Arabidopsis thaliana). HDA15 interacted with the core subunits of the MOS4-associated complex (MAC), MAC3A and MAC3B, with interaction between HDA15 and MAC3B enhanced by ABA. hda15 and mac3a/mac3b mutants were ABA-insensitive during seed germination and hyposensitive to salinity. RNA sequencing analysis demonstrated that HDA15 and MAC3A/MAC3B co-regulate ABA-responsive intron retention (IR). Furthermore, HDA15 reduced the histone acetylation level of genomic regions near ABA-responsive IR sites and the association of MAC3B with ABA-responsive pre-mRNA was dependent on HDA15. Our results indicate that HDA15 is involved in ABA responses by interacting with MAC3A/MAC3B to mediate splicing of introns.

SWI3B and HDA6 interact and are required for transposon silencing in Arabidopsis.

Although the interplay of covalent histone acetylation/deacetylation and ATP-dependent chromatin remodelling is crucial for the regulation of chromatin structure and gene expression in eukaryotes, the underlying molecular mechanism in plants remains largely unclear. Here we show a direct interaction between Arabidopsis SWI3B, an essential subunit of the SWI/SNF chromatin-remodelling complex, and the RPD3/HDA1-type histone deacetylase HDA6 both in vitro and in vivo. Furthermore, SWI3B and HDA6 co-repress the transcription of a subset of transposons. Both SWI3B and HDA6 maintain transposon silencing by decreasing histone H3 lysine 9 acetylation, but increasing histone H3 lysine 9 di-methylation, DNA methylation and nucleosome occupancy. Our findings reveal that SWI3B and HDA6 may act in the same co-repressor complex to maintain transposon silencing in Arabidopsis.

Global impacts of chromosomal imbalance on gene expression in Arabidopsis and other taxa.

Changes in dosage of part of the genome (aneuploidy) have long been known to produce much more severe phenotypic consequences than changes in the number of whole genomes (ploidy). To examine the basis of these differences, global gene expression in mature leaf tissue for all five trisomies and in diploids, triploids, and tetraploids of Arabidopsis thaliana was studied. The trisomies displayed a greater spread of expression modulation than the ploidy series. In general, expression of genes on the varied chromosome ranged from compensation to dosage effect, whereas genes from the remainder of the genome ranged from no effect to reduced expression approaching the inverse level of chromosomal imbalance (2/3). Genome-wide DNA methylation was examined in each genotype and found to shift most prominently with trisomy 4 but otherwise exhibited little change, indicating that genetic imbalance is generally mechanistically unrelated to DNA methylation. Independent analysis of gene functional classes demonstrated that ribosomal, proteasomal, and gene body methylated genes were less modulated compared with all classes of genes, whereas transcription factors, signal transduction components, and organelle-targeted protein genes were more tightly inversely affected. Comparing transcription factors and their targets in the trisomies and in expression networks revealed considerable discordance, illustrating that altered regulatory stoichiometry is a major contributor to genetic imbalance. Reanalysis of published data on gene expression in disomic yeast and trisomic mouse cells detected similar stoichiometric effects across broad phylogenetic taxa, and indicated that these effects reflect normal gene regulatory processes.

Epigenomic regulation of OTU5 in Arabidopsis thaliana.

Epigenetic regulation by DNA methylation and histone marks is crucial to plant development. In Arabidopsis, the otu5 mutant exhibited altered root phenotypes resembling those of phosphate-deficient plants. In low phosphate (Pi) conditions, altered H3K4 and H3K27 trimethylation were associated with the expression of Pi homeostasis-related genes. However, the genetic effect of OTU5 on the epigenomes was left unexplored. We assessed genome-wide DNA methylation, gene expression and histone modifications of roots from both Col-0 and otu5 mutants. We found that OTU5 altered DNA methylation profile with a context-specific effect through targeting local genomic regions. Our analysis showed that in otu5 the abundance of H3K4me3 was clearly associated with the changes of DNA methylation, leading to the transcriptional difference from wildtype. We concluded that OTU5 induced cross-talks among epigenomes that altogether impacted the regulation of approximately 7060 genes. Of which 186 genes associated with root development were likely to be epigenetically regulated.

MethGET: web-based bioinformatics software for correlating genome-wide DNA methylation and gene expression.

BACKGROUND: DNA methylation is a major epigenetic modification involved in regulating gene expression. The effects of DNA methylation on gene expression differ by genomic location and vary across kingdoms, species and environmental conditions. To identify the functional regulatory roles of DNA methylation, the correlation between DNA methylation changes and alterations in gene expression is crucial. With the advance of next-generation sequencing, genome-wide methylation and gene expression profiling have become feasible. Current bioinformatics tools for investigating such correlation are designed to the assessment of DNA methylation at CG sites. The correlation of non-CG methylation and gene expression is very limited. Some bioinformatics databases allow correlation analysis, but they are limited to specific genomes such as that of humans and do not allow user-provided data. RESULTS: Here, we developed a bioinformatics web tool, MethGET (Methylation and Gene Expression Teller), that is specialized to analyse the association between genome-wide DNA methylation and gene expression. MethGET is the first web tool to which users can supply their own data from any genome. It is also the tool that correlates gene expression with CG, CHG, and CHH methylation based on whole-genome bisulfite sequencing data. MethGET not only reveals the correlation within an individual sample (single-methylome) but also performs comparisons between two groups of samples (multiple-methylomes). For single-methylome analyses, MethGET provides Pearson correlations and ordinal associations to investigate the relationship between DNA methylation and gene expression. It also groups genes with different gene expression levels to view the methylation distribution at specific genomic regions. Multiple-methylome analyses include comparative analyses and heatmap representations between two groups. These functions enable the detailed investigation of the role of DNA methylation in gene regulation. Additionally, we applied MethGET to rice regeneration data and discovered that CHH methylation in the gene body region may play a role in the tissue culture process, which demonstrates the capability of MethGET for use in epigenomic research. CONCLUSIONS: MethGET is a Python software that correlates DNA methylation and gene expression. Its web interface is publicly available at https://paoyang.ipmb.sinica.edu.tw/Software.html. The stand-alone version and source codes are available on GitHub at https://github.com/Jason-Teng/MethGET.

Detecting and prioritizing biosynthetic gene clusters for bioactive compounds in bacteria and fungi.

Secondary metabolites (SM) produced by fungi and bacteria have long been of exceptional interest owing to their unique biomedical ramifications. The traditional discovery of new natural products that was mainly driven by bioactivity screening has now experienced a fresh new approach in the form of genome mining. Several bioinformatics tools have been continuously developed to detect potential biosynthetic gene clusters (BGCs) that are responsible for the production of SM. Although the principles underlying the computation of these tools have been discussed, the biological background is left underrated and ambiguous. In this review, we emphasize the biological hypotheses in BGC formation driven from the observations across genomes in bacteria and fungi, and provide a comprehensive list of updated algorithms/tools exclusively for BGC detection. Our review points to a direction that the biological hypotheses should be systematically incorporated into the BGC prediction and assist the prioritization of candidate BGC.

Deubiquitinating Enzyme OTU5 Contributes to DNA Methylation Patterns and Is Critical for Phosphate Nutrition Signals.

Phosphate (Pi) starvation induces a suite of adaptive responses aimed at recalibrating cellular Pi homeostasis. Plants harboring a mutation in OVARIAN TUMOR DOMAIN-CONTAINING DEUBIQUITINATING ENZYME5 (OTU5) showed altered DNA methylation of root hair-related genes and altered Pi-responsive root traits. Unlike the wild type, homozygous otu5 mutants did not respond to Pi starvation by increased lateral root formation and increased root hair length but formed very short root hairs when grown on low-Pi media. Under Pi-replete conditions, otu5 plants developed more root hairs than the wild type due to attenuated primary root growth, a phenotype that resembled that of Pi-deficient plants. Growth of plants on low-Pi media altered both H3K4 and H3K27 trimethylation levels at the transcriptional start site of a subset of genes encoding key players in Pi homeostasis, which was correlated with mRNA abundance changes of these genes. Pi starvation had a minor impact on DNA methylation. Differentially methylated regions were enriched in transposable elements, suggesting that DNA methylation associated with low Pi supply is required for maintaining genome integrity. It is concluded that DNA methylation and histone methylation constitute critical, interdependent regulatory components that orchestrate the activity of a subset of Pi-responsive genes.

MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data.

BACKGROUND: DNA methylation is a major epigenetic modification regulating several biological processes. A standard approach to measure DNA methylation is bisulfite sequencing (BS-Seq). BS-Seq couples bisulfite conversion of DNA with next-generation sequencing to profile genome-wide DNA methylation at single base resolution. The analysis of BS-Seq data involves the use of customized aligners for mapping bisulfite converted reads and the bioinformatic pipelines for downstream data analysis. RESULTS: Here we developed MethGo, a software tool designed for the analysis of data from whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS). MethGo provides both genomic and epigenomic analyses including: 1) coverage distribution of each cytosine; 2) global cytosine methylation level; 3) cytosine methylation level distribution; 4) cytosine methylation level of genomic elements; 5) chromosome-wide cytosine methylation level distribution; 6) Gene-centric cytosine methylation level; 7) cytosine methylation levels at transcription factor binding sites (TFBSs); 8) single nucleotide polymorphism (SNP) calling, and 9) copy number variation (CNV) calling. CONCLUSIONS: MethGo is a simple and effective tool for the analysis of BS-Seq data including both WGBS and RRBS. It contains 9 analyses in 5 major modules to profile (epi)genome. It profiles genome-wide DNA methylation in global and in gene level scale. It can also analyze the methylation pattern around the transcription factor binding sites, and assess genetic variations such as SNPs and CNVs. MethGo is coded in Python and is publically available at http://paoyangchen-laboratory.github.io/methgo/.

Examining the condition-specific antisense transcription in S. cerevisiae and S. paradoxus.

BACKGROUND: Recent studies have demonstrated that antisense transcription is pervasive in budding yeasts and is conserved between Saccharomyces cerevisiae and S. paradoxus. While studies have examined antisense transcripts of S. cerevisiae for inverse expression in stationary phase and stress conditions, there is a lack of comprehensive analysis of the conditional specific evolutionary characteristics of antisense transcription between yeasts. Here we attempt to decipher the evolutionary relationship of antisense transcription of S. cerevisiae and S. paradoxus cultured in mid log, early stationary phase, and heat shock conditions. RESULTS: Massively parallel sequencing of sequence strand-specific cDNA library was performed from RNA isolated from S. cerevisiae and S. paradoxus cells at mid log, stationary phase and heat shock conditions. We performed this analysis using a stringent set of sense ORF transcripts and non-coding antisense transcripts that were expressed in all the three conditions, as well as in both species. We found the divergence of the condition-specific anti-sense transcription levels is higher than that in condition-specific sense transcription levels, suggesting that antisense transcription played a potential role in adapting to different conditions. Furthermore, 43% of sense-antisense pairs demonstrated inverse expression in either stationary phase or heat shock conditions relative to the mid log conditions. In addition, a large part of sense-antisense pairs (67%), which demonstrated inverse expression, were highly conserved between the two species. Our results were also concordant with known functional analyses from previous studies and with the evidence from mechanistic experiments of role of individual genes. CONCLUSIONS: By performing a genome-scale computational analysis, we have tried to evaluate the role of antisense transcription in mediating sense transcription under different environmental conditions across and in two related yeast species. Our findings suggest that antisense regulation could control expression of the corresponding sense transcript via inverse expression under a range of different circumstances.

Methylome Imputation by Methylation Patterns.

DNA methylation is studied extensively for its relations with several biological processes such as transcriptional regulation. While methylation levels are usually estimated per cytosine or genomic region, additional information on methylation heterogeneity can be obtained when considering stretches of successive cytosines on the same reads; however, the majority of methylomes suffer from low coverage of genomic regions with sequencing depths enough for accurate estimation of methylation heterogeneity using existing methods. Here we describe a probabilistic-based imputation method that makes use of methylation information from neighboring sites to recover partially observed methylation patterns. Our method and software are proven to be faster and more accurate among all evaluated. Ultimately, our method allows for a more streamlined monitoring of epigenetic changes within cellular populations and their putative role in disease.

MethylC-analyzer: a comprehensive downstream pipeline for the analysis of genome-wide DNA methylation.

DNA methylation is a crucial epigenetic modification involved in multiple biological processes and diseases. Current approaches for measuring genome-wide DNA methylation via bisulfite sequencing (BS-seq) include whole-genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS), and enzymatic methyl-seq (EM-seq). The computational analysis tools available for BS-seq data include customized aligners for mapping bisulfite-converted reads and computational pipelines for downstream data analysis. Current post-alignment methylation tools are specialized for the interpretation of CG methylation, which is known to dominate mammalian genomes, however, non-CG methylation (CHG and CHH, where H refers to A, C, or T) is commonly observed in plants and fungi and is closely associated with gene regulation, transposon silencing, and plant development. Thus, we have developed a MethylC-analyzer to analyze and visualize post-alignment WGBS, RRBS, and EM-seq data focusing on CG. The tool is able to also analyze non-CG sites to enhance deciphering genomes of plants and fungi. By processing aligned data and gene location files, MethylC-analyzer generates a genome-wide view of methylation levels and methylation in user-specified genomic regions. The meta-plot, for example, allows the investigation of DNA methylation within specific genomic elements. Moreover, our tool identifies differentially methylated regions (DMRs) and investigates the enrichment of genomic features associated with variable methylation. MethylC-analyzer functionality is not limited to specific genomes, and we demonstrated its performance on both plant and human BS-seq data. MethylC-analyzer is a Python- and R-based program designed to perform comprehensive downstream analyses of methylation data, providing an intuitive analysis platform for scientists unfamiliar with DNA methylation analysis. It is available as either a standalone version for command-line uses or a graphical user interface (GUI) and is publicly accessible at https://github.com/RitataLU/MethylC-analyzer .

Whole-genome DNA methylome analysis of different developmental stages of the entomopathogenic fungus Beauveria bassiana NCHU-157 by nanopore sequencing.

The entomopathogenic fungus (EPF), Beauveria bassiana, is an important and commonly used EPF for microbial control. However, the role of DNA methylation has not been thoroughly studied. Therefore, the whole genomic DNA methylome of one promising EPF isolate, B. bassiana NCHU-157 (Bb-NCHU-157), was investigated by Oxford Nanopore Technologies (ONT). First, the whole genome of Bb-NCHU-157 was sequenced by next-generation sequencing (NGS) and ONT. The genome of Bb-NCHU-157 contains 16 contigs with 34.19 Mb and 50% GC content, which are composed of 10,848 putative protein-coding genes. Two putative DNA methyltransferases (DNMTs) were found, including Dim-2 and C-5 cytosine-specific DNA methylases. Both DNMTs showed higher expression levels in the mycelium stage than in the conidia stage, indicating that development of DNA methylation in Bb-NCHU-157 might occur in the mycelium stage. The global methylation level of the mycelium stage (5 mC = 4.56%, CG = 3.33%, CHG = 0.74%, CHH = 0.49%) was higher than that of the conidial stage (5 mC = 2.99%, CG = 1.99%, CHG = 0.63%, CHH = 0.37%) in both the gene and transposable element (TE) regions. Furthermore, the TE regions showed higher methylation frequencies than the gene regions, especially for CHH site methylation, suggesting regulation of genomic stabilization during mycelium development. In the gene regions, high methylation frequencies were found around the transcription start site (TSS) and transcription end site (TES). Moreover, CG and CHG methylation mainly occur in the promoter and intergenic regions, while CHH methylation occurs in the TE region. Among the methylated regions, 371, 661, and 756 differentially DNA methylated regions (DMRs) were hypermethylated in the mycelium in CG, CHG, and CHH, while only 13 and 7 DMRs were hypomethylated in the mycelium in CHG, and CHH, respectively. Genes located in the DMR shared the GO terms, DNA binding (GO: 0003677), and sequence-specific DNA binding (GO: 0043565) for hypermethylation in the mycelium, suggesting that methylation might regulate gene expression from the initial process. Evaluation of the DNA methylome in Bb-NCHU-157 by ONT provided new insight into this field. These data will be further validated, and epigenetic regulation during the development of B. bassiana will be explored.

BSImp: Imputing Partially Observed Methylation Patterns for Evaluating Methylation Heterogeneity.

DNA methylation is one of the most studied epigenetic modifications that has applications ranging from transcriptional regulation to aging, and can be assessed by bisulfite sequencing (BS-seq) or enzymatic methyl sequencing (EM-seq) at single base-pair resolution. The permutations of methylation statuses given by aligned reads reflect the methylation patterns of individual cells. These patterns at specific genomic locations are sought to be indicative of cellular heterogeneity within a cellular population, which are predictive of developments and diseases; therefore, methylation heterogeneity has potentials in early detection of these changes. Computational methods have been developed to assess methylation heterogeneity using methylation patterns formed by four consecutive CpGs, but the nature of shotgun sequencing often give partially observed patterns, which makes very limited data available for downstream analysis. While many programs are developed to impute genome-wide methylation levels, currently there is only one method developed for recovering partially observed methylation patterns; however, the program needs lots of data to train and cannot be used directly; therefore, we developed a probabilistic-based imputation method that uses information from neighbouring sites to recover partially observed methylation patterns speedily. It is demonstrated to allow for the evaluation of methylation heterogeneity at 15% more regions genome-wide with high accuracy for data with moderate depth. To make it more user-friendly we also provide a computational pipeline for genome-screening, which can be used in both evaluating methylation levels and profiling methylation patterns genomewide for all cytosine contexts, which is the first of its kind. Our method allows for accurate estimation of methylation levels and makes evaluating methylation heterogeneity available for much more data with reasonable coverage, which has important implications in using methylation heterogeneity for monitoring changes within the cellular populations that were impossible to detect for the assessment of development and diseases.

EED is required for mouse primordial germ cell differentiation in the embryonic gonad.

Development of primordial germ cells (PGCs) is required for reproduction. During PGC development in mammals, major epigenetic remodeling occurs, which is hypothesized to establish an epigenetic landscape for sex-specific germ cell differentiation and gametogenesis. In order to address the role of embryonic ectoderm development (EED) and histone 3 lysine 27 trimethylation (H3K27me3) in this process, we created an EED conditional knockout mouse and show that EED is essential for regulating the timing of sex-specific PGC differentiation in both ovaries and testes, as well as X chromosome dosage decompensation in testes. Integrating chromatin and whole genome bisulfite sequencing of epiblast and PGCs, we identified a poised repressive signature of H3K27me3/DNA methylation that we propose is established in the epiblast where EED and DNMT1 interact. Thus, EED joins DNMT1 in regulating the timing of sex-specific PGC differentiation during the critical window when the gonadal niche cells specialize into an ovary or testis.

Aberrant overexpression of HOTAIR inhibits abdominal adipogenesis through remodelling of genome-wide DNA methylation and transcription.

OBJECTIVE: Abdominal adiposity is strongly associated with diabetic and cardiovascular comorbidities. The long noncoding RNA HOTAIR (HOX Transcript Antisense Intergenic RNA) is an important epigenetic regulator with fat depot-specific expression. Its functional roles and epigenetic regulation in abdominal adipogenesis remain uncertain. METHODS: We collected different fat depots from healthy, severely obese, and uraemic subjects to measure fat-depot specific gene expression and quantify regional adiposity via dual-energy X-ray absorptiometry (DXA). HOTAIR was overexpressed to evaluate its functional roles. Reduced representation bisulfite sequencing (RRBS), RNA-sequencing, real-time qPCR and RNA/chromatin immunoprecipitation were performed to analyse HOTAIR-mediated epigenetic regulation. RESULTS: A negative correlation between adipose tissue HOTAIR expression (arm or abdominal subcutaneous fat depots) and regional adiposity under the status of severe obesity or uraemia was observed. HOTAIR overexpression using human immortalized abdominal preadipocytes further revealed its anti-adipogenic effects. Integrative analysis of genome-wide DNA methylation by reduced representation bisulfite sequencing (RRBS) and gene expression was performed. Overall, the differentially methylated genes were functionally enriched for nervous system development, suggesting that HOTAIR may be epigenetically associated with cell lineage commitment. We specifically found that HOTAIR-mediated genes showed strong changes in both DNA methylation and gene expression during abdominal adipogenesis. We observed that two HOTAIR-repressed genes, SLITRK4 and PITPNC1, present an obesity-driven fat-depot specific expression pattern that is positively correlated with the central body fat distribution. CONCLUSIONS: Our study indicated that HOTAIR is a key regulator of abdominal adipogenesis via intricate DNA methylation and is likely to be associated with the transcriptional regulation of genes involved in nervous system development and lipid metabolism, such as SLITRK4 and PITPNC1.

Transcriptome of Nosema ceranae and Upregulated Microsporidia Genes during Its Infection of Western Honey Bee (Apis mellifera).

Nosema ceranae is one of the fungal parasites of Apis mellifera. It causes physical and behavioral effects in honey bees. However, only a few studies have reported on gene expression profiling during A. mellifera infection. In this study, the transcriptome profile of mature spores at each time point of infection (5, 10, and 20 days post-infection, d.p.i.) were investigated. Based on the transcriptome and expression profile analysis, a total of 878, 952, and 981 differentially expressed genes (DEGs) (fold change ≥ 2 or ≤ -2) were identified in N. ceranae spores (NcSp) at 5 d.p.i., 10 d.p.i., and 20 d.p.i., respectively. Moreover, 70 upregulated genes and 340 downregulated genes among common DEGs (so-called common DEGs) and 166 stage-specific genes at each stage of infection were identified. The Gene Ontology (GO) analysis indicated that the DEGs and corresponding common DEGs are involved in the functions of cytosol (GO:0005829), cytoplasm (GO:0005737), and ATP binding (GO:0005524). Furthermore, the pathway analysis found that the DEGs and common DEGs are involved in metabolism, environmental information processing, and organismal systems. Four upregulated common DEGs with higher fold-change values, highly associated with spore proteins and transcription factors, were selected for validation. In addition, the stage-specific genes are highly involved in the mechanism of pre-mRNA splicing according to GO enrichment analysis; thus, three of them showed high expression at each d.p.i. and were also subjected to validation. The relative gene expression levels showed a similar tendency as the transcriptome predictions at different d.p.i., revealing that the gene expression of N. ceranae during infection may be related to the mechanism of gene transcription, protein synthesis, and structural proteins. Our data suggest that the gene expression profiling of N. ceranae at the transcriptomic level could be a reference for the monitoring of nosemosis at the genetic level.

The Transporter Classification Database: recent advances.

The Transporter Classification Database (TCDB), freely accessible at http://www.tcdb.org, is a relational database containing sequence, structural, functional and evolutionary information about transport systems from a variety of living organisms, based on the International Union of Biochemistry and Molecular Biology-approved transporter classification (TC) system. It is a curated repository for factual information compiled largely from published references. It uses a functional/phylogenetic system of classification, and currently encompasses about 5000 representative transporters and putative transporters in more than 500 families. We here describe novel software designed to support and extend the usefulness of TCDB. Our recent efforts render it more user friendly, incorporate machine learning to input novel data in a semiautomatic fashion, and allow analyses that are more accurate and less time consuming. The availability of these tools has resulted in recognition of distant phylogenetic relationships and tremendous expansion of the information available to TCDB users.

Transcriptome-level assessment of the impact of deformed wing virus on honey bee larvae.

Deformed wing virus (DWV) prevalence is high in honey bee (Apis mellifera) populations. The virus infects honey bees through vertical and horizontal transmission, leading to behavioural changes, wing deformity, and early mortality. To better understand the impacts of viral infection in the larval stage of honey bees, artificially reared honey bee larvae were infected with DWV (1.55 × 1010 copies/per larva). No significant mortality occurred in infected honey bee larvae, while the survival rates decreased significantly at the pupal stage. Examination of DWV replication revealed that viral replication began at 2 days post inoculation (d.p.i.), increased dramatically to 4 d.p.i., and then continuously increased in the pupal stage. To better understand the impact of DWV on the larval stage, DWV-infected and control groups were subjected to transcriptomic analysis at 4 d.p.i. Two hundred fifty-five differentially expressed genes (DEGs) (fold change ≥ 2 or ≤ -2) were identified. Of these DEGs, 168 genes were downregulated, and 87 genes were upregulated. Gene Ontology (GO) analysis showed that 141 DEGs (55.3%) were categorized into molecular functions, cellular components and biological processes. One hundred eleven genes (38 upregulated and 73 downregulated) were annotated by KO (KEGG Orthology) pathway mapping and involved metabolic pathways, biosynthesis of secondary metabolites and glycine, serine and threonine metabolism pathways. Validation of DEGs was performed, and the related gene expression levels showed a similar tendency to the DEG predictions at 4 d.p.i.; cell wall integrity and stress response component 1 (wsc1), cuticular protein and myo-inositol 2-dehydrogenase (iolG) were significantly upregulated, and small conductance calcium-activated potassium channel protein (SK) was significantly downregulated at 4 d.p.i. Related gene expression levels at different d.p.i. revealed that these DEGs were significantly regulated from the larval stage to the pupal stage, indicating the potential impacts of gene expression levels from the larval to the pupal stages. Taken together, DWV infection in the honey bee larval stage potentially influences the gene expression levels from larvae to pupae and reduces the survival rate of the pupal stage. This information emphasizes the consequences of DWV prevalence in honey bee larvae for apiculture.

Precise excision of IS5 from the intergenic region between the fucPIK and the fucAO operons and mutational control of fucPIK operon expression in Escherichia coli.

Excision of transposable genetic elements from host DNA occurs at low frequencies and is usually imprecise. A common insertion sequence element in Escherichia coli, IS5, has been shown to provide various benefits to its host by inserting into specific sites. Precise excision of this element had not previously been demonstrated. Using a unique system, the fucose (fuc) regulon, in which IS5 insertion and excision result in two distinct selectable phenotypes, we have demonstrated that IS5 can precisely excise from its insertion site, restoring the wild-type phenotype. In addition to precise excision, several "suppressor" insertion, deletion, and point mutations restore the wild-type Fuc(+) phenotype to various degrees without IS5 excision. The possible bases for these observations are discussed.

Diversity of Fungal DNA Methyltransferases and Their Association With DNA Methylation Patterns.

DNA methyltransferases (DNMTs) are a group of proteins that catalyze DNA methylation by transferring a methyl group to DNA. The genetic variation in DNMTs results in differential DNA methylation patterns associated with various biological processes. In fungal species, DNMTs and their DNA methylation profiles were found to be very diverse and have gained many research interests. We reviewed fungal DNMTs in terms of their biological functions, protein domain structures, and their associated epigenetic regulations compared to those known in plant and animal systems. In addition, we summarized recent reports on potential RNA-directed DNA methylation (RdDM) related to DNMT5 in fungi. We surveyed up to 40 fungal species with published genome-wide DNA methylation profiles (methylomes) and presented the associations between the specific patterns of fungal DNA methylation and their DNMTs based on a phylogenetic tree of protein domain structures. For example, the main DNMTs in Basidiomycota, DNMT1 with RFD domain + DNMT5, contributing to CG methylation preference, were distinct from RID + Dim-2 in Ascomycota, resulting in a non-CG methylation preference. Lastly, we revealed that the dynamic methylation involved in fungal life stage changes was particularly low in mycelium and DNA methylation was preferentially located in transposable elements (TEs). This review comprehensively discussed fungal DNMTs and methylomes and their connection with fungal development and taxonomy to present the diverse usages of DNA methylation in fungal genomes.