According to the current view, each microRNA regulates hundreds of genes. Computational tools aim at identifying microRNA targets, usually selecting evolutionarily conserved microRNA binding sites. While the false positive rates have been evaluated for some prediction programs, that information is rarely put forward in studies making use of their predictions. Here, we provide evidence that such predictions are often biologically irrelevant. Focusing on miR-223-guided repression, we observed that it is often smaller than inter-individual variability in gene expression among wild-type mice, suggesting that most predicted targets are functionally insensitive to that microRNA. Furthermore, we found that human haplo-insufficient genes tend to bear the most highly conserved microRNA binding sites. It thus appears that biological functionality of microRNA binding sites depends on the dose-sensitivity of their host gene and that, conversely, it is unlikely that every predicted microRNA target is dose-sensitive enough to be functionally regulated by microRNAs. We also observed that some mRNAs can efficiently titrate microRNAs, providing a reason for microRNA binding site conservation for inefficiently repressed targets. Finally, many conserved microRNA binding sites are conserved in a microRNA-independent fashion: Sequence elements may be conserved for other reasons, while being fortuitously complementary to microRNAs. Collectively, our data suggest that the role of microRNAs in normal and pathological conditions has been overestimated due to the frequent overlooking of false positive rates.

Comprehensive analysis of molecular pathology requires a collection of reference samples representing normal tissues from healthy donors. For the available limited collections of normal tissues from postmortal donors, there is a problem of data incompatibility, as different datasets generated using different experimental platforms often cannot be merged in a single panel. Here, we constructed and deposited the gene expression database of normal human tissues based on uniformly screened original sequencing data. In total, 142 solid tissue samples representing 20 organs were taken from post-mortal human healthy donors of different age killed in road accidents no later than 36 hours after death. Blood samples were taken from 17 healthy volunteers. We then compared them with the 758 transcriptomic profiles taken from the other databases. We found that overall 463 biosamples showed tissue-specific rather than platform- or database-specific clustering and could be aggregated in a single database termed Oncobox Atlas of Normal Tissue Expression (ANTE). Our data will be useful to all those working with the analysis of human gene expression.

In the Drosophila germline, retrotransposons are silenced by the PIWI-interacting RNA (piRNA) pathway. Telomeric retroelements HeT-A, TART and TAHRE , which are involved in telomere maintenance in Drosophila , are also the targets of piRNA-mediated silencing. We have demonstrated that expression of reporter genes driven by the HeT-A promoter is under the control of the piRNA silencing pathway independent of the transgene location. In order to test directly whether piRNAs affect the transcriptional state of retrotransposons we performed a nuclear run-on (NRO) assay and revealed increased density of the active RNA polymerase complexes at the sequences of endogenous HeT-A and TART telomeric retroelements as well as HeT-A -containing constructs in the ovaries of spn-E mutants and in flies with piwi knockdown. This strongly correlates with enrichment of two histone H3 modifications (dimethylation of lysine 79 and dimethylation of lysine 4), which mark transcriptionally active chromatin, on the same sequences in the piRNA pathway mutants. spn-E mutation and piwi knockdown results in transcriptional activation of some other non-telomeric retrotransposons in the ovaries, such as I- element and HMS Beagle. Therefore piRNA-mediated transcriptional mode of silencing is involved in the control of retrotransposon expression in the Drosophila germline.

Small regulatory RNAs (microRNAs, siRNAs, and piRNAs) exhibit several unique features that clearly distinguish them from other known gene regulators. Their genomic organization, mode of action, and proposed biological functions raise specific questions. In this review, we focus on the quantitative aspect of small regulatory RNA biology. The original nature of these small RNAs accelerated the development of novel detection techniques and improved statistical methods and promoted new concepts that may unexpectedly generalize to other gene regulators. Quantification of natural phenomena is at the core of scientific practice, and the unique challenges raised by small regulatory RNAs have prompted many creative innovations by the scientific community.

AIM. To identify the KRAS and NRAS gene mutations in patients with newly diagnosed multiple myeloma (ММ) and to classify them according to the depth of antitumor response to bortezomib-based triplet induction therapy. MATERIALS & METHODS. The trial enrolled 89 patients with newly diagnosed MM prior to chemotherapy. Among them, there were 45 women and 44 men aged 30–82 years (median 58.5 years). ММ was diagnosed according to IMWG criteria (2014). Bone marrow (BM) plasma cells were isolated from the aspirate using gradient method with subsequent immunomagnetic CD138 marker selection. The KRAS and NRAS gene mutations in BM CD138+ cells were identified with Sanger sequencing method. The proteomic programs MutationTaster, Polyphen2, and FATHMM-XF were used for mutation analysis in the KRAS and NRAS genes. All patients received bortezomib-based triplet chemotherapy as first-line treatment. The response depth was assessed after completing 6 cycles of PAD and VCD regimens. Antitumor response was evaluated according to IMWG (2016) criteria. RESULTS. The mutation rate in the gene family RAS was 42 % (37/89). The analysis focused on the data from 33 patients with mutations detected and response identified after 6 cycles of treatment. In 22 out of 33 patients, deep response was not achieved, whereas 11 patients showed complete remission (CR) + very good partial remission (VGPR). In the group of patients without mutations in the gene family RAS, the response to therapy meeting the CR + VGPR criteria was 64 % (27/42). The differences appeared to be significant (p = 0.008). The clinical data and the evaluation of primary treatment outcomes provided the basis for distinguishing a group of 9 prognostically unfavorable mutations: NRAS Gly13Asp, Gln61His; KRAS Gly12Ala, Gly12Asp, Gly12Val, Gly13Asp, Gln61Arg, Gln61His, and Ala146Val. CONCLUSION. The mutations in KRAS and NRAS belonging to the gene family RAS had a negative effect on the efficacy of the bortezomib-based triplet induction therapy. Mutation variants in the RAS family genes differed in prognostic significance. The analysis results helped to identify the mutation variants associated with the worse response to therapy: NRAS Gly13Asp, Gln61His; KRAS Gly12Ala, Gly12Asp, Gly12Val, Gly13Asp, Gln61Arg, Gln61His, and Ala146Val.

Introduction. Multiple myeloma (MM) is a lymphoproliferative disorder, for which the duration of remission is hard to predict.Aim. To analyse the molecular genetic status of the tumour of MM patient with a short remission period at the onset and relapse of the disease, as well as to conduct its comparison with the clinical course of the disease.Materials and methods. Somatic mutations were detected through Sanger sequencing. The level of gene expression was analysed using RNA sequencing on the Illumina platform. In order to study chromosomal rearrangements, the authors performed fluorescence hybridisation in situ (FISH study).Results. Prior to the treatment and during the relapse of the disease, the patient revealed a heterozygous clonal mutation p.182A>C (p.Q61P) in the N-RAS gene, which is known to hamper regulation of the MAPK signalling pathway. The transcriptome analysis performed using the RNA-seq method revealed a sharp increase in the expression of the IL6 gene during relapse (by 30 times), which could have served as a trigger for the progression of multiple myeloma, given that this cytokine stimulates cell proliferation by activating various signalling pathways (MAPK, JAK- STAT, PI3K). The progression of the disease was also accompanied by an increased expression of key regulatory genes (с-MYC, Notch2, MDM, RAF1, STAT4, mTOR) and a sharp decrease in the expression of immunoglobulin genes, which caused deep immunodeficiency in the patient. A molecular cytogenetic study (FISH) revealed trisomy of chromosomes 5, 9 and 15 at the onset of the disease. Disease relapse occurred with the amplification of the 1q21 locus, with hyperdiploidy being preserved.Conclusion. In order to predict the duration of the remission period, a complex molecular genetic screening is required.