Experimental modeling of the microbiota of a biocontrol population of the predatory mite Neoseiulus californicus bred on the spider mite Tetranychus urticae was carried out to both eliminate bacterial pathogens and increase the viability of the mite line. We produced an isofemale line of N. californicus BioDefence2 and a derived line with an optimized microbiota BioDefence3. The microbiota was optimized by the sequential treatment of the mite line with tetracycline to eliminate pathogenic bacteria, followed by treatment with the probiotic bacterium Bacillus subtilis to restore the viability of the mite line. The microbiotas of the BioDefence2 and BioDefence3 mite strains were compared using metagenomic 16S rRNA gene data. The metagenomic data were extracted from the hologenomes of the mite strains obtained through Oxford Nanopore long read sequencing. The bacterial species comprising the microbiotas of the original and optimized mite strains were identified. The saprophytic soil bacteria, Stenotrophomonas maltophilia, Acinetobacter johnsonii, and Enterobacter hormaechei, also known as opportunistic human pathogens, form the basis of the N. californicus microbiota. The optimization of the microbiota eliminates the intracellular bacterium Renibacterium salmoninarum, a well-known fish pathogen and the toxin-producing bacterium Clostridium botulinum. The effect of optimization of the mite microbiota on the viability of the biocontrol population of N. californicus is discussed. The results obtained may provide a basis for improving the technology of rearing N. californicus.

Genes of the small nucleolar RNA host gene (SNHG) family may participate in oncogenesis through the regulatory functions of encoded long non-coding RNAs (lncRNAs) and by influencing formation of small nucleolar RNAs and ribosome biogenesis. The aim of this work was to evaluate changes in the methylation levels and extent of co-methylation of the SNHG family lncRNA genes (SNHG1, GAS5/SNHG2, SNHG6, SNHG12, SNHG17) in clinical samples of ovarian cancer (OC) as an indication for the similarity of their roles in oncogenesis. Analysis of a representative set of 122 OC samples by quantitative methylation-specific PCR showed a statistically significant (p < 0.01-0.0001) increase in the methylation level of all five studied lncRNA genes. There was also a correlation between the increased methylation levels of GAS5, SNHG6, and SNHG12 and OC progression (clinical stage, tumor size, and metastasis), indicating possible functional significance of hypermethylation of these genes. For four genes (SNHG1, GAS5, SNHG6, and SNHG12), a statistically significant pairwise positive correlation of methylation levels (co-methylation) was observed (rs > 0.35; p ≤ 0.001), which was in agreement with the GEPIA 2.0 data (426 OC samples) showing co-expression of these genes (rs > 0.5; p < 0.001). The correlation between the expression levels of GAS5 and SNHG6 was confirmed by RT-qPCR (rs = 0.46; p = 0.007). Bioinformatics analysis predicted miRNAs common for the SNHG1, GAS5, SNHG6, and SNHG12 lncRNA and potentially capable of interacting with one or more of these lncRNAs via competing endogenous RNA mechanism, as well as mRNAs, whose expression might be affected by the studied lncRNAs. We also investigated a possible involvement of genes for these mRNAs in oncogenesis-related processes, such as RNA processing and splicing and epithelial–mesenchymal transition. As a result of this work, four SNHG family lncRNAs with coregulation and joint putative biological functions in the pathogenesis of OC were identified.

Recently, more and more data have been accumulating indicating the role of long noncoding RNAs (lncRNAs) in the regulation of biological processes in cells, as well as in the mechanisms of cancer development and progression. Aberrant methylation of promoter regions of both protein genes and lncRNA genes can disrupt their expression and functional activity. Using bioinformatics databases, six lncRNA genes (GAS5, HOTAIR, LINC00472, LINC00886, SNHG17, and TUG1) with CpG islands differentially expressed and presumably hypermethylated in tumors of patients with ovarian cancer (OC) were selected. Using a sample of 93 OC samples, real-time methylation specific PCR showed a statistically significant (p < 0.05) increase in the level of methylation in tumors. Moreover, for the genes LINC00472, LINC00886, SNHG17, and TUG1, hypermethylation in OC was detected for the first time. Five genes (except SNHG17) showed a further increase in methylation levels at a more advanced stage, and four genes (except SNHG17 and LINC00886) showed a significant association with metastasis. Using real-time RT-PCR, differential changes in the expression level of the GAS5, HOTAIR, SNHG17, and TUG1 genes and a significant correlation of methylation with expression for the GAS5 gene were shown. Thus, hypermethylation associated with the progression and/or development of OC was detected for six lncRNA genes, which is important for elucidating the epigenetic processes involved in the pathogenesis of OC and can be used as new biomarkers of OC.

Our work aimed to evaluate and differentiate the role of ten lncRNA genes (GAS5, HAND2-AS1, KCNK15-AS1, MAGI2-AS3, MEG3, SEMA3B-AS1, SNHG6, SSTR5-AS1, ZEB1-AS1, and ZNF667-AS1) in the development and progression of epithelial ovarian cancer (EOC). A representative set of clinical samples was used: 140 primary tumors from patients without and with metastases and 59 peritoneal metastases. Using MS-qPCR, we demonstrated an increase in methylation levels of all ten lncRNA genes in tumors compared to normal tissues (p < 0.001). Using RT-qPCR, we showed downregulation and an inverse relationship between methylation and expression levels for ten lncRNAs (rs < -0.5). We further identified lncRNA genes that were specifically hypermethylated in tumors from patients with metastases to lymph nodes (HAND2-AS1), peritoneum (KCNK15-AS1, MEG3, and SEMA3B-AS1), and greater omentum (MEG3, SEMA3B-AS1, and ZNF667-AS1). The same four lncRNA genes involved in peritoneal spread were associated with clinical stage and tumor extent (p < 0.001). Interestingly, we found a reversion from increase to decrease in the hypermethylation level of five metastasis-related lncRNA genes (MEG3, SEMA3B-AS1, SSTR5-AS1, ZEB1-AS1, and ZNF667-AS1) in 59 peritoneal metastases. This reversion may be associated with partial epithelial-mesenchymal transition (EMT) in metastatic cells, as indicated by a decrease in the level of the EMT marker, CDH1 mRNA (p < 0.01). Furthermore, novel mRNA targets and regulated miRNAs were predicted for a number of the studied lncRNAs using the NCBI GEO datasets and analyzed by RT-qPCR and transfection of SKOV3 and OVCAR3 cells. In addition, hypermethylation of SEMA3B-AS1, SSTR5-AS1, and ZNF667-AS1 genes was proposed as a marker for overall survival in patients with EOC.

Long-read transcriptome sequencing provides us with a convenient tool for the thorough study of biological processes such as neuronal plasticity. Here, we aimed to perform transcriptional profiling of rat hippocampal primary neuron cultures after stimulation with picrotoxin (PTX) to further understand molecular mechanisms of neuronal activation. To overcome the limitations of short-read RNA-Seq approaches, we performed an Oxford Nanopore Technologies MinION-based long-read sequencing and transcriptome assembly of rat primary hippocampal culture mRNA at three time points after the PTX activation. We used a specific approach to exclude uncapped mRNAs during sample preparation. Overall, we found 23,652 novel transcripts in comparison to reference annotations, out of which ~6000 were entirely novel and mostly transposon-derived loci. Analysis of differentially expressed genes (DEG) showed that 3046 genes were differentially expressed, of which 2037 were upregulated and 1009 were downregulated at 30 min after the PTX application, with only 446 and 13 genes differentially expressed at 1 h and 5 h time points, respectively. Most notably, multiple genes encoding ribosomal proteins, with a high basal expression level, were downregulated after 30 min incubation with PTX; we suggest that this indicates redistribution of transcriptional resources towards activity-induced genes. Novel loci and isoforms observed in this study may help us further understand the functional mRNA repertoire in neuronal plasticity processes. Together with other NGS techniques, differential gene expression analysis of sequencing data obtained using MinION platform might provide a simple method to optimize further study of neuronal plasticity.

Ovarian cancer (OC) develops asymptomatically and escapes diagnosis until advanced stages, the feature contributing to a higher mortality rate. New prospects of OC diagnosis and treatment have been opened in studies of the gene regulation mechanisms that involve long noncoding RNAs (lncRNAs) and identification of the lncRNA genes that are inhibited via methylation of the promoter region. A set of 122 samples of primary OC tumors was examined by methylation specific real-time PCR to assess the methylation level of the lncRNA genes PLUT, SNHG1, SNHG6, SNHG12, and TINCR. A significant increase in their methylation levels was observed in OC (p < 0.001 by the nonparametric Mann-Whitney test). The methylation levels of SNHG6, SNHG12, and TINCR were found to correlate significantly (p < 0.05) with the stage of the tumor process, the histological grade, and metastasis. Downregulation of SNHG6, SNHG12, and TINCR was detected by real-time RT-qPCR, and a significant correlation between methylation and expression was demonstrated for SNHG6 and TINCR (r(s) <= -0.5, p < 0.001). The respective lncRNA genes were assumed to provide potential epigenetic markers of OC.

Neural crest cells are highly multipotent stem cells, but it remains unclear how their fate restriction to specific fates occurs. The direct fate restriction model hypothesises that migrating cells maintain full multipotency, whilst progressive fate restriction envisages fully multipotent cells transitioning to partially-restricted intermediates before committing to individual fates. Using zebrafish pigment cell development as a model, we show applying NanoString hybridization single cell transcriptional profiling and RNAscope in situ hybridization that neural crest cells retain broad multipotency throughout migration and even in post-migratory cells in vivo, with no evidence for partially-restricted intermediates. We find that leukocyte tyrosine kinase early expression marks a multipotent stage, with signalling driving iridophore differentiation through repression of fate-specific transcription factors for other fates. We reconcile the direct and progressive fate restriction models by proposing that pigment cell development occurs directly, but dynamically, from a highly multipotent state, consistent with our recently-proposed Cyclical Fate Restriction model.

Neoseiulus californicus is widely used as an effective biocontrol agent of spider mites. In this study, the complete mitochondrial genome sequence of N. californicus was determined using Oxford Nanopore sequencing technology. The complete mitochondrial genome is 21,318 bp in length and contains 13 protein-coding genes, 2 ribosomal rRNA genes and 22 transfer RNA genes. Its AT content is 78.4%. All start and stop codons of the protein-coding genes are canonical, except for the missing stop codon for the cox3 gene. The control region was polymorphic in length between the sublines of N. californicus due to variable number of direct repeats. The mitogenome presented in this paper contributes to the study of the genetic structure of N. californicus biocontrol populations.

БИОИНФОРМАТИЧЕСКИЙ СКРИНИНГ НЕКОДИРУЮЩИХ РНК, ВОВЛЕЧЕННЫХ В ПАТОГЕНЕЗ ЭПИТЕЛИАЛЬНОГО РАКА ЯИЧНИКОВЛ.А.Урошлев., И.В.Пронина, А.М Бурденный, В.И.Логинов, Э

Neoseiulus californicus is an effective predatory mite for spider mites biocontrol. We sequenced and assembled the genomes of two isofemale lines of N. californicus: BioDefence and BioDefence2, derived from a biocontrol mite population, using the Oxford Nanopore long-read sequencing method. A total of 3507265 reads were obtained for the genome of the BioDefence line and 1769217 reads for the BioDefence2 line. Canu v.2.3 software was used for contig assembly. The genome of the BioDefence line was assembled as 419 contigs of 191.4 Mb in length, with a G+C content of 50.33%. The N50 is 13147 and the average coverage is 26.798. The annotation identified – 12253 genes, including 11607 protein-coding genes, 28 microsatellites, 9 families of small RNA genes, 2 families of LTR retrotransposons, 3 families of DNA transposons, 12 rRNA genes and 634 tRNA genes. The genome of line BioDefence2 was obtained using a similar procedure. Based on the contigs obtained, we assembled two new complete mitochondrial genomes of N. californicus from the BioDefence and BioDefence2 lines. We identified hypervariable regions of the genome within the mitochondrial control region that show inter-lineage variability. This study adds a new complete genome of N. californicus assembled at the contig level to the two other complete N. californicus genomes registered in GenBank and assembled at the contig level.

Background It is generally accepted that most evolutionary transformations at the phenotype level are associated either with rearrangements of genomic regulatory elements, which control the activity of gene networks, or with changes in the amino acid contents of proteins. Recently, evidence has accumulated that significant evolutionary transformations could also be associated with the loss/emergence of whole genes. The targeted identification of such genes is a challenging problem for both bioinformatics and evo-devo research. Results To solve this problem we propose the WINEGRET method, named after the first letters of the title. Its main idea is to search for genes that satisfy two requirements: first, the desired genes were lost/emerged at the same evolutionary stage at which the phenotypic trait of interest was lost/emerged, and second, the expression of these genes changes significantly during the development of the trait of interest in the model organism. To verify the first requirement, we do not use existing databases of orthologs, but rely purely on gene homology and local synteny by using some novel quickly computable conditions. Genes satisfying the second requirement are found by deep RNA sequencing. As a proof of principle, we used our method to find genes absent in extant amniotes (reptiles, birds, mammals) but present in anamniotes (fish and amphibians), in which these genes are involved in the regeneration of large body appendages. As a result, 57 genes were identified. For three of them, c-c motif chemokine 4 , eotaxin-like , and a previously unknown gene called here sod4 , essential roles for tail regeneration were demonstrated. Noteworthy, we established that the latter gene belongs to a novel family of Cu/Zn-superoxide dismutases lost by amniotes, SOD4. Conclusions We present a method for targeted identification of genes whose loss/emergence in evolution could be associated with the loss/emergence of a phenotypic trait of interest. In a proof-of-principle study, we identified genes absent in amniotes that participate in body appendage regeneration in anamniotes. Our method provides a wide range of opportunities for studying the relationship between the loss/emergence of phenotypic traits and the loss/emergence of specific genes in evolution.

Our work aimed to differentiate 20 aberrantly methylated miRNA genes that participate at different stages of development and metastasis of ovarian carcinoma (OvCa) using methylation-specific qPCR in a representative set of clinical samples: 102 primary tumors without and with metastases (to lymph nodes, peritoneum, or distant organs) and 30 peritoneal macroscopic metastases (PMM). Thirteen miRNA genes (MIR107, MIR124-2, MIR124-3, MIR125B-1, MIR127, MIR129-2, MIR130B, MIR132, MIR193A, MIR339, MIR34B/C, MIR9-1, and MIR9-3) were hypermethylated already at the early stages of OvCa, while hypermethylation of MIR1258, MIR137, MIR203A, and MIR375 was pronounced in metastatic tumors, and MIR148A showed high methylation levels specifically in PMM. We confirmed the significant relationship between methylation and expression levels for 11 out of 12 miRNAs analyzed by qRT-PCR. Moreover, expression levels of six miRNAs were significantly decreased in metastatic tumors in comparison with nonmetastatic ones, and downregulation of miR-203a-3p was the most significant. We revealed an inverse relationship between expression levels of miR-203a-3p and those of ZEB1 and ZEB2 genes, which are EMT drivers. We also identified three miRNA genes (MIR148A, MIR9-1, and MIR193A) that likely regulate EMT–MET reversion in the colonization of PMM. According to the Kaplan–Meier analysis, hypermethylation of several examined miRNA genes was associated with poorer overall survival of OvCa patients, and high methylation levels of MIR130B and MIR9-1 were related to the greatest relative risk of death.

Late diagnosis of ovarian cancer is one of the most important problems in its treatment. Long non-coding RNA (lncRNA) are a poorly studied, but promising type of diagnostic biomarkers. We studied the lncRNA interactome to identify biomarkers with potential significance for molecular diagnostics of ovarian cancer. By screening the TCGA database, we identified differentially expressed lncRNA CCAT1 and SNHG14. Based on the indices of complementarity of CCAT1 and SNHG14 to the mRNA sequences, we selected 5 protein-coding genes MAPK1, c-MET, TGFB2, SNAIL1, and WNT4 associated with the epithelial-mesenchymal transition. Real-time PCR on 54 ovarian cancer samples confirmed the high expression levels of CCAT1 and SNHG14 (logFC>1.5, p<0.05). A positive correlation between the expression levels of two lncRNA and mRNA of 5 genes in 6 pairs was established. The activating effect of CCAT1 and SNHG14 on the expression of these genes can be mediated by miR-203 and miR-124.

Ovarian cancer (OC) is one of the most common types of cancer among malignancies of the female reproductive system. This pathology is asymptomatic until advanced stages and has a poor prognosis. Our study aimed to search for lncRNA–miRNA–mRNA competing triplets that promote ovarian tumorigenesis. For this purpose, we analyzed tumor samples from the TCGA database and verified the results experimentally in a set of 46 paired samples of tumor and matched histologically unchanged ovarian tissues from OC patients. The list of RNAs selected in silico for experimental studies included 13 mRNAs, 10 lncRNAs, and 5 miRNAs related to epithelial–mesenchymal transition and angiogenesis. We evaluated the expression of these RNAs by qRT-PCR and assessed the correlation between levels of miRNAs, mRNAs, and lncRNAs. Sixteen significant triplets were revealed, in some of which, e.g., OIP5-AS1–miR-203a–c-MET and OIP5-AS1–miR-203a–ZEB2, both lncRNA and mRNA had sites for miR-203a direct binding. Transfection of the OVCAR-3 and SKOV-3 cell lines with the miR-203a mimic was used to confirm the novel links of miR-203a with ZEB2 and c-MET in OC. These connections suggest that the interactomes have the potential for diagnostics of metastasis at early onset.

Endogenous hot spots of DNA double-strand breaks (DSBs) are tightly linked with transcription patterns and cancer. There are nine hot spots of DSBs (denoted Pleiades) in human rDNA units that are located exclusively inside the intergenic spacer (IGS). Profiles of Pleiades coincide with the profiles of γ-H2AX, suggesting a high level of in vivo breakage inside rDNA genes. The data were confirmed by microscopic observation of the largest γ-H2AX foci inside nucleoli in interphase chromosomes. Circular chromosome conformation capture (4C) data indicate that the rDNA units often make contact with a specific set of chromosomal regions containing genes that are involved in differentiation and cancer. Interestingly, these regions also often possess hot spots of DSBs that provide the potential for Robertsonian and oncogenic translocations. In this study, we searched for translocations in which rDNA clusters are involved. The whole genome sequence (WGS) data of normal T cells and NK-cell lymphomas from the same individuals revealed numerous translocations in which Pleiades were involved. The sites of these translocations in normal T cells and in the lymphomas were mostly different, although there were also some common sites. The genes at translocations in normal cells and in lymphomas are associated with predominantly non-overlapping lists of genes that are depleted with silenced genes. Our data indicate that rDNA-mediated translocations occur at about the same frequency in the normal T cells and NK-lymphoma cells but differ at particular sites that correspond to open chromatin. We conclude that oncogenic translocations lead to dysregulation of a specific set of genes controlling development. In normal T cells and in NK cells, there are hot spots of translocations at sites possessing strong H3K27ac marks. The data indicate that Pleiades are involved in rDNA-mediated translocation.

Several models of long short-term memory (LSTM) neural networks were constructed. Each model was trained on the complete mouse genome to predict the exon–intron structure of a gene. The performance of the neural networks was compared using a test sample and experimental sequencing data obtained using rat brain cell cultures after treatment with spicing inhibitors.

In the course of sample preparation for Next Generation Sequencing (NGS), DNA is fragmented by various methods. Fragmentation shows a persistent bias with regard to the cleavage rates of various dinucleotides. With the exception of CpG dinucleotides the previously described biases were consistent with results of the DNA cleavage in solution. Here we computed cleavage rates of all dinucleotides including the methylated CpG and unmethylated CpG dinucleotides using data of the Whole Genome Sequencing datasets of the 1000 Genomes project. We found that the cleavage rate of CpG is significantly higher for the methylated CpG dinucleotides. Using this information, we developed a classifier for distinguishing cancer and healthy tissues based on their CpG islands statuses of the fragmentation. A simple Support Vector Machine classifier based on this algorithm shows an accuracy of 84%. The proposed method allows the detection of epigenetic markers purely based on mechanochemical DNA fragmentation, which can be detected by a simple analysis of the NGS sequencing data.